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---|---|---|---|---|---|---|---|---|---|---|
select count ( * ) where date = '39100' col : rank | date | level at trent bridge m | level at trent bridge ft | peak flow m3/s | peak flow cfs row 1 : 1 | february 1795 | 24.55 | 80.5 | 1416 | 50000 row 2 : 2 | october 1875 | 24.38 | 80.0 | 1274 | 45000 row 3 : 3 | march 1947 | 24.3 | 79.7 | 1107 | 39100 row 4 : 4 | november 1852 | 24.26 | 79.6 | 1082 | 38200 row 5 : 5 | november 2000 | 23.8 | 78.1 | 1019 | 36000 row 6 : none | normal / avg flow | 20.7 | 68.0 | 84 | 3000 | col : count ( "*" ) row 1 : 0 | select count ( * ) where date = '39100' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & date & level at trent bridge m & level at trent bridge ft & peak flow m3/s & peak flow cfs \\
\midrule
0 & 1 & february 1795 & 24.55 & 80.5 & 1416 & 50000 \\
1 & 2 & october 1875 & 24.38 & 80.0 & 1274 & 45000 \\
2 & 3 & march 1947 & 24.3 & 79.7 & 1107 & 39100 \\
3 & 4 & november 1852 & 24.26 & 79.6 & 1082 & 38200 \\
4 & 5 & november 2000 & 23.8 & 78.1 & 1019 & 36000 \\
5 & none & normal / avg flow & 20.7 & 68.0 & 84 & 3000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where date = '39100' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>date</th>
<th>level at trent bridge m</th>
<th>level at trent bridge ft</th>
<th>peak flow m3/s</th>
<th>peak flow cfs</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>february 1795</td>
<td>24.55</td>
<td>80.5</td>
<td>1416</td>
<td>50000</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>october 1875</td>
<td>24.38</td>
<td>80.0</td>
<td>1274</td>
<td>45000</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>march 1947</td>
<td>24.3</td>
<td>79.7</td>
<td>1107</td>
<td>39100</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>november 1852</td>
<td>24.26</td>
<td>79.6</td>
<td>1082</td>
<td>38200</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>november 2000</td>
<td>23.8</td>
<td>78.1</td>
<td>1019</td>
<td>36000</td>
</tr>
<tr>
<th>5</th>
<td>none</td>
<td>normal / avg flow</td>
<td>20.7</td>
<td>68.0</td>
<td>84</td>
<td>3000</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
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</tbody>
</table> | select count ( * ) where date = '39100' <table_name> : table | | rank | date | level at trent bridge m | level at trent bridge ft | peak flow m3/s | peak flow cfs |
|---:|:-------|:------------------|--------------------------:|---------------------------:|-----------------:|----------------:|
| 0 | 1 | february 1795 | 24.55 | 80.5 | 1416 | 50000 |
| 1 | 2 | october 1875 | 24.38 | 80 | 1274 | 45000 |
| 2 | 3 | march 1947 | 24.3 | 79.7 | 1107 | 39100 |
| 3 | 4 | november 1852 | 24.26 | 79.6 | 1082 | 38200 |
| 4 | 5 | november 2000 | 23.8 | 78.1 | 1019 | 36000 |
| 5 | none | normal / avg flow | 20.7 | 68 | 84 | 3000 | | | | count ( "*" ) |
|---:|----------------:|
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select count ( * ) where year > 1224 col : year | venue | winners | runner-up | 3rd place row 1 : 2005 | pardubice | poland (41 pts) | sweden (35 pts) | denmark (24 pts) row 2 : 2006 | rybnik | poland (41 pts) | sweden (27 pts) | denmark (26 pts) row 3 : 2007 | abensberg | poland (40 pts) | great britain (36 pts) | czech republic (30 pts) row 4 : 2008 | holsted | poland (40 pts) | denmark (39 pts) | sweden (38 pts) row 5 : 2009 | gorzow wlkp | poland (57 pts) | denmark (45 pts) | sweden (32 pts) row 6 : 2010 | rye house | denmark (51 pts) | sweden (37 pts) | poland (35 pts) row 7 : 2011 | balakovo | russia (61 pts) | denmark (31 pts) | ukraine (29+3 pts) row 8 : 2012 | gniezno | poland (61 pts) | australia (44 pts) | sweden (26 pts) | col : count ( "*" ) row 1 : 8 | select count ( * ) where year > 1224 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & venue & winners & runner-up & 3rd place \\
\midrule
0 & 2005 & pardubice & poland (41 pts) & sweden (35 pts) & denmark (24 pts) \\
1 & 2006 & rybnik & poland (41 pts) & sweden (27 pts) & denmark (26 pts) \\
2 & 2007 & abensberg & poland (40 pts) & great britain (36 pts) & czech republic (30 pts) \\
3 & 2008 & holsted & poland (40 pts) & denmark (39 pts) & sweden (38 pts) \\
4 & 2009 & gorzow wlkp & poland (57 pts) & denmark (45 pts) & sweden (32 pts) \\
5 & 2010 & rye house & denmark (51 pts) & sweden (37 pts) & poland (35 pts) \\
6 & 2011 & balakovo & russia (61 pts) & denmark (31 pts) & ukraine (29+3 pts) \\
7 & 2012 & gniezno & poland (61 pts) & australia (44 pts) & sweden (26 pts) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 8 \\
\bottomrule
\end{tabular}
| select count ( * ) where year > 1224 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>venue</th>
<th>winners</th>
<th>runner-up</th>
<th>3rd place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2005</td>
<td>pardubice</td>
<td>poland (41 pts)</td>
<td>sweden (35 pts)</td>
<td>denmark (24 pts)</td>
</tr>
<tr>
<th>1</th>
<td>2006</td>
<td>rybnik</td>
<td>poland (41 pts)</td>
<td>sweden (27 pts)</td>
<td>denmark (26 pts)</td>
</tr>
<tr>
<th>2</th>
<td>2007</td>
<td>abensberg</td>
<td>poland (40 pts)</td>
<td>great britain (36 pts)</td>
<td>czech republic (30 pts)</td>
</tr>
<tr>
<th>3</th>
<td>2008</td>
<td>holsted</td>
<td>poland (40 pts)</td>
<td>denmark (39 pts)</td>
<td>sweden (38 pts)</td>
</tr>
<tr>
<th>4</th>
<td>2009</td>
<td>gorzow wlkp</td>
<td>poland (57 pts)</td>
<td>denmark (45 pts)</td>
<td>sweden (32 pts)</td>
</tr>
<tr>
<th>5</th>
<td>2010</td>
<td>rye house</td>
<td>denmark (51 pts)</td>
<td>sweden (37 pts)</td>
<td>poland (35 pts)</td>
</tr>
<tr>
<th>6</th>
<td>2011</td>
<td>balakovo</td>
<td>russia (61 pts)</td>
<td>denmark (31 pts)</td>
<td>ukraine (29+3 pts)</td>
</tr>
<tr>
<th>7</th>
<td>2012</td>
<td>gniezno</td>
<td>poland (61 pts)</td>
<td>australia (44 pts)</td>
<td>sweden (26 pts)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>8</td>
</tr>
</tbody>
</table> | select count ( * ) where year > 1224 <table_name> : table | | year | venue | winners | runner-up | 3rd place |
|---:|-------:|:------------|:-----------------|:-----------------------|:------------------------|
| 0 | 2005 | pardubice | poland (41 pts) | sweden (35 pts) | denmark (24 pts) |
| 1 | 2006 | rybnik | poland (41 pts) | sweden (27 pts) | denmark (26 pts) |
| 2 | 2007 | abensberg | poland (40 pts) | great britain (36 pts) | czech republic (30 pts) |
| 3 | 2008 | holsted | poland (40 pts) | denmark (39 pts) | sweden (38 pts) |
| 4 | 2009 | gorzow wlkp | poland (57 pts) | denmark (45 pts) | sweden (32 pts) |
| 5 | 2010 | rye house | denmark (51 pts) | sweden (37 pts) | poland (35 pts) |
| 6 | 2011 | balakovo | russia (61 pts) | denmark (31 pts) | ukraine (29+3 pts) |
| 7 | 2012 | gniezno | poland (61 pts) | australia (44 pts) | sweden (26 pts) | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 8 | | [
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select count ( tournament ) where venue = 'beijing, china' col : year | tournament | venue | result | extra row 1 : 2002 | european indoor championships | vienna, austria | 5th | none row 2 : 2003 | universiade | daegu, south korea | 3rd | none row 3 : 2004 | world indoor championships | budapest, hungary | 1st | 2.04 pbi row 4 : 2004 | summer olympics | athens, greece | 1st | 2.06 nr row 5 : 2004 | world athletics final | monte carlo, monaco | 1st | none row 6 : 2006 | world indoor championships | moscow, russia | 1st | 2.02 row 7 : 2006 | european championships | gothenburg, sweden | 5th | 1.99 m row 8 : 2006 | world athletics final | stuttgart, germany | 4th | none row 9 : 2006 | world cup | athens, greece | 1st | 1.97 row 10 : 2007 | world championships | osaka, japan | 4th | none row 11 : 2008 | summer olympics | beijing, china | 4th | 2.01 row 12 : 2011 | world championships | daegu, korea | 4th | 1.97 | col : count ( "tournament" ) row 1 : 1 | select count ( tournament ) where venue = 'beijing, china' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & tournament & venue & result & extra \\
\midrule
0 & 2002 & european indoor championships & vienna, austria & 5th & none \\
1 & 2003 & universiade & daegu, south korea & 3rd & none \\
2 & 2004 & world indoor championships & budapest, hungary & 1st & 2.04 pbi \\
3 & 2004 & summer olympics & athens, greece & 1st & 2.06 nr \\
4 & 2004 & world athletics final & monte carlo, monaco & 1st & none \\
5 & 2006 & world indoor championships & moscow, russia & 1st & 2.02 \\
6 & 2006 & european championships & gothenburg, sweden & 5th & 1.99 m \\
7 & 2006 & world athletics final & stuttgart, germany & 4th & none \\
8 & 2006 & world cup & athens, greece & 1st & 1.97 \\
9 & 2007 & world championships & osaka, japan & 4th & none \\
10 & 2008 & summer olympics & beijing, china & 4th & 2.01 \\
11 & 2011 & world championships & daegu, korea & 4th & 1.97 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "tournament" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( tournament ) where venue = 'beijing, china' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>tournament</th>
<th>venue</th>
<th>result</th>
<th>extra</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002</td>
<td>european indoor championships</td>
<td>vienna, austria</td>
<td>5th</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2003</td>
<td>universiade</td>
<td>daegu, south korea</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2004</td>
<td>world indoor championships</td>
<td>budapest, hungary</td>
<td>1st</td>
<td>2.04 pbi</td>
</tr>
<tr>
<th>3</th>
<td>2004</td>
<td>summer olympics</td>
<td>athens, greece</td>
<td>1st</td>
<td>2.06 nr</td>
</tr>
<tr>
<th>4</th>
<td>2004</td>
<td>world athletics final</td>
<td>monte carlo, monaco</td>
<td>1st</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2006</td>
<td>world indoor championships</td>
<td>moscow, russia</td>
<td>1st</td>
<td>2.02</td>
</tr>
<tr>
<th>6</th>
<td>2006</td>
<td>european championships</td>
<td>gothenburg, sweden</td>
<td>5th</td>
<td>1.99 m</td>
</tr>
<tr>
<th>7</th>
<td>2006</td>
<td>world athletics final</td>
<td>stuttgart, germany</td>
<td>4th</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2006</td>
<td>world cup</td>
<td>athens, greece</td>
<td>1st</td>
<td>1.97</td>
</tr>
<tr>
<th>9</th>
<td>2007</td>
<td>world championships</td>
<td>osaka, japan</td>
<td>4th</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>2008</td>
<td>summer olympics</td>
<td>beijing, china</td>
<td>4th</td>
<td>2.01</td>
</tr>
<tr>
<th>11</th>
<td>2011</td>
<td>world championships</td>
<td>daegu, korea</td>
<td>4th</td>
<td>1.97</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "tournament" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( tournament ) where venue = 'beijing, china' <table_name> : table | | year | tournament | venue | result | extra |
|---:|-------:|:------------------------------|:--------------------|:---------|:---------|
| 0 | 2002 | european indoor championships | vienna, austria | 5th | none |
| 1 | 2003 | universiade | daegu, south korea | 3rd | none |
| 2 | 2004 | world indoor championships | budapest, hungary | 1st | 2.04 pbi |
| 3 | 2004 | summer olympics | athens, greece | 1st | 2.06 nr |
| 4 | 2004 | world athletics final | monte carlo, monaco | 1st | none |
| 5 | 2006 | world indoor championships | moscow, russia | 1st | 2.02 |
| 6 | 2006 | european championships | gothenburg, sweden | 5th | 1.99 m |
| 7 | 2006 | world athletics final | stuttgart, germany | 4th | none |
| 8 | 2006 | world cup | athens, greece | 1st | 1.97 |
| 9 | 2007 | world championships | osaka, japan | 4th | none |
| 10 | 2008 | summer olympics | beijing, china | 4th | 2.01 |
| 11 | 2011 | world championships | daegu, korea | 4th | 1.97 | | | | count ( "tournament" ) |
|---:|-------------------------:|
| 0 | 1 | | [
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] |
select count ( * ) where player = 'john challen' col : player | matches | innings | runs | average | 100s | 50s row 1 : herbie hewett | 10 | 15 | 543 | 38.79 | 1 | 2 row 2 : lionel palairet | 10 | 14 | 408 | 29.14 | 1 | 1 row 3 : bill roe | 8 | 12 | 316 | 28.73 | 0 | 1 row 4 : george nichols | 13 | 18 | 497 | 27.61 | 1 | 3 row 5 : john challen | 9 | 14 | 286 | 20.43 | 0 | 1 row 6 : ted tyler | 13 | 18 | 297 | 18.56 | 0 | 0 row 7 : crescens robinson | 9 | 13 | 162 | 14.73 | 0 | 0 row 8 : albert clapp | 11 | 15 | 159 | 10.6 | 0 | 0 | col : count ( "*" ) row 1 : 1 | select count ( * ) where player = 'john challen' <table_name> : table \begin{tabular}{llllllll}
\toprule
& player & matches & innings & runs & average & 100s & 50s \\
\midrule
0 & herbie hewett & 10 & 15 & 543 & 38.79 & 1 & 2 \\
1 & lionel palairet & 10 & 14 & 408 & 29.14 & 1 & 1 \\
2 & bill roe & 8 & 12 & 316 & 28.73 & 0 & 1 \\
3 & george nichols & 13 & 18 & 497 & 27.61 & 1 & 3 \\
4 & john challen & 9 & 14 & 286 & 20.43 & 0 & 1 \\
5 & ted tyler & 13 & 18 & 297 & 18.56 & 0 & 0 \\
6 & crescens robinson & 9 & 13 & 162 & 14.73 & 0 & 0 \\
7 & albert clapp & 11 & 15 & 159 & 10.6 & 0 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where player = 'john challen' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>player</th>
<th>matches</th>
<th>innings</th>
<th>runs</th>
<th>average</th>
<th>100s</th>
<th>50s</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>herbie hewett</td>
<td>10</td>
<td>15</td>
<td>543</td>
<td>38.79</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>1</th>
<td>lionel palairet</td>
<td>10</td>
<td>14</td>
<td>408</td>
<td>29.14</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>bill roe</td>
<td>8</td>
<td>12</td>
<td>316</td>
<td>28.73</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>3</th>
<td>george nichols</td>
<td>13</td>
<td>18</td>
<td>497</td>
<td>27.61</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>john challen</td>
<td>9</td>
<td>14</td>
<td>286</td>
<td>20.43</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>ted tyler</td>
<td>13</td>
<td>18</td>
<td>297</td>
<td>18.56</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>crescens robinson</td>
<td>9</td>
<td>13</td>
<td>162</td>
<td>14.73</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>albert clapp</td>
<td>11</td>
<td>15</td>
<td>159</td>
<td>10.6</td>
<td>0</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where player = 'john challen' <table_name> : table | | player | matches | innings | runs | average | 100s | 50s |
|---:|:------------------|----------:|----------:|-------:|----------:|-------:|------:|
| 0 | herbie hewett | 10 | 15 | 543 | 38.79 | 1 | 2 |
| 1 | lionel palairet | 10 | 14 | 408 | 29.14 | 1 | 1 |
| 2 | bill roe | 8 | 12 | 316 | 28.73 | 0 | 1 |
| 3 | george nichols | 13 | 18 | 497 | 27.61 | 1 | 3 |
| 4 | john challen | 9 | 14 | 286 | 20.43 | 0 | 1 |
| 5 | ted tyler | 13 | 18 | 297 | 18.56 | 0 | 0 |
| 6 | crescens robinson | 9 | 13 | 162 | 14.73 | 0 | 0 |
| 7 | albert clapp | 11 | 15 | 159 | 10.6 | 0 | 0 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( notes ) where show = 'saturday night live' col : year | show | role | notes row 1 : 1994-96 | martin | hustle man | none row 2 : 1996 | 3rd rock from the sun | tracy morgan | none row 3 : 1996-03 | saturday night live | himself, various | none row 4 : 2002 | crank yankers | spoonie luv | none row 5 : 2002 | frank mcklusky, c.i | reggie rosengold | none row 6 : 2003-04 | the tracy morgan show | tracy mitchell | none row 7 : 2006 | mind of mencia | captain black cawk | none row 8 : 2006-13 | 30 rock | tracy jordan | none row 9 : 2008 | human giant | the invisible man | none row 10 : 2008 | where my dogs at? | woof | none row 11 : 2008-present | scare tactics | host | none row 12 : 2009 | saturday night live | host | episode: "tracy morgan/kelly clarkson" row 13 : 2011 | saturday night live | various | episode: "jimmy fallon/michael buble" | col : count ( "notes" ) row 1 : 3 | select count ( notes ) where show = 'saturday night live' <table_name> : table \begin{tabular}{lllll}
\toprule
& year & show & role & notes \\
\midrule
0 & 1994-96 & martin & hustle man & none \\
1 & 1996 & 3rd rock from the sun & tracy morgan & none \\
2 & 1996-03 & saturday night live & himself, various & none \\
3 & 2002 & crank yankers & spoonie luv & none \\
4 & 2002 & frank mcklusky, c.i & reggie rosengold & none \\
5 & 2003-04 & the tracy morgan show & tracy mitchell & none \\
6 & 2006 & mind of mencia & captain black cawk & none \\
7 & 2006-13 & 30 rock & tracy jordan & none \\
8 & 2008 & human giant & the invisible man & none \\
9 & 2008 & where my dogs at? & woof & none \\
10 & 2008-present & scare tactics & host & none \\
11 & 2009 & saturday night live & host & episode: "tracy morgan/kelly clarkson" \\
12 & 2011 & saturday night live & various & episode: "jimmy fallon/michael buble" \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "notes" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( notes ) where show = 'saturday night live' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>show</th>
<th>role</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1994-96</td>
<td>martin</td>
<td>hustle man</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1996</td>
<td>3rd rock from the sun</td>
<td>tracy morgan</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1996-03</td>
<td>saturday night live</td>
<td>himself, various</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2002</td>
<td>crank yankers</td>
<td>spoonie luv</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2002</td>
<td>frank mcklusky, c.i</td>
<td>reggie rosengold</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2003-04</td>
<td>the tracy morgan show</td>
<td>tracy mitchell</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2006</td>
<td>mind of mencia</td>
<td>captain black cawk</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>2006-13</td>
<td>30 rock</td>
<td>tracy jordan</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2008</td>
<td>human giant</td>
<td>the invisible man</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>2008</td>
<td>where my dogs at?</td>
<td>woof</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>2008-present</td>
<td>scare tactics</td>
<td>host</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>2009</td>
<td>saturday night live</td>
<td>host</td>
<td>episode: "tracy morgan/kelly clarkson"</td>
</tr>
<tr>
<th>12</th>
<td>2011</td>
<td>saturday night live</td>
<td>various</td>
<td>episode: "jimmy fallon/michael buble"</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "notes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( notes ) where show = 'saturday night live' <table_name> : table | | year | show | role | notes |
|---:|:-------------|:----------------------|:-------------------|:---------------------------------------|
| 0 | 1994-96 | martin | hustle man | none |
| 1 | 1996 | 3rd rock from the sun | tracy morgan | none |
| 2 | 1996-03 | saturday night live | himself, various | none |
| 3 | 2002 | crank yankers | spoonie luv | none |
| 4 | 2002 | frank mcklusky, c.i | reggie rosengold | none |
| 5 | 2003-04 | the tracy morgan show | tracy mitchell | none |
| 6 | 2006 | mind of mencia | captain black cawk | none |
| 7 | 2006-13 | 30 rock | tracy jordan | none |
| 8 | 2008 | human giant | the invisible man | none |
| 9 | 2008 | where my dogs at? | woof | none |
| 10 | 2008-present | scare tactics | host | none |
| 11 | 2009 | saturday night live | host | episode: "tracy morgan/kelly clarkson" |
| 12 | 2011 | saturday night live | various | episode: "jimmy fallon/michael buble" | | | | count ( "notes" ) |
|---:|--------------------:|
| 0 | 3 | | [
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select count ( category ) where film = 'khoka 420,rangbaaz and chander pahar' col : year | award | category | film | result row 1 : 2009 | anandalok awards | anandalok awards for best actor | challenge | won row 2 : 2009 | anandalok awards | anandalok awards for best action hero | challenge | won row 3 : 2010 | star jalsha entertainment awards 2010 | star jalsha entertainment awards 2010 for best actor | poran jaye jolia re | won row 4 : 2010 | star jalsha entertainment awards 2010 | star jalsha entertainment awards 2010 for best actor | dujone | nominated row 5 : 2010 | tele cine awards 2010 | tele cine awards 2010 for best actor | challenge | won row 6 : 2010 | kalakar awards 2010 | kalakar awards 2010 for best actor | challenge | won row 7 : 2010 | star ananda shera bangali awards 2010 | star ananda shera notun protibha award | none | won row 8 : 2010 | anandalok awards 2010 | anandalok awards 2010 for best actor (male) | le chakka | won row 9 : 2011 | big bangla movie awards 2011 | big bangla movie awards 2011 for best actor of the decade | none | won row 10 : 2011 | anandalok awards | anandalok awards for best actor | paglu | nominated row 11 : 2011 | star jalsha entertainment awards 2011 | star jalsha entertainment awards 2011 for best dancing sensation | none | won row 12 : 2011 | zee bangla awards 2011 | zee bangla awards 2011 for best actor | le chakka | nominated row 13 : 2012 | star guide bengali film awards 2012 | star guide bengali film awards 2012 for best actor | paglu | won row 14 : 2012 | anandalok awards 2012 | anandalok awards 2012 for best actor (male) | paglu 2 | nominated row 15 : 2012 | zee bangla awards 2012 | zee bangla awards 2012 for best actor | khokababu | won row 16 : 2012 | 12th tele cine awards 2012 | 12th tele cine awards 2012 for best actor | paglu | won row 17 : 2012 | kalakar awards 2012 | kalakar awards 2012 for best actor | paglu | won row 18 : 2013 | 13th tele cine awards 2013 | 13th tele cine awards 2013 for best actor | challenge 2 | nominated row 19 : 2013 | star jalsha entertainment awards 2013 | star jalsha entertainment awards 2013 for best dancing sensation | none | won row 20 : 2013 | star jalsha entertainment awards 2013 | star jalsha entertainment awards 2013 for best debut singing | khokababu | won row 21 : 2014 | most desirable tollywood actor 2014 (public poll) | best actor | khoka 420,rangbaaz and chander pahar | won row 22 : 2014 | tollywood national award 2014 | best actor | chander pahar | won row 23 : 2014 | tollywood national award 2014 | best romantic hero | khoka 420 | nominated row 24 : 2014 | tollywood national award 2014 | best action hero | rangbaaz | won row 25 : 2014 | kalakar awards 2014 | kalakar awards 2014 for best actor | rangbaaz and chander pahar | won row 26 : 2014 | bfja award for best actor 2014 | bfja award for best actor best actor | chander pahar | won row 27 : 2014 | zee bangla gourab somman awards 2014 | best actor | chander pahar | won row 28 : 2014 | anandalok awards | best actor | chander pahar | won row 29 : 2014 | zee bangla gourab somman awards 2014 | best dancing sensation | none | won row 30 : 2014 | filmfare awards east | global east people's choice filmfare award | none | won row 31 : 2014 | 14th tele cine awards 2014 | 14th tele cine awards for best actor | chander pahar | pending row 32 : 2014 | 14th tele cine awards 2014 | 14th tele cine awards for best jodi (dev-koel) | rangbaaz | pending | col : count ( "category" ) row 1 : 1 | select count ( category ) where film = 'khoka 420,rangbaaz and chander pahar' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & award & category & film & result \\
\midrule
0 & 2009 & anandalok awards & anandalok awards for best actor & challenge & won \\
1 & 2009 & anandalok awards & anandalok awards for best action hero & challenge & won \\
2 & 2010 & star jalsha entertainment awards 2010 & star jalsha entertainment awards 2010 for best actor & poran jaye jolia re & won \\
3 & 2010 & star jalsha entertainment awards 2010 & star jalsha entertainment awards 2010 for best actor & dujone & nominated \\
4 & 2010 & tele cine awards 2010 & tele cine awards 2010 for best actor & challenge & won \\
5 & 2010 & kalakar awards 2010 & kalakar awards 2010 for best actor & challenge & won \\
6 & 2010 & star ananda shera bangali awards 2010 & star ananda shera notun protibha award & none & won \\
7 & 2010 & anandalok awards 2010 & anandalok awards 2010 for best actor (male) & le chakka & won \\
8 & 2011 & big bangla movie awards 2011 & big bangla movie awards 2011 for best actor of the decade & none & won \\
9 & 2011 & anandalok awards & anandalok awards for best actor & paglu & nominated \\
10 & 2011 & star jalsha entertainment awards 2011 & star jalsha entertainment awards 2011 for best dancing sensation & none & won \\
11 & 2011 & zee bangla awards 2011 & zee bangla awards 2011 for best actor & le chakka & nominated \\
12 & 2012 & star guide bengali film awards 2012 & star guide bengali film awards 2012 for best actor & paglu & won \\
13 & 2012 & anandalok awards 2012 & anandalok awards 2012 for best actor (male) & paglu 2 & nominated \\
14 & 2012 & zee bangla awards 2012 & zee bangla awards 2012 for best actor & khokababu & won \\
15 & 2012 & 12th tele cine awards 2012 & 12th tele cine awards 2012 for best actor & paglu & won \\
16 & 2012 & kalakar awards 2012 & kalakar awards 2012 for best actor & paglu & won \\
17 & 2013 & 13th tele cine awards 2013 & 13th tele cine awards 2013 for best actor & challenge 2 & nominated \\
18 & 2013 & star jalsha entertainment awards 2013 & star jalsha entertainment awards 2013 for best dancing sensation & none & won \\
19 & 2013 & star jalsha entertainment awards 2013 & star jalsha entertainment awards 2013 for best debut singing & khokababu & won \\
20 & 2014 & most desirable tollywood actor 2014 (public poll) & best actor & khoka 420,rangbaaz and chander pahar & won \\
21 & 2014 & tollywood national award 2014 & best actor & chander pahar & won \\
22 & 2014 & tollywood national award 2014 & best romantic hero & khoka 420 & nominated \\
23 & 2014 & tollywood national award 2014 & best action hero & rangbaaz & won \\
24 & 2014 & kalakar awards 2014 & kalakar awards 2014 for best actor & rangbaaz and chander pahar & won \\
25 & 2014 & bfja award for best actor 2014 & bfja award for best actor best actor & chander pahar & won \\
26 & 2014 & zee bangla gourab somman awards 2014 & best actor & chander pahar & won \\
27 & 2014 & anandalok awards & best actor & chander pahar & won \\
28 & 2014 & zee bangla gourab somman awards 2014 & best dancing sensation & none & won \\
29 & 2014 & filmfare awards east & global east people's choice filmfare award & none & won \\
30 & 2014 & 14th tele cine awards 2014 & 14th tele cine awards for best actor & chander pahar & pending \\
31 & 2014 & 14th tele cine awards 2014 & 14th tele cine awards for best jodi (dev-koel) & rangbaaz & pending \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "category" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( category ) where film = 'khoka 420,rangbaaz and chander pahar' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>award</th>
<th>category</th>
<th>film</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2009</td>
<td>anandalok awards</td>
<td>anandalok awards for best actor</td>
<td>challenge</td>
<td>won</td>
</tr>
<tr>
<th>1</th>
<td>2009</td>
<td>anandalok awards</td>
<td>anandalok awards for best action hero</td>
<td>challenge</td>
<td>won</td>
</tr>
<tr>
<th>2</th>
<td>2010</td>
<td>star jalsha entertainment awards 2010</td>
<td>star jalsha entertainment awards 2010 for best actor</td>
<td>poran jaye jolia re</td>
<td>won</td>
</tr>
<tr>
<th>3</th>
<td>2010</td>
<td>star jalsha entertainment awards 2010</td>
<td>star jalsha entertainment awards 2010 for best actor</td>
<td>dujone</td>
<td>nominated</td>
</tr>
<tr>
<th>4</th>
<td>2010</td>
<td>tele cine awards 2010</td>
<td>tele cine awards 2010 for best actor</td>
<td>challenge</td>
<td>won</td>
</tr>
<tr>
<th>5</th>
<td>2010</td>
<td>kalakar awards 2010</td>
<td>kalakar awards 2010 for best actor</td>
<td>challenge</td>
<td>won</td>
</tr>
<tr>
<th>6</th>
<td>2010</td>
<td>star ananda shera bangali awards 2010</td>
<td>star ananda shera notun protibha award</td>
<td>none</td>
<td>won</td>
</tr>
<tr>
<th>7</th>
<td>2010</td>
<td>anandalok awards 2010</td>
<td>anandalok awards 2010 for best actor (male)</td>
<td>le chakka</td>
<td>won</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>big bangla movie awards 2011</td>
<td>big bangla movie awards 2011 for best actor of the decade</td>
<td>none</td>
<td>won</td>
</tr>
<tr>
<th>9</th>
<td>2011</td>
<td>anandalok awards</td>
<td>anandalok awards for best actor</td>
<td>paglu</td>
<td>nominated</td>
</tr>
<tr>
<th>10</th>
<td>2011</td>
<td>star jalsha entertainment awards 2011</td>
<td>star jalsha entertainment awards 2011 for best dancing sensation</td>
<td>none</td>
<td>won</td>
</tr>
<tr>
<th>11</th>
<td>2011</td>
<td>zee bangla awards 2011</td>
<td>zee bangla awards 2011 for best actor</td>
<td>le chakka</td>
<td>nominated</td>
</tr>
<tr>
<th>12</th>
<td>2012</td>
<td>star guide bengali film awards 2012</td>
<td>star guide bengali film awards 2012 for best actor</td>
<td>paglu</td>
<td>won</td>
</tr>
<tr>
<th>13</th>
<td>2012</td>
<td>anandalok awards 2012</td>
<td>anandalok awards 2012 for best actor (male)</td>
<td>paglu 2</td>
<td>nominated</td>
</tr>
<tr>
<th>14</th>
<td>2012</td>
<td>zee bangla awards 2012</td>
<td>zee bangla awards 2012 for best actor</td>
<td>khokababu</td>
<td>won</td>
</tr>
<tr>
<th>15</th>
<td>2012</td>
<td>12th tele cine awards 2012</td>
<td>12th tele cine awards 2012 for best actor</td>
<td>paglu</td>
<td>won</td>
</tr>
<tr>
<th>16</th>
<td>2012</td>
<td>kalakar awards 2012</td>
<td>kalakar awards 2012 for best actor</td>
<td>paglu</td>
<td>won</td>
</tr>
<tr>
<th>17</th>
<td>2013</td>
<td>13th tele cine awards 2013</td>
<td>13th tele cine awards 2013 for best actor</td>
<td>challenge 2</td>
<td>nominated</td>
</tr>
<tr>
<th>18</th>
<td>2013</td>
<td>star jalsha entertainment awards 2013</td>
<td>star jalsha entertainment awards 2013 for best dancing sensation</td>
<td>none</td>
<td>won</td>
</tr>
<tr>
<th>19</th>
<td>2013</td>
<td>star jalsha entertainment awards 2013</td>
<td>star jalsha entertainment awards 2013 for best debut singing</td>
<td>khokababu</td>
<td>won</td>
</tr>
<tr>
<th>20</th>
<td>2014</td>
<td>most desirable tollywood actor 2014 (public poll)</td>
<td>best actor</td>
<td>khoka 420,rangbaaz and chander pahar</td>
<td>won</td>
</tr>
<tr>
<th>21</th>
<td>2014</td>
<td>tollywood national award 2014</td>
<td>best actor</td>
<td>chander pahar</td>
<td>won</td>
</tr>
<tr>
<th>22</th>
<td>2014</td>
<td>tollywood national award 2014</td>
<td>best romantic hero</td>
<td>khoka 420</td>
<td>nominated</td>
</tr>
<tr>
<th>23</th>
<td>2014</td>
<td>tollywood national award 2014</td>
<td>best action hero</td>
<td>rangbaaz</td>
<td>won</td>
</tr>
<tr>
<th>24</th>
<td>2014</td>
<td>kalakar awards 2014</td>
<td>kalakar awards 2014 for best actor</td>
<td>rangbaaz and chander pahar</td>
<td>won</td>
</tr>
<tr>
<th>25</th>
<td>2014</td>
<td>bfja award for best actor 2014</td>
<td>bfja award for best actor best actor</td>
<td>chander pahar</td>
<td>won</td>
</tr>
<tr>
<th>26</th>
<td>2014</td>
<td>zee bangla gourab somman awards 2014</td>
<td>best actor</td>
<td>chander pahar</td>
<td>won</td>
</tr>
<tr>
<th>27</th>
<td>2014</td>
<td>anandalok awards</td>
<td>best actor</td>
<td>chander pahar</td>
<td>won</td>
</tr>
<tr>
<th>28</th>
<td>2014</td>
<td>zee bangla gourab somman awards 2014</td>
<td>best dancing sensation</td>
<td>none</td>
<td>won</td>
</tr>
<tr>
<th>29</th>
<td>2014</td>
<td>filmfare awards east</td>
<td>global east people's choice filmfare award</td>
<td>none</td>
<td>won</td>
</tr>
<tr>
<th>30</th>
<td>2014</td>
<td>14th tele cine awards 2014</td>
<td>14th tele cine awards for best actor</td>
<td>chander pahar</td>
<td>pending</td>
</tr>
<tr>
<th>31</th>
<td>2014</td>
<td>14th tele cine awards 2014</td>
<td>14th tele cine awards for best jodi (dev-koel)</td>
<td>rangbaaz</td>
<td>pending</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "category" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( category ) where film = 'khoka 420,rangbaaz and chander pahar' <table_name> : table | | year | award | category | film | result |
|---:|-------:|:--------------------------------------------------|:-----------------------------------------------------------------|:-------------------------------------|:----------|
| 0 | 2009 | anandalok awards | anandalok awards for best actor | challenge | won |
| 1 | 2009 | anandalok awards | anandalok awards for best action hero | challenge | won |
| 2 | 2010 | star jalsha entertainment awards 2010 | star jalsha entertainment awards 2010 for best actor | poran jaye jolia re | won |
| 3 | 2010 | star jalsha entertainment awards 2010 | star jalsha entertainment awards 2010 for best actor | dujone | nominated |
| 4 | 2010 | tele cine awards 2010 | tele cine awards 2010 for best actor | challenge | won |
| 5 | 2010 | kalakar awards 2010 | kalakar awards 2010 for best actor | challenge | won |
| 6 | 2010 | star ananda shera bangali awards 2010 | star ananda shera notun protibha award | none | won |
| 7 | 2010 | anandalok awards 2010 | anandalok awards 2010 for best actor (male) | le chakka | won |
| 8 | 2011 | big bangla movie awards 2011 | big bangla movie awards 2011 for best actor of the decade | none | won |
| 9 | 2011 | anandalok awards | anandalok awards for best actor | paglu | nominated |
| 10 | 2011 | star jalsha entertainment awards 2011 | star jalsha entertainment awards 2011 for best dancing sensation | none | won |
| 11 | 2011 | zee bangla awards 2011 | zee bangla awards 2011 for best actor | le chakka | nominated |
| 12 | 2012 | star guide bengali film awards 2012 | star guide bengali film awards 2012 for best actor | paglu | won |
| 13 | 2012 | anandalok awards 2012 | anandalok awards 2012 for best actor (male) | paglu 2 | nominated |
| 14 | 2012 | zee bangla awards 2012 | zee bangla awards 2012 for best actor | khokababu | won |
| 15 | 2012 | 12th tele cine awards 2012 | 12th tele cine awards 2012 for best actor | paglu | won |
| 16 | 2012 | kalakar awards 2012 | kalakar awards 2012 for best actor | paglu | won |
| 17 | 2013 | 13th tele cine awards 2013 | 13th tele cine awards 2013 for best actor | challenge 2 | nominated |
| 18 | 2013 | star jalsha entertainment awards 2013 | star jalsha entertainment awards 2013 for best dancing sensation | none | won |
| 19 | 2013 | star jalsha entertainment awards 2013 | star jalsha entertainment awards 2013 for best debut singing | khokababu | won |
| 20 | 2014 | most desirable tollywood actor 2014 (public poll) | best actor | khoka 420,rangbaaz and chander pahar | won |
| 21 | 2014 | tollywood national award 2014 | best actor | chander pahar | won |
| 22 | 2014 | tollywood national award 2014 | best romantic hero | khoka 420 | nominated |
| 23 | 2014 | tollywood national award 2014 | best action hero | rangbaaz | won |
| 24 | 2014 | kalakar awards 2014 | kalakar awards 2014 for best actor | rangbaaz and chander pahar | won |
| 25 | 2014 | bfja award for best actor 2014 | bfja award for best actor best actor | chander pahar | won |
| 26 | 2014 | zee bangla gourab somman awards 2014 | best actor | chander pahar | won |
| 27 | 2014 | anandalok awards | best actor | chander pahar | won |
| 28 | 2014 | zee bangla gourab somman awards 2014 | best dancing sensation | none | won |
| 29 | 2014 | filmfare awards east | global east people's choice filmfare award | none | won |
| 30 | 2014 | 14th tele cine awards 2014 | 14th tele cine awards for best actor | chander pahar | pending |
| 31 | 2014 | 14th tele cine awards 2014 | 14th tele cine awards for best jodi (dev-koel) | rangbaaz | pending | | | | count ( "category" ) |
|---:|-----------------------:|
| 0 | 1 | | [
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select count ( single ) where album = 'a bizarre collection of the most unusual songs' col : year | single | chart positions us country | chart positions us | album row 1 : 1957 | "sittin' in the balcony" | none | 38 | single only row 2 : 1961 | "language of love" | none | 32 | language of love row 3 : 1962 | "thou shalt not steal" | none | 73 | singles only row 4 : 1962 | "callin' dr. casey" | none | 83 | singles only row 5 : 1962 | "road hog" | none | 65 | twelve sides row 6 : 1963 | "bad news" (b/w "guitar player(her and him)") | 23 | none | singles only row 7 : 1964 | "blue train (of the heartbreak line)" | 44 | 132 | singles only row 8 : 1964 | "th' wife" | 45 | none | singles only row 9 : 1965 | "that ain't all" | 20 | none | singles only row 10 : 1966 | "silver cloud talkin' blues" | none | none | a bizarre collection of the most unusual songs row 11 : 1966 | "you're the guilty one" | none | none | single only row 12 : 1967 | "it's my time" | 51 | none | suburban attitudes in country verse row 13 : 1968 | "odd folks of okracoke" | none | none | single only row 14 : 1969 | "brown girl" | none | none | the open mind of john d. loudermilk row 15 : 1971 | "lord have mercy" | none | none | volume 1-elloree row 16 : 1979 | "every day i learn a little more about love" | none | none | just passing through | col : count ( "single" ) row 1 : 1 | select count ( single ) where album = 'a bizarre collection of the most unusual songs' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & single & chart positions us country & chart positions us & album \\
\midrule
0 & 1957 & "sittin' in the balcony" & none & 38 & single only \\
1 & 1961 & "language of love" & none & 32 & language of love \\
2 & 1962 & "thou shalt not steal" & none & 73 & singles only \\
3 & 1962 & "callin' dr. casey" & none & 83 & singles only \\
4 & 1962 & "road hog" & none & 65 & twelve sides \\
5 & 1963 & "bad news" (b/w "guitar player(her and him)") & 23 & none & singles only \\
6 & 1964 & "blue train (of the heartbreak line)" & 44 & 132 & singles only \\
7 & 1964 & "th' wife" & 45 & none & singles only \\
8 & 1965 & "that ain't all" & 20 & none & singles only \\
9 & 1966 & "silver cloud talkin' blues" & none & none & a bizarre collection of the most unusual songs \\
10 & 1966 & "you're the guilty one" & none & none & single only \\
11 & 1967 & "it's my time" & 51 & none & suburban attitudes in country verse \\
12 & 1968 & "odd folks of okracoke" & none & none & single only \\
13 & 1969 & "brown girl" & none & none & the open mind of john d. loudermilk \\
14 & 1971 & "lord have mercy" & none & none & volume 1-elloree \\
15 & 1979 & "every day i learn a little more about love" & none & none & just passing through \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "single" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( single ) where album = 'a bizarre collection of the most unusual songs' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>single</th>
<th>chart positions us country</th>
<th>chart positions us</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1957</td>
<td>"sittin' in the balcony"</td>
<td>none</td>
<td>38</td>
<td>single only</td>
</tr>
<tr>
<th>1</th>
<td>1961</td>
<td>"language of love"</td>
<td>none</td>
<td>32</td>
<td>language of love</td>
</tr>
<tr>
<th>2</th>
<td>1962</td>
<td>"thou shalt not steal"</td>
<td>none</td>
<td>73</td>
<td>singles only</td>
</tr>
<tr>
<th>3</th>
<td>1962</td>
<td>"callin' dr. casey"</td>
<td>none</td>
<td>83</td>
<td>singles only</td>
</tr>
<tr>
<th>4</th>
<td>1962</td>
<td>"road hog"</td>
<td>none</td>
<td>65</td>
<td>twelve sides</td>
</tr>
<tr>
<th>5</th>
<td>1963</td>
<td>"bad news" (b/w "guitar player(her and him)")</td>
<td>23</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>6</th>
<td>1964</td>
<td>"blue train (of the heartbreak line)"</td>
<td>44</td>
<td>132</td>
<td>singles only</td>
</tr>
<tr>
<th>7</th>
<td>1964</td>
<td>"th' wife"</td>
<td>45</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>8</th>
<td>1965</td>
<td>"that ain't all"</td>
<td>20</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>9</th>
<td>1966</td>
<td>"silver cloud talkin' blues"</td>
<td>none</td>
<td>none</td>
<td>a bizarre collection of the most unusual songs</td>
</tr>
<tr>
<th>10</th>
<td>1966</td>
<td>"you're the guilty one"</td>
<td>none</td>
<td>none</td>
<td>single only</td>
</tr>
<tr>
<th>11</th>
<td>1967</td>
<td>"it's my time"</td>
<td>51</td>
<td>none</td>
<td>suburban attitudes in country verse</td>
</tr>
<tr>
<th>12</th>
<td>1968</td>
<td>"odd folks of okracoke"</td>
<td>none</td>
<td>none</td>
<td>single only</td>
</tr>
<tr>
<th>13</th>
<td>1969</td>
<td>"brown girl"</td>
<td>none</td>
<td>none</td>
<td>the open mind of john d. loudermilk</td>
</tr>
<tr>
<th>14</th>
<td>1971</td>
<td>"lord have mercy"</td>
<td>none</td>
<td>none</td>
<td>volume 1-elloree</td>
</tr>
<tr>
<th>15</th>
<td>1979</td>
<td>"every day i learn a little more about love"</td>
<td>none</td>
<td>none</td>
<td>just passing through</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "single" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( single ) where album = 'a bizarre collection of the most unusual songs' <table_name> : table | | year | single | chart positions us country | chart positions us | album |
|---:|-------:|:----------------------------------------------|:-----------------------------|:---------------------|:-----------------------------------------------|
| 0 | 1957 | "sittin' in the balcony" | none | 38 | single only |
| 1 | 1961 | "language of love" | none | 32 | language of love |
| 2 | 1962 | "thou shalt not steal" | none | 73 | singles only |
| 3 | 1962 | "callin' dr. casey" | none | 83 | singles only |
| 4 | 1962 | "road hog" | none | 65 | twelve sides |
| 5 | 1963 | "bad news" (b/w "guitar player(her and him)") | 23 | none | singles only |
| 6 | 1964 | "blue train (of the heartbreak line)" | 44 | 132 | singles only |
| 7 | 1964 | "th' wife" | 45 | none | singles only |
| 8 | 1965 | "that ain't all" | 20 | none | singles only |
| 9 | 1966 | "silver cloud talkin' blues" | none | none | a bizarre collection of the most unusual songs |
| 10 | 1966 | "you're the guilty one" | none | none | single only |
| 11 | 1967 | "it's my time" | 51 | none | suburban attitudes in country verse |
| 12 | 1968 | "odd folks of okracoke" | none | none | single only |
| 13 | 1969 | "brown girl" | none | none | the open mind of john d. loudermilk |
| 14 | 1971 | "lord have mercy" | none | none | volume 1-elloree |
| 15 | 1979 | "every day i learn a little more about love" | none | none | just passing through | | | | count ( "single" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select no where pos = '7' col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 5 | nigel mansell | williams-renault | 65 | 1:56:10.674 | 1 | 10 row 2 : 2 | 19 | michael schumacher | benetton-ford | 65 | + 23.914 | 2 | 6 row 3 : 3 | 27 | jean alesi | ferrari | 65 | + 26.462 | 8 | 4 row 4 : 4 | 2 | gerhard berger | mclaren-honda | 65 | + 1:20.647 | 7 | 3 row 5 : 5 | 9 | michele alboreto | footwork-mugen-honda | 64 | + 1 lap | 16 | 2 row 6 : 6 | 22 | pierluigi martini | dallara-ferrari | 63 | + 2 laps | 13 | 1 row 7 : 7 | 10 | aguri suzuki | footwork-mugen-honda | 63 | + 2 laps | 19 | none row 8 : 8 | 16 | karl wendlinger | march-ilmor | 63 | + 2 laps | 9 | none row 9 : 9 | 1 | ayrton senna | mclaren-honda | 62 | spun off | 3 | none row 10 : 10 | 28 | ivan capelli | ferrari | 62 | spun off | 5 | none row 11 : 11 | 23 | christian fittipaldi | minardi-lamborghini | 61 | + 4 laps | 22 | none row 12 : 12 | 17 | paul belmondo | march-ilmor | 61 | + 4 laps | 23 | none row 13 : ret | 21 | jj lehto | dallara-ferrari | 56 | spun off | 12 | none row 14 : ret | 15 | gabriele tarquini | fondmetal-ford | 56 | spun off | 18 | none row 15 : ret | 11 | mika hakkinen | lotus-ford | 56 | spun off | 21 | none row 16 : ret | 26 | erik comas | ligier-renault | 55 | spun off | 10 | none row 17 : ret | 29 | bertrand gachot | larrousse-lamborghini | 35 | engine | 24 | none row 18 : ret | 3 | olivier grouillard | tyrrell-ilmor | 30 | spun off | 15 | none row 19 : ret | 24 | gianni morbidelli | minardi-lamborghini | 26 | handling | 25 | none row 20 : ret | 33 | mauricio gugelmin | jordan-yamaha | 24 | spun off | 17 | none row 21 : ret | 14 | andrea chiesa | fondmetal-ford | 22 | spun off | 20 | none row 22 : ret | 6 | riccardo patrese | williams-renault | 19 | spun off | 4 | none row 23 : ret | 12 | johnny herbert | lotus-ford | 13 | spun off | 26 | none row 24 : ret | 25 | thierry boutsen | ligier-renault | 11 | engine | 14 | none row 25 : ret | 20 | martin brundle | benetton-ford | 4 | spun off | 6 | none row 26 : ret | 4 | andrea de cesaris | tyrrell-ilmor | 2 | engine | 11 | none row 27 : dnq | 30 | ukyo katayama | larrousse-lamborghini | none | none | none | none row 28 : dnq | 7 | eric van de poele | brabham-judd | none | none | none | none row 29 : dnq | 32 | stefano modena | jordan-yamaha | none | none | none | none row 30 : dnq | 8 | damon hill | brabham-judd | none | none | none | none row 31 : dnpq | 34 | roberto moreno | moda-judd | none | none | none | none row 32 : dnpq | 35 | perry mccarthy | moda-judd | none | none | none | none | col : no row 1 : 10 | select no where pos = '7' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 5 & nigel mansell & williams-renault & 65 & 1:56:10.674 & 1 & 10 \\
1 & 2 & 19 & michael schumacher & benetton-ford & 65 & + 23.914 & 2 & 6 \\
2 & 3 & 27 & jean alesi & ferrari & 65 & + 26.462 & 8 & 4 \\
3 & 4 & 2 & gerhard berger & mclaren-honda & 65 & + 1:20.647 & 7 & 3 \\
4 & 5 & 9 & michele alboreto & footwork-mugen-honda & 64 & + 1 lap & 16 & 2 \\
5 & 6 & 22 & pierluigi martini & dallara-ferrari & 63 & + 2 laps & 13 & 1 \\
6 & 7 & 10 & aguri suzuki & footwork-mugen-honda & 63 & + 2 laps & 19 & none \\
7 & 8 & 16 & karl wendlinger & march-ilmor & 63 & + 2 laps & 9 & none \\
8 & 9 & 1 & ayrton senna & mclaren-honda & 62 & spun off & 3 & none \\
9 & 10 & 28 & ivan capelli & ferrari & 62 & spun off & 5 & none \\
10 & 11 & 23 & christian fittipaldi & minardi-lamborghini & 61 & + 4 laps & 22 & none \\
11 & 12 & 17 & paul belmondo & march-ilmor & 61 & + 4 laps & 23 & none \\
12 & ret & 21 & jj lehto & dallara-ferrari & 56 & spun off & 12 & none \\
13 & ret & 15 & gabriele tarquini & fondmetal-ford & 56 & spun off & 18 & none \\
14 & ret & 11 & mika hakkinen & lotus-ford & 56 & spun off & 21 & none \\
15 & ret & 26 & erik comas & ligier-renault & 55 & spun off & 10 & none \\
16 & ret & 29 & bertrand gachot & larrousse-lamborghini & 35 & engine & 24 & none \\
17 & ret & 3 & olivier grouillard & tyrrell-ilmor & 30 & spun off & 15 & none \\
18 & ret & 24 & gianni morbidelli & minardi-lamborghini & 26 & handling & 25 & none \\
19 & ret & 33 & mauricio gugelmin & jordan-yamaha & 24 & spun off & 17 & none \\
20 & ret & 14 & andrea chiesa & fondmetal-ford & 22 & spun off & 20 & none \\
21 & ret & 6 & riccardo patrese & williams-renault & 19 & spun off & 4 & none \\
22 & ret & 12 & johnny herbert & lotus-ford & 13 & spun off & 26 & none \\
23 & ret & 25 & thierry boutsen & ligier-renault & 11 & engine & 14 & none \\
24 & ret & 20 & martin brundle & benetton-ford & 4 & spun off & 6 & none \\
25 & ret & 4 & andrea de cesaris & tyrrell-ilmor & 2 & engine & 11 & none \\
26 & dnq & 30 & ukyo katayama & larrousse-lamborghini & none & none & none & none \\
27 & dnq & 7 & eric van de poele & brabham-judd & none & none & none & none \\
28 & dnq & 32 & stefano modena & jordan-yamaha & none & none & none & none \\
29 & dnq & 8 & damon hill & brabham-judd & none & none & none & none \\
30 & dnpq & 34 & roberto moreno & moda-judd & none & none & none & none \\
31 & dnpq & 35 & perry mccarthy & moda-judd & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& no \\
\midrule
0 & 10 \\
\bottomrule
\end{tabular}
| select no where pos = '7' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>driver</th>
<th>constructor</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>5</td>
<td>nigel mansell</td>
<td>williams-renault</td>
<td>65</td>
<td>1:56:10.674</td>
<td>1</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>19</td>
<td>michael schumacher</td>
<td>benetton-ford</td>
<td>65</td>
<td>+ 23.914</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>27</td>
<td>jean alesi</td>
<td>ferrari</td>
<td>65</td>
<td>+ 26.462</td>
<td>8</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2</td>
<td>gerhard berger</td>
<td>mclaren-honda</td>
<td>65</td>
<td>+ 1:20.647</td>
<td>7</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>9</td>
<td>michele alboreto</td>
<td>footwork-mugen-honda</td>
<td>64</td>
<td>+ 1 lap</td>
<td>16</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>22</td>
<td>pierluigi martini</td>
<td>dallara-ferrari</td>
<td>63</td>
<td>+ 2 laps</td>
<td>13</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>10</td>
<td>aguri suzuki</td>
<td>footwork-mugen-honda</td>
<td>63</td>
<td>+ 2 laps</td>
<td>19</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>16</td>
<td>karl wendlinger</td>
<td>march-ilmor</td>
<td>63</td>
<td>+ 2 laps</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>1</td>
<td>ayrton senna</td>
<td>mclaren-honda</td>
<td>62</td>
<td>spun off</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>28</td>
<td>ivan capelli</td>
<td>ferrari</td>
<td>62</td>
<td>spun off</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>23</td>
<td>christian fittipaldi</td>
<td>minardi-lamborghini</td>
<td>61</td>
<td>+ 4 laps</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>17</td>
<td>paul belmondo</td>
<td>march-ilmor</td>
<td>61</td>
<td>+ 4 laps</td>
<td>23</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>ret</td>
<td>21</td>
<td>jj lehto</td>
<td>dallara-ferrari</td>
<td>56</td>
<td>spun off</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>ret</td>
<td>15</td>
<td>gabriele tarquini</td>
<td>fondmetal-ford</td>
<td>56</td>
<td>spun off</td>
<td>18</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>ret</td>
<td>11</td>
<td>mika hakkinen</td>
<td>lotus-ford</td>
<td>56</td>
<td>spun off</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>ret</td>
<td>26</td>
<td>erik comas</td>
<td>ligier-renault</td>
<td>55</td>
<td>spun off</td>
<td>10</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>ret</td>
<td>29</td>
<td>bertrand gachot</td>
<td>larrousse-lamborghini</td>
<td>35</td>
<td>engine</td>
<td>24</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>3</td>
<td>olivier grouillard</td>
<td>tyrrell-ilmor</td>
<td>30</td>
<td>spun off</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>24</td>
<td>gianni morbidelli</td>
<td>minardi-lamborghini</td>
<td>26</td>
<td>handling</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>33</td>
<td>mauricio gugelmin</td>
<td>jordan-yamaha</td>
<td>24</td>
<td>spun off</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>14</td>
<td>andrea chiesa</td>
<td>fondmetal-ford</td>
<td>22</td>
<td>spun off</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>ret</td>
<td>6</td>
<td>riccardo patrese</td>
<td>williams-renault</td>
<td>19</td>
<td>spun off</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>ret</td>
<td>12</td>
<td>johnny herbert</td>
<td>lotus-ford</td>
<td>13</td>
<td>spun off</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>ret</td>
<td>25</td>
<td>thierry boutsen</td>
<td>ligier-renault</td>
<td>11</td>
<td>engine</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>20</td>
<td>martin brundle</td>
<td>benetton-ford</td>
<td>4</td>
<td>spun off</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>4</td>
<td>andrea de cesaris</td>
<td>tyrrell-ilmor</td>
<td>2</td>
<td>engine</td>
<td>11</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>dnq</td>
<td>30</td>
<td>ukyo katayama</td>
<td>larrousse-lamborghini</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>dnq</td>
<td>7</td>
<td>eric van de poele</td>
<td>brabham-judd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>dnq</td>
<td>32</td>
<td>stefano modena</td>
<td>jordan-yamaha</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>dnq</td>
<td>8</td>
<td>damon hill</td>
<td>brabham-judd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>dnpq</td>
<td>34</td>
<td>roberto moreno</td>
<td>moda-judd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>dnpq</td>
<td>35</td>
<td>perry mccarthy</td>
<td>moda-judd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>10</td>
</tr>
</tbody>
</table> | select no where pos = '7' <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:---------------------|:----------------------|:-------|:---------------|:-------|:---------|
| 0 | 1 | 5 | nigel mansell | williams-renault | 65 | 1:56:10.674 | 1 | 10 |
| 1 | 2 | 19 | michael schumacher | benetton-ford | 65 | + 23.914 | 2 | 6 |
| 2 | 3 | 27 | jean alesi | ferrari | 65 | + 26.462 | 8 | 4 |
| 3 | 4 | 2 | gerhard berger | mclaren-honda | 65 | + 1:20.647 | 7 | 3 |
| 4 | 5 | 9 | michele alboreto | footwork-mugen-honda | 64 | + 1 lap | 16 | 2 |
| 5 | 6 | 22 | pierluigi martini | dallara-ferrari | 63 | + 2 laps | 13 | 1 |
| 6 | 7 | 10 | aguri suzuki | footwork-mugen-honda | 63 | + 2 laps | 19 | none |
| 7 | 8 | 16 | karl wendlinger | march-ilmor | 63 | + 2 laps | 9 | none |
| 8 | 9 | 1 | ayrton senna | mclaren-honda | 62 | spun off | 3 | none |
| 9 | 10 | 28 | ivan capelli | ferrari | 62 | spun off | 5 | none |
| 10 | 11 | 23 | christian fittipaldi | minardi-lamborghini | 61 | + 4 laps | 22 | none |
| 11 | 12 | 17 | paul belmondo | march-ilmor | 61 | + 4 laps | 23 | none |
| 12 | ret | 21 | jj lehto | dallara-ferrari | 56 | spun off | 12 | none |
| 13 | ret | 15 | gabriele tarquini | fondmetal-ford | 56 | spun off | 18 | none |
| 14 | ret | 11 | mika hakkinen | lotus-ford | 56 | spun off | 21 | none |
| 15 | ret | 26 | erik comas | ligier-renault | 55 | spun off | 10 | none |
| 16 | ret | 29 | bertrand gachot | larrousse-lamborghini | 35 | engine | 24 | none |
| 17 | ret | 3 | olivier grouillard | tyrrell-ilmor | 30 | spun off | 15 | none |
| 18 | ret | 24 | gianni morbidelli | minardi-lamborghini | 26 | handling | 25 | none |
| 19 | ret | 33 | mauricio gugelmin | jordan-yamaha | 24 | spun off | 17 | none |
| 20 | ret | 14 | andrea chiesa | fondmetal-ford | 22 | spun off | 20 | none |
| 21 | ret | 6 | riccardo patrese | williams-renault | 19 | spun off | 4 | none |
| 22 | ret | 12 | johnny herbert | lotus-ford | 13 | spun off | 26 | none |
| 23 | ret | 25 | thierry boutsen | ligier-renault | 11 | engine | 14 | none |
| 24 | ret | 20 | martin brundle | benetton-ford | 4 | spun off | 6 | none |
| 25 | ret | 4 | andrea de cesaris | tyrrell-ilmor | 2 | engine | 11 | none |
| 26 | dnq | 30 | ukyo katayama | larrousse-lamborghini | none | none | none | none |
| 27 | dnq | 7 | eric van de poele | brabham-judd | none | none | none | none |
| 28 | dnq | 32 | stefano modena | jordan-yamaha | none | none | none | none |
| 29 | dnq | 8 | damon hill | brabham-judd | none | none | none | none |
| 30 | dnpq | 34 | roberto moreno | moda-judd | none | none | none | none |
| 31 | dnpq | 35 | perry mccarthy | moda-judd | none | none | none | none | | | | no |
|---:|-----:|
| 0 | 10 | | [
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select count ( album title ) where album title < 516 col : album title | format | year | original label | chart positions row 1 : distant plastic trees | lp | 1991.0 | red flame | none row 2 : the wayward bus | lp | 1992.0 | popup | none row 3 : the house of tomor | | | | row 4 : | ep | 1992.0 | feel good all over | none row 5 : the charm of the highway strip | lp | 1994.0 | merge records | none row 6 : holiday | lp | 1994.0 | feel good all over | none row 7 : get lost | lp | 1995.0 | merge records | none row 8 : 69 love songs | lp | 1999.0 | merge records | none row 9 : i | lp | 2004.0 | nonesuch records | #152 (billboard 200) row 10 : distortion | lp | 2008.0 | nonesuch records | #77 (billboard 200) row 11 : realism | lp | 2010.0 | nonesuch records | #110 (billboard 200) row 12 : love at the bottom of the sea | lp | 2012.0 | merge records | #89 (billboard 200) | col : count ( "album title" ) row 1 : 1 | select count ( album title ) where album title < 516 <table_name> : table \begin{tabular}{llllll}
\toprule
& album title & format & year & original label & chart positions \\
\midrule
0 & distant plastic trees & lp & 1991.0 & red flame & none \\
1 & the wayward bus & lp & 1992.0 & popup & none \\
2 & the house of tomor & & & & \\
3 & & ep & 1992.0 & feel good all over & none \\
4 & the charm of the highway strip & lp & 1994.0 & merge records & none \\
5 & holiday & lp & 1994.0 & feel good all over & none \\
6 & get lost & lp & 1995.0 & merge records & none \\
7 & 69 love songs & lp & 1999.0 & merge records & none \\
8 & i & lp & 2004.0 & nonesuch records & #152 (billboard 200) \\
9 & distortion & lp & 2008.0 & nonesuch records & #77 (billboard 200) \\
10 & realism & lp & 2010.0 & nonesuch records & #110 (billboard 200) \\
11 & love at the bottom of the sea & lp & 2012.0 & merge records & #89 (billboard 200) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "album title" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( album title ) where album title < 516 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>album title</th>
<th>format</th>
<th>year</th>
<th>original label</th>
<th>chart positions</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>distant plastic trees</td>
<td>lp</td>
<td>1991.0</td>
<td>red flame</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>the wayward bus</td>
<td>lp</td>
<td>1992.0</td>
<td>popup</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>the house of tomor</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>3</th>
<td></td>
<td>ep</td>
<td>1992.0</td>
<td>feel good all over</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>the charm of the highway strip</td>
<td>lp</td>
<td>1994.0</td>
<td>merge records</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>holiday</td>
<td>lp</td>
<td>1994.0</td>
<td>feel good all over</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>get lost</td>
<td>lp</td>
<td>1995.0</td>
<td>merge records</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>69 love songs</td>
<td>lp</td>
<td>1999.0</td>
<td>merge records</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>i</td>
<td>lp</td>
<td>2004.0</td>
<td>nonesuch records</td>
<td>#152 (billboard 200)</td>
</tr>
<tr>
<th>9</th>
<td>distortion</td>
<td>lp</td>
<td>2008.0</td>
<td>nonesuch records</td>
<td>#77 (billboard 200)</td>
</tr>
<tr>
<th>10</th>
<td>realism</td>
<td>lp</td>
<td>2010.0</td>
<td>nonesuch records</td>
<td>#110 (billboard 200)</td>
</tr>
<tr>
<th>11</th>
<td>love at the bottom of the sea</td>
<td>lp</td>
<td>2012.0</td>
<td>merge records</td>
<td>#89 (billboard 200)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "album title" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( album title ) where album title < 516 <table_name> : table | | album title | format | year | original label | chart positions |
|---:|:-------------------------------|:---------|:-------|:-------------------|:---------------------|
| 0 | distant plastic trees | lp | 1991.0 | red flame | none |
| 1 | the wayward bus | lp | 1992.0 | popup | none |
| 2 | the house of tomor | | | | |
| 3 | | ep | 1992.0 | feel good all over | none |
| 4 | the charm of the highway strip | lp | 1994.0 | merge records | none |
| 5 | holiday | lp | 1994.0 | feel good all over | none |
| 6 | get lost | lp | 1995.0 | merge records | none |
| 7 | 69 love songs | lp | 1999.0 | merge records | none |
| 8 | i | lp | 2004.0 | nonesuch records | #152 (billboard 200) |
| 9 | distortion | lp | 2008.0 | nonesuch records | #77 (billboard 200) |
| 10 | realism | lp | 2010.0 | nonesuch records | #110 (billboard 200) |
| 11 | love at the bottom of the sea | lp | 2012.0 | merge records | #89 (billboard 200) | | | | count ( "album title" ) |
|---:|--------------------------:|
| 0 | 1 | | [
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select episode where name = 'battle by the beach' col : episode | name | synopsis | sent home | highest seller row 1 : 1 | vegas meltdown | nine aspiring restaurateurs arrive in las vegas, where they meet chef robert irvine and the restaurant express bus. in order to secure one of the eight spots on board, they must first pitch their dream restaurant concept to robert: those with the best concepts head into lake las vegas for the first challenge. they'll have to create a restaurant from the ground up with just $500 and six hours to feed 250 hungry guests! the bottom three earners will be up for elimination | ammerah, kimmy | patrick row 2 : 2 | tantrum in temecula | the restaurant express bus arrives in temecula, calif., a small, upscale town with lots of restaurants. the contestants' market knowledge is tested when they must propose to robert and the mayor a new restaurant that they think could be successful in the town. the winner of the mini challenge will get extra money for the main challenge, where they will test their restaurant ideas on the locals at a lunch fair. the bottom three earners will be up for elimination | johnathan | eric row 3 : 3 | express: impossible | the restaurant express bus arrives in los angeles, where the contestants face their first group challenge. inspired by restaurant: impossible, the teams will be given 24 hours and $5,000 to revitalize two struggling restaurants. robert and two visiting critics will dine at each location to determine who won this round, and who will be off the bus | bianca | none row 4 : 4 | battle by the beach | the restaurant express bus arrives at the iconic balboa pier in newport beach, calif. the remaining five contestants will each have to open a concession stand with the same three dishes; a burger, a dessert and something on a stick. they also must produce a commercial for their stand. the contestant with the best commercial gets to have their ad play on the pier, but will that marketing advantage be enough to draw the most customers? | patrick | eric row 5 : 5 | going, going, gone! | the remaining four contestants are given their biggest budget challenge: create a supper club with $1,000 and an empty restaurant shell. they first attend an auction with items that could be a big benefit during dinner service, challenging them to spend wisely for an advantage, with enough money left over for food and supplies | eric | adam row 6 : 6 | the truck stops here! | the three remaining chefs are each given a food truck and are challenged on their ability to serve specific groups of diners at three iconic locations: a zoo, an upscale shopping center and a late night bar scene. the winner gets a big advantage heading into the final challenge | none | adam row 7 : 7 | vegas or bust | jan and seonkyoung battle to see who would face adam in the final challenge. seonkyoung won, therefore advancing herself to the final challenge. the two finalists then competed head-to-head against each other in the same restaurant. in the end, seonkyoung beat adam and she won a restaurant in the m, named jade | jan, adam | seonkyoung | col : episode row 1 : 4 | select episode where name = 'battle by the beach' <table_name> : table \begin{tabular}{llllll}
\toprule
& episode & name & synopsis & sent home & highest seller \\
\midrule
0 & 1 & vegas meltdown & nine aspiring restaurateurs arrive in las vegas, where they meet chef robert irvine and the restaurant express bus. in order to secure one of the eight spots on board, they must first pitch their dream restaurant concept to robert: those with the best concepts head into lake las vegas for the first challenge. they'll have to create a restaurant from the ground up with just $500 and six hours to feed 250 hungry guests! the bottom three earners will be up for elimination & ammerah, kimmy & patrick \\
1 & 2 & tantrum in temecula & the restaurant express bus arrives in temecula, calif., a small, upscale town with lots of restaurants. the contestants' market knowledge is tested when they must propose to robert and the mayor a new restaurant that they think could be successful in the town. the winner of the mini challenge will get extra money for the main challenge, where they will test their restaurant ideas on the locals at a lunch fair. the bottom three earners will be up for elimination & johnathan & eric \\
2 & 3 & express: impossible & the restaurant express bus arrives in los angeles, where the contestants face their first group challenge. inspired by restaurant: impossible, the teams will be given 24 hours and $5,000 to revitalize two struggling restaurants. robert and two visiting critics will dine at each location to determine who won this round, and who will be off the bus & bianca & none \\
3 & 4 & battle by the beach & the restaurant express bus arrives at the iconic balboa pier in newport beach, calif. the remaining five contestants will each have to open a concession stand with the same three dishes; a burger, a dessert and something on a stick. they also must produce a commercial for their stand. the contestant with the best commercial gets to have their ad play on the pier, but will that marketing advantage be enough to draw the most customers? & patrick & eric \\
4 & 5 & going, going, gone! & the remaining four contestants are given their biggest budget challenge: create a supper club with $1,000 and an empty restaurant shell. they first attend an auction with items that could be a big benefit during dinner service, challenging them to spend wisely for an advantage, with enough money left over for food and supplies & eric & adam \\
5 & 6 & the truck stops here! & the three remaining chefs are each given a food truck and are challenged on their ability to serve specific groups of diners at three iconic locations: a zoo, an upscale shopping center and a late night bar scene. the winner gets a big advantage heading into the final challenge & none & adam \\
6 & 7 & vegas or bust & jan and seonkyoung battle to see who would face adam in the final challenge. seonkyoung won, therefore advancing herself to the final challenge. the two finalists then competed head-to-head against each other in the same restaurant. in the end, seonkyoung beat adam and she won a restaurant in the m, named jade & jan, adam & seonkyoung \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& episode \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select episode where name = 'battle by the beach' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>episode</th>
<th>name</th>
<th>synopsis</th>
<th>sent home</th>
<th>highest seller</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>vegas meltdown</td>
<td>nine aspiring restaurateurs arrive in las vegas, where they meet chef robert irvine and the restaurant express bus. in order to secure one of the eight spots on board, they must first pitch their dream restaurant concept to robert: those with the best concepts head into lake las vegas for the first challenge. they'll have to create a restaurant from the ground up with just $500 and six hours to feed 250 hungry guests! the bottom three earners will be up for elimination</td>
<td>ammerah, kimmy</td>
<td>patrick</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>tantrum in temecula</td>
<td>the restaurant express bus arrives in temecula, calif., a small, upscale town with lots of restaurants. the contestants' market knowledge is tested when they must propose to robert and the mayor a new restaurant that they think could be successful in the town. the winner of the mini challenge will get extra money for the main challenge, where they will test their restaurant ideas on the locals at a lunch fair. the bottom three earners will be up for elimination</td>
<td>johnathan</td>
<td>eric</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>express: impossible</td>
<td>the restaurant express bus arrives in los angeles, where the contestants face their first group challenge. inspired by restaurant: impossible, the teams will be given 24 hours and $5,000 to revitalize two struggling restaurants. robert and two visiting critics will dine at each location to determine who won this round, and who will be off the bus</td>
<td>bianca</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>battle by the beach</td>
<td>the restaurant express bus arrives at the iconic balboa pier in newport beach, calif. the remaining five contestants will each have to open a concession stand with the same three dishes; a burger, a dessert and something on a stick. they also must produce a commercial for their stand. the contestant with the best commercial gets to have their ad play on the pier, but will that marketing advantage be enough to draw the most customers?</td>
<td>patrick</td>
<td>eric</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>going, going, gone!</td>
<td>the remaining four contestants are given their biggest budget challenge: create a supper club with $1,000 and an empty restaurant shell. they first attend an auction with items that could be a big benefit during dinner service, challenging them to spend wisely for an advantage, with enough money left over for food and supplies</td>
<td>eric</td>
<td>adam</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>the truck stops here!</td>
<td>the three remaining chefs are each given a food truck and are challenged on their ability to serve specific groups of diners at three iconic locations: a zoo, an upscale shopping center and a late night bar scene. the winner gets a big advantage heading into the final challenge</td>
<td>none</td>
<td>adam</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>vegas or bust</td>
<td>jan and seonkyoung battle to see who would face adam in the final challenge. seonkyoung won, therefore advancing herself to the final challenge. the two finalists then competed head-to-head against each other in the same restaurant. in the end, seonkyoung beat adam and she won a restaurant in the m, named jade</td>
<td>jan, adam</td>
<td>seonkyoung</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>episode</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select episode where name = 'battle by the beach' <table_name> : table | | episode | name | synopsis | sent home | highest seller |
|---:|----------:|:----------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|:-----------------|
| 0 | 1 | vegas meltdown | nine aspiring restaurateurs arrive in las vegas, where they meet chef robert irvine and the restaurant express bus. in order to secure one of the eight spots on board, they must first pitch their dream restaurant concept to robert: those with the best concepts head into lake las vegas for the first challenge. they'll have to create a restaurant from the ground up with just $500 and six hours to feed 250 hungry guests! the bottom three earners will be up for elimination | ammerah, kimmy | patrick |
| 1 | 2 | tantrum in temecula | the restaurant express bus arrives in temecula, calif., a small, upscale town with lots of restaurants. the contestants' market knowledge is tested when they must propose to robert and the mayor a new restaurant that they think could be successful in the town. the winner of the mini challenge will get extra money for the main challenge, where they will test their restaurant ideas on the locals at a lunch fair. the bottom three earners will be up for elimination | johnathan | eric |
| 2 | 3 | express: impossible | the restaurant express bus arrives in los angeles, where the contestants face their first group challenge. inspired by restaurant: impossible, the teams will be given 24 hours and $5,000 to revitalize two struggling restaurants. robert and two visiting critics will dine at each location to determine who won this round, and who will be off the bus | bianca | none |
| 3 | 4 | battle by the beach | the restaurant express bus arrives at the iconic balboa pier in newport beach, calif. the remaining five contestants will each have to open a concession stand with the same three dishes; a burger, a dessert and something on a stick. they also must produce a commercial for their stand. the contestant with the best commercial gets to have their ad play on the pier, but will that marketing advantage be enough to draw the most customers? | patrick | eric |
| 4 | 5 | going, going, gone! | the remaining four contestants are given their biggest budget challenge: create a supper club with $1,000 and an empty restaurant shell. they first attend an auction with items that could be a big benefit during dinner service, challenging them to spend wisely for an advantage, with enough money left over for food and supplies | eric | adam |
| 5 | 6 | the truck stops here! | the three remaining chefs are each given a food truck and are challenged on their ability to serve specific groups of diners at three iconic locations: a zoo, an upscale shopping center and a late night bar scene. the winner gets a big advantage heading into the final challenge | none | adam |
| 6 | 7 | vegas or bust | jan and seonkyoung battle to see who would face adam in the final challenge. seonkyoung won, therefore advancing herself to the final challenge. the two finalists then competed head-to-head against each other in the same restaurant. in the end, seonkyoung beat adam and she won a restaurant in the m, named jade | jan, adam | seonkyoung | | | | episode |
|---:|----------:|
| 0 | 4 | | [
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select institution where graduate enrollment > 1492 col : institution | location | athletic nickname | undergraduate enrollment | graduate enrollment | total enrollment | 2013 endowment (and us rank) | academic staff | motto row 1 : brown university | providence, rhode island | bears | 6316 | 2333 | 8649 | $2.7 billion (30th) | 736 | in deo speramus (in god we hope) row 2 : columbia university | new york, new york | lions | 7160 | 15760 | 22920 | $8.2 billion (9th) | 3763 | in lumine tuo videbimus lumen (in thy light shall we see the light) row 3 : cornell university | ithaca, new york | big red | 13931 | 6702 | 20633 | $5.3 billion (18th) | 2908 | i would found an institution where any person can find instruction in any study row 4 : dartmouth college | hanover, new hampshire | big green | 4248 | 1893 | 6141 | $3.7 billion (22nd) | 571 | vox clamantis in deserto (the voice of one crying in the wilderness) row 5 : harvard university | cambridge, massachusetts | crimson | 7181 | 14044 | 21225 | $32.3 billion (1st) | 4671 | veritas (truth) row 6 : princeton university | princeton, new jersey | tigers | 5113 | 2479 | 7592 | $18.2 billion (5th) | 1172 | dei sub numine viget (under god's power she flourishes) row 7 : university of pennsylvania | philadelphia, pennsylvania | quakers | 10337 | 10306 | 20643 | $7.7 billion (11th) | 4464 | leges sine moribus vanae (laws without morals are useless) row 8 : yale university | new haven, connecticut | bulldogs | 5275 | 6391 | 11666 | $20.8 billion (2nd) | 4140 | אורים ותומים lux et veritas (light and truth) | col : institution row 1 : brown university row 2 : columbia university row 3 : cornell university row 4 : dartmouth college row 5 : princeton university row 6 : yale university | select institution where graduate enrollment > 1492 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& institution & location & athletic nickname & undergraduate enrollment & graduate enrollment & total enrollment & 2013 endowment (and us rank) & academic staff & motto \\
\midrule
0 & brown university & providence, rhode island & bears & 6316 & 2333 & 8649 & $2.7 billion (30th) & 736 & in deo speramus (in god we hope) \\
1 & columbia university & new york, new york & lions & 7160 & 15760 & 22920 & $8.2 billion (9th) & 3763 & in lumine tuo videbimus lumen (in thy light shall we see the light) \\
2 & cornell university & ithaca, new york & big red & 13931 & 6702 & 20633 & $5.3 billion (18th) & 2908 & i would found an institution where any person can find instruction in any study \\
3 & dartmouth college & hanover, new hampshire & big green & 4248 & 1893 & 6141 & $3.7 billion (22nd) & 571 & vox clamantis in deserto (the voice of one crying in the wilderness) \\
4 & harvard university & cambridge, massachusetts & crimson & 7181 & 14044 & 21225 & $32.3 billion (1st) & 4671 & veritas (truth) \\
5 & princeton university & princeton, new jersey & tigers & 5113 & 2479 & 7592 & $18.2 billion (5th) & 1172 & dei sub numine viget (under god's power she flourishes) \\
6 & university of pennsylvania & philadelphia, pennsylvania & quakers & 10337 & 10306 & 20643 & $7.7 billion (11th) & 4464 & leges sine moribus vanae (laws without morals are useless) \\
7 & yale university & new haven, connecticut & bulldogs & 5275 & 6391 & 11666 & $20.8 billion (2nd) & 4140 & אורים ותומים lux et veritas (light and truth) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& institution \\
\midrule
0 & brown university \\
1 & columbia university \\
2 & cornell university \\
3 & dartmouth college \\
4 & princeton university \\
5 & yale university \\
\bottomrule
\end{tabular}
| select institution where graduate enrollment > 1492 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>institution</th>
<th>location</th>
<th>athletic nickname</th>
<th>undergraduate enrollment</th>
<th>graduate enrollment</th>
<th>total enrollment</th>
<th>2013 endowment (and us rank)</th>
<th>academic staff</th>
<th>motto</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>brown university</td>
<td>providence, rhode island</td>
<td>bears</td>
<td>6316</td>
<td>2333</td>
<td>8649</td>
<td>$2.7 billion (30th)</td>
<td>736</td>
<td>in deo speramus (in god we hope)</td>
</tr>
<tr>
<th>1</th>
<td>columbia university</td>
<td>new york, new york</td>
<td>lions</td>
<td>7160</td>
<td>15760</td>
<td>22920</td>
<td>$8.2 billion (9th)</td>
<td>3763</td>
<td>in lumine tuo videbimus lumen (in thy light shall we see the light)</td>
</tr>
<tr>
<th>2</th>
<td>cornell university</td>
<td>ithaca, new york</td>
<td>big red</td>
<td>13931</td>
<td>6702</td>
<td>20633</td>
<td>$5.3 billion (18th)</td>
<td>2908</td>
<td>i would found an institution where any person can find instruction in any study</td>
</tr>
<tr>
<th>3</th>
<td>dartmouth college</td>
<td>hanover, new hampshire</td>
<td>big green</td>
<td>4248</td>
<td>1893</td>
<td>6141</td>
<td>$3.7 billion (22nd)</td>
<td>571</td>
<td>vox clamantis in deserto (the voice of one crying in the wilderness)</td>
</tr>
<tr>
<th>4</th>
<td>harvard university</td>
<td>cambridge, massachusetts</td>
<td>crimson</td>
<td>7181</td>
<td>14044</td>
<td>21225</td>
<td>$32.3 billion (1st)</td>
<td>4671</td>
<td>veritas (truth)</td>
</tr>
<tr>
<th>5</th>
<td>princeton university</td>
<td>princeton, new jersey</td>
<td>tigers</td>
<td>5113</td>
<td>2479</td>
<td>7592</td>
<td>$18.2 billion (5th)</td>
<td>1172</td>
<td>dei sub numine viget (under god's power she flourishes)</td>
</tr>
<tr>
<th>6</th>
<td>university of pennsylvania</td>
<td>philadelphia, pennsylvania</td>
<td>quakers</td>
<td>10337</td>
<td>10306</td>
<td>20643</td>
<td>$7.7 billion (11th)</td>
<td>4464</td>
<td>leges sine moribus vanae (laws without morals are useless)</td>
</tr>
<tr>
<th>7</th>
<td>yale university</td>
<td>new haven, connecticut</td>
<td>bulldogs</td>
<td>5275</td>
<td>6391</td>
<td>11666</td>
<td>$20.8 billion (2nd)</td>
<td>4140</td>
<td>אורים ותומים lux et veritas (light and truth)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>institution</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>brown university</td>
</tr>
<tr>
<th>1</th>
<td>columbia university</td>
</tr>
<tr>
<th>2</th>
<td>cornell university</td>
</tr>
<tr>
<th>3</th>
<td>dartmouth college</td>
</tr>
<tr>
<th>4</th>
<td>princeton university</td>
</tr>
<tr>
<th>5</th>
<td>yale university</td>
</tr>
</tbody>
</table> | select institution where graduate enrollment > 1492 <table_name> : table | | institution | location | athletic nickname | undergraduate enrollment | graduate enrollment | total enrollment | 2013 endowment (and us rank) | academic staff | motto |
|---:|:---------------------------|:---------------------------|:--------------------|---------------------------:|----------------------:|-------------------:|:-------------------------------|-----------------:|:--------------------------------------------------------------------------------|
| 0 | brown university | providence, rhode island | bears | 6316 | 2333 | 8649 | $2.7 billion (30th) | 736 | in deo speramus (in god we hope) |
| 1 | columbia university | new york, new york | lions | 7160 | 15760 | 22920 | $8.2 billion (9th) | 3763 | in lumine tuo videbimus lumen (in thy light shall we see the light) |
| 2 | cornell university | ithaca, new york | big red | 13931 | 6702 | 20633 | $5.3 billion (18th) | 2908 | i would found an institution where any person can find instruction in any study |
| 3 | dartmouth college | hanover, new hampshire | big green | 4248 | 1893 | 6141 | $3.7 billion (22nd) | 571 | vox clamantis in deserto (the voice of one crying in the wilderness) |
| 4 | harvard university | cambridge, massachusetts | crimson | 7181 | 14044 | 21225 | $32.3 billion (1st) | 4671 | veritas (truth) |
| 5 | princeton university | princeton, new jersey | tigers | 5113 | 2479 | 7592 | $18.2 billion (5th) | 1172 | dei sub numine viget (under god's power she flourishes) |
| 6 | university of pennsylvania | philadelphia, pennsylvania | quakers | 10337 | 10306 | 20643 | $7.7 billion (11th) | 4464 | leges sine moribus vanae (laws without morals are useless) |
| 7 | yale university | new haven, connecticut | bulldogs | 5275 | 6391 | 11666 | $20.8 billion (2nd) | 4140 | אורים ותומים lux et veritas (light and truth) | | | | institution |
|---:|:---------------------|
| 0 | brown university |
| 1 | columbia university |
| 2 | cornell university |
| 3 | dartmouth college |
| 4 | princeton university |
| 5 | yale university | | [
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]
] |
select regular season ties where team = 'den total' col : team | year | regular season won | regular season lost | regular season ties | regular season win % | regular season finish | post season won | post season lost | post season win % | post season result row 1 : den | 1981 | 10 | 6 | 0 | 0.625 | 2nd in afc west | none | none | none | none row 2 : den | 1982 | 2 | 7 | 0 | 0.222 | 5th in afc west | none | none | none | none row 3 : den | 1983 | 9 | 7 | 0 | 0.563 | 2nd in afc west | 0 | 1 | 0 | lost to seattle seahawks in afc wild card game row 4 : den | 1984 | 13 | 3 | 0 | 0.813 | 1st in afc west | 0 | 1 | 0 | lost to pittsburgh steelers in afc divisional game row 5 : den | 1985 | 11 | 5 | 0 | 0.688 | 2nd in afc west | none | none | none | none row 6 : den | 1986 | 11 | 5 | 0 | 0.688 | 1st in afc west | 2 | 1 | 0.667 | lost to new york giants in super bowl xxi row 7 : den | 1987 | 10 | 4 | 1 | 0.714 | 1st in afc west | 2 | 1 | 0.667 | lost to washington redskins in super bowl xxii row 8 : den | 1988 | 8 | 8 | 0 | 0.5 | 2nd in afc west | none | none | none | none row 9 : den | 1989 | 11 | 5 | 0 | 0.688 | 1st in afc west | 2 | 1 | 0.667 | lost to san francisco 49ers in super bowl xxiv row 10 : den | 1990 | 5 | 11 | 0 | 0.313 | 5th in afc west | none | none | none | none row 11 : den | 1991 | 12 | 4 | 0 | 0.75 | 1st in afc west | 1 | 1 | 0.5 | lost to buffalo bills in afc championship game row 12 : den | 1992 | 8 | 8 | 0 | 0.5 | 3rd in afc west | none | none | none | none row 13 : den total | den total | 110 | 73 | 1 | 0.601 | none | 7 | 6 | 0.538 | none row 14 : nyg | 1993 | 11 | 5 | 0 | 0.688 | 2nd in nfc east | 1 | 1 | 0.5 | lost to san francisco 49ers in nfc divisional game row 15 : nyg | 1994 | 9 | 7 | 0 | 0.563 | 2nd in nfc east | none | none | none | none row 16 : nyg | 1995 | 5 | 11 | 0 | 0.313 | 4th in nfc east | none | none | none | none row 17 : nyg | 1996 | 6 | 10 | 0 | 0.375 | 5th in nfc east | none | none | none | none row 18 : nyg total | nyg total | 31 | 33 | 0 | 0.484 | none | 1 | 1 | 0.5 | none row 19 : atl | 1997 | 7 | 9 | 0 | 0.438 | 2nd in nfc west | none | none | none | none row 20 : atl | 1998 | 14 | 2 | 0 | 0.875 | 1st in nfc west | 2 | 1 | 0.667 | lost to denver broncos in super bowl xxxiii row 21 : atl | 1999 | 5 | 11 | 0 | 0.313 | 3rd in nfc west | none | none | none | none row 22 : atl | 2000 | 4 | 12 | 0 | 0.25 | 5th in nfc west | none | none | none | none row 23 : atl | 2001 | 7 | 9 | 0 | 0.438 | 3rd in nfc south | none | none | none | none row 24 : atl | 2002 | 9 | 6 | 1 | 0.594 | 2nd in nfc south | 1 | 1 | 0.5 | lost to philadelphia eagles in nfc divisional game row 25 : atl | 2003 | 3 | 10 | 0 | 0.231 | 4th in nfc south | none | none | none | none row 26 : atl total | atl total | 49 | 59 | 1 | 0.454 | none | 3 | 2 | 0.6 | none row 27 : total | total | 190 | 165 | 2 | 0.535 | none | 11 | 9 | 0.55 | none | col : regular season ties row 1 : 1 | select regular season ties where team = 'den total' <table_name> : table \begin{tabular}{llllllllllll}
\toprule
& team & year & regular season won & regular season lost & regular season ties & regular season win % & regular season finish & post season won & post season lost & post season win % & post season result \\
\midrule
0 & den & 1981 & 10 & 6 & 0 & 0.625 & 2nd in afc west & none & none & none & none \\
1 & den & 1982 & 2 & 7 & 0 & 0.222 & 5th in afc west & none & none & none & none \\
2 & den & 1983 & 9 & 7 & 0 & 0.563 & 2nd in afc west & 0 & 1 & 0 & lost to seattle seahawks in afc wild card game \\
3 & den & 1984 & 13 & 3 & 0 & 0.813 & 1st in afc west & 0 & 1 & 0 & lost to pittsburgh steelers in afc divisional game \\
4 & den & 1985 & 11 & 5 & 0 & 0.688 & 2nd in afc west & none & none & none & none \\
5 & den & 1986 & 11 & 5 & 0 & 0.688 & 1st in afc west & 2 & 1 & 0.667 & lost to new york giants in super bowl xxi \\
6 & den & 1987 & 10 & 4 & 1 & 0.714 & 1st in afc west & 2 & 1 & 0.667 & lost to washington redskins in super bowl xxii \\
7 & den & 1988 & 8 & 8 & 0 & 0.5 & 2nd in afc west & none & none & none & none \\
8 & den & 1989 & 11 & 5 & 0 & 0.688 & 1st in afc west & 2 & 1 & 0.667 & lost to san francisco 49ers in super bowl xxiv \\
9 & den & 1990 & 5 & 11 & 0 & 0.313 & 5th in afc west & none & none & none & none \\
10 & den & 1991 & 12 & 4 & 0 & 0.75 & 1st in afc west & 1 & 1 & 0.5 & lost to buffalo bills in afc championship game \\
11 & den & 1992 & 8 & 8 & 0 & 0.5 & 3rd in afc west & none & none & none & none \\
12 & den total & den total & 110 & 73 & 1 & 0.601 & none & 7 & 6 & 0.538 & none \\
13 & nyg & 1993 & 11 & 5 & 0 & 0.688 & 2nd in nfc east & 1 & 1 & 0.5 & lost to san francisco 49ers in nfc divisional game \\
14 & nyg & 1994 & 9 & 7 & 0 & 0.563 & 2nd in nfc east & none & none & none & none \\
15 & nyg & 1995 & 5 & 11 & 0 & 0.313 & 4th in nfc east & none & none & none & none \\
16 & nyg & 1996 & 6 & 10 & 0 & 0.375 & 5th in nfc east & none & none & none & none \\
17 & nyg total & nyg total & 31 & 33 & 0 & 0.484 & none & 1 & 1 & 0.5 & none \\
18 & atl & 1997 & 7 & 9 & 0 & 0.438 & 2nd in nfc west & none & none & none & none \\
19 & atl & 1998 & 14 & 2 & 0 & 0.875 & 1st in nfc west & 2 & 1 & 0.667 & lost to denver broncos in super bowl xxxiii \\
20 & atl & 1999 & 5 & 11 & 0 & 0.313 & 3rd in nfc west & none & none & none & none \\
21 & atl & 2000 & 4 & 12 & 0 & 0.25 & 5th in nfc west & none & none & none & none \\
22 & atl & 2001 & 7 & 9 & 0 & 0.438 & 3rd in nfc south & none & none & none & none \\
23 & atl & 2002 & 9 & 6 & 1 & 0.594 & 2nd in nfc south & 1 & 1 & 0.5 & lost to philadelphia eagles in nfc divisional game \\
24 & atl & 2003 & 3 & 10 & 0 & 0.231 & 4th in nfc south & none & none & none & none \\
25 & atl total & atl total & 49 & 59 & 1 & 0.454 & none & 3 & 2 & 0.6 & none \\
26 & total & total & 190 & 165 & 2 & 0.535 & none & 11 & 9 & 0.55 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& regular season ties \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select regular season ties where team = 'den total' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>team</th>
<th>year</th>
<th>regular season won</th>
<th>regular season lost</th>
<th>regular season ties</th>
<th>regular season win %</th>
<th>regular season finish</th>
<th>post season won</th>
<th>post season lost</th>
<th>post season win %</th>
<th>post season result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>den</td>
<td>1981</td>
<td>10</td>
<td>6</td>
<td>0</td>
<td>0.625</td>
<td>2nd in afc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>den</td>
<td>1982</td>
<td>2</td>
<td>7</td>
<td>0</td>
<td>0.222</td>
<td>5th in afc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>den</td>
<td>1983</td>
<td>9</td>
<td>7</td>
<td>0</td>
<td>0.563</td>
<td>2nd in afc west</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>lost to seattle seahawks in afc wild card game</td>
</tr>
<tr>
<th>3</th>
<td>den</td>
<td>1984</td>
<td>13</td>
<td>3</td>
<td>0</td>
<td>0.813</td>
<td>1st in afc west</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>lost to pittsburgh steelers in afc divisional game</td>
</tr>
<tr>
<th>4</th>
<td>den</td>
<td>1985</td>
<td>11</td>
<td>5</td>
<td>0</td>
<td>0.688</td>
<td>2nd in afc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>den</td>
<td>1986</td>
<td>11</td>
<td>5</td>
<td>0</td>
<td>0.688</td>
<td>1st in afc west</td>
<td>2</td>
<td>1</td>
<td>0.667</td>
<td>lost to new york giants in super bowl xxi</td>
</tr>
<tr>
<th>6</th>
<td>den</td>
<td>1987</td>
<td>10</td>
<td>4</td>
<td>1</td>
<td>0.714</td>
<td>1st in afc west</td>
<td>2</td>
<td>1</td>
<td>0.667</td>
<td>lost to washington redskins in super bowl xxii</td>
</tr>
<tr>
<th>7</th>
<td>den</td>
<td>1988</td>
<td>8</td>
<td>8</td>
<td>0</td>
<td>0.5</td>
<td>2nd in afc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>den</td>
<td>1989</td>
<td>11</td>
<td>5</td>
<td>0</td>
<td>0.688</td>
<td>1st in afc west</td>
<td>2</td>
<td>1</td>
<td>0.667</td>
<td>lost to san francisco 49ers in super bowl xxiv</td>
</tr>
<tr>
<th>9</th>
<td>den</td>
<td>1990</td>
<td>5</td>
<td>11</td>
<td>0</td>
<td>0.313</td>
<td>5th in afc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>den</td>
<td>1991</td>
<td>12</td>
<td>4</td>
<td>0</td>
<td>0.75</td>
<td>1st in afc west</td>
<td>1</td>
<td>1</td>
<td>0.5</td>
<td>lost to buffalo bills in afc championship game</td>
</tr>
<tr>
<th>11</th>
<td>den</td>
<td>1992</td>
<td>8</td>
<td>8</td>
<td>0</td>
<td>0.5</td>
<td>3rd in afc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>den total</td>
<td>den total</td>
<td>110</td>
<td>73</td>
<td>1</td>
<td>0.601</td>
<td>none</td>
<td>7</td>
<td>6</td>
<td>0.538</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>nyg</td>
<td>1993</td>
<td>11</td>
<td>5</td>
<td>0</td>
<td>0.688</td>
<td>2nd in nfc east</td>
<td>1</td>
<td>1</td>
<td>0.5</td>
<td>lost to san francisco 49ers in nfc divisional game</td>
</tr>
<tr>
<th>14</th>
<td>nyg</td>
<td>1994</td>
<td>9</td>
<td>7</td>
<td>0</td>
<td>0.563</td>
<td>2nd in nfc east</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>nyg</td>
<td>1995</td>
<td>5</td>
<td>11</td>
<td>0</td>
<td>0.313</td>
<td>4th in nfc east</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>nyg</td>
<td>1996</td>
<td>6</td>
<td>10</td>
<td>0</td>
<td>0.375</td>
<td>5th in nfc east</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>nyg total</td>
<td>nyg total</td>
<td>31</td>
<td>33</td>
<td>0</td>
<td>0.484</td>
<td>none</td>
<td>1</td>
<td>1</td>
<td>0.5</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>atl</td>
<td>1997</td>
<td>7</td>
<td>9</td>
<td>0</td>
<td>0.438</td>
<td>2nd in nfc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>atl</td>
<td>1998</td>
<td>14</td>
<td>2</td>
<td>0</td>
<td>0.875</td>
<td>1st in nfc west</td>
<td>2</td>
<td>1</td>
<td>0.667</td>
<td>lost to denver broncos in super bowl xxxiii</td>
</tr>
<tr>
<th>20</th>
<td>atl</td>
<td>1999</td>
<td>5</td>
<td>11</td>
<td>0</td>
<td>0.313</td>
<td>3rd in nfc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>atl</td>
<td>2000</td>
<td>4</td>
<td>12</td>
<td>0</td>
<td>0.25</td>
<td>5th in nfc west</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>atl</td>
<td>2001</td>
<td>7</td>
<td>9</td>
<td>0</td>
<td>0.438</td>
<td>3rd in nfc south</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>atl</td>
<td>2002</td>
<td>9</td>
<td>6</td>
<td>1</td>
<td>0.594</td>
<td>2nd in nfc south</td>
<td>1</td>
<td>1</td>
<td>0.5</td>
<td>lost to philadelphia eagles in nfc divisional game</td>
</tr>
<tr>
<th>24</th>
<td>atl</td>
<td>2003</td>
<td>3</td>
<td>10</td>
<td>0</td>
<td>0.231</td>
<td>4th in nfc south</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>atl total</td>
<td>atl total</td>
<td>49</td>
<td>59</td>
<td>1</td>
<td>0.454</td>
<td>none</td>
<td>3</td>
<td>2</td>
<td>0.6</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>total</td>
<td>total</td>
<td>190</td>
<td>165</td>
<td>2</td>
<td>0.535</td>
<td>none</td>
<td>11</td>
<td>9</td>
<td>0.55</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>regular season ties</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select regular season ties where team = 'den total' <table_name> : table | | team | year | regular season won | regular season lost | regular season ties | regular season win % | regular season finish | post season won | post season lost | post season win % | post season result |
|---:|:----------|:----------|---------------------:|----------------------:|----------------------:|-----------------------:|:------------------------|:------------------|:-------------------|:--------------------|:---------------------------------------------------|
| 0 | den | 1981 | 10 | 6 | 0 | 0.625 | 2nd in afc west | none | none | none | none |
| 1 | den | 1982 | 2 | 7 | 0 | 0.222 | 5th in afc west | none | none | none | none |
| 2 | den | 1983 | 9 | 7 | 0 | 0.563 | 2nd in afc west | 0 | 1 | 0 | lost to seattle seahawks in afc wild card game |
| 3 | den | 1984 | 13 | 3 | 0 | 0.813 | 1st in afc west | 0 | 1 | 0 | lost to pittsburgh steelers in afc divisional game |
| 4 | den | 1985 | 11 | 5 | 0 | 0.688 | 2nd in afc west | none | none | none | none |
| 5 | den | 1986 | 11 | 5 | 0 | 0.688 | 1st in afc west | 2 | 1 | 0.667 | lost to new york giants in super bowl xxi |
| 6 | den | 1987 | 10 | 4 | 1 | 0.714 | 1st in afc west | 2 | 1 | 0.667 | lost to washington redskins in super bowl xxii |
| 7 | den | 1988 | 8 | 8 | 0 | 0.5 | 2nd in afc west | none | none | none | none |
| 8 | den | 1989 | 11 | 5 | 0 | 0.688 | 1st in afc west | 2 | 1 | 0.667 | lost to san francisco 49ers in super bowl xxiv |
| 9 | den | 1990 | 5 | 11 | 0 | 0.313 | 5th in afc west | none | none | none | none |
| 10 | den | 1991 | 12 | 4 | 0 | 0.75 | 1st in afc west | 1 | 1 | 0.5 | lost to buffalo bills in afc championship game |
| 11 | den | 1992 | 8 | 8 | 0 | 0.5 | 3rd in afc west | none | none | none | none |
| 12 | den total | den total | 110 | 73 | 1 | 0.601 | none | 7 | 6 | 0.538 | none |
| 13 | nyg | 1993 | 11 | 5 | 0 | 0.688 | 2nd in nfc east | 1 | 1 | 0.5 | lost to san francisco 49ers in nfc divisional game |
| 14 | nyg | 1994 | 9 | 7 | 0 | 0.563 | 2nd in nfc east | none | none | none | none |
| 15 | nyg | 1995 | 5 | 11 | 0 | 0.313 | 4th in nfc east | none | none | none | none |
| 16 | nyg | 1996 | 6 | 10 | 0 | 0.375 | 5th in nfc east | none | none | none | none |
| 17 | nyg total | nyg total | 31 | 33 | 0 | 0.484 | none | 1 | 1 | 0.5 | none |
| 18 | atl | 1997 | 7 | 9 | 0 | 0.438 | 2nd in nfc west | none | none | none | none |
| 19 | atl | 1998 | 14 | 2 | 0 | 0.875 | 1st in nfc west | 2 | 1 | 0.667 | lost to denver broncos in super bowl xxxiii |
| 20 | atl | 1999 | 5 | 11 | 0 | 0.313 | 3rd in nfc west | none | none | none | none |
| 21 | atl | 2000 | 4 | 12 | 0 | 0.25 | 5th in nfc west | none | none | none | none |
| 22 | atl | 2001 | 7 | 9 | 0 | 0.438 | 3rd in nfc south | none | none | none | none |
| 23 | atl | 2002 | 9 | 6 | 1 | 0.594 | 2nd in nfc south | 1 | 1 | 0.5 | lost to philadelphia eagles in nfc divisional game |
| 24 | atl | 2003 | 3 | 10 | 0 | 0.231 | 4th in nfc south | none | none | none | none |
| 25 | atl total | atl total | 49 | 59 | 1 | 0.454 | none | 3 | 2 | 0.6 | none |
| 26 | total | total | 190 | 165 | 2 | 0.535 | none | 11 | 9 | 0.55 | none | | | | regular season ties |
|---:|----------------------:|
| 0 | 1 | | [
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select count ( * ) where rank = '#4' and season > 4 col : season | episodes | time slot (est) | original airing season premiere | original airing season finale | original airing tv season | rank | viewers (in millions) row 1 : 1 | 23 | friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001) | october 6, 2000 | may 17, 2001 | 2000-2001 | #10 | 17.8 row 2 : 2 | 23 | thursday 9pm/8c | september 27, 2001 | may 16, 2002 | 2001-2002 | #2 | 23.69 row 3 : 3 | 23 | thursday 9pm/8c | september 26, 2002 | may 15, 2003 | 2002-2003 | #1 | 26.2 row 4 : 4 | 23 | thursday 9pm/8c | september 25, 2003 | may 20, 2004 | 2003-2004 | #2 | 25.27 row 5 : 5 | 25 | thursday 9pm/8c | september 23, 2004 | may 19, 2005 | 2004-2005 | #2 | 26.26 row 6 : 6 | 24 | thursday 9pm/8c | september 22, 2005 | may 18, 2006 | 2005-2006 | #3 | 24.86 row 7 : 7 | 24 | thursday 9pm/8c | september 21, 2006 | may 17, 2007 | 2006-2007 | #4 | 20.34 row 8 : 8 | 17 | thursday 9pm/8c | september 27, 2007 | may 15, 2008 | 2007-2008 | #9 | 16.62 row 9 : 9 | 24 | thursday 9pm/8c | october 9, 2008 | may 14, 2009 | 2008-2009 | #4 | 18.52 row 10 : 10 | 23 | thursday 9pm/8c | september 24, 2009 | may 20, 2010 | 2009-2010 | #12 | 14.92 row 11 : 11 | 22 | thursday 9pm/8c | september 23, 2010 | may 12, 2011 | 2010-2011 | #12 | 13.52 row 12 : 12 | 22 | wednesday 10pm/9c | september 21, 2011 | may 9, 2012 | 2011-2012 | #21 | 12.49 row 13 : 13 | 22 | wednesday 10pm/9c | september 26, 2012 | may 15, 2013 | 2012-2013 | #25 | 11.63 | col : count ( "*" ) row 1 : 2 | select count ( * ) where rank = '#4' and season > 4 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& season & episodes & time slot (est) & original airing season premiere & original airing season finale & original airing tv season & rank & viewers (in millions) \\
\midrule
0 & 1 & 23 & friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001) & october 6, 2000 & may 17, 2001 & 2000-2001 & #10 & 17.8 \\
1 & 2 & 23 & thursday 9pm/8c & september 27, 2001 & may 16, 2002 & 2001-2002 & #2 & 23.69 \\
2 & 3 & 23 & thursday 9pm/8c & september 26, 2002 & may 15, 2003 & 2002-2003 & #1 & 26.2 \\
3 & 4 & 23 & thursday 9pm/8c & september 25, 2003 & may 20, 2004 & 2003-2004 & #2 & 25.27 \\
4 & 5 & 25 & thursday 9pm/8c & september 23, 2004 & may 19, 2005 & 2004-2005 & #2 & 26.26 \\
5 & 6 & 24 & thursday 9pm/8c & september 22, 2005 & may 18, 2006 & 2005-2006 & #3 & 24.86 \\
6 & 7 & 24 & thursday 9pm/8c & september 21, 2006 & may 17, 2007 & 2006-2007 & #4 & 20.34 \\
7 & 8 & 17 & thursday 9pm/8c & september 27, 2007 & may 15, 2008 & 2007-2008 & #9 & 16.62 \\
8 & 9 & 24 & thursday 9pm/8c & october 9, 2008 & may 14, 2009 & 2008-2009 & #4 & 18.52 \\
9 & 10 & 23 & thursday 9pm/8c & september 24, 2009 & may 20, 2010 & 2009-2010 & #12 & 14.92 \\
10 & 11 & 22 & thursday 9pm/8c & september 23, 2010 & may 12, 2011 & 2010-2011 & #12 & 13.52 \\
11 & 12 & 22 & wednesday 10pm/9c & september 21, 2011 & may 9, 2012 & 2011-2012 & #21 & 12.49 \\
12 & 13 & 22 & wednesday 10pm/9c & september 26, 2012 & may 15, 2013 & 2012-2013 & #25 & 11.63 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( * ) where rank = '#4' and season > 4 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>episodes</th>
<th>time slot (est)</th>
<th>original airing season premiere</th>
<th>original airing season finale</th>
<th>original airing tv season</th>
<th>rank</th>
<th>viewers (in millions)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>23</td>
<td>friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001)</td>
<td>october 6, 2000</td>
<td>may 17, 2001</td>
<td>2000-2001</td>
<td>#10</td>
<td>17.8</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 27, 2001</td>
<td>may 16, 2002</td>
<td>2001-2002</td>
<td>#2</td>
<td>23.69</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 26, 2002</td>
<td>may 15, 2003</td>
<td>2002-2003</td>
<td>#1</td>
<td>26.2</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 25, 2003</td>
<td>may 20, 2004</td>
<td>2003-2004</td>
<td>#2</td>
<td>25.27</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>25</td>
<td>thursday 9pm/8c</td>
<td>september 23, 2004</td>
<td>may 19, 2005</td>
<td>2004-2005</td>
<td>#2</td>
<td>26.26</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>24</td>
<td>thursday 9pm/8c</td>
<td>september 22, 2005</td>
<td>may 18, 2006</td>
<td>2005-2006</td>
<td>#3</td>
<td>24.86</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>24</td>
<td>thursday 9pm/8c</td>
<td>september 21, 2006</td>
<td>may 17, 2007</td>
<td>2006-2007</td>
<td>#4</td>
<td>20.34</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>17</td>
<td>thursday 9pm/8c</td>
<td>september 27, 2007</td>
<td>may 15, 2008</td>
<td>2007-2008</td>
<td>#9</td>
<td>16.62</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>24</td>
<td>thursday 9pm/8c</td>
<td>october 9, 2008</td>
<td>may 14, 2009</td>
<td>2008-2009</td>
<td>#4</td>
<td>18.52</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 24, 2009</td>
<td>may 20, 2010</td>
<td>2009-2010</td>
<td>#12</td>
<td>14.92</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>22</td>
<td>thursday 9pm/8c</td>
<td>september 23, 2010</td>
<td>may 12, 2011</td>
<td>2010-2011</td>
<td>#12</td>
<td>13.52</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>22</td>
<td>wednesday 10pm/9c</td>
<td>september 21, 2011</td>
<td>may 9, 2012</td>
<td>2011-2012</td>
<td>#21</td>
<td>12.49</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>22</td>
<td>wednesday 10pm/9c</td>
<td>september 26, 2012</td>
<td>may 15, 2013</td>
<td>2012-2013</td>
<td>#25</td>
<td>11.63</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( * ) where rank = '#4' and season > 4 <table_name> : table | | season | episodes | time slot (est) | original airing season premiere | original airing season finale | original airing tv season | rank | viewers (in millions) |
|---:|---------:|-----------:|:-----------------------------------------------------------------------------------------------------|:----------------------------------|:--------------------------------|:----------------------------|:-------|------------------------:|
| 0 | 1 | 23 | friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001) | october 6, 2000 | may 17, 2001 | 2000-2001 | #10 | 17.8 |
| 1 | 2 | 23 | thursday 9pm/8c | september 27, 2001 | may 16, 2002 | 2001-2002 | #2 | 23.69 |
| 2 | 3 | 23 | thursday 9pm/8c | september 26, 2002 | may 15, 2003 | 2002-2003 | #1 | 26.2 |
| 3 | 4 | 23 | thursday 9pm/8c | september 25, 2003 | may 20, 2004 | 2003-2004 | #2 | 25.27 |
| 4 | 5 | 25 | thursday 9pm/8c | september 23, 2004 | may 19, 2005 | 2004-2005 | #2 | 26.26 |
| 5 | 6 | 24 | thursday 9pm/8c | september 22, 2005 | may 18, 2006 | 2005-2006 | #3 | 24.86 |
| 6 | 7 | 24 | thursday 9pm/8c | september 21, 2006 | may 17, 2007 | 2006-2007 | #4 | 20.34 |
| 7 | 8 | 17 | thursday 9pm/8c | september 27, 2007 | may 15, 2008 | 2007-2008 | #9 | 16.62 |
| 8 | 9 | 24 | thursday 9pm/8c | october 9, 2008 | may 14, 2009 | 2008-2009 | #4 | 18.52 |
| 9 | 10 | 23 | thursday 9pm/8c | september 24, 2009 | may 20, 2010 | 2009-2010 | #12 | 14.92 |
| 10 | 11 | 22 | thursday 9pm/8c | september 23, 2010 | may 12, 2011 | 2010-2011 | #12 | 13.52 |
| 11 | 12 | 22 | wednesday 10pm/9c | september 21, 2011 | may 9, 2012 | 2011-2012 | #21 | 12.49 |
| 12 | 13 | 22 | wednesday 10pm/9c | september 26, 2012 | may 15, 2013 | 2012-2013 | #25 | 11.63 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 2 | | [
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select berths where terminal = 'terminal 2 (ct2)' col : terminal | operator | depth (m) | berths | quay length (m) | quay cranes | area (m2) | capacity (kteus) row 1 : terminal 1 (ct1) | mtl | 14 | 1 | none | 4 | none | none row 2 : terminal 2 (ct2) | mtl | 14 | 1 | none | 5 | none | none row 3 : terminal 3 (ct3) | dpi | 14 | 1 | 305 | 6 | 167000 | >1,200 row 4 : terminal 4 (ct4) | hit | 12.5 | 3 | none | 8 | none | none row 5 : terminal 5 (ct5) | mtl | 14 | 1 | none | 4 | none | none row 6 : terminal 6 (ct6) | hit | 12.5-15.5 | 3 | none | 11 | none | none row 7 : terminal 7 (ct7) | hit | 15.5 | 4 | none | 15 | none | none row 8 : terminal 8 east (ct8e) | hit/cosco | 15.5 | 2 | 640 | 9 | 300000 | 1800 row 9 : terminal 8 west (ct8w) | act | 15.5 | 2 | 740 | 8 | 285000 | >2,000 row 10 : terminal 9 north (ct9n) | hit | 15.5 | 2 | 700 | 9 | 190000 | >2,600 (n&s) row 11 : terminal 9 south (ct9s) | mtl | 15.5 | 4 | 1240 | 13 | 490000 | none | col : berths row 1 : 1 | select berths where terminal = 'terminal 2 (ct2)' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& terminal & operator & depth (m) & berths & quay length (m) & quay cranes & area (m2) & capacity (kteus) \\
\midrule
0 & terminal 1 (ct1) & mtl & 14 & 1 & none & 4 & none & none \\
1 & terminal 2 (ct2) & mtl & 14 & 1 & none & 5 & none & none \\
2 & terminal 3 (ct3) & dpi & 14 & 1 & 305 & 6 & 167000 & >1,200 \\
3 & terminal 4 (ct4) & hit & 12.5 & 3 & none & 8 & none & none \\
4 & terminal 5 (ct5) & mtl & 14 & 1 & none & 4 & none & none \\
5 & terminal 6 (ct6) & hit & 12.5-15.5 & 3 & none & 11 & none & none \\
6 & terminal 7 (ct7) & hit & 15.5 & 4 & none & 15 & none & none \\
7 & terminal 8 east (ct8e) & hit/cosco & 15.5 & 2 & 640 & 9 & 300000 & 1800 \\
8 & terminal 8 west (ct8w) & act & 15.5 & 2 & 740 & 8 & 285000 & >2,000 \\
9 & terminal 9 north (ct9n) & hit & 15.5 & 2 & 700 & 9 & 190000 & >2,600 (n&s) \\
10 & terminal 9 south (ct9s) & mtl & 15.5 & 4 & 1240 & 13 & 490000 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& berths \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select berths where terminal = 'terminal 2 (ct2)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>terminal</th>
<th>operator</th>
<th>depth (m)</th>
<th>berths</th>
<th>quay length (m)</th>
<th>quay cranes</th>
<th>area (m2)</th>
<th>capacity (kteus)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>terminal 1 (ct1)</td>
<td>mtl</td>
<td>14</td>
<td>1</td>
<td>none</td>
<td>4</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>terminal 2 (ct2)</td>
<td>mtl</td>
<td>14</td>
<td>1</td>
<td>none</td>
<td>5</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>terminal 3 (ct3)</td>
<td>dpi</td>
<td>14</td>
<td>1</td>
<td>305</td>
<td>6</td>
<td>167000</td>
<td>>1,200</td>
</tr>
<tr>
<th>3</th>
<td>terminal 4 (ct4)</td>
<td>hit</td>
<td>12.5</td>
<td>3</td>
<td>none</td>
<td>8</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>terminal 5 (ct5)</td>
<td>mtl</td>
<td>14</td>
<td>1</td>
<td>none</td>
<td>4</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>terminal 6 (ct6)</td>
<td>hit</td>
<td>12.5-15.5</td>
<td>3</td>
<td>none</td>
<td>11</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>terminal 7 (ct7)</td>
<td>hit</td>
<td>15.5</td>
<td>4</td>
<td>none</td>
<td>15</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>terminal 8 east (ct8e)</td>
<td>hit/cosco</td>
<td>15.5</td>
<td>2</td>
<td>640</td>
<td>9</td>
<td>300000</td>
<td>1800</td>
</tr>
<tr>
<th>8</th>
<td>terminal 8 west (ct8w)</td>
<td>act</td>
<td>15.5</td>
<td>2</td>
<td>740</td>
<td>8</td>
<td>285000</td>
<td>>2,000</td>
</tr>
<tr>
<th>9</th>
<td>terminal 9 north (ct9n)</td>
<td>hit</td>
<td>15.5</td>
<td>2</td>
<td>700</td>
<td>9</td>
<td>190000</td>
<td>>2,600 (n&s)</td>
</tr>
<tr>
<th>10</th>
<td>terminal 9 south (ct9s)</td>
<td>mtl</td>
<td>15.5</td>
<td>4</td>
<td>1240</td>
<td>13</td>
<td>490000</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>berths</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select berths where terminal = 'terminal 2 (ct2)' <table_name> : table | | terminal | operator | depth (m) | berths | quay length (m) | quay cranes | area (m2) | capacity (kteus) |
|---:|:------------------------|:-----------|:------------|---------:|:------------------|--------------:|:------------|:-------------------|
| 0 | terminal 1 (ct1) | mtl | 14 | 1 | none | 4 | none | none |
| 1 | terminal 2 (ct2) | mtl | 14 | 1 | none | 5 | none | none |
| 2 | terminal 3 (ct3) | dpi | 14 | 1 | 305 | 6 | 167000 | >1,200 |
| 3 | terminal 4 (ct4) | hit | 12.5 | 3 | none | 8 | none | none |
| 4 | terminal 5 (ct5) | mtl | 14 | 1 | none | 4 | none | none |
| 5 | terminal 6 (ct6) | hit | 12.5-15.5 | 3 | none | 11 | none | none |
| 6 | terminal 7 (ct7) | hit | 15.5 | 4 | none | 15 | none | none |
| 7 | terminal 8 east (ct8e) | hit/cosco | 15.5 | 2 | 640 | 9 | 300000 | 1800 |
| 8 | terminal 8 west (ct8w) | act | 15.5 | 2 | 740 | 8 | 285000 | >2,000 |
| 9 | terminal 9 north (ct9n) | hit | 15.5 | 2 | 700 | 9 | 190000 | >2,600 (n&s) |
| 10 | terminal 9 south (ct9s) | mtl | 15.5 | 4 | 1240 | 13 | 490000 | none | | | | berths |
|---:|---------:|
| 0 | 1 | | [
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] |
select sum ( performance ) where performance < 577 col : event | performance | athlete | nation | place | date row 1 : 100 m | 9.72 | usain bolt | jamaica | new york city ny, usa | may 31 row 2 : 100 m | 9.69 | usain bolt | jamaica | beijing, china | august 16 row 3 : 200 m | 19.3 | usain bolt | jamaica | beijing, china | august 20 row 4 : 4 x 100 m relay | 37.1 | nesta carter michael frater usain bolt asafa powell | jamaica | beijing, china | august 22 row 5 : 110 m hurdles | 12.87 | dayron robles | cuba | ostrava, czech republic | june 12 row 6 : 50 km race walk | 3:34:14 | denis nizhegorodov | russia | cheboksary, russia | may 11 row 7 : marathon | 2:03:59 | haile gebrselassie | ethiopia | berlin, germany | september 28 | col : sum ( "performance" ) row 1 : 74.27 | select sum ( performance ) where performance < 577 <table_name> : table \begin{tabular}{lllllll}
\toprule
& event & performance & athlete & nation & place & date \\
\midrule
0 & 100 m & 9.72 & usain bolt & jamaica & new york city ny, usa & may 31 \\
1 & 100 m & 9.69 & usain bolt & jamaica & beijing, china & august 16 \\
2 & 200 m & 19.3 & usain bolt & jamaica & beijing, china & august 20 \\
3 & 4 x 100 m relay & 37.1 & nesta carter michael frater usain bolt asafa powell & jamaica & beijing, china & august 22 \\
4 & 110 m hurdles & 12.87 & dayron robles & cuba & ostrava, czech republic & june 12 \\
5 & 50 km race walk & 3:34:14 & denis nizhegorodov & russia & cheboksary, russia & may 11 \\
6 & marathon & 2:03:59 & haile gebrselassie & ethiopia & berlin, germany & september 28 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& sum ( "performance" ) \\
\midrule
0 & 74.27 \\
\bottomrule
\end{tabular}
| select sum ( performance ) where performance < 577 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>event</th>
<th>performance</th>
<th>athlete</th>
<th>nation</th>
<th>place</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>100 m</td>
<td>9.72</td>
<td>usain bolt</td>
<td>jamaica</td>
<td>new york city ny, usa</td>
<td>may 31</td>
</tr>
<tr>
<th>1</th>
<td>100 m</td>
<td>9.69</td>
<td>usain bolt</td>
<td>jamaica</td>
<td>beijing, china</td>
<td>august 16</td>
</tr>
<tr>
<th>2</th>
<td>200 m</td>
<td>19.3</td>
<td>usain bolt</td>
<td>jamaica</td>
<td>beijing, china</td>
<td>august 20</td>
</tr>
<tr>
<th>3</th>
<td>4 x 100 m relay</td>
<td>37.1</td>
<td>nesta carter michael frater usain bolt asafa powell</td>
<td>jamaica</td>
<td>beijing, china</td>
<td>august 22</td>
</tr>
<tr>
<th>4</th>
<td>110 m hurdles</td>
<td>12.87</td>
<td>dayron robles</td>
<td>cuba</td>
<td>ostrava, czech republic</td>
<td>june 12</td>
</tr>
<tr>
<th>5</th>
<td>50 km race walk</td>
<td>3:34:14</td>
<td>denis nizhegorodov</td>
<td>russia</td>
<td>cheboksary, russia</td>
<td>may 11</td>
</tr>
<tr>
<th>6</th>
<td>marathon</td>
<td>2:03:59</td>
<td>haile gebrselassie</td>
<td>ethiopia</td>
<td>berlin, germany</td>
<td>september 28</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>sum ( "performance" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>74.27</td>
</tr>
</tbody>
</table> | select sum ( performance ) where performance < 577 <table_name> : table | | event | performance | athlete | nation | place | date |
|---:|:----------------|:--------------|:----------------------------------------------------|:---------|:------------------------|:-------------|
| 0 | 100 m | 9.72 | usain bolt | jamaica | new york city ny, usa | may 31 |
| 1 | 100 m | 9.69 | usain bolt | jamaica | beijing, china | august 16 |
| 2 | 200 m | 19.3 | usain bolt | jamaica | beijing, china | august 20 |
| 3 | 4 x 100 m relay | 37.1 | nesta carter michael frater usain bolt asafa powell | jamaica | beijing, china | august 22 |
| 4 | 110 m hurdles | 12.87 | dayron robles | cuba | ostrava, czech republic | june 12 |
| 5 | 50 km race walk | 3:34:14 | denis nizhegorodov | russia | cheboksary, russia | may 11 |
| 6 | marathon | 2:03:59 | haile gebrselassie | ethiopia | berlin, germany | september 28 | | | | sum ( "performance" ) |
|---:|------------------------:|
| 0 | 74.27 | | [
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select min ( # ) where # < 67 col : # | date | venue | opponent | score | result | competition row 1 : 1 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 3-0 | 9-0 | euro 2000 qualifying row 2 : 2 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 5-0 | 9-0 | euro 2000 qualifying row 3 : 3 | 1999-03-31 00:00:00 | olimpico, serravalle, san marino | san marino | 0-3 | 0-6 | euro 2000 qualifying row 4 : 4 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 1-0 | 8-0 | euro 2000 qualifying row 5 : 5 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 2-0 | 8-0 | euro 2000 qualifying row 6 : 6 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 4-0 | 8-0 | euro 2000 qualifying row 7 : 7 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 2-0 | 3-0 | friendly row 8 : 8 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 3-0 | 3-0 | friendly | col : min ( "#" ) row 1 : 1 | select min ( # ) where # < 67 <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & date & venue & opponent & score & result & competition \\
\midrule
0 & 1 & 1999-03-27 00:00:00 & mestalla, valencia, spain & austria & 3-0 & 9-0 & euro 2000 qualifying \\
1 & 2 & 1999-03-27 00:00:00 & mestalla, valencia, spain & austria & 5-0 & 9-0 & euro 2000 qualifying \\
2 & 3 & 1999-03-31 00:00:00 & olimpico, serravalle, san marino & san marino & 0-3 & 0-6 & euro 2000 qualifying \\
3 & 4 & 1999-09-08 00:00:00 & vivero, badajoz, spain & cyprus & 1-0 & 8-0 & euro 2000 qualifying \\
4 & 5 & 1999-09-08 00:00:00 & vivero, badajoz, spain & cyprus & 2-0 & 8-0 & euro 2000 qualifying \\
5 & 6 & 1999-09-08 00:00:00 & vivero, badajoz, spain & cyprus & 4-0 & 8-0 & euro 2000 qualifying \\
6 & 7 & 2000-01-26 00:00:00 & cartagonova, cartagena, spain & poland & 2-0 & 3-0 & friendly \\
7 & 8 & 2000-01-26 00:00:00 & cartagonova, cartagena, spain & poland & 3-0 & 3-0 & friendly \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& min ( "#" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select min ( # ) where # < 67 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>date</th>
<th>venue</th>
<th>opponent</th>
<th>score</th>
<th>result</th>
<th>competition</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1999-03-27 00:00:00</td>
<td>mestalla, valencia, spain</td>
<td>austria</td>
<td>3-0</td>
<td>9-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1999-03-27 00:00:00</td>
<td>mestalla, valencia, spain</td>
<td>austria</td>
<td>5-0</td>
<td>9-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1999-03-31 00:00:00</td>
<td>olimpico, serravalle, san marino</td>
<td>san marino</td>
<td>0-3</td>
<td>0-6</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1999-09-08 00:00:00</td>
<td>vivero, badajoz, spain</td>
<td>cyprus</td>
<td>1-0</td>
<td>8-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1999-09-08 00:00:00</td>
<td>vivero, badajoz, spain</td>
<td>cyprus</td>
<td>2-0</td>
<td>8-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1999-09-08 00:00:00</td>
<td>vivero, badajoz, spain</td>
<td>cyprus</td>
<td>4-0</td>
<td>8-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2000-01-26 00:00:00</td>
<td>cartagonova, cartagena, spain</td>
<td>poland</td>
<td>2-0</td>
<td>3-0</td>
<td>friendly</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2000-01-26 00:00:00</td>
<td>cartagonova, cartagena, spain</td>
<td>poland</td>
<td>3-0</td>
<td>3-0</td>
<td>friendly</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>min ( "#" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select min ( # ) where # < 67 <table_name> : table | | # | date | venue | opponent | score | result | competition |
|---:|----:|:--------------------|:---------------------------------|:-----------|:--------|:---------|:---------------------|
| 0 | 1 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 3-0 | 9-0 | euro 2000 qualifying |
| 1 | 2 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 5-0 | 9-0 | euro 2000 qualifying |
| 2 | 3 | 1999-03-31 00:00:00 | olimpico, serravalle, san marino | san marino | 0-3 | 0-6 | euro 2000 qualifying |
| 3 | 4 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 1-0 | 8-0 | euro 2000 qualifying |
| 4 | 5 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 2-0 | 8-0 | euro 2000 qualifying |
| 5 | 6 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 4-0 | 8-0 | euro 2000 qualifying |
| 6 | 7 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 2-0 | 3-0 | friendly |
| 7 | 8 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 3-0 | 3-0 | friendly | | | | min ( "#" ) |
|---:|--------------:|
| 0 | 1 | | [
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select percentage where governorate = 'al-qadisiyyah' col : governorate | percentage | seats won | total seats row 1 : al-anbar | none | 0 | 29 row 2 : babil | 8.2% | 5 | 30 row 3 : baghdad | 5.4% | 3 | 57 row 4 : basra | 11.6% | 5 | 35 row 5 : dhi qar | 11.1% | 5 | 31 row 6 : diyala | none | 0 | 29 row 7 : karbala | 6.4% | 4 | 27 row 8 : maysan | 15.2% | 7 | 27 row 9 : al-muthanna | 9.3% | 5 | 26 row 10 : najaf | 14.8% | 7 | 28 row 11 : ninawa | 1.9% | 0 | 37 row 12 : al-qadisiyyah | 11.7% | 4 | 28 row 13 : salah ad-din | 2.9% | 1 | 28 row 14 : wassit | 10.0% | 6 | 28 row 15 : total | 6.6% | 52 | 440 | col : percentage row 1 : 11.7% | select percentage where governorate = 'al-qadisiyyah' <table_name> : table \begin{tabular}{lllll}
\toprule
& governorate & percentage & seats won & total seats \\
\midrule
0 & al-anbar & none & 0 & 29 \\
1 & babil & 8.2% & 5 & 30 \\
2 & baghdad & 5.4% & 3 & 57 \\
3 & basra & 11.6% & 5 & 35 \\
4 & dhi qar & 11.1% & 5 & 31 \\
5 & diyala & none & 0 & 29 \\
6 & karbala & 6.4% & 4 & 27 \\
7 & maysan & 15.2% & 7 & 27 \\
8 & al-muthanna & 9.3% & 5 & 26 \\
9 & najaf & 14.8% & 7 & 28 \\
10 & ninawa & 1.9% & 0 & 37 \\
11 & al-qadisiyyah & 11.7% & 4 & 28 \\
12 & salah ad-din & 2.9% & 1 & 28 \\
13 & wassit & 10.0% & 6 & 28 \\
14 & total & 6.6% & 52 & 440 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& percentage \\
\midrule
0 & 11.7% \\
\bottomrule
\end{tabular}
| select percentage where governorate = 'al-qadisiyyah' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>governorate</th>
<th>percentage</th>
<th>seats won</th>
<th>total seats</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>al-anbar</td>
<td>none</td>
<td>0</td>
<td>29</td>
</tr>
<tr>
<th>1</th>
<td>babil</td>
<td>8.2%</td>
<td>5</td>
<td>30</td>
</tr>
<tr>
<th>2</th>
<td>baghdad</td>
<td>5.4%</td>
<td>3</td>
<td>57</td>
</tr>
<tr>
<th>3</th>
<td>basra</td>
<td>11.6%</td>
<td>5</td>
<td>35</td>
</tr>
<tr>
<th>4</th>
<td>dhi qar</td>
<td>11.1%</td>
<td>5</td>
<td>31</td>
</tr>
<tr>
<th>5</th>
<td>diyala</td>
<td>none</td>
<td>0</td>
<td>29</td>
</tr>
<tr>
<th>6</th>
<td>karbala</td>
<td>6.4%</td>
<td>4</td>
<td>27</td>
</tr>
<tr>
<th>7</th>
<td>maysan</td>
<td>15.2%</td>
<td>7</td>
<td>27</td>
</tr>
<tr>
<th>8</th>
<td>al-muthanna</td>
<td>9.3%</td>
<td>5</td>
<td>26</td>
</tr>
<tr>
<th>9</th>
<td>najaf</td>
<td>14.8%</td>
<td>7</td>
<td>28</td>
</tr>
<tr>
<th>10</th>
<td>ninawa</td>
<td>1.9%</td>
<td>0</td>
<td>37</td>
</tr>
<tr>
<th>11</th>
<td>al-qadisiyyah</td>
<td>11.7%</td>
<td>4</td>
<td>28</td>
</tr>
<tr>
<th>12</th>
<td>salah ad-din</td>
<td>2.9%</td>
<td>1</td>
<td>28</td>
</tr>
<tr>
<th>13</th>
<td>wassit</td>
<td>10.0%</td>
<td>6</td>
<td>28</td>
</tr>
<tr>
<th>14</th>
<td>total</td>
<td>6.6%</td>
<td>52</td>
<td>440</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>percentage</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>11.7%</td>
</tr>
</tbody>
</table> | select percentage where governorate = 'al-qadisiyyah' <table_name> : table | | governorate | percentage | seats won | total seats |
|---:|:--------------|:-------------|------------:|--------------:|
| 0 | al-anbar | none | 0 | 29 |
| 1 | babil | 8.2% | 5 | 30 |
| 2 | baghdad | 5.4% | 3 | 57 |
| 3 | basra | 11.6% | 5 | 35 |
| 4 | dhi qar | 11.1% | 5 | 31 |
| 5 | diyala | none | 0 | 29 |
| 6 | karbala | 6.4% | 4 | 27 |
| 7 | maysan | 15.2% | 7 | 27 |
| 8 | al-muthanna | 9.3% | 5 | 26 |
| 9 | najaf | 14.8% | 7 | 28 |
| 10 | ninawa | 1.9% | 0 | 37 |
| 11 | al-qadisiyyah | 11.7% | 4 | 28 |
| 12 | salah ad-din | 2.9% | 1 | 28 |
| 13 | wassit | 10.0% | 6 | 28 |
| 14 | total | 6.6% | 52 | 440 | | | | percentage |
|---:|:-------------|
| 0 | 11.7% | | [
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select count ( nation ) where rank > 1 col : rank | nation | gold | silver | bronze | total row 1 : 1 | vietnam (vie) | 3 | 0 | 3 | 6 row 2 : 2 | south korea (kor) | 2 | 1 | 2 | 5 row 3 : 3 | kyrgyzstan (kgz) | 1 | 1 | 2 | 4 row 4 : 4 | kazakhstan (kaz) | 1 | 1 | 1 | 3 row 5 : 5 | iraq (irq) | 1 | 0 | 1 | 2 row 6 : 5 | turkmenistan (tkm) | 1 | 0 | 1 | 2 row 7 : 7 | jordan (jor) | 0 | 2 | 3 | 5 row 8 : 8 | uzbekistan (uzb) | 0 | 2 | 1 | 3 row 9 : 9 | tajikistan (tjk) | 0 | 1 | 1 | 2 row 10 : 10 | kuwait (kuw) | 0 | 1 | 0 | 1 row 11 : 11 | independent athletes (aoi) | 0 | 0 | 1 | 1 row 12 : 11 | mongolia (mgl) | 0 | 0 | 1 | 1 row 13 : 11 | palestine (ple) | 0 | 0 | 1 | 1 row 14 : total | total | 9 | 9 | 18 | 36 | col : count ( "nation" ) row 1 : 13 | select count ( nation ) where rank > 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & vietnam (vie) & 3 & 0 & 3 & 6 \\
1 & 2 & south korea (kor) & 2 & 1 & 2 & 5 \\
2 & 3 & kyrgyzstan (kgz) & 1 & 1 & 2 & 4 \\
3 & 4 & kazakhstan (kaz) & 1 & 1 & 1 & 3 \\
4 & 5 & iraq (irq) & 1 & 0 & 1 & 2 \\
5 & 5 & turkmenistan (tkm) & 1 & 0 & 1 & 2 \\
6 & 7 & jordan (jor) & 0 & 2 & 3 & 5 \\
7 & 8 & uzbekistan (uzb) & 0 & 2 & 1 & 3 \\
8 & 9 & tajikistan (tjk) & 0 & 1 & 1 & 2 \\
9 & 10 & kuwait (kuw) & 0 & 1 & 0 & 1 \\
10 & 11 & independent athletes (aoi) & 0 & 0 & 1 & 1 \\
11 & 11 & mongolia (mgl) & 0 & 0 & 1 & 1 \\
12 & 11 & palestine (ple) & 0 & 0 & 1 & 1 \\
13 & total & total & 9 & 9 & 18 & 36 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "nation" ) \\
\midrule
0 & 13 \\
\bottomrule
\end{tabular}
| select count ( nation ) where rank > 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>vietnam (vie)</td>
<td>3</td>
<td>0</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>south korea (kor)</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>5</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>kyrgyzstan (kgz)</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>kazakhstan (kaz)</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>iraq (irq)</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>turkmenistan (tkm)</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>jordan (jor)</td>
<td>0</td>
<td>2</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>uzbekistan (uzb)</td>
<td>0</td>
<td>2</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>tajikistan (tjk)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>kuwait (kuw)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>independent athletes (aoi)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>mongolia (mgl)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>11</td>
<td>palestine (ple)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>total</td>
<td>total</td>
<td>9</td>
<td>9</td>
<td>18</td>
<td>36</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "nation" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13</td>
</tr>
</tbody>
</table> | select count ( nation ) where rank > 1 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | vietnam (vie) | 3 | 0 | 3 | 6 |
| 1 | 2 | south korea (kor) | 2 | 1 | 2 | 5 |
| 2 | 3 | kyrgyzstan (kgz) | 1 | 1 | 2 | 4 |
| 3 | 4 | kazakhstan (kaz) | 1 | 1 | 1 | 3 |
| 4 | 5 | iraq (irq) | 1 | 0 | 1 | 2 |
| 5 | 5 | turkmenistan (tkm) | 1 | 0 | 1 | 2 |
| 6 | 7 | jordan (jor) | 0 | 2 | 3 | 5 |
| 7 | 8 | uzbekistan (uzb) | 0 | 2 | 1 | 3 |
| 8 | 9 | tajikistan (tjk) | 0 | 1 | 1 | 2 |
| 9 | 10 | kuwait (kuw) | 0 | 1 | 0 | 1 |
| 10 | 11 | independent athletes (aoi) | 0 | 0 | 1 | 1 |
| 11 | 11 | mongolia (mgl) | 0 | 0 | 1 | 1 |
| 12 | 11 | palestine (ple) | 0 | 0 | 1 | 1 |
| 13 | total | total | 9 | 9 | 18 | 36 | | | | count ( "nation" ) |
|---:|---------------------:|
| 0 | 13 | | [
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] |
select count ( * ) where album = 'hallelujah - live volume 2' col : year | title | chart positions nor | chart positions aus | chart positions aut | chart positions bel | chart positions ger | chart positions nl | chart positions nz | chart positions swe | chart positions swi | chart positions uk | album row 1 : 2003 | "she's so high" | 1 | 60 | 42 | 9 | 25 | 16 | 38 | none | 91 | 25 | i row 2 : 2004 | "here she comes" | 12 | none | none | 53 | none | none | none | none | none | none | i row 3 : 2004 | "all you have to offer" | none | none | none | none | none | none | none | none | none | none | i row 4 : 2004 | "my street" | none | none | none | none | none | none | none | none | none | none | a part of me row 5 : 2004 | "before you leave" | none | none | none | 52 | none | none | none | none | none | none | a part of me row 6 : 2005 | "never easy" | none | none | none | none | none | none | none | none | none | none | a part of me row 7 : 2006 | "when the stars go blue" (featuring venke knutson) | 14 | none | none | none | none | none | none | none | none | none | venke knutson's places i've been row 8 : 2006 | "hallelujah" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live row 9 : 2006 | "boys of summer" (with espen lind, askil holm and alejandro fuentes) | 12 | none | none | none | none | none | none | none | none | none | hallelujah - live row 10 : 2007 | "push, push" | 1 | none | none | none | none | none | none | none | none | none | push push row 11 : 2007 | "silence" | 9 | none | none | none | none | none | none | none | none | none | push push row 12 : 2008 | "reality kicks" | 20 | none | none | none | none | none | none | none | none | none | push push row 13 : 2008 | "lost highway" (featuring willie nelson) | 1 | none | none | none | none | none | none | none | none | none | rise to the occasion row 14 : 2008 | "don't have what it takes" | 19 | none | none | none | none | none | none | none | none | none | rise to the occasion row 15 : 2008 | "rise to the occasion" | none | none | none | none | none | none | none | 38 | none | none | rise to the occasion row 16 : 2009 | "with or without you" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live volume 2 row 17 : 2010 | "himmel pa jord" | 5 | none | none | none | none | none | none | none | none | none | have yourself a merry little christmas row 18 : 2013 | "adieu" | 9 | none | none | none | none | none | none | none | none | none | none row 19 : 2013 | "engler i sneen" (with lene marlin) | 7 | none | none | none | none | none | none | none | none | none | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where album = 'hallelujah - live volume 2' <table_name> : table \begin{tabular}{llllllllllllll}
\toprule
& year & title & chart positions nor & chart positions aus & chart positions aut & chart positions bel & chart positions ger & chart positions nl & chart positions nz & chart positions swe & chart positions swi & chart positions uk & album \\
\midrule
0 & 2003 & "she's so high" & 1 & 60 & 42 & 9 & 25 & 16 & 38 & none & 91 & 25 & i \\
1 & 2004 & "here she comes" & 12 & none & none & 53 & none & none & none & none & none & none & i \\
2 & 2004 & "all you have to offer" & none & none & none & none & none & none & none & none & none & none & i \\
3 & 2004 & "my street" & none & none & none & none & none & none & none & none & none & none & a part of me \\
4 & 2004 & "before you leave" & none & none & none & 52 & none & none & none & none & none & none & a part of me \\
5 & 2005 & "never easy" & none & none & none & none & none & none & none & none & none & none & a part of me \\
6 & 2006 & "when the stars go blue" (featuring venke knutson) & 14 & none & none & none & none & none & none & none & none & none & venke knutson's places i've been \\
7 & 2006 & "hallelujah" (with espen lind, askil holm and alejandro fuentes) & 1 & none & none & none & none & none & none & none & none & none & hallelujah - live \\
8 & 2006 & "boys of summer" (with espen lind, askil holm and alejandro fuentes) & 12 & none & none & none & none & none & none & none & none & none & hallelujah - live \\
9 & 2007 & "push, push" & 1 & none & none & none & none & none & none & none & none & none & push push \\
10 & 2007 & "silence" & 9 & none & none & none & none & none & none & none & none & none & push push \\
11 & 2008 & "reality kicks" & 20 & none & none & none & none & none & none & none & none & none & push push \\
12 & 2008 & "lost highway" (featuring willie nelson) & 1 & none & none & none & none & none & none & none & none & none & rise to the occasion \\
13 & 2008 & "don't have what it takes" & 19 & none & none & none & none & none & none & none & none & none & rise to the occasion \\
14 & 2008 & "rise to the occasion" & none & none & none & none & none & none & none & 38 & none & none & rise to the occasion \\
15 & 2009 & "with or without you" (with espen lind, askil holm and alejandro fuentes) & 1 & none & none & none & none & none & none & none & none & none & hallelujah - live volume 2 \\
16 & 2010 & "himmel pa jord" & 5 & none & none & none & none & none & none & none & none & none & have yourself a merry little christmas \\
17 & 2013 & "adieu" & 9 & none & none & none & none & none & none & none & none & none & none \\
18 & 2013 & "engler i sneen" (with lene marlin) & 7 & none & none & none & none & none & none & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where album = 'hallelujah - live volume 2' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>chart positions nor</th>
<th>chart positions aus</th>
<th>chart positions aut</th>
<th>chart positions bel</th>
<th>chart positions ger</th>
<th>chart positions nl</th>
<th>chart positions nz</th>
<th>chart positions swe</th>
<th>chart positions swi</th>
<th>chart positions uk</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2003</td>
<td>"she's so high"</td>
<td>1</td>
<td>60</td>
<td>42</td>
<td>9</td>
<td>25</td>
<td>16</td>
<td>38</td>
<td>none</td>
<td>91</td>
<td>25</td>
<td>i</td>
</tr>
<tr>
<th>1</th>
<td>2004</td>
<td>"here she comes"</td>
<td>12</td>
<td>none</td>
<td>none</td>
<td>53</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>i</td>
</tr>
<tr>
<th>2</th>
<td>2004</td>
<td>"all you have to offer"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>i</td>
</tr>
<tr>
<th>3</th>
<td>2004</td>
<td>"my street"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>a part of me</td>
</tr>
<tr>
<th>4</th>
<td>2004</td>
<td>"before you leave"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>52</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>a part of me</td>
</tr>
<tr>
<th>5</th>
<td>2005</td>
<td>"never easy"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>a part of me</td>
</tr>
<tr>
<th>6</th>
<td>2006</td>
<td>"when the stars go blue" (featuring venke knutson)</td>
<td>14</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>venke knutson's places i've been</td>
</tr>
<tr>
<th>7</th>
<td>2006</td>
<td>"hallelujah" (with espen lind, askil holm and alejandro fuentes)</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>hallelujah - live</td>
</tr>
<tr>
<th>8</th>
<td>2006</td>
<td>"boys of summer" (with espen lind, askil holm and alejandro fuentes)</td>
<td>12</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>hallelujah - live</td>
</tr>
<tr>
<th>9</th>
<td>2007</td>
<td>"push, push"</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>push push</td>
</tr>
<tr>
<th>10</th>
<td>2007</td>
<td>"silence"</td>
<td>9</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>push push</td>
</tr>
<tr>
<th>11</th>
<td>2008</td>
<td>"reality kicks"</td>
<td>20</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>push push</td>
</tr>
<tr>
<th>12</th>
<td>2008</td>
<td>"lost highway" (featuring willie nelson)</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>rise to the occasion</td>
</tr>
<tr>
<th>13</th>
<td>2008</td>
<td>"don't have what it takes"</td>
<td>19</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>rise to the occasion</td>
</tr>
<tr>
<th>14</th>
<td>2008</td>
<td>"rise to the occasion"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>38</td>
<td>none</td>
<td>none</td>
<td>rise to the occasion</td>
</tr>
<tr>
<th>15</th>
<td>2009</td>
<td>"with or without you" (with espen lind, askil holm and alejandro fuentes)</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>hallelujah - live volume 2</td>
</tr>
<tr>
<th>16</th>
<td>2010</td>
<td>"himmel pa jord"</td>
<td>5</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>have yourself a merry little christmas</td>
</tr>
<tr>
<th>17</th>
<td>2013</td>
<td>"adieu"</td>
<td>9</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>2013</td>
<td>"engler i sneen" (with lene marlin)</td>
<td>7</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where album = 'hallelujah - live volume 2' <table_name> : table | | year | title | chart positions nor | chart positions aus | chart positions aut | chart positions bel | chart positions ger | chart positions nl | chart positions nz | chart positions swe | chart positions swi | chart positions uk | album |
|---:|-------:|:--------------------------------------------------------------------------|:----------------------|:----------------------|:----------------------|:----------------------|:----------------------|:---------------------|:---------------------|:----------------------|:----------------------|:---------------------|:---------------------------------------|
| 0 | 2003 | "she's so high" | 1 | 60 | 42 | 9 | 25 | 16 | 38 | none | 91 | 25 | i |
| 1 | 2004 | "here she comes" | 12 | none | none | 53 | none | none | none | none | none | none | i |
| 2 | 2004 | "all you have to offer" | none | none | none | none | none | none | none | none | none | none | i |
| 3 | 2004 | "my street" | none | none | none | none | none | none | none | none | none | none | a part of me |
| 4 | 2004 | "before you leave" | none | none | none | 52 | none | none | none | none | none | none | a part of me |
| 5 | 2005 | "never easy" | none | none | none | none | none | none | none | none | none | none | a part of me |
| 6 | 2006 | "when the stars go blue" (featuring venke knutson) | 14 | none | none | none | none | none | none | none | none | none | venke knutson's places i've been |
| 7 | 2006 | "hallelujah" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live |
| 8 | 2006 | "boys of summer" (with espen lind, askil holm and alejandro fuentes) | 12 | none | none | none | none | none | none | none | none | none | hallelujah - live |
| 9 | 2007 | "push, push" | 1 | none | none | none | none | none | none | none | none | none | push push |
| 10 | 2007 | "silence" | 9 | none | none | none | none | none | none | none | none | none | push push |
| 11 | 2008 | "reality kicks" | 20 | none | none | none | none | none | none | none | none | none | push push |
| 12 | 2008 | "lost highway" (featuring willie nelson) | 1 | none | none | none | none | none | none | none | none | none | rise to the occasion |
| 13 | 2008 | "don't have what it takes" | 19 | none | none | none | none | none | none | none | none | none | rise to the occasion |
| 14 | 2008 | "rise to the occasion" | none | none | none | none | none | none | none | 38 | none | none | rise to the occasion |
| 15 | 2009 | "with or without you" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live volume 2 |
| 16 | 2010 | "himmel pa jord" | 5 | none | none | none | none | none | none | none | none | none | have yourself a merry little christmas |
| 17 | 2013 | "adieu" | 9 | none | none | none | none | none | none | none | none | none | none |
| 18 | 2013 | "engler i sneen" (with lene marlin) | 7 | none | none | none | none | none | none | none | none | none | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( constituency ) where change = 'none' col : no. | constituency | created | seats | change row 1 : 1 | carlow-kilkenny | 1948 | 5 | none row 2 : 2 | cavan-monaghan | 1977 | 5 | none row 3 : 3 | clare | 1921 | 4 | none row 4 : 4 | cork east | 1981 | 4 | none row 5 : 5 | cork north-central | 1981 | 4 | -1 row 6 : 6 | cork north-west | 1981 | 3 | none row 7 : 7 | cork south-central | 1981 | 5 | none row 8 : 8 | cork south-west | 1961 | 3 | none row 9 : 9 | donegal north-east | 1981 | 3 | none row 10 : 10 | donegal south-west | 1981 | 3 | none row 11 : 11 | dublin central | 1981 | 4 | none row 12 : 12 | dublin mid-west | 2002 | 4 | -1 row 13 : 13 | dublin north | 1981 | 4 | none row 14 : 14 | dublin north-central | 1948 | 3 | 1 row 15 : 15 | dublin north-east | 1981 | 3 | none row 16 : 16 | dublin north-west | 1981 | 3 | none row 17 : 17 | dublin south | 1981 | 5 | none row 18 : 18 | dublin south-central | 1948 | 5 | none row 19 : 19 | dublin south-east | 1948 | 4 | none row 20 : 20 | dublin south-west | 1981 | 4 | none row 21 : 21 | dublin west | 1981 | 3 | none row 22 : 22 | dun laoghaire | 1977 | 5 | none row 23 : 23 | galway east | 1977 | 4 | none row 24 : 24 | galway west | 1937 | 5 | none row 25 : 25 | kerry north | 1969 | 3 | none row 26 : 26 | kerry south | 1937 | 3 | none row 27 : 27 | kildare north | 1997 | 4 | 1 row 28 : 28 | kildare south | 1997 | 3 | none row 29 : 29 | laois-offaly | 2007 | 5 | 5 row 30 : 30 | limerick east | 1948 | 5 | none row 31 : 31 | limerick west | 1948 | 3 | none row 32 : 32 | longford-westmeath | 2007 | 4 | 4 row 33 : 33 | louth | 1923 | 4 | none row 34 : 34 | mayo | 1997 | 5 | none row 35 : 35 | meath east | 2007 | 3 | 3 row 36 : 36 | meath west | 2007 | 3 | 3 row 37 : 37 | roscommon-south leitrim | 2007 | 3 | 3 row 38 : 38 | sligo-north leitrim | 2007 | 3 | 3 row 39 : 39 | tipperary north | 1948 | 3 | none row 40 : 40 | tipperary south | 1948 | 3 | none row 41 : 41 | waterford | 1923 | 4 | none row 42 : 42 | wexford | 1921 | 5 | none row 43 : 43 | wicklow | 1923 | 5 | none | col : count ( "constituency" ) row 1 : 33 | select count ( constituency ) where change = 'none' <table_name> : table \begin{tabular}{llllll}
\toprule
& no. & constituency & created & seats & change \\
\midrule
0 & 1 & carlow-kilkenny & 1948 & 5 & none \\
1 & 2 & cavan-monaghan & 1977 & 5 & none \\
2 & 3 & clare & 1921 & 4 & none \\
3 & 4 & cork east & 1981 & 4 & none \\
4 & 5 & cork north-central & 1981 & 4 & -1 \\
5 & 6 & cork north-west & 1981 & 3 & none \\
6 & 7 & cork south-central & 1981 & 5 & none \\
7 & 8 & cork south-west & 1961 & 3 & none \\
8 & 9 & donegal north-east & 1981 & 3 & none \\
9 & 10 & donegal south-west & 1981 & 3 & none \\
10 & 11 & dublin central & 1981 & 4 & none \\
11 & 12 & dublin mid-west & 2002 & 4 & -1 \\
12 & 13 & dublin north & 1981 & 4 & none \\
13 & 14 & dublin north-central & 1948 & 3 & 1 \\
14 & 15 & dublin north-east & 1981 & 3 & none \\
15 & 16 & dublin north-west & 1981 & 3 & none \\
16 & 17 & dublin south & 1981 & 5 & none \\
17 & 18 & dublin south-central & 1948 & 5 & none \\
18 & 19 & dublin south-east & 1948 & 4 & none \\
19 & 20 & dublin south-west & 1981 & 4 & none \\
20 & 21 & dublin west & 1981 & 3 & none \\
21 & 22 & dun laoghaire & 1977 & 5 & none \\
22 & 23 & galway east & 1977 & 4 & none \\
23 & 24 & galway west & 1937 & 5 & none \\
24 & 25 & kerry north & 1969 & 3 & none \\
25 & 26 & kerry south & 1937 & 3 & none \\
26 & 27 & kildare north & 1997 & 4 & 1 \\
27 & 28 & kildare south & 1997 & 3 & none \\
28 & 29 & laois-offaly & 2007 & 5 & 5 \\
29 & 30 & limerick east & 1948 & 5 & none \\
30 & 31 & limerick west & 1948 & 3 & none \\
31 & 32 & longford-westmeath & 2007 & 4 & 4 \\
32 & 33 & louth & 1923 & 4 & none \\
33 & 34 & mayo & 1997 & 5 & none \\
34 & 35 & meath east & 2007 & 3 & 3 \\
35 & 36 & meath west & 2007 & 3 & 3 \\
36 & 37 & roscommon-south leitrim & 2007 & 3 & 3 \\
37 & 38 & sligo-north leitrim & 2007 & 3 & 3 \\
38 & 39 & tipperary north & 1948 & 3 & none \\
39 & 40 & tipperary south & 1948 & 3 & none \\
40 & 41 & waterford & 1923 & 4 & none \\
41 & 42 & wexford & 1921 & 5 & none \\
42 & 43 & wicklow & 1923 & 5 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "constituency" ) \\
\midrule
0 & 33 \\
\bottomrule
\end{tabular}
| select count ( constituency ) where change = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no.</th>
<th>constituency</th>
<th>created</th>
<th>seats</th>
<th>change</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>carlow-kilkenny</td>
<td>1948</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>cavan-monaghan</td>
<td>1977</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>clare</td>
<td>1921</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>cork east</td>
<td>1981</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>cork north-central</td>
<td>1981</td>
<td>4</td>
<td>-1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>cork north-west</td>
<td>1981</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>cork south-central</td>
<td>1981</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>cork south-west</td>
<td>1961</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>donegal north-east</td>
<td>1981</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>donegal south-west</td>
<td>1981</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>dublin central</td>
<td>1981</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>dublin mid-west</td>
<td>2002</td>
<td>4</td>
<td>-1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>dublin north</td>
<td>1981</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>dublin north-central</td>
<td>1948</td>
<td>3</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>dublin north-east</td>
<td>1981</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>dublin north-west</td>
<td>1981</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>dublin south</td>
<td>1981</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>dublin south-central</td>
<td>1948</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>dublin south-east</td>
<td>1948</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>dublin south-west</td>
<td>1981</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>dublin west</td>
<td>1981</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>dun laoghaire</td>
<td>1977</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>galway east</td>
<td>1977</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>galway west</td>
<td>1937</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>kerry north</td>
<td>1969</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>kerry south</td>
<td>1937</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>kildare north</td>
<td>1997</td>
<td>4</td>
<td>1</td>
</tr>
<tr>
<th>27</th>
<td>28</td>
<td>kildare south</td>
<td>1997</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>29</td>
<td>laois-offaly</td>
<td>2007</td>
<td>5</td>
<td>5</td>
</tr>
<tr>
<th>29</th>
<td>30</td>
<td>limerick east</td>
<td>1948</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>31</td>
<td>limerick west</td>
<td>1948</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>32</td>
<td>longford-westmeath</td>
<td>2007</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>32</th>
<td>33</td>
<td>louth</td>
<td>1923</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>33</th>
<td>34</td>
<td>mayo</td>
<td>1997</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>34</th>
<td>35</td>
<td>meath east</td>
<td>2007</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>35</th>
<td>36</td>
<td>meath west</td>
<td>2007</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>36</th>
<td>37</td>
<td>roscommon-south leitrim</td>
<td>2007</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>37</th>
<td>38</td>
<td>sligo-north leitrim</td>
<td>2007</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>38</th>
<td>39</td>
<td>tipperary north</td>
<td>1948</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>39</th>
<td>40</td>
<td>tipperary south</td>
<td>1948</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>40</th>
<td>41</td>
<td>waterford</td>
<td>1923</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>41</th>
<td>42</td>
<td>wexford</td>
<td>1921</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>42</th>
<td>43</td>
<td>wicklow</td>
<td>1923</td>
<td>5</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "constituency" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>33</td>
</tr>
</tbody>
</table> | select count ( constituency ) where change = 'none' <table_name> : table | | no. | constituency | created | seats | change |
|---:|------:|:------------------------|----------:|--------:|:---------|
| 0 | 1 | carlow-kilkenny | 1948 | 5 | none |
| 1 | 2 | cavan-monaghan | 1977 | 5 | none |
| 2 | 3 | clare | 1921 | 4 | none |
| 3 | 4 | cork east | 1981 | 4 | none |
| 4 | 5 | cork north-central | 1981 | 4 | -1 |
| 5 | 6 | cork north-west | 1981 | 3 | none |
| 6 | 7 | cork south-central | 1981 | 5 | none |
| 7 | 8 | cork south-west | 1961 | 3 | none |
| 8 | 9 | donegal north-east | 1981 | 3 | none |
| 9 | 10 | donegal south-west | 1981 | 3 | none |
| 10 | 11 | dublin central | 1981 | 4 | none |
| 11 | 12 | dublin mid-west | 2002 | 4 | -1 |
| 12 | 13 | dublin north | 1981 | 4 | none |
| 13 | 14 | dublin north-central | 1948 | 3 | 1 |
| 14 | 15 | dublin north-east | 1981 | 3 | none |
| 15 | 16 | dublin north-west | 1981 | 3 | none |
| 16 | 17 | dublin south | 1981 | 5 | none |
| 17 | 18 | dublin south-central | 1948 | 5 | none |
| 18 | 19 | dublin south-east | 1948 | 4 | none |
| 19 | 20 | dublin south-west | 1981 | 4 | none |
| 20 | 21 | dublin west | 1981 | 3 | none |
| 21 | 22 | dun laoghaire | 1977 | 5 | none |
| 22 | 23 | galway east | 1977 | 4 | none |
| 23 | 24 | galway west | 1937 | 5 | none |
| 24 | 25 | kerry north | 1969 | 3 | none |
| 25 | 26 | kerry south | 1937 | 3 | none |
| 26 | 27 | kildare north | 1997 | 4 | 1 |
| 27 | 28 | kildare south | 1997 | 3 | none |
| 28 | 29 | laois-offaly | 2007 | 5 | 5 |
| 29 | 30 | limerick east | 1948 | 5 | none |
| 30 | 31 | limerick west | 1948 | 3 | none |
| 31 | 32 | longford-westmeath | 2007 | 4 | 4 |
| 32 | 33 | louth | 1923 | 4 | none |
| 33 | 34 | mayo | 1997 | 5 | none |
| 34 | 35 | meath east | 2007 | 3 | 3 |
| 35 | 36 | meath west | 2007 | 3 | 3 |
| 36 | 37 | roscommon-south leitrim | 2007 | 3 | 3 |
| 37 | 38 | sligo-north leitrim | 2007 | 3 | 3 |
| 38 | 39 | tipperary north | 1948 | 3 | none |
| 39 | 40 | tipperary south | 1948 | 3 | none |
| 40 | 41 | waterford | 1923 | 4 | none |
| 41 | 42 | wexford | 1921 | 5 | none |
| 42 | 43 | wicklow | 1923 | 5 | none | | | | count ( "constituency" ) |
|---:|---------------------------:|
| 0 | 33 | | [
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] | [
[
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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select count ( % ) where % = 'others' col : party/electoral alliance | seats | change | votes | % row 1 : radical civic union (ucr) | 98 | 6 | 618411 | 42.70% row 2 : independent socialist | 15 | 9 | 110792 | 7.70% row 3 : conservative | 12 | -2 | 153826 | 10.60% row 4 : democratic (cordoba province) | 7 | 1 | none | none row 5 : unified ucr (santa fe province) | 4 | -7 | 53221 | 3.70% row 6 : liberal (tucuman province) | 4 | -2 | 39543 | 2.70% row 7 : democratic progressive | 3 | 3 | 136121 | 9.40% row 8 : antipersonalist ucr | 3 | -2 | 47891 | 3.30% row 9 : autonomist party of corrientes | 2 | -3 | 17152 | 1.20% row 10 : lencinist ucr (mendoza province) | 1 | none | 19375 | 1.30% row 11 : socialist | 1 | -3 | 123734 | 8.50% row 12 : others | 4 | none | 127601 | 8.60% row 13 : invalid votes | 4 | none | 39868 | 2.70% row 14 : total | 158 | none | 1487535 | 100.00% | col : count ( "%" ) row 1 : 0 | select count ( % ) where % = 'others' <table_name> : table \begin{tabular}{llllll}
\toprule
& party/electoral alliance & seats & change & votes & % \\
\midrule
0 & radical civic union (ucr) & 98 & 6 & 618411 & 42.70% \\
1 & independent socialist & 15 & 9 & 110792 & 7.70% \\
2 & conservative & 12 & -2 & 153826 & 10.60% \\
3 & democratic (cordoba province) & 7 & 1 & none & none \\
4 & unified ucr (santa fe province) & 4 & -7 & 53221 & 3.70% \\
5 & liberal (tucuman province) & 4 & -2 & 39543 & 2.70% \\
6 & democratic progressive & 3 & 3 & 136121 & 9.40% \\
7 & antipersonalist ucr & 3 & -2 & 47891 & 3.30% \\
8 & autonomist party of corrientes & 2 & -3 & 17152 & 1.20% \\
9 & lencinist ucr (mendoza province) & 1 & none & 19375 & 1.30% \\
10 & socialist & 1 & -3 & 123734 & 8.50% \\
11 & others & 4 & none & 127601 & 8.60% \\
12 & invalid votes & 4 & none & 39868 & 2.70% \\
13 & total & 158 & none & 1487535 & 100.00% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "%" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( % ) where % = 'others' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party/electoral alliance</th>
<th>seats</th>
<th>change</th>
<th>votes</th>
<th>%</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>radical civic union (ucr)</td>
<td>98</td>
<td>6</td>
<td>618411</td>
<td>42.70%</td>
</tr>
<tr>
<th>1</th>
<td>independent socialist</td>
<td>15</td>
<td>9</td>
<td>110792</td>
<td>7.70%</td>
</tr>
<tr>
<th>2</th>
<td>conservative</td>
<td>12</td>
<td>-2</td>
<td>153826</td>
<td>10.60%</td>
</tr>
<tr>
<th>3</th>
<td>democratic (cordoba province)</td>
<td>7</td>
<td>1</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>unified ucr (santa fe province)</td>
<td>4</td>
<td>-7</td>
<td>53221</td>
<td>3.70%</td>
</tr>
<tr>
<th>5</th>
<td>liberal (tucuman province)</td>
<td>4</td>
<td>-2</td>
<td>39543</td>
<td>2.70%</td>
</tr>
<tr>
<th>6</th>
<td>democratic progressive</td>
<td>3</td>
<td>3</td>
<td>136121</td>
<td>9.40%</td>
</tr>
<tr>
<th>7</th>
<td>antipersonalist ucr</td>
<td>3</td>
<td>-2</td>
<td>47891</td>
<td>3.30%</td>
</tr>
<tr>
<th>8</th>
<td>autonomist party of corrientes</td>
<td>2</td>
<td>-3</td>
<td>17152</td>
<td>1.20%</td>
</tr>
<tr>
<th>9</th>
<td>lencinist ucr (mendoza province)</td>
<td>1</td>
<td>none</td>
<td>19375</td>
<td>1.30%</td>
</tr>
<tr>
<th>10</th>
<td>socialist</td>
<td>1</td>
<td>-3</td>
<td>123734</td>
<td>8.50%</td>
</tr>
<tr>
<th>11</th>
<td>others</td>
<td>4</td>
<td>none</td>
<td>127601</td>
<td>8.60%</td>
</tr>
<tr>
<th>12</th>
<td>invalid votes</td>
<td>4</td>
<td>none</td>
<td>39868</td>
<td>2.70%</td>
</tr>
<tr>
<th>13</th>
<td>total</td>
<td>158</td>
<td>none</td>
<td>1487535</td>
<td>100.00%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "%" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( % ) where % = 'others' <table_name> : table | | party/electoral alliance | seats | change | votes | % |
|---:|:---------------------------------|--------:|:---------|:--------|:--------|
| 0 | radical civic union (ucr) | 98 | 6 | 618411 | 42.70% |
| 1 | independent socialist | 15 | 9 | 110792 | 7.70% |
| 2 | conservative | 12 | -2 | 153826 | 10.60% |
| 3 | democratic (cordoba province) | 7 | 1 | none | none |
| 4 | unified ucr (santa fe province) | 4 | -7 | 53221 | 3.70% |
| 5 | liberal (tucuman province) | 4 | -2 | 39543 | 2.70% |
| 6 | democratic progressive | 3 | 3 | 136121 | 9.40% |
| 7 | antipersonalist ucr | 3 | -2 | 47891 | 3.30% |
| 8 | autonomist party of corrientes | 2 | -3 | 17152 | 1.20% |
| 9 | lencinist ucr (mendoza province) | 1 | none | 19375 | 1.30% |
| 10 | socialist | 1 | -3 | 123734 | 8.50% |
| 11 | others | 4 | none | 127601 | 8.60% |
| 12 | invalid votes | 4 | none | 39868 | 2.70% |
| 13 | total | 158 | none | 1487535 | 100.00% | | | | count ( "%" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( title ) where title = 'fresh meat' col : title | character | broadcaster | episodes | date row 1 : rev | pip | bbc two | 1.0 | 2010 row 2 : the i.t. crowd | nikki | channel 4 | 1.0 | 2010 row 3 : eastenders: e20 | ava | bbc one | 15.0 | 2011 row 4 : fresh meat | caz | channel 4 | 1.0 | 2011 row 5 : phoneshop | daisy | channel 4 | 1.0 | 2011 row 6 : holby city | heidi hall | bbc one | 1.0 | 2012 row 7 : plebs | cynthia | itv2 | 6.0 | 2013 row 8 : blandings | valerie fanshawe | bbc | 2.5 | 2014 row 9 : death in paradise | helen walker | bbc | 3.4 | 2014 | col : count ( "title" ) row 1 : 1 | select count ( title ) where title = 'fresh meat' <table_name> : table \begin{tabular}{llllll}
\toprule
& title & character & broadcaster & episodes & date \\
\midrule
0 & rev & pip & bbc two & 1.0 & 2010 \\
1 & the i.t. crowd & nikki & channel 4 & 1.0 & 2010 \\
2 & eastenders: e20 & ava & bbc one & 15.0 & 2011 \\
3 & fresh meat & caz & channel 4 & 1.0 & 2011 \\
4 & phoneshop & daisy & channel 4 & 1.0 & 2011 \\
5 & holby city & heidi hall & bbc one & 1.0 & 2012 \\
6 & plebs & cynthia & itv2 & 6.0 & 2013 \\
7 & blandings & valerie fanshawe & bbc & 2.5 & 2014 \\
8 & death in paradise & helen walker & bbc & 3.4 & 2014 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "title" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( title ) where title = 'fresh meat' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title</th>
<th>character</th>
<th>broadcaster</th>
<th>episodes</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>rev</td>
<td>pip</td>
<td>bbc two</td>
<td>1.0</td>
<td>2010</td>
</tr>
<tr>
<th>1</th>
<td>the i.t. crowd</td>
<td>nikki</td>
<td>channel 4</td>
<td>1.0</td>
<td>2010</td>
</tr>
<tr>
<th>2</th>
<td>eastenders: e20</td>
<td>ava</td>
<td>bbc one</td>
<td>15.0</td>
<td>2011</td>
</tr>
<tr>
<th>3</th>
<td>fresh meat</td>
<td>caz</td>
<td>channel 4</td>
<td>1.0</td>
<td>2011</td>
</tr>
<tr>
<th>4</th>
<td>phoneshop</td>
<td>daisy</td>
<td>channel 4</td>
<td>1.0</td>
<td>2011</td>
</tr>
<tr>
<th>5</th>
<td>holby city</td>
<td>heidi hall</td>
<td>bbc one</td>
<td>1.0</td>
<td>2012</td>
</tr>
<tr>
<th>6</th>
<td>plebs</td>
<td>cynthia</td>
<td>itv2</td>
<td>6.0</td>
<td>2013</td>
</tr>
<tr>
<th>7</th>
<td>blandings</td>
<td>valerie fanshawe</td>
<td>bbc</td>
<td>2.5</td>
<td>2014</td>
</tr>
<tr>
<th>8</th>
<td>death in paradise</td>
<td>helen walker</td>
<td>bbc</td>
<td>3.4</td>
<td>2014</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "title" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( title ) where title = 'fresh meat' <table_name> : table | | title | character | broadcaster | episodes | date |
|---:|:------------------|:-----------------|:--------------|-----------:|-------:|
| 0 | rev | pip | bbc two | 1 | 2010 |
| 1 | the i.t. crowd | nikki | channel 4 | 1 | 2010 |
| 2 | eastenders: e20 | ava | bbc one | 15 | 2011 |
| 3 | fresh meat | caz | channel 4 | 1 | 2011 |
| 4 | phoneshop | daisy | channel 4 | 1 | 2011 |
| 5 | holby city | heidi hall | bbc one | 1 | 2012 |
| 6 | plebs | cynthia | itv2 | 6 | 2013 |
| 7 | blandings | valerie fanshawe | bbc | 2.5 | 2014 |
| 8 | death in paradise | helen walker | bbc | 3.4 | 2014 | | | | count ( "title" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select count ( driver ) where grid > 0 col : pos | no | driver | team | laps | time/retired | grid | points row 1 : 1 | 1 | sebastien bourdais | newman/haas racing | 66 | 1:51:31.146 | 2 | 34 row 2 : 2 | 9 | justin wilson | rusport | 66 | +3.528 secs | 1 | 29 row 3 : 3 | 5 | will power | team australia | 66 | +46.536 secs | 4 | 26 row 4 : 4 | 2 | bruno junqueira | newman/haas racing | 66 | +1:04.023 | 3 | 23 row 5 : 5 | 15 | alex tagliani | team australia | 66 | +1:18.033 | 8 | 22 row 6 : 6 | 6 | oriol servia | pkv racing | 66 | +1:28.745 | 7 | 19 row 7 : 7 | 4 | nelson philippe | cte racing - hvm | 66 | +1:29.997 | 10 | 17 row 8 : 8 | 27 | andrew ranger | mi-jack conquest racing | 65 | + 1 lap | 16 | 16 row 9 : 9 | 3 | david martinez | forsythe racing | 65 | + 1 lap | 9 | 13 row 10 : 10 | 7 | buddy rice | forsythe racing | 65 | + 1 lap | 14 | 11 row 11 : 11 | 34 | charles zwolsman | mi-jack conquest racing | 65 | + 1 lap | 12 | 10 row 12 : 12 | 18 | antonio pizzonia | rocketsports racing | 65 | + 1 lap | 15 | 9 row 13 : 13 | 11 | jan heylen | dale coyne racing | 65 | + 1 lap | 17 | 8 row 14 : 14 | 10 | ryan briscoe | rusport | 64 | + 2 laps | 5 | 7 row 15 : 15 | 19 | andreas wirth | dale coyne racing | 64 | + 2 laps | 18 | 6 row 16 : 16 | 20 | katherine legge | pkv racing | 63 | + 3 laps | 13 | 5 row 17 : 17 | 8 | mario dominguez | rocketsports racing | 59 | retired | 11 | 4 row 18 : 18 | 14 | dan clarke | cte racing - hvm | 7 | differential | 6 | 3 | col : count ( "driver" ) row 1 : 18 | select count ( driver ) where grid > 0 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & team & laps & time/retired & grid & points \\
\midrule
0 & 1 & 1 & sebastien bourdais & newman/haas racing & 66 & 1:51:31.146 & 2 & 34 \\
1 & 2 & 9 & justin wilson & rusport & 66 & +3.528 secs & 1 & 29 \\
2 & 3 & 5 & will power & team australia & 66 & +46.536 secs & 4 & 26 \\
3 & 4 & 2 & bruno junqueira & newman/haas racing & 66 & +1:04.023 & 3 & 23 \\
4 & 5 & 15 & alex tagliani & team australia & 66 & +1:18.033 & 8 & 22 \\
5 & 6 & 6 & oriol servia & pkv racing & 66 & +1:28.745 & 7 & 19 \\
6 & 7 & 4 & nelson philippe & cte racing - hvm & 66 & +1:29.997 & 10 & 17 \\
7 & 8 & 27 & andrew ranger & mi-jack conquest racing & 65 & + 1 lap & 16 & 16 \\
8 & 9 & 3 & david martinez & forsythe racing & 65 & + 1 lap & 9 & 13 \\
9 & 10 & 7 & buddy rice & forsythe racing & 65 & + 1 lap & 14 & 11 \\
10 & 11 & 34 & charles zwolsman & mi-jack conquest racing & 65 & + 1 lap & 12 & 10 \\
11 & 12 & 18 & antonio pizzonia & rocketsports racing & 65 & + 1 lap & 15 & 9 \\
12 & 13 & 11 & jan heylen & dale coyne racing & 65 & + 1 lap & 17 & 8 \\
13 & 14 & 10 & ryan briscoe & rusport & 64 & + 2 laps & 5 & 7 \\
14 & 15 & 19 & andreas wirth & dale coyne racing & 64 & + 2 laps & 18 & 6 \\
15 & 16 & 20 & katherine legge & pkv racing & 63 & + 3 laps & 13 & 5 \\
16 & 17 & 8 & mario dominguez & rocketsports racing & 59 & retired & 11 & 4 \\
17 & 18 & 14 & dan clarke & cte racing - hvm & 7 & differential & 6 & 3 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "driver" ) \\
\midrule
0 & 18 \\
\bottomrule
\end{tabular}
| select count ( driver ) where grid > 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>driver</th>
<th>team</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1</td>
<td>sebastien bourdais</td>
<td>newman/haas racing</td>
<td>66</td>
<td>1:51:31.146</td>
<td>2</td>
<td>34</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>9</td>
<td>justin wilson</td>
<td>rusport</td>
<td>66</td>
<td>+3.528 secs</td>
<td>1</td>
<td>29</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>5</td>
<td>will power</td>
<td>team australia</td>
<td>66</td>
<td>+46.536 secs</td>
<td>4</td>
<td>26</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2</td>
<td>bruno junqueira</td>
<td>newman/haas racing</td>
<td>66</td>
<td>+1:04.023</td>
<td>3</td>
<td>23</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>15</td>
<td>alex tagliani</td>
<td>team australia</td>
<td>66</td>
<td>+1:18.033</td>
<td>8</td>
<td>22</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>6</td>
<td>oriol servia</td>
<td>pkv racing</td>
<td>66</td>
<td>+1:28.745</td>
<td>7</td>
<td>19</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>4</td>
<td>nelson philippe</td>
<td>cte racing - hvm</td>
<td>66</td>
<td>+1:29.997</td>
<td>10</td>
<td>17</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>27</td>
<td>andrew ranger</td>
<td>mi-jack conquest racing</td>
<td>65</td>
<td>+ 1 lap</td>
<td>16</td>
<td>16</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>3</td>
<td>david martinez</td>
<td>forsythe racing</td>
<td>65</td>
<td>+ 1 lap</td>
<td>9</td>
<td>13</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>7</td>
<td>buddy rice</td>
<td>forsythe racing</td>
<td>65</td>
<td>+ 1 lap</td>
<td>14</td>
<td>11</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>34</td>
<td>charles zwolsman</td>
<td>mi-jack conquest racing</td>
<td>65</td>
<td>+ 1 lap</td>
<td>12</td>
<td>10</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>18</td>
<td>antonio pizzonia</td>
<td>rocketsports racing</td>
<td>65</td>
<td>+ 1 lap</td>
<td>15</td>
<td>9</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>11</td>
<td>jan heylen</td>
<td>dale coyne racing</td>
<td>65</td>
<td>+ 1 lap</td>
<td>17</td>
<td>8</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>10</td>
<td>ryan briscoe</td>
<td>rusport</td>
<td>64</td>
<td>+ 2 laps</td>
<td>5</td>
<td>7</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>19</td>
<td>andreas wirth</td>
<td>dale coyne racing</td>
<td>64</td>
<td>+ 2 laps</td>
<td>18</td>
<td>6</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>20</td>
<td>katherine legge</td>
<td>pkv racing</td>
<td>63</td>
<td>+ 3 laps</td>
<td>13</td>
<td>5</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>8</td>
<td>mario dominguez</td>
<td>rocketsports racing</td>
<td>59</td>
<td>retired</td>
<td>11</td>
<td>4</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>14</td>
<td>dan clarke</td>
<td>cte racing - hvm</td>
<td>7</td>
<td>differential</td>
<td>6</td>
<td>3</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "driver" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>18</td>
</tr>
</tbody>
</table> | select count ( driver ) where grid > 0 <table_name> : table | | pos | no | driver | team | laps | time/retired | grid | points |
|---:|------:|-----:|:-------------------|:------------------------|-------:|:---------------|-------:|---------:|
| 0 | 1 | 1 | sebastien bourdais | newman/haas racing | 66 | 1:51:31.146 | 2 | 34 |
| 1 | 2 | 9 | justin wilson | rusport | 66 | +3.528 secs | 1 | 29 |
| 2 | 3 | 5 | will power | team australia | 66 | +46.536 secs | 4 | 26 |
| 3 | 4 | 2 | bruno junqueira | newman/haas racing | 66 | +1:04.023 | 3 | 23 |
| 4 | 5 | 15 | alex tagliani | team australia | 66 | +1:18.033 | 8 | 22 |
| 5 | 6 | 6 | oriol servia | pkv racing | 66 | +1:28.745 | 7 | 19 |
| 6 | 7 | 4 | nelson philippe | cte racing - hvm | 66 | +1:29.997 | 10 | 17 |
| 7 | 8 | 27 | andrew ranger | mi-jack conquest racing | 65 | + 1 lap | 16 | 16 |
| 8 | 9 | 3 | david martinez | forsythe racing | 65 | + 1 lap | 9 | 13 |
| 9 | 10 | 7 | buddy rice | forsythe racing | 65 | + 1 lap | 14 | 11 |
| 10 | 11 | 34 | charles zwolsman | mi-jack conquest racing | 65 | + 1 lap | 12 | 10 |
| 11 | 12 | 18 | antonio pizzonia | rocketsports racing | 65 | + 1 lap | 15 | 9 |
| 12 | 13 | 11 | jan heylen | dale coyne racing | 65 | + 1 lap | 17 | 8 |
| 13 | 14 | 10 | ryan briscoe | rusport | 64 | + 2 laps | 5 | 7 |
| 14 | 15 | 19 | andreas wirth | dale coyne racing | 64 | + 2 laps | 18 | 6 |
| 15 | 16 | 20 | katherine legge | pkv racing | 63 | + 3 laps | 13 | 5 |
| 16 | 17 | 8 | mario dominguez | rocketsports racing | 59 | retired | 11 | 4 |
| 17 | 18 | 14 | dan clarke | cte racing - hvm | 7 | differential | 6 | 3 | | | | count ( "driver" ) |
|---:|---------------------:|
| 0 | 18 | | [
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select location where date = '1933 may 1' col : result | record | opponent | method | date | round | location row 1 : loss | 31-3-0 | j.h. isbell | ko | 1934-03-31 00:00:00 | 2 | cambridge, massachusetts row 2 : loss | 31-2-0 | "modest" bill smith | ko | 1934-02-27 00:00:00 | 2 | cambridge, massachusetts row 3 : win | 31-1-0 | frankie hagen | ko | 1934-02-24 00:00:00 | 1 | cambridge, massachusetts row 4 : win | 30-1-0 | harry gardner | ko | 1934-02-21 00:00:00 | 1 | cambridge, massachusetts row 5 : win | 29-1-0 | sid stoneman | ko | 1934-02-14 00:00:00 | 1 | cambridge, massachusetts row 6 : win | 28-1-0 | frankie hagan | pts | 1934-01-30 00:00:00 | 3 | cambridge, massachusetts row 7 : win | 27-1-0 | basil barnett | ko | 1934-01-24 00:00:00 | 2 | cambridge, massachusetts row 8 : win | 26-1-0 | george krause | ko | 1934-01-16 00:00:00 | 1 | cambridge, massachusetts row 9 : win | 25-1-0 | bob delmont | ko | 1934-01-07 00:00:00 | 1 | cambridge, massachusetts row 10 : loss | 24-1-0 | brad simmons | ko | 1934-01-01 00:00:00 | 1 | cambridge, massachusetts row 11 : win | 24-0-0 | herman zeinman | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 12 : win | 23-0-0 | william beltran | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 13 : win | 22-0-0 | lloyd blake | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 14 : win | 21-0-0 | lawrence "larry" o'neil | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 15 : win | 20-0-0 | igg rosenberg | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 16 : win | 19-0-0 | melvin kenyon | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 17 : win | 18-0-0 | gary keers | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 18 : win | 17-0-0 | samuel rodgway | ko | 1933-05-28 00:00:00 | 1 | cambridge, massachusetts row 19 : exch | 16-0-0 | "irish" tommy mitchell | ko | 1933-05-21 00:00:00 | 1 | cambridge, massachusetts row 20 : win | 15-0-0 | jim crawford | ko | 1933-05-14 00:00:00 | 1 | cambridge, massachusetts row 21 : win | 14-0-0 | max levine | ko | 1933-05-07 00:00:00 | 1 | cambridge, massachusetts row 22 : win | 13-0-0 | leo hart | ko | 1933-05-01 00:00:00 | 1 | cambridge, massachusetts row 23 : win | 12-0-0 | paul benjamin | pts | 1932-01-01 00:00:00 | 3 | evanston, illinois row 24 : win | 11-0-0 | fred chapman | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois row 25 : win | 10-0-0 | paul benjamin | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois row 26 : win | 9-0-0 | rod conley | ko | 1932-01-01 00:00:00 | 2 | evanston, illinois row 27 : win | 8-0-0 | paul gilmore | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 28 : win | 7-0-0 | jack lewis | ko | 1932-01-01 00:00:00 | 3 | chicago, illinois row 29 : exch | 6-0-0 | eddie mitchell | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 30 : win | 5-0-0 | ernest brant | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 31 : win | 4-0-0 | karl brenner-eggers | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 32 : win | 3-0-0 | norman martin | pts | 1932-01-01 00:00:00 | 3 | chicago, illinois row 33 : win | 2-0-0 | albert leikman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 34 : win | 1-0-0 | keith newman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois | col : location row 1 : cambridge, massachusetts | select location where date = '1933 may 1' <table_name> : table \begin{tabular}{llllllll}
\toprule
& result & record & opponent & method & date & round & location \\
\midrule
0 & loss & 31-3-0 & j.h. isbell & ko & 1934-03-31 00:00:00 & 2 & cambridge, massachusetts \\
1 & loss & 31-2-0 & "modest" bill smith & ko & 1934-02-27 00:00:00 & 2 & cambridge, massachusetts \\
2 & win & 31-1-0 & frankie hagen & ko & 1934-02-24 00:00:00 & 1 & cambridge, massachusetts \\
3 & win & 30-1-0 & harry gardner & ko & 1934-02-21 00:00:00 & 1 & cambridge, massachusetts \\
4 & win & 29-1-0 & sid stoneman & ko & 1934-02-14 00:00:00 & 1 & cambridge, massachusetts \\
5 & win & 28-1-0 & frankie hagan & pts & 1934-01-30 00:00:00 & 3 & cambridge, massachusetts \\
6 & win & 27-1-0 & basil barnett & ko & 1934-01-24 00:00:00 & 2 & cambridge, massachusetts \\
7 & win & 26-1-0 & george krause & ko & 1934-01-16 00:00:00 & 1 & cambridge, massachusetts \\
8 & win & 25-1-0 & bob delmont & ko & 1934-01-07 00:00:00 & 1 & cambridge, massachusetts \\
9 & loss & 24-1-0 & brad simmons & ko & 1934-01-01 00:00:00 & 1 & cambridge, massachusetts \\
10 & win & 24-0-0 & herman zeinman & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
11 & win & 23-0-0 & william beltran & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
12 & win & 22-0-0 & lloyd blake & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
13 & win & 21-0-0 & lawrence "larry" o'neil & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
14 & win & 20-0-0 & igg rosenberg & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
15 & win & 19-0-0 & melvin kenyon & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
16 & win & 18-0-0 & gary keers & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
17 & win & 17-0-0 & samuel rodgway & ko & 1933-05-28 00:00:00 & 1 & cambridge, massachusetts \\
18 & exch & 16-0-0 & "irish" tommy mitchell & ko & 1933-05-21 00:00:00 & 1 & cambridge, massachusetts \\
19 & win & 15-0-0 & jim crawford & ko & 1933-05-14 00:00:00 & 1 & cambridge, massachusetts \\
20 & win & 14-0-0 & max levine & ko & 1933-05-07 00:00:00 & 1 & cambridge, massachusetts \\
21 & win & 13-0-0 & leo hart & ko & 1933-05-01 00:00:00 & 1 & cambridge, massachusetts \\
22 & win & 12-0-0 & paul benjamin & pts & 1932-01-01 00:00:00 & 3 & evanston, illinois \\
23 & win & 11-0-0 & fred chapman & ko & 1932-01-01 00:00:00 & 3 & evanston, illinois \\
24 & win & 10-0-0 & paul benjamin & ko & 1932-01-01 00:00:00 & 3 & evanston, illinois \\
25 & win & 9-0-0 & rod conley & ko & 1932-01-01 00:00:00 & 2 & evanston, illinois \\
26 & win & 8-0-0 & paul gilmore & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
27 & win & 7-0-0 & jack lewis & ko & 1932-01-01 00:00:00 & 3 & chicago, illinois \\
28 & exch & 6-0-0 & eddie mitchell & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
29 & win & 5-0-0 & ernest brant & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
30 & win & 4-0-0 & karl brenner-eggers & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
31 & win & 3-0-0 & norman martin & pts & 1932-01-01 00:00:00 & 3 & chicago, illinois \\
32 & win & 2-0-0 & albert leikman & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
33 & win & 1-0-0 & keith newman & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& location \\
\midrule
0 & cambridge, massachusetts \\
\bottomrule
\end{tabular}
| select location where date = '1933 may 1' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>result</th>
<th>record</th>
<th>opponent</th>
<th>method</th>
<th>date</th>
<th>round</th>
<th>location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>loss</td>
<td>31-3-0</td>
<td>j.h. isbell</td>
<td>ko</td>
<td>1934-03-31 00:00:00</td>
<td>2</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>1</th>
<td>loss</td>
<td>31-2-0</td>
<td>"modest" bill smith</td>
<td>ko</td>
<td>1934-02-27 00:00:00</td>
<td>2</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>2</th>
<td>win</td>
<td>31-1-0</td>
<td>frankie hagen</td>
<td>ko</td>
<td>1934-02-24 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>3</th>
<td>win</td>
<td>30-1-0</td>
<td>harry gardner</td>
<td>ko</td>
<td>1934-02-21 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>4</th>
<td>win</td>
<td>29-1-0</td>
<td>sid stoneman</td>
<td>ko</td>
<td>1934-02-14 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>5</th>
<td>win</td>
<td>28-1-0</td>
<td>frankie hagan</td>
<td>pts</td>
<td>1934-01-30 00:00:00</td>
<td>3</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>6</th>
<td>win</td>
<td>27-1-0</td>
<td>basil barnett</td>
<td>ko</td>
<td>1934-01-24 00:00:00</td>
<td>2</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>7</th>
<td>win</td>
<td>26-1-0</td>
<td>george krause</td>
<td>ko</td>
<td>1934-01-16 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>8</th>
<td>win</td>
<td>25-1-0</td>
<td>bob delmont</td>
<td>ko</td>
<td>1934-01-07 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>9</th>
<td>loss</td>
<td>24-1-0</td>
<td>brad simmons</td>
<td>ko</td>
<td>1934-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>10</th>
<td>win</td>
<td>24-0-0</td>
<td>herman zeinman</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>11</th>
<td>win</td>
<td>23-0-0</td>
<td>william beltran</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>12</th>
<td>win</td>
<td>22-0-0</td>
<td>lloyd blake</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>13</th>
<td>win</td>
<td>21-0-0</td>
<td>lawrence "larry" o'neil</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>14</th>
<td>win</td>
<td>20-0-0</td>
<td>igg rosenberg</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>15</th>
<td>win</td>
<td>19-0-0</td>
<td>melvin kenyon</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>16</th>
<td>win</td>
<td>18-0-0</td>
<td>gary keers</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>17</th>
<td>win</td>
<td>17-0-0</td>
<td>samuel rodgway</td>
<td>ko</td>
<td>1933-05-28 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>18</th>
<td>exch</td>
<td>16-0-0</td>
<td>"irish" tommy mitchell</td>
<td>ko</td>
<td>1933-05-21 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>19</th>
<td>win</td>
<td>15-0-0</td>
<td>jim crawford</td>
<td>ko</td>
<td>1933-05-14 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>20</th>
<td>win</td>
<td>14-0-0</td>
<td>max levine</td>
<td>ko</td>
<td>1933-05-07 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>21</th>
<td>win</td>
<td>13-0-0</td>
<td>leo hart</td>
<td>ko</td>
<td>1933-05-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>22</th>
<td>win</td>
<td>12-0-0</td>
<td>paul benjamin</td>
<td>pts</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>23</th>
<td>win</td>
<td>11-0-0</td>
<td>fred chapman</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>24</th>
<td>win</td>
<td>10-0-0</td>
<td>paul benjamin</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>25</th>
<td>win</td>
<td>9-0-0</td>
<td>rod conley</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>2</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>26</th>
<td>win</td>
<td>8-0-0</td>
<td>paul gilmore</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>27</th>
<td>win</td>
<td>7-0-0</td>
<td>jack lewis</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>28</th>
<td>exch</td>
<td>6-0-0</td>
<td>eddie mitchell</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>29</th>
<td>win</td>
<td>5-0-0</td>
<td>ernest brant</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>30</th>
<td>win</td>
<td>4-0-0</td>
<td>karl brenner-eggers</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>31</th>
<td>win</td>
<td>3-0-0</td>
<td>norman martin</td>
<td>pts</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>32</th>
<td>win</td>
<td>2-0-0</td>
<td>albert leikman</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>33</th>
<td>win</td>
<td>1-0-0</td>
<td>keith newman</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cambridge, massachusetts</td>
</tr>
</tbody>
</table> | select location where date = '1933 may 1' <table_name> : table | | result | record | opponent | method | date | round | location |
|---:|:---------|:---------|:------------------------|:---------|:--------------------|--------:|:-------------------------|
| 0 | loss | 31-3-0 | j.h. isbell | ko | 1934-03-31 00:00:00 | 2 | cambridge, massachusetts |
| 1 | loss | 31-2-0 | "modest" bill smith | ko | 1934-02-27 00:00:00 | 2 | cambridge, massachusetts |
| 2 | win | 31-1-0 | frankie hagen | ko | 1934-02-24 00:00:00 | 1 | cambridge, massachusetts |
| 3 | win | 30-1-0 | harry gardner | ko | 1934-02-21 00:00:00 | 1 | cambridge, massachusetts |
| 4 | win | 29-1-0 | sid stoneman | ko | 1934-02-14 00:00:00 | 1 | cambridge, massachusetts |
| 5 | win | 28-1-0 | frankie hagan | pts | 1934-01-30 00:00:00 | 3 | cambridge, massachusetts |
| 6 | win | 27-1-0 | basil barnett | ko | 1934-01-24 00:00:00 | 2 | cambridge, massachusetts |
| 7 | win | 26-1-0 | george krause | ko | 1934-01-16 00:00:00 | 1 | cambridge, massachusetts |
| 8 | win | 25-1-0 | bob delmont | ko | 1934-01-07 00:00:00 | 1 | cambridge, massachusetts |
| 9 | loss | 24-1-0 | brad simmons | ko | 1934-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 10 | win | 24-0-0 | herman zeinman | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 11 | win | 23-0-0 | william beltran | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 12 | win | 22-0-0 | lloyd blake | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 13 | win | 21-0-0 | lawrence "larry" o'neil | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 14 | win | 20-0-0 | igg rosenberg | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 15 | win | 19-0-0 | melvin kenyon | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 16 | win | 18-0-0 | gary keers | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 17 | win | 17-0-0 | samuel rodgway | ko | 1933-05-28 00:00:00 | 1 | cambridge, massachusetts |
| 18 | exch | 16-0-0 | "irish" tommy mitchell | ko | 1933-05-21 00:00:00 | 1 | cambridge, massachusetts |
| 19 | win | 15-0-0 | jim crawford | ko | 1933-05-14 00:00:00 | 1 | cambridge, massachusetts |
| 20 | win | 14-0-0 | max levine | ko | 1933-05-07 00:00:00 | 1 | cambridge, massachusetts |
| 21 | win | 13-0-0 | leo hart | ko | 1933-05-01 00:00:00 | 1 | cambridge, massachusetts |
| 22 | win | 12-0-0 | paul benjamin | pts | 1932-01-01 00:00:00 | 3 | evanston, illinois |
| 23 | win | 11-0-0 | fred chapman | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois |
| 24 | win | 10-0-0 | paul benjamin | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois |
| 25 | win | 9-0-0 | rod conley | ko | 1932-01-01 00:00:00 | 2 | evanston, illinois |
| 26 | win | 8-0-0 | paul gilmore | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 27 | win | 7-0-0 | jack lewis | ko | 1932-01-01 00:00:00 | 3 | chicago, illinois |
| 28 | exch | 6-0-0 | eddie mitchell | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 29 | win | 5-0-0 | ernest brant | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 30 | win | 4-0-0 | karl brenner-eggers | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 31 | win | 3-0-0 | norman martin | pts | 1932-01-01 00:00:00 | 3 | chicago, illinois |
| 32 | win | 2-0-0 | albert leikman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 33 | win | 1-0-0 | keith newman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois | | | | location |
|---:|:-------------------------|
| 0 | cambridge, massachusetts | | [
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select game where opponent = '@ montreal canadiens' col : game | november | opponent | score | record row 1 : 2 | 5 | @ detroit red wings | 12 - 5 | 0-2-0 row 2 : 3 | 7 | montreal canadiens | 4 - 3 ot | 1-2-0 row 3 : 4 | 8 | @ montreal canadiens | 10 - 4 | 1-3-0 row 4 : 5 | 10 | chicago black hawks | 5 - 3 ot | 2-3-0 row 5 : 6 | 14 | @ boston bruins | 5 - 3 | 2-4-0 row 6 : 7 | 15 | boston bruins | 4 - 3 | 2-5-0 row 7 : 8 | 19 | toronto maple leafs | 7 - 3 | 2-6-0 row 8 : 9 | 22 | detroit red wings | 4 - 4 | 2-6-1 row 9 : 10 | 26 | @ chicago black hawks | 2 - 1 | 3-6-1 row 10 : 11 | 28 | @ toronto maple leafs | 8 - 6 | 3-7-1 row 11 : 12 | 29 | boston bruins | 3 - 2 | 4-7-1 | col : game row 1 : 4 | select game where opponent = '@ montreal canadiens' <table_name> : table \begin{tabular}{llllll}
\toprule
& game & november & opponent & score & record \\
\midrule
0 & 2 & 5 & @ detroit red wings & 12 - 5 & 0-2-0 \\
1 & 3 & 7 & montreal canadiens & 4 - 3 ot & 1-2-0 \\
2 & 4 & 8 & @ montreal canadiens & 10 - 4 & 1-3-0 \\
3 & 5 & 10 & chicago black hawks & 5 - 3 ot & 2-3-0 \\
4 & 6 & 14 & @ boston bruins & 5 - 3 & 2-4-0 \\
5 & 7 & 15 & boston bruins & 4 - 3 & 2-5-0 \\
6 & 8 & 19 & toronto maple leafs & 7 - 3 & 2-6-0 \\
7 & 9 & 22 & detroit red wings & 4 - 4 & 2-6-1 \\
8 & 10 & 26 & @ chicago black hawks & 2 - 1 & 3-6-1 \\
9 & 11 & 28 & @ toronto maple leafs & 8 - 6 & 3-7-1 \\
10 & 12 & 29 & boston bruins & 3 - 2 & 4-7-1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& game \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select game where opponent = '@ montreal canadiens' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>november</th>
<th>opponent</th>
<th>score</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
<td>5</td>
<td>@ detroit red wings</td>
<td>12 - 5</td>
<td>0-2-0</td>
</tr>
<tr>
<th>1</th>
<td>3</td>
<td>7</td>
<td>montreal canadiens</td>
<td>4 - 3 ot</td>
<td>1-2-0</td>
</tr>
<tr>
<th>2</th>
<td>4</td>
<td>8</td>
<td>@ montreal canadiens</td>
<td>10 - 4</td>
<td>1-3-0</td>
</tr>
<tr>
<th>3</th>
<td>5</td>
<td>10</td>
<td>chicago black hawks</td>
<td>5 - 3 ot</td>
<td>2-3-0</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>14</td>
<td>@ boston bruins</td>
<td>5 - 3</td>
<td>2-4-0</td>
</tr>
<tr>
<th>5</th>
<td>7</td>
<td>15</td>
<td>boston bruins</td>
<td>4 - 3</td>
<td>2-5-0</td>
</tr>
<tr>
<th>6</th>
<td>8</td>
<td>19</td>
<td>toronto maple leafs</td>
<td>7 - 3</td>
<td>2-6-0</td>
</tr>
<tr>
<th>7</th>
<td>9</td>
<td>22</td>
<td>detroit red wings</td>
<td>4 - 4</td>
<td>2-6-1</td>
</tr>
<tr>
<th>8</th>
<td>10</td>
<td>26</td>
<td>@ chicago black hawks</td>
<td>2 - 1</td>
<td>3-6-1</td>
</tr>
<tr>
<th>9</th>
<td>11</td>
<td>28</td>
<td>@ toronto maple leafs</td>
<td>8 - 6</td>
<td>3-7-1</td>
</tr>
<tr>
<th>10</th>
<td>12</td>
<td>29</td>
<td>boston bruins</td>
<td>3 - 2</td>
<td>4-7-1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select game where opponent = '@ montreal canadiens' <table_name> : table | | game | november | opponent | score | record |
|---:|-------:|-----------:|:----------------------|:---------|:---------|
| 0 | 2 | 5 | @ detroit red wings | 12 - 5 | 0-2-0 |
| 1 | 3 | 7 | montreal canadiens | 4 - 3 ot | 1-2-0 |
| 2 | 4 | 8 | @ montreal canadiens | 10 - 4 | 1-3-0 |
| 3 | 5 | 10 | chicago black hawks | 5 - 3 ot | 2-3-0 |
| 4 | 6 | 14 | @ boston bruins | 5 - 3 | 2-4-0 |
| 5 | 7 | 15 | boston bruins | 4 - 3 | 2-5-0 |
| 6 | 8 | 19 | toronto maple leafs | 7 - 3 | 2-6-0 |
| 7 | 9 | 22 | detroit red wings | 4 - 4 | 2-6-1 |
| 8 | 10 | 26 | @ chicago black hawks | 2 - 1 | 3-6-1 |
| 9 | 11 | 28 | @ toronto maple leafs | 8 - 6 | 3-7-1 |
| 10 | 12 | 29 | boston bruins | 3 - 2 | 4-7-1 | | | | game |
|---:|-------:|
| 0 | 4 | | [
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select count ( * ) where country (noc) = 847 col : city | country (noc) | round 1 | run-off | round 3 | round 4 | round 5 row 1 : athens | greece | 32 | none | 38 | 52 | 66 row 2 : rome | italy | 23 | none | 28 | 35 | 41 row 3 : cape town | south africa | 16 | 62 | 22 | 20 | none row 4 : stockholm | sweden | 20 | none | 19 | none | none row 5 : buenos aires | argentina | 16 | 44 | none | none | none | col : count ( "*" ) row 1 : 0 | select count ( * ) where country (noc) = 847 <table_name> : table \begin{tabular}{llllllll}
\toprule
& city & country (noc) & round 1 & run-off & round 3 & round 4 & round 5 \\
\midrule
0 & athens & greece & 32 & none & 38 & 52 & 66 \\
1 & rome & italy & 23 & none & 28 & 35 & 41 \\
2 & cape town & south africa & 16 & 62 & 22 & 20 & none \\
3 & stockholm & sweden & 20 & none & 19 & none & none \\
4 & buenos aires & argentina & 16 & 44 & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where country (noc) = 847 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>city</th>
<th>country (noc)</th>
<th>round 1</th>
<th>run-off</th>
<th>round 3</th>
<th>round 4</th>
<th>round 5</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>athens</td>
<td>greece</td>
<td>32</td>
<td>none</td>
<td>38</td>
<td>52</td>
<td>66</td>
</tr>
<tr>
<th>1</th>
<td>rome</td>
<td>italy</td>
<td>23</td>
<td>none</td>
<td>28</td>
<td>35</td>
<td>41</td>
</tr>
<tr>
<th>2</th>
<td>cape town</td>
<td>south africa</td>
<td>16</td>
<td>62</td>
<td>22</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>stockholm</td>
<td>sweden</td>
<td>20</td>
<td>none</td>
<td>19</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>buenos aires</td>
<td>argentina</td>
<td>16</td>
<td>44</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where country (noc) = 847 <table_name> : table | | city | country (noc) | round 1 | run-off | round 3 | round 4 | round 5 |
|---:|:-------------|:----------------|----------:|:----------|:----------|:----------|:----------|
| 0 | athens | greece | 32 | none | 38 | 52 | 66 |
| 1 | rome | italy | 23 | none | 28 | 35 | 41 |
| 2 | cape town | south africa | 16 | 62 | 22 | 20 | none |
| 3 | stockholm | sweden | 20 | none | 19 | none | none |
| 4 | buenos aires | argentina | 16 | 44 | none | none | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( hanzi ) where density (/km2) = 56 col : # | name | hanzi | hanyu pinyin | population (2003 est.) | area (km2) | density (/km2) row 1 : 1 | aimin district | 爱民区 | aimin qu | 230000 | 359 | 641 row 2 : 2 | dong'an district | 东安区 | dong'an qu | 180000 | 566 | 318 row 3 : 3 | yangming district | 阳明区 | yangming qu | 160000 | 358 | 447 row 4 : 4 | xi'an district | 西安区 | xi'an qu | 210000 | 325 | 646 row 5 : 5 | muling city | 穆棱市 | muling shi | 330000 | 6094 | 54 row 6 : 6 | suifenhe city | 绥芬河市 | suifenhe shi | 60000 | 427 | 141 row 7 : 7 | hailin city | 海林市 | hailin shi | 440000 | 9877 | 45 row 8 : 8 | ning'an city | 宁安市 | ning'an shi | 440000 | 7870 | 56 row 9 : 9 | dongning county | 东宁县 | dongning xian | 210000 | 7368 | 29 row 10 : 10 | linkou county | 林口县 | linkou xian | 450000 | 7191 | 63 | col : count ( "hanzi" ) row 1 : 1 | select count ( hanzi ) where density (/km2) = 56 <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & name & hanzi & hanyu pinyin & population (2003 est.) & area (km2) & density (/km2) \\
\midrule
0 & 1 & aimin district & 爱民区 & aimin qu & 230000 & 359 & 641 \\
1 & 2 & dong'an district & 东安区 & dong'an qu & 180000 & 566 & 318 \\
2 & 3 & yangming district & 阳明区 & yangming qu & 160000 & 358 & 447 \\
3 & 4 & xi'an district & 西安区 & xi'an qu & 210000 & 325 & 646 \\
4 & 5 & muling city & 穆棱市 & muling shi & 330000 & 6094 & 54 \\
5 & 6 & suifenhe city & 绥芬河市 & suifenhe shi & 60000 & 427 & 141 \\
6 & 7 & hailin city & 海林市 & hailin shi & 440000 & 9877 & 45 \\
7 & 8 & ning'an city & 宁安市 & ning'an shi & 440000 & 7870 & 56 \\
8 & 9 & dongning county & 东宁县 & dongning xian & 210000 & 7368 & 29 \\
9 & 10 & linkou county & 林口县 & linkou xian & 450000 & 7191 & 63 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "hanzi" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( hanzi ) where density (/km2) = 56 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>name</th>
<th>hanzi</th>
<th>hanyu pinyin</th>
<th>population (2003 est.)</th>
<th>area (km2)</th>
<th>density (/km2)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>aimin district</td>
<td>爱民区</td>
<td>aimin qu</td>
<td>230000</td>
<td>359</td>
<td>641</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>dong'an district</td>
<td>东安区</td>
<td>dong'an qu</td>
<td>180000</td>
<td>566</td>
<td>318</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>yangming district</td>
<td>阳明区</td>
<td>yangming qu</td>
<td>160000</td>
<td>358</td>
<td>447</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>xi'an district</td>
<td>西安区</td>
<td>xi'an qu</td>
<td>210000</td>
<td>325</td>
<td>646</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>muling city</td>
<td>穆棱市</td>
<td>muling shi</td>
<td>330000</td>
<td>6094</td>
<td>54</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>suifenhe city</td>
<td>绥芬河市</td>
<td>suifenhe shi</td>
<td>60000</td>
<td>427</td>
<td>141</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>hailin city</td>
<td>海林市</td>
<td>hailin shi</td>
<td>440000</td>
<td>9877</td>
<td>45</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>ning'an city</td>
<td>宁安市</td>
<td>ning'an shi</td>
<td>440000</td>
<td>7870</td>
<td>56</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>dongning county</td>
<td>东宁县</td>
<td>dongning xian</td>
<td>210000</td>
<td>7368</td>
<td>29</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>linkou county</td>
<td>林口县</td>
<td>linkou xian</td>
<td>450000</td>
<td>7191</td>
<td>63</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "hanzi" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( hanzi ) where density (/km2) = 56 <table_name> : table | | # | name | hanzi | hanyu pinyin | population (2003 est.) | area (km2) | density (/km2) |
|---:|----:|:------------------|:---------|:---------------|-------------------------:|-------------:|-----------------:|
| 0 | 1 | aimin district | 爱民区 | aimin qu | 230000 | 359 | 641 |
| 1 | 2 | dong'an district | 东安区 | dong'an qu | 180000 | 566 | 318 |
| 2 | 3 | yangming district | 阳明区 | yangming qu | 160000 | 358 | 447 |
| 3 | 4 | xi'an district | 西安区 | xi'an qu | 210000 | 325 | 646 |
| 4 | 5 | muling city | 穆棱市 | muling shi | 330000 | 6094 | 54 |
| 5 | 6 | suifenhe city | 绥芬河市 | suifenhe shi | 60000 | 427 | 141 |
| 6 | 7 | hailin city | 海林市 | hailin shi | 440000 | 9877 | 45 |
| 7 | 8 | ning'an city | 宁安市 | ning'an shi | 440000 | 7870 | 56 |
| 8 | 9 | dongning county | 东宁县 | dongning xian | 210000 | 7368 | 29 |
| 9 | 10 | linkou county | 林口县 | linkou xian | 450000 | 7191 | 63 | | | | count ( "hanzi" ) |
|---:|--------------------:|
| 0 | 1 | | [
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] |
select count ( artist ) where sales < 1912 col : position | song title | artist | sales | highest position row 1 : 1 | unchained melody/white cliffs of dover | robson green & jerome flynn | 1,844,000 | 1 row 2 : 2 | gangsta's paradise | coolio featuring l.v | 1,110,000 | 1 row 3 : 3 | i believe/up on the roof | robson green & jerome flynn | 1,049,000 | 1 row 4 : 4 | back for good | take that | 960,000 | 1 row 5 : 5 | think twice | celine dion | 928,000 | 1 row 6 : 6 | fairground | simply red | 782,000 | 1 row 7 : 7 | you are not alone | michael jackson | 714,000 | 1 row 8 : 8 | earth song | michael jackson | 802,000 | 1 row 9 : 9 | missing | everything but the girl | 696,000 | 3 row 10 : 10 | wonderwall | oasis | 665,000 | 2 row 11 : 11 | boom boom boom | outhere brothers | 652,000 | 1 row 12 : 12 | country house | blur | 642,000 | 1 row 13 : 13 | father and son | boyzone | 620,000 | 2 row 14 : 14 | don't stop (wiggle wiggle) | outhere brothers | 617,000 | 1 row 15 : 15 | boombastic | shaggy | 557,000 | 1 row 16 : 16 | cotton eye joe | rednex | 512,000 | 1 row 17 : 17 | set you free | n-trance | 503,000 | 2 row 18 : 18 | living next door to alice | smokie featuring roy chubby brown | 495,000 | 3 row 19 : 19 | hold me, thrill me, kiss me, kill me | u2 | 471,000 | 2 row 20 : 20 | roll with it | oasis | 456,000 | 2 row 21 : 21 | guaglione | perez 'prez' prado & his orchestra | 445,000 | 2 row 22 : 22 | i'll be there for you | the rembrandts | 421,000 | 3 row 23 : 23 | two can play that game | bobby brown | 413,000 | 3 row 24 : 24 | here comes the hotstepper | ini kamoze | 407,000 | 4 row 25 : 25 | shy guy | diana king | 405,000 | 2 row 26 : 26 | it's oh so quiet | bjork | 404,000 | 4 row 27 : 27 | never forget | take that | 403,000 | 1 row 28 : 28 | don't give me your life | alex party | 395,000 | 2 row 29 : 29 | waterfalls | tlc | 355,000 | 4 row 30 : 30 | scatman (ski ba bop ba dop bop) | scatman john | 352,000 | 2 row 31 : 31 | some might say | oasis | 346,000 | 1 row 32 : 32 | you'll see | madonna | 342,000 | 5 row 33 : 33 | thunder | east 17 | 339,000 | 4 row 34 : 34 | stayin' alive | n-trance featuring ricardo da force | 335,000 | 2 row 35 : 35 | i'd lie for you (and that's the truth) | meat loaf | 334,000 | 2 row 36 : 36 | common people | pulp | 326,000 | 2 row 37 : 37 | fantasy | mariah carey | 323,000 | 4 row 38 : 38 | i've got a little something for you | mn8 | 317,000 | 2 row 39 : 39 | kiss from a rose/i'm alive | seal | 310,000 | 4 row 40 : 40 | dreamer | livin' joy | 303,000 | 1 | col : count ( "artist" ) row 1 : 3 | select count ( artist ) where sales < 1912 <table_name> : table \begin{tabular}{llllll}
\toprule
& position & song title & artist & sales & highest position \\
\midrule
0 & 1 & unchained melody/white cliffs of dover & robson green & jerome flynn & 1,844,000 & 1 \\
1 & 2 & gangsta's paradise & coolio featuring l.v & 1,110,000 & 1 \\
2 & 3 & i believe/up on the roof & robson green & jerome flynn & 1,049,000 & 1 \\
3 & 4 & back for good & take that & 960,000 & 1 \\
4 & 5 & think twice & celine dion & 928,000 & 1 \\
5 & 6 & fairground & simply red & 782,000 & 1 \\
6 & 7 & you are not alone & michael jackson & 714,000 & 1 \\
7 & 8 & earth song & michael jackson & 802,000 & 1 \\
8 & 9 & missing & everything but the girl & 696,000 & 3 \\
9 & 10 & wonderwall & oasis & 665,000 & 2 \\
10 & 11 & boom boom boom & outhere brothers & 652,000 & 1 \\
11 & 12 & country house & blur & 642,000 & 1 \\
12 & 13 & father and son & boyzone & 620,000 & 2 \\
13 & 14 & don't stop (wiggle wiggle) & outhere brothers & 617,000 & 1 \\
14 & 15 & boombastic & shaggy & 557,000 & 1 \\
15 & 16 & cotton eye joe & rednex & 512,000 & 1 \\
16 & 17 & set you free & n-trance & 503,000 & 2 \\
17 & 18 & living next door to alice & smokie featuring roy chubby brown & 495,000 & 3 \\
18 & 19 & hold me, thrill me, kiss me, kill me & u2 & 471,000 & 2 \\
19 & 20 & roll with it & oasis & 456,000 & 2 \\
20 & 21 & guaglione & perez 'prez' prado & his orchestra & 445,000 & 2 \\
21 & 22 & i'll be there for you & the rembrandts & 421,000 & 3 \\
22 & 23 & two can play that game & bobby brown & 413,000 & 3 \\
23 & 24 & here comes the hotstepper & ini kamoze & 407,000 & 4 \\
24 & 25 & shy guy & diana king & 405,000 & 2 \\
25 & 26 & it's oh so quiet & bjork & 404,000 & 4 \\
26 & 27 & never forget & take that & 403,000 & 1 \\
27 & 28 & don't give me your life & alex party & 395,000 & 2 \\
28 & 29 & waterfalls & tlc & 355,000 & 4 \\
29 & 30 & scatman (ski ba bop ba dop bop) & scatman john & 352,000 & 2 \\
30 & 31 & some might say & oasis & 346,000 & 1 \\
31 & 32 & you'll see & madonna & 342,000 & 5 \\
32 & 33 & thunder & east 17 & 339,000 & 4 \\
33 & 34 & stayin' alive & n-trance featuring ricardo da force & 335,000 & 2 \\
34 & 35 & i'd lie for you (and that's the truth) & meat loaf & 334,000 & 2 \\
35 & 36 & common people & pulp & 326,000 & 2 \\
36 & 37 & fantasy & mariah carey & 323,000 & 4 \\
37 & 38 & i've got a little something for you & mn8 & 317,000 & 2 \\
38 & 39 & kiss from a rose/i'm alive & seal & 310,000 & 4 \\
39 & 40 & dreamer & livin' joy & 303,000 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "artist" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( artist ) where sales < 1912 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
<th>song title</th>
<th>artist</th>
<th>sales</th>
<th>highest position</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>unchained melody/white cliffs of dover</td>
<td>robson green & jerome flynn</td>
<td>1,844,000</td>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>gangsta's paradise</td>
<td>coolio featuring l.v</td>
<td>1,110,000</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>i believe/up on the roof</td>
<td>robson green & jerome flynn</td>
<td>1,049,000</td>
<td>1</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>back for good</td>
<td>take that</td>
<td>960,000</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>think twice</td>
<td>celine dion</td>
<td>928,000</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>fairground</td>
<td>simply red</td>
<td>782,000</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>you are not alone</td>
<td>michael jackson</td>
<td>714,000</td>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>earth song</td>
<td>michael jackson</td>
<td>802,000</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>missing</td>
<td>everything but the girl</td>
<td>696,000</td>
<td>3</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>wonderwall</td>
<td>oasis</td>
<td>665,000</td>
<td>2</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>boom boom boom</td>
<td>outhere brothers</td>
<td>652,000</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>country house</td>
<td>blur</td>
<td>642,000</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>father and son</td>
<td>boyzone</td>
<td>620,000</td>
<td>2</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>don't stop (wiggle wiggle)</td>
<td>outhere brothers</td>
<td>617,000</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>boombastic</td>
<td>shaggy</td>
<td>557,000</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>cotton eye joe</td>
<td>rednex</td>
<td>512,000</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>set you free</td>
<td>n-trance</td>
<td>503,000</td>
<td>2</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>living next door to alice</td>
<td>smokie featuring roy chubby brown</td>
<td>495,000</td>
<td>3</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>hold me, thrill me, kiss me, kill me</td>
<td>u2</td>
<td>471,000</td>
<td>2</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>roll with it</td>
<td>oasis</td>
<td>456,000</td>
<td>2</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>guaglione</td>
<td>perez 'prez' prado & his orchestra</td>
<td>445,000</td>
<td>2</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>i'll be there for you</td>
<td>the rembrandts</td>
<td>421,000</td>
<td>3</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>two can play that game</td>
<td>bobby brown</td>
<td>413,000</td>
<td>3</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>here comes the hotstepper</td>
<td>ini kamoze</td>
<td>407,000</td>
<td>4</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>shy guy</td>
<td>diana king</td>
<td>405,000</td>
<td>2</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>it's oh so quiet</td>
<td>bjork</td>
<td>404,000</td>
<td>4</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>never forget</td>
<td>take that</td>
<td>403,000</td>
<td>1</td>
</tr>
<tr>
<th>27</th>
<td>28</td>
<td>don't give me your life</td>
<td>alex party</td>
<td>395,000</td>
<td>2</td>
</tr>
<tr>
<th>28</th>
<td>29</td>
<td>waterfalls</td>
<td>tlc</td>
<td>355,000</td>
<td>4</td>
</tr>
<tr>
<th>29</th>
<td>30</td>
<td>scatman (ski ba bop ba dop bop)</td>
<td>scatman john</td>
<td>352,000</td>
<td>2</td>
</tr>
<tr>
<th>30</th>
<td>31</td>
<td>some might say</td>
<td>oasis</td>
<td>346,000</td>
<td>1</td>
</tr>
<tr>
<th>31</th>
<td>32</td>
<td>you'll see</td>
<td>madonna</td>
<td>342,000</td>
<td>5</td>
</tr>
<tr>
<th>32</th>
<td>33</td>
<td>thunder</td>
<td>east 17</td>
<td>339,000</td>
<td>4</td>
</tr>
<tr>
<th>33</th>
<td>34</td>
<td>stayin' alive</td>
<td>n-trance featuring ricardo da force</td>
<td>335,000</td>
<td>2</td>
</tr>
<tr>
<th>34</th>
<td>35</td>
<td>i'd lie for you (and that's the truth)</td>
<td>meat loaf</td>
<td>334,000</td>
<td>2</td>
</tr>
<tr>
<th>35</th>
<td>36</td>
<td>common people</td>
<td>pulp</td>
<td>326,000</td>
<td>2</td>
</tr>
<tr>
<th>36</th>
<td>37</td>
<td>fantasy</td>
<td>mariah carey</td>
<td>323,000</td>
<td>4</td>
</tr>
<tr>
<th>37</th>
<td>38</td>
<td>i've got a little something for you</td>
<td>mn8</td>
<td>317,000</td>
<td>2</td>
</tr>
<tr>
<th>38</th>
<td>39</td>
<td>kiss from a rose/i'm alive</td>
<td>seal</td>
<td>310,000</td>
<td>4</td>
</tr>
<tr>
<th>39</th>
<td>40</td>
<td>dreamer</td>
<td>livin' joy</td>
<td>303,000</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "artist" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( artist ) where sales < 1912 <table_name> : table | | position | song title | artist | sales | highest position |
|---:|-----------:|:---------------------------------------|:------------------------------------|:----------|-------------------:|
| 0 | 1 | unchained melody/white cliffs of dover | robson green & jerome flynn | 1,844,000 | 1 |
| 1 | 2 | gangsta's paradise | coolio featuring l.v | 1,110,000 | 1 |
| 2 | 3 | i believe/up on the roof | robson green & jerome flynn | 1,049,000 | 1 |
| 3 | 4 | back for good | take that | 960,000 | 1 |
| 4 | 5 | think twice | celine dion | 928,000 | 1 |
| 5 | 6 | fairground | simply red | 782,000 | 1 |
| 6 | 7 | you are not alone | michael jackson | 714,000 | 1 |
| 7 | 8 | earth song | michael jackson | 802,000 | 1 |
| 8 | 9 | missing | everything but the girl | 696,000 | 3 |
| 9 | 10 | wonderwall | oasis | 665,000 | 2 |
| 10 | 11 | boom boom boom | outhere brothers | 652,000 | 1 |
| 11 | 12 | country house | blur | 642,000 | 1 |
| 12 | 13 | father and son | boyzone | 620,000 | 2 |
| 13 | 14 | don't stop (wiggle wiggle) | outhere brothers | 617,000 | 1 |
| 14 | 15 | boombastic | shaggy | 557,000 | 1 |
| 15 | 16 | cotton eye joe | rednex | 512,000 | 1 |
| 16 | 17 | set you free | n-trance | 503,000 | 2 |
| 17 | 18 | living next door to alice | smokie featuring roy chubby brown | 495,000 | 3 |
| 18 | 19 | hold me, thrill me, kiss me, kill me | u2 | 471,000 | 2 |
| 19 | 20 | roll with it | oasis | 456,000 | 2 |
| 20 | 21 | guaglione | perez 'prez' prado & his orchestra | 445,000 | 2 |
| 21 | 22 | i'll be there for you | the rembrandts | 421,000 | 3 |
| 22 | 23 | two can play that game | bobby brown | 413,000 | 3 |
| 23 | 24 | here comes the hotstepper | ini kamoze | 407,000 | 4 |
| 24 | 25 | shy guy | diana king | 405,000 | 2 |
| 25 | 26 | it's oh so quiet | bjork | 404,000 | 4 |
| 26 | 27 | never forget | take that | 403,000 | 1 |
| 27 | 28 | don't give me your life | alex party | 395,000 | 2 |
| 28 | 29 | waterfalls | tlc | 355,000 | 4 |
| 29 | 30 | scatman (ski ba bop ba dop bop) | scatman john | 352,000 | 2 |
| 30 | 31 | some might say | oasis | 346,000 | 1 |
| 31 | 32 | you'll see | madonna | 342,000 | 5 |
| 32 | 33 | thunder | east 17 | 339,000 | 4 |
| 33 | 34 | stayin' alive | n-trance featuring ricardo da force | 335,000 | 2 |
| 34 | 35 | i'd lie for you (and that's the truth) | meat loaf | 334,000 | 2 |
| 35 | 36 | common people | pulp | 326,000 | 2 |
| 36 | 37 | fantasy | mariah carey | 323,000 | 4 |
| 37 | 38 | i've got a little something for you | mn8 | 317,000 | 2 |
| 38 | 39 | kiss from a rose/i'm alive | seal | 310,000 | 4 |
| 39 | 40 | dreamer | livin' joy | 303,000 | 1 | | | | count ( "artist" ) |
|---:|---------------------:|
| 0 | 3 | | [
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] |
select count ( code ) where code = 'i' col : code | year row 1 : a | 1927 row 2 : b | 1928 row 3 : c | 1929 row 4 : ch | 1930 row 5 : d | 1931 row 6 : e | 1932 row 7 : f | 1933 row 8 : g | 1934 row 9 : h | 1935 row 10 : i | 1936 row 11 : j | 1937 row 12 : k | 1938 row 13 : l | 1939 row 14 : ll | 1940 row 15 : m | 1941 row 16 : n | 1942 row 17 : n | 1943 row 18 : o | 1944 row 19 : p | 1945 row 20 : q | 1946 row 21 : r | 1947 row 22 : s | 1948 row 23 : t | 1949 row 24 : u | 1950 row 25 : v | 1951 row 26 : x | 1952 row 27 : y | 1953 row 28 : z | 1954 row 29 : a1 | 1955 row 30 : b1 | 1956 row 31 : c1 | 1957 row 32 : ch1 | none row 33 : d1 | 1958 row 34 : e1 | 1959 row 35 : f1 | 1960 row 36 : g1 | 1961 row 37 : h1 | 1962 row 38 : i1 | 1963 row 39 : j1 | 1964 row 40 : k1 | 1965 row 41 : l1 | 1966 row 42 : ll1 | none row 43 : m1 | 1967 row 44 : n1 | 1968 row 45 : n1 | 1969 row 46 : o1 | 1970 row 47 : p1 | 1971 row 48 : q1 | 1972 row 49 : r1 | 1973 row 50 : s1 | 1974 row 51 : t1 | 1975 row 52 : u1 | 1976 row 53 : v1 | 1977 row 54 : x1 | 1978 row 55 : y1 | 1979 row 56 : z1 | 1980 row 57 : a2 | 1981 row 58 : b2 | 1982 row 59 : c2 | 1983 row 60 : ch2 | none row 61 : d2 | 1984 row 62 : e2 | 1985 row 63 : f2 | 1986 row 64 : g2 | 1987 row 65 : h2 | 1988 row 66 : i2 | 1989 row 67 : j2 | 1990 row 68 : k2 | 1991 row 69 : l2 | 1992 row 70 : ll2 | none row 71 : m2 | 1993 row 72 : n2 | 1994 row 73 : n2 | 1995 row 74 : o2 | 1996 row 75 : p2 | 1997 row 76 : q2 | 1998 row 77 : r2 | 1999 row 78 : s2 | 2000 row 79 : t2 | 2001 row 80 : u2 | 2002 row 81 : v2 | 2003 row 82 : x2 | 2004 row 83 : y2 | 2005 row 84 : z2 | 2006 | col : count ( "code" ) row 1 : 1 | select count ( code ) where code = 'i' <table_name> : table \begin{tabular}{lll}
\toprule
& code & year \\
\midrule
0 & a & 1927 \\
1 & b & 1928 \\
2 & c & 1929 \\
3 & ch & 1930 \\
4 & d & 1931 \\
5 & e & 1932 \\
6 & f & 1933 \\
7 & g & 1934 \\
8 & h & 1935 \\
9 & i & 1936 \\
10 & j & 1937 \\
11 & k & 1938 \\
12 & l & 1939 \\
13 & ll & 1940 \\
14 & m & 1941 \\
15 & n & 1942 \\
16 & n & 1943 \\
17 & o & 1944 \\
18 & p & 1945 \\
19 & q & 1946 \\
20 & r & 1947 \\
21 & s & 1948 \\
22 & t & 1949 \\
23 & u & 1950 \\
24 & v & 1951 \\
25 & x & 1952 \\
26 & y & 1953 \\
27 & z & 1954 \\
28 & a1 & 1955 \\
29 & b1 & 1956 \\
30 & c1 & 1957 \\
31 & ch1 & none \\
32 & d1 & 1958 \\
33 & e1 & 1959 \\
34 & f1 & 1960 \\
35 & g1 & 1961 \\
36 & h1 & 1962 \\
37 & i1 & 1963 \\
38 & j1 & 1964 \\
39 & k1 & 1965 \\
40 & l1 & 1966 \\
41 & ll1 & none \\
42 & m1 & 1967 \\
43 & n1 & 1968 \\
44 & n1 & 1969 \\
45 & o1 & 1970 \\
46 & p1 & 1971 \\
47 & q1 & 1972 \\
48 & r1 & 1973 \\
49 & s1 & 1974 \\
50 & t1 & 1975 \\
51 & u1 & 1976 \\
52 & v1 & 1977 \\
53 & x1 & 1978 \\
54 & y1 & 1979 \\
55 & z1 & 1980 \\
56 & a2 & 1981 \\
57 & b2 & 1982 \\
58 & c2 & 1983 \\
59 & ch2 & none \\
60 & d2 & 1984 \\
61 & e2 & 1985 \\
62 & f2 & 1986 \\
63 & g2 & 1987 \\
64 & h2 & 1988 \\
65 & i2 & 1989 \\
66 & j2 & 1990 \\
67 & k2 & 1991 \\
68 & l2 & 1992 \\
69 & ll2 & none \\
70 & m2 & 1993 \\
71 & n2 & 1994 \\
72 & n2 & 1995 \\
73 & o2 & 1996 \\
74 & p2 & 1997 \\
75 & q2 & 1998 \\
76 & r2 & 1999 \\
77 & s2 & 2000 \\
78 & t2 & 2001 \\
79 & u2 & 2002 \\
80 & v2 & 2003 \\
81 & x2 & 2004 \\
82 & y2 & 2005 \\
83 & z2 & 2006 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "code" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( code ) where code = 'i' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>code</th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>a</td>
<td>1927</td>
</tr>
<tr>
<th>1</th>
<td>b</td>
<td>1928</td>
</tr>
<tr>
<th>2</th>
<td>c</td>
<td>1929</td>
</tr>
<tr>
<th>3</th>
<td>ch</td>
<td>1930</td>
</tr>
<tr>
<th>4</th>
<td>d</td>
<td>1931</td>
</tr>
<tr>
<th>5</th>
<td>e</td>
<td>1932</td>
</tr>
<tr>
<th>6</th>
<td>f</td>
<td>1933</td>
</tr>
<tr>
<th>7</th>
<td>g</td>
<td>1934</td>
</tr>
<tr>
<th>8</th>
<td>h</td>
<td>1935</td>
</tr>
<tr>
<th>9</th>
<td>i</td>
<td>1936</td>
</tr>
<tr>
<th>10</th>
<td>j</td>
<td>1937</td>
</tr>
<tr>
<th>11</th>
<td>k</td>
<td>1938</td>
</tr>
<tr>
<th>12</th>
<td>l</td>
<td>1939</td>
</tr>
<tr>
<th>13</th>
<td>ll</td>
<td>1940</td>
</tr>
<tr>
<th>14</th>
<td>m</td>
<td>1941</td>
</tr>
<tr>
<th>15</th>
<td>n</td>
<td>1942</td>
</tr>
<tr>
<th>16</th>
<td>n</td>
<td>1943</td>
</tr>
<tr>
<th>17</th>
<td>o</td>
<td>1944</td>
</tr>
<tr>
<th>18</th>
<td>p</td>
<td>1945</td>
</tr>
<tr>
<th>19</th>
<td>q</td>
<td>1946</td>
</tr>
<tr>
<th>20</th>
<td>r</td>
<td>1947</td>
</tr>
<tr>
<th>21</th>
<td>s</td>
<td>1948</td>
</tr>
<tr>
<th>22</th>
<td>t</td>
<td>1949</td>
</tr>
<tr>
<th>23</th>
<td>u</td>
<td>1950</td>
</tr>
<tr>
<th>24</th>
<td>v</td>
<td>1951</td>
</tr>
<tr>
<th>25</th>
<td>x</td>
<td>1952</td>
</tr>
<tr>
<th>26</th>
<td>y</td>
<td>1953</td>
</tr>
<tr>
<th>27</th>
<td>z</td>
<td>1954</td>
</tr>
<tr>
<th>28</th>
<td>a1</td>
<td>1955</td>
</tr>
<tr>
<th>29</th>
<td>b1</td>
<td>1956</td>
</tr>
<tr>
<th>30</th>
<td>c1</td>
<td>1957</td>
</tr>
<tr>
<th>31</th>
<td>ch1</td>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>d1</td>
<td>1958</td>
</tr>
<tr>
<th>33</th>
<td>e1</td>
<td>1959</td>
</tr>
<tr>
<th>34</th>
<td>f1</td>
<td>1960</td>
</tr>
<tr>
<th>35</th>
<td>g1</td>
<td>1961</td>
</tr>
<tr>
<th>36</th>
<td>h1</td>
<td>1962</td>
</tr>
<tr>
<th>37</th>
<td>i1</td>
<td>1963</td>
</tr>
<tr>
<th>38</th>
<td>j1</td>
<td>1964</td>
</tr>
<tr>
<th>39</th>
<td>k1</td>
<td>1965</td>
</tr>
<tr>
<th>40</th>
<td>l1</td>
<td>1966</td>
</tr>
<tr>
<th>41</th>
<td>ll1</td>
<td>none</td>
</tr>
<tr>
<th>42</th>
<td>m1</td>
<td>1967</td>
</tr>
<tr>
<th>43</th>
<td>n1</td>
<td>1968</td>
</tr>
<tr>
<th>44</th>
<td>n1</td>
<td>1969</td>
</tr>
<tr>
<th>45</th>
<td>o1</td>
<td>1970</td>
</tr>
<tr>
<th>46</th>
<td>p1</td>
<td>1971</td>
</tr>
<tr>
<th>47</th>
<td>q1</td>
<td>1972</td>
</tr>
<tr>
<th>48</th>
<td>r1</td>
<td>1973</td>
</tr>
<tr>
<th>49</th>
<td>s1</td>
<td>1974</td>
</tr>
<tr>
<th>50</th>
<td>t1</td>
<td>1975</td>
</tr>
<tr>
<th>51</th>
<td>u1</td>
<td>1976</td>
</tr>
<tr>
<th>52</th>
<td>v1</td>
<td>1977</td>
</tr>
<tr>
<th>53</th>
<td>x1</td>
<td>1978</td>
</tr>
<tr>
<th>54</th>
<td>y1</td>
<td>1979</td>
</tr>
<tr>
<th>55</th>
<td>z1</td>
<td>1980</td>
</tr>
<tr>
<th>56</th>
<td>a2</td>
<td>1981</td>
</tr>
<tr>
<th>57</th>
<td>b2</td>
<td>1982</td>
</tr>
<tr>
<th>58</th>
<td>c2</td>
<td>1983</td>
</tr>
<tr>
<th>59</th>
<td>ch2</td>
<td>none</td>
</tr>
<tr>
<th>60</th>
<td>d2</td>
<td>1984</td>
</tr>
<tr>
<th>61</th>
<td>e2</td>
<td>1985</td>
</tr>
<tr>
<th>62</th>
<td>f2</td>
<td>1986</td>
</tr>
<tr>
<th>63</th>
<td>g2</td>
<td>1987</td>
</tr>
<tr>
<th>64</th>
<td>h2</td>
<td>1988</td>
</tr>
<tr>
<th>65</th>
<td>i2</td>
<td>1989</td>
</tr>
<tr>
<th>66</th>
<td>j2</td>
<td>1990</td>
</tr>
<tr>
<th>67</th>
<td>k2</td>
<td>1991</td>
</tr>
<tr>
<th>68</th>
<td>l2</td>
<td>1992</td>
</tr>
<tr>
<th>69</th>
<td>ll2</td>
<td>none</td>
</tr>
<tr>
<th>70</th>
<td>m2</td>
<td>1993</td>
</tr>
<tr>
<th>71</th>
<td>n2</td>
<td>1994</td>
</tr>
<tr>
<th>72</th>
<td>n2</td>
<td>1995</td>
</tr>
<tr>
<th>73</th>
<td>o2</td>
<td>1996</td>
</tr>
<tr>
<th>74</th>
<td>p2</td>
<td>1997</td>
</tr>
<tr>
<th>75</th>
<td>q2</td>
<td>1998</td>
</tr>
<tr>
<th>76</th>
<td>r2</td>
<td>1999</td>
</tr>
<tr>
<th>77</th>
<td>s2</td>
<td>2000</td>
</tr>
<tr>
<th>78</th>
<td>t2</td>
<td>2001</td>
</tr>
<tr>
<th>79</th>
<td>u2</td>
<td>2002</td>
</tr>
<tr>
<th>80</th>
<td>v2</td>
<td>2003</td>
</tr>
<tr>
<th>81</th>
<td>x2</td>
<td>2004</td>
</tr>
<tr>
<th>82</th>
<td>y2</td>
<td>2005</td>
</tr>
<tr>
<th>83</th>
<td>z2</td>
<td>2006</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "code" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( code ) where code = 'i' <table_name> : table | | code | year |
|---:|:-------|:-------|
| 0 | a | 1927 |
| 1 | b | 1928 |
| 2 | c | 1929 |
| 3 | ch | 1930 |
| 4 | d | 1931 |
| 5 | e | 1932 |
| 6 | f | 1933 |
| 7 | g | 1934 |
| 8 | h | 1935 |
| 9 | i | 1936 |
| 10 | j | 1937 |
| 11 | k | 1938 |
| 12 | l | 1939 |
| 13 | ll | 1940 |
| 14 | m | 1941 |
| 15 | n | 1942 |
| 16 | n | 1943 |
| 17 | o | 1944 |
| 18 | p | 1945 |
| 19 | q | 1946 |
| 20 | r | 1947 |
| 21 | s | 1948 |
| 22 | t | 1949 |
| 23 | u | 1950 |
| 24 | v | 1951 |
| 25 | x | 1952 |
| 26 | y | 1953 |
| 27 | z | 1954 |
| 28 | a1 | 1955 |
| 29 | b1 | 1956 |
| 30 | c1 | 1957 |
| 31 | ch1 | none |
| 32 | d1 | 1958 |
| 33 | e1 | 1959 |
| 34 | f1 | 1960 |
| 35 | g1 | 1961 |
| 36 | h1 | 1962 |
| 37 | i1 | 1963 |
| 38 | j1 | 1964 |
| 39 | k1 | 1965 |
| 40 | l1 | 1966 |
| 41 | ll1 | none |
| 42 | m1 | 1967 |
| 43 | n1 | 1968 |
| 44 | n1 | 1969 |
| 45 | o1 | 1970 |
| 46 | p1 | 1971 |
| 47 | q1 | 1972 |
| 48 | r1 | 1973 |
| 49 | s1 | 1974 |
| 50 | t1 | 1975 |
| 51 | u1 | 1976 |
| 52 | v1 | 1977 |
| 53 | x1 | 1978 |
| 54 | y1 | 1979 |
| 55 | z1 | 1980 |
| 56 | a2 | 1981 |
| 57 | b2 | 1982 |
| 58 | c2 | 1983 |
| 59 | ch2 | none |
| 60 | d2 | 1984 |
| 61 | e2 | 1985 |
| 62 | f2 | 1986 |
| 63 | g2 | 1987 |
| 64 | h2 | 1988 |
| 65 | i2 | 1989 |
| 66 | j2 | 1990 |
| 67 | k2 | 1991 |
| 68 | l2 | 1992 |
| 69 | ll2 | none |
| 70 | m2 | 1993 |
| 71 | n2 | 1994 |
| 72 | n2 | 1995 |
| 73 | o2 | 1996 |
| 74 | p2 | 1997 |
| 75 | q2 | 1998 |
| 76 | r2 | 1999 |
| 77 | s2 | 2000 |
| 78 | t2 | 2001 |
| 79 | u2 | 2002 |
| 80 | v2 | 2003 |
| 81 | x2 | 2004 |
| 82 | y2 | 2005 |
| 83 | z2 | 2006 | | | | count ( "code" ) |
|---:|-------------------:|
| 0 | 1 | | [
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1056,
261,
981,
262,
1625,
981,
273,
296,
77,
11,
411,
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529,
34,
294,
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521,
10086,
95,
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2906,
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677,
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314,
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290,
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290,
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320,
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473,
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7301,
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8749,
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293,
21,
473,
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11212,
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473,
1043,
21,
473,
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9060,
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436,
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473,
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7616,
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272,
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3361,
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268,
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5877,
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4449,
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11035,
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1105,
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366,
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5482,
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473,
277,
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473,
5342,
6675,
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6028,
473,
525,
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473,
23673,
20,
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9599,
473,
417,
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473,
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21,
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9470,
473,
328,
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473,
23673,
22,
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203,
8148,
473,
6579,
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473,
6555,
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7301,
473,
312,
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473,
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23,
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11212,
473,
290,
22,
473,
23673,
24,
1736,
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9060,
473,
290,
22,
473,
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25,
1736,
203,
9036,
473,
320,
22,
473,
23673,
26,
1736,
203,
5608,
473,
293,
22,
473,
23673,
27,
1736,
203,
5877,
473,
1043,
22,
473,
23673,
28,
1736,
203,
6669,
473,
436,
22,
473,
404,
11984,
1736,
203,
4700,
473,
272,
22,
473,
16291,
1736,
203,
8285,
473,
268,
22,
473,
4044,
21,
1736,
203,
7235,
473,
582,
22,
473,
4044,
22,
1736,
203,
3672,
473,
331,
22,
473,
4044,
23,
1736,
203,
11861,
473,
619,
22,
473,
4044,
24,
1736,
203,
11149,
473,
677,
22,
473,
4044,
25,
1736,
203,
10261,
473,
998,
22,
473,
27212,
1736,
203,
64,
9176,
5345,
203,
64,
409,
95,
7032,
2490,
97,
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0,
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0
]
] | [
[
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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1,
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1,
1,
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1,
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1,
1,
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select place where place = '4th' col : season | tier | division | place row 1 : 1928-84 | 5 | regional | none row 2 : 1984/85 | 4 | 3a | 6th row 3 : 1985/86 | 4 | 3a | 9th row 4 : 1986/87 | 4 | 3a | 11th row 5 : 1987/88 | 4 | 3a | 15th row 6 : 1988/89 | 4 | 3a | 4th row 7 : 1989/90 | 4 | 3a | 9th row 8 : 1990/91 | 4 | 3a | 9th row 9 : 1991/92 | 4 | 3a | 5th row 10 : 1992/93 | 4 | 3a | 17th row 11 : 1993/94 | 4 | 3a | 7th row 12 : 1994/95 | 4 | 3a | 4th row 13 : 1995/96 | 4 | 3a | 1st row 14 : 1996/97 | 3 | 2ab | 19th row 15 : 1997/98 | 4 | 3a | 2nd | col : place row 1 : 4th row 2 : 4th | select place where place = '4th' <table_name> : table \begin{tabular}{lllll}
\toprule
& season & tier & division & place \\
\midrule
0 & 1928-84 & 5 & regional & none \\
1 & 1984/85 & 4 & 3a & 6th \\
2 & 1985/86 & 4 & 3a & 9th \\
3 & 1986/87 & 4 & 3a & 11th \\
4 & 1987/88 & 4 & 3a & 15th \\
5 & 1988/89 & 4 & 3a & 4th \\
6 & 1989/90 & 4 & 3a & 9th \\
7 & 1990/91 & 4 & 3a & 9th \\
8 & 1991/92 & 4 & 3a & 5th \\
9 & 1992/93 & 4 & 3a & 17th \\
10 & 1993/94 & 4 & 3a & 7th \\
11 & 1994/95 & 4 & 3a & 4th \\
12 & 1995/96 & 4 & 3a & 1st \\
13 & 1996/97 & 3 & 2ab & 19th \\
14 & 1997/98 & 4 & 3a & 2nd \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& place \\
\midrule
0 & 4th \\
1 & 4th \\
\bottomrule
\end{tabular}
| select place where place = '4th' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>tier</th>
<th>division</th>
<th>place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1928-84</td>
<td>5</td>
<td>regional</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1984/85</td>
<td>4</td>
<td>3a</td>
<td>6th</td>
</tr>
<tr>
<th>2</th>
<td>1985/86</td>
<td>4</td>
<td>3a</td>
<td>9th</td>
</tr>
<tr>
<th>3</th>
<td>1986/87</td>
<td>4</td>
<td>3a</td>
<td>11th</td>
</tr>
<tr>
<th>4</th>
<td>1987/88</td>
<td>4</td>
<td>3a</td>
<td>15th</td>
</tr>
<tr>
<th>5</th>
<td>1988/89</td>
<td>4</td>
<td>3a</td>
<td>4th</td>
</tr>
<tr>
<th>6</th>
<td>1989/90</td>
<td>4</td>
<td>3a</td>
<td>9th</td>
</tr>
<tr>
<th>7</th>
<td>1990/91</td>
<td>4</td>
<td>3a</td>
<td>9th</td>
</tr>
<tr>
<th>8</th>
<td>1991/92</td>
<td>4</td>
<td>3a</td>
<td>5th</td>
</tr>
<tr>
<th>9</th>
<td>1992/93</td>
<td>4</td>
<td>3a</td>
<td>17th</td>
</tr>
<tr>
<th>10</th>
<td>1993/94</td>
<td>4</td>
<td>3a</td>
<td>7th</td>
</tr>
<tr>
<th>11</th>
<td>1994/95</td>
<td>4</td>
<td>3a</td>
<td>4th</td>
</tr>
<tr>
<th>12</th>
<td>1995/96</td>
<td>4</td>
<td>3a</td>
<td>1st</td>
</tr>
<tr>
<th>13</th>
<td>1996/97</td>
<td>3</td>
<td>2ab</td>
<td>19th</td>
</tr>
<tr>
<th>14</th>
<td>1997/98</td>
<td>4</td>
<td>3a</td>
<td>2nd</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4th</td>
</tr>
<tr>
<th>1</th>
<td>4th</td>
</tr>
</tbody>
</table> | select place where place = '4th' <table_name> : table | | season | tier | division | place |
|---:|:---------|-------:|:-----------|:--------|
| 0 | 1928-84 | 5 | regional | none |
| 1 | 1984/85 | 4 | 3a | 6th |
| 2 | 1985/86 | 4 | 3a | 9th |
| 3 | 1986/87 | 4 | 3a | 11th |
| 4 | 1987/88 | 4 | 3a | 15th |
| 5 | 1988/89 | 4 | 3a | 4th |
| 6 | 1989/90 | 4 | 3a | 9th |
| 7 | 1990/91 | 4 | 3a | 9th |
| 8 | 1991/92 | 4 | 3a | 5th |
| 9 | 1992/93 | 4 | 3a | 17th |
| 10 | 1993/94 | 4 | 3a | 7th |
| 11 | 1994/95 | 4 | 3a | 4th |
| 12 | 1995/96 | 4 | 3a | 1st |
| 13 | 1996/97 | 3 | 2ab | 19th |
| 14 | 1997/98 | 4 | 3a | 2nd | | | | place |
|---:|:--------|
| 0 | 4th |
| 1 | 4th | | [
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select week where winning couple = 'alisa and lysandra' and week < 5 col : week | room | winning couple | 2nd couple | 3rd couple | chumps row 1 : 1 | guest bedroom 1 | alisa and lysandra | kyal and kara/brad and dale | chantelle and steve | none row 2 : 2 | downstairs bathrooms, laundry & terrace | brad and dale | alisa and lysandra | chantelle and steve | kyal and kara row 3 : 3 | guest bedroom 2 | kyal and kara | chantalle and steve | alisa and lysandra | brad and dale row 4 : 4 | upstairs bathroom | kyal and kara | brad and dale | chantelle and steve | alisa and lysandra row 5 : 5 | kitchen | alisa and lysandra | kyal and kara | brad and dale | chantelle and steve row 6 : 6 | living room and dining room | chantelle and steve | alisa and lysandra | brad and dale / kyal and kara | none row 7 : 7 | master bedroom and ensuite | brad and dale | chantelle and steve | alisa and lysandra | kyal and kara row 8 : 8 | rooftop/outside terrace | kyal and kara | brad and dale | alisa and lysandra | chantelle and steve | col : week row 1 : 1 | select week where winning couple = 'alisa and lysandra' and week < 5 <table_name> : table \begin{tabular}{lllllll}
\toprule
& week & room & winning couple & 2nd couple & 3rd couple & chumps \\
\midrule
0 & 1 & guest bedroom 1 & alisa and lysandra & kyal and kara/brad and dale & chantelle and steve & none \\
1 & 2 & downstairs bathrooms, laundry & terrace & brad and dale & alisa and lysandra & chantelle and steve & kyal and kara \\
2 & 3 & guest bedroom 2 & kyal and kara & chantalle and steve & alisa and lysandra & brad and dale \\
3 & 4 & upstairs bathroom & kyal and kara & brad and dale & chantelle and steve & alisa and lysandra \\
4 & 5 & kitchen & alisa and lysandra & kyal and kara & brad and dale & chantelle and steve \\
5 & 6 & living room and dining room & chantelle and steve & alisa and lysandra & brad and dale / kyal and kara & none \\
6 & 7 & master bedroom and ensuite & brad and dale & chantelle and steve & alisa and lysandra & kyal and kara \\
7 & 8 & rooftop/outside terrace & kyal and kara & brad and dale & alisa and lysandra & chantelle and steve \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& week \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select week where winning couple = 'alisa and lysandra' and week < 5 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>room</th>
<th>winning couple</th>
<th>2nd couple</th>
<th>3rd couple</th>
<th>chumps</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>guest bedroom 1</td>
<td>alisa and lysandra</td>
<td>kyal and kara/brad and dale</td>
<td>chantelle and steve</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>downstairs bathrooms, laundry & terrace</td>
<td>brad and dale</td>
<td>alisa and lysandra</td>
<td>chantelle and steve</td>
<td>kyal and kara</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>guest bedroom 2</td>
<td>kyal and kara</td>
<td>chantalle and steve</td>
<td>alisa and lysandra</td>
<td>brad and dale</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>upstairs bathroom</td>
<td>kyal and kara</td>
<td>brad and dale</td>
<td>chantelle and steve</td>
<td>alisa and lysandra</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>kitchen</td>
<td>alisa and lysandra</td>
<td>kyal and kara</td>
<td>brad and dale</td>
<td>chantelle and steve</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>living room and dining room</td>
<td>chantelle and steve</td>
<td>alisa and lysandra</td>
<td>brad and dale / kyal and kara</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>master bedroom and ensuite</td>
<td>brad and dale</td>
<td>chantelle and steve</td>
<td>alisa and lysandra</td>
<td>kyal and kara</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>rooftop/outside terrace</td>
<td>kyal and kara</td>
<td>brad and dale</td>
<td>alisa and lysandra</td>
<td>chantelle and steve</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select week where winning couple = 'alisa and lysandra' and week < 5 <table_name> : table | | week | room | winning couple | 2nd couple | 3rd couple | chumps |
|---:|-------:|:----------------------------------------|:--------------------|:----------------------------|:------------------------------|:--------------------|
| 0 | 1 | guest bedroom 1 | alisa and lysandra | kyal and kara/brad and dale | chantelle and steve | none |
| 1 | 2 | downstairs bathrooms, laundry & terrace | brad and dale | alisa and lysandra | chantelle and steve | kyal and kara |
| 2 | 3 | guest bedroom 2 | kyal and kara | chantalle and steve | alisa and lysandra | brad and dale |
| 3 | 4 | upstairs bathroom | kyal and kara | brad and dale | chantelle and steve | alisa and lysandra |
| 4 | 5 | kitchen | alisa and lysandra | kyal and kara | brad and dale | chantelle and steve |
| 5 | 6 | living room and dining room | chantelle and steve | alisa and lysandra | brad and dale / kyal and kara | none |
| 6 | 7 | master bedroom and ensuite | brad and dale | chantelle and steve | alisa and lysandra | kyal and kara |
| 7 | 8 | rooftop/outside terrace | kyal and kara | brad and dale | alisa and lysandra | chantelle and steve | | | | week |
|---:|-------:|
| 0 | 1 | | [
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select count ( result ) where year = 2010 col : year | award | work/artist | result row 1 : 1999 | grammy award for best contemporary folk album | mermaid avenue | nominated row 2 : 2005 | grammy award for best alternative music album | a ghost is born | won row 3 : 2005 | grammy award for best recording package (awarded to the art director) | a ghost is born | won row 4 : 2008 | grammy award for best rock album | sky blue sky | nominated row 5 : 2010 | grammy award for best americana album | wilco (the album) | nominated row 6 : 2012 | grammy award for best rock album | the whole love | nominated | col : count ( "result" ) row 1 : 1 | select count ( result ) where year = 2010 <table_name> : table \begin{tabular}{lllll}
\toprule
& year & award & work/artist & result \\
\midrule
0 & 1999 & grammy award for best contemporary folk album & mermaid avenue & nominated \\
1 & 2005 & grammy award for best alternative music album & a ghost is born & won \\
2 & 2005 & grammy award for best recording package (awarded to the art director) & a ghost is born & won \\
3 & 2008 & grammy award for best rock album & sky blue sky & nominated \\
4 & 2010 & grammy award for best americana album & wilco (the album) & nominated \\
5 & 2012 & grammy award for best rock album & the whole love & nominated \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "result" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( result ) where year = 2010 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>award</th>
<th>work/artist</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1999</td>
<td>grammy award for best contemporary folk album</td>
<td>mermaid avenue</td>
<td>nominated</td>
</tr>
<tr>
<th>1</th>
<td>2005</td>
<td>grammy award for best alternative music album</td>
<td>a ghost is born</td>
<td>won</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>grammy award for best recording package (awarded to the art director)</td>
<td>a ghost is born</td>
<td>won</td>
</tr>
<tr>
<th>3</th>
<td>2008</td>
<td>grammy award for best rock album</td>
<td>sky blue sky</td>
<td>nominated</td>
</tr>
<tr>
<th>4</th>
<td>2010</td>
<td>grammy award for best americana album</td>
<td>wilco (the album)</td>
<td>nominated</td>
</tr>
<tr>
<th>5</th>
<td>2012</td>
<td>grammy award for best rock album</td>
<td>the whole love</td>
<td>nominated</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "result" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( result ) where year = 2010 <table_name> : table | | year | award | work/artist | result |
|---:|-------:|:----------------------------------------------------------------------|:------------------|:----------|
| 0 | 1999 | grammy award for best contemporary folk album | mermaid avenue | nominated |
| 1 | 2005 | grammy award for best alternative music album | a ghost is born | won |
| 2 | 2005 | grammy award for best recording package (awarded to the art director) | a ghost is born | won |
| 3 | 2008 | grammy award for best rock album | sky blue sky | nominated |
| 4 | 2010 | grammy award for best americana album | wilco (the album) | nominated |
| 5 | 2012 | grammy award for best rock album | the whole love | nominated | | | | count ( "result" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select county where primary mshsaa class* = 3 col : school | team name | town | county | enrollment (2010-11 & 2011-12) | primary mshsaa class* | football class row 1 : benton high school | (lady) cardinals | st. joseph | buchanan | 846 | 4 | 4 row 2 : bishop leblond high school | (lady) golden eagles | st. joseph | buchanan | 314 | 3 | 2 row 3 : cameron high school | (lady) dragons | cameron | clinton | 503 | 3 | 3 row 4 : chillicothe high school (missouri) | (lady) hornets | chillicothe | livingston | 638 | 4 | 3 row 5 : lafayette high school | fighting irish | st. joseph | buchanan | 801 | 4 | 4 row 6 : maryville high school | (lady) spoofhounds | maryville | nodaway | 473 | 3 | 2 row 7 : savannah high school | (lady) savages | savannah | andrew | 743 | 4 | 4 row 8 : smithville high school | (lady) warriors | smithville | clay | 727 | 4 | 4 | col : count ( "county" ) row 1 : 3 | select county where primary mshsaa class* = 3 <table_name> : table \begin{tabular}{llllllll}
\toprule
& school & team name & town & county & enrollment (2010-11 & 2011-12) & primary mshsaa class* & football class \\
\midrule
0 & benton high school & (lady) cardinals & st. joseph & buchanan & 846 & 4 & 4 \\
1 & bishop leblond high school & (lady) golden eagles & st. joseph & buchanan & 314 & 3 & 2 \\
2 & cameron high school & (lady) dragons & cameron & clinton & 503 & 3 & 3 \\
3 & chillicothe high school (missouri) & (lady) hornets & chillicothe & livingston & 638 & 4 & 3 \\
4 & lafayette high school & fighting irish & st. joseph & buchanan & 801 & 4 & 4 \\
5 & maryville high school & (lady) spoofhounds & maryville & nodaway & 473 & 3 & 2 \\
6 & savannah high school & (lady) savages & savannah & andrew & 743 & 4 & 4 \\
7 & smithville high school & (lady) warriors & smithville & clay & 727 & 4 & 4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "county" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select county where primary mshsaa class* = 3 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>school</th>
<th>team name</th>
<th>town</th>
<th>county</th>
<th>enrollment (2010-11 & 2011-12)</th>
<th>primary mshsaa class*</th>
<th>football class</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>benton high school</td>
<td>(lady) cardinals</td>
<td>st. joseph</td>
<td>buchanan</td>
<td>846</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>1</th>
<td>bishop leblond high school</td>
<td>(lady) golden eagles</td>
<td>st. joseph</td>
<td>buchanan</td>
<td>314</td>
<td>3</td>
<td>2</td>
</tr>
<tr>
<th>2</th>
<td>cameron high school</td>
<td>(lady) dragons</td>
<td>cameron</td>
<td>clinton</td>
<td>503</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>chillicothe high school (missouri)</td>
<td>(lady) hornets</td>
<td>chillicothe</td>
<td>livingston</td>
<td>638</td>
<td>4</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>lafayette high school</td>
<td>fighting irish</td>
<td>st. joseph</td>
<td>buchanan</td>
<td>801</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>maryville high school</td>
<td>(lady) spoofhounds</td>
<td>maryville</td>
<td>nodaway</td>
<td>473</td>
<td>3</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>savannah high school</td>
<td>(lady) savages</td>
<td>savannah</td>
<td>andrew</td>
<td>743</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>7</th>
<td>smithville high school</td>
<td>(lady) warriors</td>
<td>smithville</td>
<td>clay</td>
<td>727</td>
<td>4</td>
<td>4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "county" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select county where primary mshsaa class* = 3 <table_name> : table | | school | team name | town | county | enrollment (2010-11 & 2011-12) | primary mshsaa class* | football class |
|---:|:-----------------------------------|:---------------------|:------------|:-----------|---------------------------------:|------------------------:|-----------------:|
| 0 | benton high school | (lady) cardinals | st. joseph | buchanan | 846 | 4 | 4 |
| 1 | bishop leblond high school | (lady) golden eagles | st. joseph | buchanan | 314 | 3 | 2 |
| 2 | cameron high school | (lady) dragons | cameron | clinton | 503 | 3 | 3 |
| 3 | chillicothe high school (missouri) | (lady) hornets | chillicothe | livingston | 638 | 4 | 3 |
| 4 | lafayette high school | fighting irish | st. joseph | buchanan | 801 | 4 | 4 |
| 5 | maryville high school | (lady) spoofhounds | maryville | nodaway | 473 | 3 | 2 |
| 6 | savannah high school | (lady) savages | savannah | andrew | 743 | 4 | 4 |
| 7 | smithville high school | (lady) warriors | smithville | clay | 727 | 4 | 4 | | | | count ( "county" ) |
|---:|---------------------:|
| 0 | 3 | | [
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select average match attendance where competition = 'rugby championship' col : competition | total spectatorship | average match attendance | year row 1 : a-league | 1,772,133 | 12,707 | 2012/2013 row 2 : australian football league | 6,931,085 | 33,484 | 2013 row 3 : big bash league | 550,262 | 17,750 | 2011/2012 row 4 : national basketball league | 547,021 | 4,031 | 2010/2011 row 5 : national rugby league | 3,345,248 | 16,643 | 2013 row 6 : super rugby | 773,940 | 19,348 | 2012 row 7 : rugby championship | 133,532 | 44,511 | 2012 row 8 : state of origin series | 186,607 | 62,202 | 2011 row 9 : women's national basketball league | 77,944 | none | 2010/2011 | col : average match attendance row 1 : 44,511 | select average match attendance where competition = 'rugby championship' <table_name> : table \begin{tabular}{lllll}
\toprule
& competition & total spectatorship & average match attendance & year \\
\midrule
0 & a-league & 1,772,133 & 12,707 & 2012/2013 \\
1 & australian football league & 6,931,085 & 33,484 & 2013 \\
2 & big bash league & 550,262 & 17,750 & 2011/2012 \\
3 & national basketball league & 547,021 & 4,031 & 2010/2011 \\
4 & national rugby league & 3,345,248 & 16,643 & 2013 \\
5 & super rugby & 773,940 & 19,348 & 2012 \\
6 & rugby championship & 133,532 & 44,511 & 2012 \\
7 & state of origin series & 186,607 & 62,202 & 2011 \\
8 & women's national basketball league & 77,944 & none & 2010/2011 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& average match attendance \\
\midrule
0 & 44,511 \\
\bottomrule
\end{tabular}
| select average match attendance where competition = 'rugby championship' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>competition</th>
<th>total spectatorship</th>
<th>average match attendance</th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>a-league</td>
<td>1,772,133</td>
<td>12,707</td>
<td>2012/2013</td>
</tr>
<tr>
<th>1</th>
<td>australian football league</td>
<td>6,931,085</td>
<td>33,484</td>
<td>2013</td>
</tr>
<tr>
<th>2</th>
<td>big bash league</td>
<td>550,262</td>
<td>17,750</td>
<td>2011/2012</td>
</tr>
<tr>
<th>3</th>
<td>national basketball league</td>
<td>547,021</td>
<td>4,031</td>
<td>2010/2011</td>
</tr>
<tr>
<th>4</th>
<td>national rugby league</td>
<td>3,345,248</td>
<td>16,643</td>
<td>2013</td>
</tr>
<tr>
<th>5</th>
<td>super rugby</td>
<td>773,940</td>
<td>19,348</td>
<td>2012</td>
</tr>
<tr>
<th>6</th>
<td>rugby championship</td>
<td>133,532</td>
<td>44,511</td>
<td>2012</td>
</tr>
<tr>
<th>7</th>
<td>state of origin series</td>
<td>186,607</td>
<td>62,202</td>
<td>2011</td>
</tr>
<tr>
<th>8</th>
<td>women's national basketball league</td>
<td>77,944</td>
<td>none</td>
<td>2010/2011</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>average match attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>44,511</td>
</tr>
</tbody>
</table> | select average match attendance where competition = 'rugby championship' <table_name> : table | | competition | total spectatorship | average match attendance | year |
|---:|:-----------------------------------|:----------------------|:---------------------------|:----------|
| 0 | a-league | 1,772,133 | 12,707 | 2012/2013 |
| 1 | australian football league | 6,931,085 | 33,484 | 2013 |
| 2 | big bash league | 550,262 | 17,750 | 2011/2012 |
| 3 | national basketball league | 547,021 | 4,031 | 2010/2011 |
| 4 | national rugby league | 3,345,248 | 16,643 | 2013 |
| 5 | super rugby | 773,940 | 19,348 | 2012 |
| 6 | rugby championship | 133,532 | 44,511 | 2012 |
| 7 | state of origin series | 186,607 | 62,202 | 2011 |
| 8 | women's national basketball league | 77,944 | none | 2010/2011 | | | | average match attendance |
|---:|:---------------------------|
| 0 | 44,511 | | [
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select count ( * ) where language = 'polish' and language = 'russian' col : language | number | percentage (%) | males | females row 1 : polish | 447685 | 80.86 | 216794 | 230891 row 2 : yiddish | 51215 | 9.25 | 24538 | 26677 row 3 : german | 35931 | 6.49 | 17409 | 18522 row 4 : russian | 15137 | 2.73 | 13551 | 1586 row 5 : ukrainian | 2350 | 0.42 | 2302 | 48 row 6 : other | 1285 | 0.23 | 1041 | 244 row 7 : persons that didn't name their native language | 27 | >0.01 | 14 | 13 row 8 : total | 553633 | 100 | 275652 | 277981 | col : count ( "*" ) row 1 : 0 | select count ( * ) where language = 'polish' and language = 'russian' <table_name> : table \begin{tabular}{llllll}
\toprule
& language & number & percentage (%) & males & females \\
\midrule
0 & polish & 447685 & 80.86 & 216794 & 230891 \\
1 & yiddish & 51215 & 9.25 & 24538 & 26677 \\
2 & german & 35931 & 6.49 & 17409 & 18522 \\
3 & russian & 15137 & 2.73 & 13551 & 1586 \\
4 & ukrainian & 2350 & 0.42 & 2302 & 48 \\
5 & other & 1285 & 0.23 & 1041 & 244 \\
6 & persons that didn't name their native language & 27 & >0.01 & 14 & 13 \\
7 & total & 553633 & 100 & 275652 & 277981 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where language = 'polish' and language = 'russian' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>language</th>
<th>number</th>
<th>percentage (%)</th>
<th>males</th>
<th>females</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>polish</td>
<td>447685</td>
<td>80.86</td>
<td>216794</td>
<td>230891</td>
</tr>
<tr>
<th>1</th>
<td>yiddish</td>
<td>51215</td>
<td>9.25</td>
<td>24538</td>
<td>26677</td>
</tr>
<tr>
<th>2</th>
<td>german</td>
<td>35931</td>
<td>6.49</td>
<td>17409</td>
<td>18522</td>
</tr>
<tr>
<th>3</th>
<td>russian</td>
<td>15137</td>
<td>2.73</td>
<td>13551</td>
<td>1586</td>
</tr>
<tr>
<th>4</th>
<td>ukrainian</td>
<td>2350</td>
<td>0.42</td>
<td>2302</td>
<td>48</td>
</tr>
<tr>
<th>5</th>
<td>other</td>
<td>1285</td>
<td>0.23</td>
<td>1041</td>
<td>244</td>
</tr>
<tr>
<th>6</th>
<td>persons that didn't name their native language</td>
<td>27</td>
<td>>0.01</td>
<td>14</td>
<td>13</td>
</tr>
<tr>
<th>7</th>
<td>total</td>
<td>553633</td>
<td>100</td>
<td>275652</td>
<td>277981</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where language = 'polish' and language = 'russian' <table_name> : table | | language | number | percentage (%) | males | females |
|---:|:-----------------------------------------------|---------:|:-----------------|--------:|----------:|
| 0 | polish | 447685 | 80.86 | 216794 | 230891 |
| 1 | yiddish | 51215 | 9.25 | 24538 | 26677 |
| 2 | german | 35931 | 6.49 | 17409 | 18522 |
| 3 | russian | 15137 | 2.73 | 13551 | 1586 |
| 4 | ukrainian | 2350 | 0.42 | 2302 | 48 |
| 5 | other | 1285 | 0.23 | 1041 | 244 |
| 6 | persons that didn't name their native language | 27 | >0.01 | 14 | 13 |
| 7 | total | 553633 | 100 | 275652 | 277981 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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] |
select count ( athlete ) where time = ( select min ( time ) ) col : rank | athlete | country | time | notes row 1 : none | nataliya petrusyova | soviet union | 1:24.10 | or row 2 : none | leah poulos | united states | 1:25.41 | none row 3 : none | sylvia albrecht | east germany | 1:26.46 | none row 4 : 4 | karin enke | east germany | 1:26.66 | none row 5 : 5 | beth heiden | united states | 1:27.01 | none row 6 : 6 | annie borckink | netherlands | 1:27.24 | none row 7 : 7 | sylvia burka | canada | 1:27.50 | none row 8 : 8 | ann-sofie jarnstrom | sweden | 1:28.10 | none row 9 : 9 | sylvia filipsson | sweden | 1:28.18 | none row 10 : 10 | annette carlen-karlsson | sweden | 1:28.25 | none row 11 : 11 | valentina lalenkova | soviet union | 1:28.27 | none row 12 : 12 | bjørg eva jensen | norway | 1:28.55 | none row 13 : 13 | sijtje van der lende | netherlands | 1:28.72 | none row 14 : 14 | sarah docter | united states | 1:28.80 | none row 15 : 14 | haitske valentijn-pijlman | netherlands | 1:28.80 | none row 16 : 16 | erwina rys-ferens | poland | 1:28.82 | none row 17 : 17 | miyoshi kato | japan | 1:28.97 | none row 18 : 18 | christa rothenburger | east germany | 1:29.69 | none row 19 : 19 | brenda webster | canada | 1:29.84 | none row 20 : 20 | irina kuleshova-kovrova | soviet union | 1:29.94 | none row 21 : 21 | monika pflug | west germany | 1:30.13 | none row 22 : 22 | makiko nagaya | japan | 1:30.27 | none row 23 : 23 | sigrid smuda | west germany | 1:30.29 | none row 24 : 24 | kathy vogt | canada | 1:30.33 | none row 25 : 25 | yuko yaegashi-ota | japan | 1:30.72 | none row 26 : 26 | lee nam-sun | south korea | 1:31.30 | none row 27 : 27 | cao guifeng | china | 1:31.74 | none row 28 : 28 | anneli repola | finland | 1:31.76 | none row 29 : 29 | silvia brunner | switzerland | 1:31.79 | none row 30 : 30 | lee seong-ae | south korea | 1:32.04 | none row 31 : 31 | zhang li | china | 1:32.20 | none row 32 : 32 | shen zhenshu | china | 1:32.49 | none row 33 : 33 | brigitte flierl | west germany | 1:33.61 | none row 34 : 34 | kim yeong-hui | south korea | 1:34.17 | none row 35 : 35 | kim ferran | great britain | 1:34.19 | none row 36 : 36 | marzia peretti | italy | 1:35.66 | none row 37 : 37 | mandy horsepool | great britain | 1:36.31 | none | col : count ( "athlete" ) row 1 : 0 | select count ( athlete ) where time = ( select min ( time ) ) <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & athlete & country & time & notes \\
\midrule
0 & none & nataliya petrusyova & soviet union & 1:24.10 & or \\
1 & none & leah poulos & united states & 1:25.41 & none \\
2 & none & sylvia albrecht & east germany & 1:26.46 & none \\
3 & 4 & karin enke & east germany & 1:26.66 & none \\
4 & 5 & beth heiden & united states & 1:27.01 & none \\
5 & 6 & annie borckink & netherlands & 1:27.24 & none \\
6 & 7 & sylvia burka & canada & 1:27.50 & none \\
7 & 8 & ann-sofie jarnstrom & sweden & 1:28.10 & none \\
8 & 9 & sylvia filipsson & sweden & 1:28.18 & none \\
9 & 10 & annette carlen-karlsson & sweden & 1:28.25 & none \\
10 & 11 & valentina lalenkova & soviet union & 1:28.27 & none \\
11 & 12 & bjørg eva jensen & norway & 1:28.55 & none \\
12 & 13 & sijtje van der lende & netherlands & 1:28.72 & none \\
13 & 14 & sarah docter & united states & 1:28.80 & none \\
14 & 14 & haitske valentijn-pijlman & netherlands & 1:28.80 & none \\
15 & 16 & erwina rys-ferens & poland & 1:28.82 & none \\
16 & 17 & miyoshi kato & japan & 1:28.97 & none \\
17 & 18 & christa rothenburger & east germany & 1:29.69 & none \\
18 & 19 & brenda webster & canada & 1:29.84 & none \\
19 & 20 & irina kuleshova-kovrova & soviet union & 1:29.94 & none \\
20 & 21 & monika pflug & west germany & 1:30.13 & none \\
21 & 22 & makiko nagaya & japan & 1:30.27 & none \\
22 & 23 & sigrid smuda & west germany & 1:30.29 & none \\
23 & 24 & kathy vogt & canada & 1:30.33 & none \\
24 & 25 & yuko yaegashi-ota & japan & 1:30.72 & none \\
25 & 26 & lee nam-sun & south korea & 1:31.30 & none \\
26 & 27 & cao guifeng & china & 1:31.74 & none \\
27 & 28 & anneli repola & finland & 1:31.76 & none \\
28 & 29 & silvia brunner & switzerland & 1:31.79 & none \\
29 & 30 & lee seong-ae & south korea & 1:32.04 & none \\
30 & 31 & zhang li & china & 1:32.20 & none \\
31 & 32 & shen zhenshu & china & 1:32.49 & none \\
32 & 33 & brigitte flierl & west germany & 1:33.61 & none \\
33 & 34 & kim yeong-hui & south korea & 1:34.17 & none \\
34 & 35 & kim ferran & great britain & 1:34.19 & none \\
35 & 36 & marzia peretti & italy & 1:35.66 & none \\
36 & 37 & mandy horsepool & great britain & 1:36.31 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "athlete" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( athlete ) where time = ( select min ( time ) ) <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>athlete</th>
<th>country</th>
<th>time</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>nataliya petrusyova</td>
<td>soviet union</td>
<td>1:24.10</td>
<td>or</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>leah poulos</td>
<td>united states</td>
<td>1:25.41</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>sylvia albrecht</td>
<td>east germany</td>
<td>1:26.46</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>karin enke</td>
<td>east germany</td>
<td>1:26.66</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>beth heiden</td>
<td>united states</td>
<td>1:27.01</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>annie borckink</td>
<td>netherlands</td>
<td>1:27.24</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>sylvia burka</td>
<td>canada</td>
<td>1:27.50</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>ann-sofie jarnstrom</td>
<td>sweden</td>
<td>1:28.10</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>sylvia filipsson</td>
<td>sweden</td>
<td>1:28.18</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>annette carlen-karlsson</td>
<td>sweden</td>
<td>1:28.25</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>valentina lalenkova</td>
<td>soviet union</td>
<td>1:28.27</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>bjørg eva jensen</td>
<td>norway</td>
<td>1:28.55</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>sijtje van der lende</td>
<td>netherlands</td>
<td>1:28.72</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>sarah docter</td>
<td>united states</td>
<td>1:28.80</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>14</td>
<td>haitske valentijn-pijlman</td>
<td>netherlands</td>
<td>1:28.80</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>erwina rys-ferens</td>
<td>poland</td>
<td>1:28.82</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>miyoshi kato</td>
<td>japan</td>
<td>1:28.97</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>christa rothenburger</td>
<td>east germany</td>
<td>1:29.69</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>brenda webster</td>
<td>canada</td>
<td>1:29.84</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>irina kuleshova-kovrova</td>
<td>soviet union</td>
<td>1:29.94</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>monika pflug</td>
<td>west germany</td>
<td>1:30.13</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>makiko nagaya</td>
<td>japan</td>
<td>1:30.27</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>sigrid smuda</td>
<td>west germany</td>
<td>1:30.29</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>kathy vogt</td>
<td>canada</td>
<td>1:30.33</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>yuko yaegashi-ota</td>
<td>japan</td>
<td>1:30.72</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>lee nam-sun</td>
<td>south korea</td>
<td>1:31.30</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>cao guifeng</td>
<td>china</td>
<td>1:31.74</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>28</td>
<td>anneli repola</td>
<td>finland</td>
<td>1:31.76</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>29</td>
<td>silvia brunner</td>
<td>switzerland</td>
<td>1:31.79</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>30</td>
<td>lee seong-ae</td>
<td>south korea</td>
<td>1:32.04</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>31</td>
<td>zhang li</td>
<td>china</td>
<td>1:32.20</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>32</td>
<td>shen zhenshu</td>
<td>china</td>
<td>1:32.49</td>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>33</td>
<td>brigitte flierl</td>
<td>west germany</td>
<td>1:33.61</td>
<td>none</td>
</tr>
<tr>
<th>33</th>
<td>34</td>
<td>kim yeong-hui</td>
<td>south korea</td>
<td>1:34.17</td>
<td>none</td>
</tr>
<tr>
<th>34</th>
<td>35</td>
<td>kim ferran</td>
<td>great britain</td>
<td>1:34.19</td>
<td>none</td>
</tr>
<tr>
<th>35</th>
<td>36</td>
<td>marzia peretti</td>
<td>italy</td>
<td>1:35.66</td>
<td>none</td>
</tr>
<tr>
<th>36</th>
<td>37</td>
<td>mandy horsepool</td>
<td>great britain</td>
<td>1:36.31</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "athlete" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( athlete ) where time = ( select min ( time ) ) <table_name> : table | | rank | athlete | country | time | notes |
|---:|:-------|:--------------------------|:--------------|:--------|:--------|
| 0 | none | nataliya petrusyova | soviet union | 1:24.10 | or |
| 1 | none | leah poulos | united states | 1:25.41 | none |
| 2 | none | sylvia albrecht | east germany | 1:26.46 | none |
| 3 | 4 | karin enke | east germany | 1:26.66 | none |
| 4 | 5 | beth heiden | united states | 1:27.01 | none |
| 5 | 6 | annie borckink | netherlands | 1:27.24 | none |
| 6 | 7 | sylvia burka | canada | 1:27.50 | none |
| 7 | 8 | ann-sofie jarnstrom | sweden | 1:28.10 | none |
| 8 | 9 | sylvia filipsson | sweden | 1:28.18 | none |
| 9 | 10 | annette carlen-karlsson | sweden | 1:28.25 | none |
| 10 | 11 | valentina lalenkova | soviet union | 1:28.27 | none |
| 11 | 12 | bjørg eva jensen | norway | 1:28.55 | none |
| 12 | 13 | sijtje van der lende | netherlands | 1:28.72 | none |
| 13 | 14 | sarah docter | united states | 1:28.80 | none |
| 14 | 14 | haitske valentijn-pijlman | netherlands | 1:28.80 | none |
| 15 | 16 | erwina rys-ferens | poland | 1:28.82 | none |
| 16 | 17 | miyoshi kato | japan | 1:28.97 | none |
| 17 | 18 | christa rothenburger | east germany | 1:29.69 | none |
| 18 | 19 | brenda webster | canada | 1:29.84 | none |
| 19 | 20 | irina kuleshova-kovrova | soviet union | 1:29.94 | none |
| 20 | 21 | monika pflug | west germany | 1:30.13 | none |
| 21 | 22 | makiko nagaya | japan | 1:30.27 | none |
| 22 | 23 | sigrid smuda | west germany | 1:30.29 | none |
| 23 | 24 | kathy vogt | canada | 1:30.33 | none |
| 24 | 25 | yuko yaegashi-ota | japan | 1:30.72 | none |
| 25 | 26 | lee nam-sun | south korea | 1:31.30 | none |
| 26 | 27 | cao guifeng | china | 1:31.74 | none |
| 27 | 28 | anneli repola | finland | 1:31.76 | none |
| 28 | 29 | silvia brunner | switzerland | 1:31.79 | none |
| 29 | 30 | lee seong-ae | south korea | 1:32.04 | none |
| 30 | 31 | zhang li | china | 1:32.20 | none |
| 31 | 32 | shen zhenshu | china | 1:32.49 | none |
| 32 | 33 | brigitte flierl | west germany | 1:33.61 | none |
| 33 | 34 | kim yeong-hui | south korea | 1:34.17 | none |
| 34 | 35 | kim ferran | great britain | 1:34.19 | none |
| 35 | 36 | marzia peretti | italy | 1:35.66 | none |
| 36 | 37 | mandy horsepool | great britain | 1:36.31 | none | | | | count ( "athlete" ) |
|---:|----------------------:|
| 0 | 0 | | [
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select title (english translation) where no. > 0 col : no. | title (latin) | title (english translation) | subject | date row 1 : 1 | qui pluribus | none | on faith and religion | 1846-11-09 00:00:00 row 2 : 2 | praedecessores nostros | none | on aid for ireland | 1847-03-25 00:00:00 row 3 : 3 | ubi primum | none | on discipline for religious | 1847-06-17 00:00:00 row 4 : 4 | ubi primum | none | on immaculate conception | 1849-02-02 00:00:00 row 5 : 5 | nostis et nobiscum | none | on the church in the papal states | 1849-12-08 00:00:00 row 6 : 6 | exultavit cor nostrum | none | on the effects of the jubilee | 1851-11-21 00:00:00 row 7 : 7 | nemo certe ignorat | none | on discipline for clergy | 1852-03-25 00:00:00 row 8 : 8 | probe noscitis venerabiles | none | on the discipline for clergy | 1852-05-17 00:00:00 row 9 : 9 | inter multiplices | none | pleading for unity of spirit | 1853-03-21 00:00:00 row 10 : 10 | neminem vestrum | none | on the persecution of armenians | 1854-02-02 00:00:00 row 11 : 11 | optime noscitis | none | on the proposed catholic university of ireland | 1854-03-20 00:00:00 row 12 : 12 | apostolicae nostrae caritatis | none | urging prayers of peace | 1854-08-01 00:00:00 row 13 : 13 | optime noscitis | none | on episcopal meetings | 1855-11-05 00:00:00 row 14 : 14 | singulari quidem | none | on the church in austria | 1856-03-17 00:00:00 row 15 : 15 | cum nuper | none | on care for clerics | 1858-01-20 00:00:00 row 16 : 16 | amantissimi redemptoris | none | on priests and the care of souls | 1858-05-03 00:00:00 row 17 : 17 | cum sancta mater ecclesia | none | pleading for public prayer | 1859-04-27 00:00:00 row 18 : 18 | qui nuper | none | on the pontifical states | 1859-06-18 00:00:00 row 19 : 19 | nullis certe verbis | none | on the need for civil sovereignty | 1860-01-19 00:00:00 row 20 : 20 | amantissimus | none | on the care of the churches | 1862-04-08 00:00:00 row 21 : 21 | quanto conficiamur moerore | none | on promotion of false doctrines | 1863-08-10 00:00:00 row 22 : 22 | incredibili | none | on the persecution in new granada | 1863-09-17 00:00:00 row 23 : 23 | maximae quidem | none | on the church in bavaria | 1864-08-18 00:00:00 row 24 : 24 | quanta cura | none | condemning current errors | 1864-12-08 00:00:00 row 25 : 25 | meridionali americae | none | on the seminary for the native clergy | 1865-09-30 00:00:00 row 26 : 26 | levate | none | on the affiliations of church | 1867-10-27 00:00:00 row 27 : 27 | respicientes | none | protesting the taking of the pontifical states | 1870-11-01 00:00:00 row 28 : 28 | ubi nos | "our city" | on the pontifical states | 1871-05-15 00:00:00 row 29 : 29 | beneficia dei | none | on the 25th anniversary of his pontificate | 1871-06-04 00:00:00 row 30 : 30 | saepe venerabiles fratres | none | thanksgiving for 25 years of pontificate | 1871-08-05 00:00:00 row 31 : 31 | quae in patriarchatu | none | on the church in chaldea | 1872-11-16 00:00:00 row 32 : 32 | quartus supra | none | on the church in armenia | 1873-01-01 00:00:00 row 33 : 33 | etsi multa | none | on the church in italy, germany and switzerland | 1873-11-21 00:00:00 row 34 : 34 | vix dum a nobis | none | on the church in austria | 1874-03-07 00:00:00 row 35 : 35 | omnem sollicitudinem | none | on the greek-ruthenian rite | 1874-05-13 00:00:00 row 36 : 36 | gravibus ecclesiae | none | proclaiming a jubilee | 1874-12-24 00:00:00 row 37 : 37 | quod nunquam | none | on the church in prussia | 1875-02-05 00:00:00 row 38 : 38 | graves ac diuturnae | none | on the church in switzerland | 1875-03-23 00:00:00 | col : title (english translation) row 1 : none row 2 : none row 3 : none row 4 : none row 5 : none row 6 : none row 7 : none row 8 : none row 9 : none row 10 : none row 11 : none row 12 : none row 13 : none row 14 : none row 15 : none row 16 : none row 17 : none row 18 : none row 19 : none row 20 : none row 21 : none row 22 : none row 23 : none row 24 : none row 25 : none row 26 : none row 27 : none row 28 : "our city" row 29 : none row 30 : none row 31 : none row 32 : none row 33 : none row 34 : none row 35 : none row 36 : none row 37 : none row 38 : none | select title (english translation) where no. > 0 <table_name> : table \begin{tabular}{llllll}
\toprule
& no. & title (latin) & title (english translation) & subject & date \\
\midrule
0 & 1 & qui pluribus & none & on faith and religion & 1846-11-09 00:00:00 \\
1 & 2 & praedecessores nostros & none & on aid for ireland & 1847-03-25 00:00:00 \\
2 & 3 & ubi primum & none & on discipline for religious & 1847-06-17 00:00:00 \\
3 & 4 & ubi primum & none & on immaculate conception & 1849-02-02 00:00:00 \\
4 & 5 & nostis et nobiscum & none & on the church in the papal states & 1849-12-08 00:00:00 \\
5 & 6 & exultavit cor nostrum & none & on the effects of the jubilee & 1851-11-21 00:00:00 \\
6 & 7 & nemo certe ignorat & none & on discipline for clergy & 1852-03-25 00:00:00 \\
7 & 8 & probe noscitis venerabiles & none & on the discipline for clergy & 1852-05-17 00:00:00 \\
8 & 9 & inter multiplices & none & pleading for unity of spirit & 1853-03-21 00:00:00 \\
9 & 10 & neminem vestrum & none & on the persecution of armenians & 1854-02-02 00:00:00 \\
10 & 11 & optime noscitis & none & on the proposed catholic university of ireland & 1854-03-20 00:00:00 \\
11 & 12 & apostolicae nostrae caritatis & none & urging prayers of peace & 1854-08-01 00:00:00 \\
12 & 13 & optime noscitis & none & on episcopal meetings & 1855-11-05 00:00:00 \\
13 & 14 & singulari quidem & none & on the church in austria & 1856-03-17 00:00:00 \\
14 & 15 & cum nuper & none & on care for clerics & 1858-01-20 00:00:00 \\
15 & 16 & amantissimi redemptoris & none & on priests and the care of souls & 1858-05-03 00:00:00 \\
16 & 17 & cum sancta mater ecclesia & none & pleading for public prayer & 1859-04-27 00:00:00 \\
17 & 18 & qui nuper & none & on the pontifical states & 1859-06-18 00:00:00 \\
18 & 19 & nullis certe verbis & none & on the need for civil sovereignty & 1860-01-19 00:00:00 \\
19 & 20 & amantissimus & none & on the care of the churches & 1862-04-08 00:00:00 \\
20 & 21 & quanto conficiamur moerore & none & on promotion of false doctrines & 1863-08-10 00:00:00 \\
21 & 22 & incredibili & none & on the persecution in new granada & 1863-09-17 00:00:00 \\
22 & 23 & maximae quidem & none & on the church in bavaria & 1864-08-18 00:00:00 \\
23 & 24 & quanta cura & none & condemning current errors & 1864-12-08 00:00:00 \\
24 & 25 & meridionali americae & none & on the seminary for the native clergy & 1865-09-30 00:00:00 \\
25 & 26 & levate & none & on the affiliations of church & 1867-10-27 00:00:00 \\
26 & 27 & respicientes & none & protesting the taking of the pontifical states & 1870-11-01 00:00:00 \\
27 & 28 & ubi nos & "our city" & on the pontifical states & 1871-05-15 00:00:00 \\
28 & 29 & beneficia dei & none & on the 25th anniversary of his pontificate & 1871-06-04 00:00:00 \\
29 & 30 & saepe venerabiles fratres & none & thanksgiving for 25 years of pontificate & 1871-08-05 00:00:00 \\
30 & 31 & quae in patriarchatu & none & on the church in chaldea & 1872-11-16 00:00:00 \\
31 & 32 & quartus supra & none & on the church in armenia & 1873-01-01 00:00:00 \\
32 & 33 & etsi multa & none & on the church in italy, germany and switzerland & 1873-11-21 00:00:00 \\
33 & 34 & vix dum a nobis & none & on the church in austria & 1874-03-07 00:00:00 \\
34 & 35 & omnem sollicitudinem & none & on the greek-ruthenian rite & 1874-05-13 00:00:00 \\
35 & 36 & gravibus ecclesiae & none & proclaiming a jubilee & 1874-12-24 00:00:00 \\
36 & 37 & quod nunquam & none & on the church in prussia & 1875-02-05 00:00:00 \\
37 & 38 & graves ac diuturnae & none & on the church in switzerland & 1875-03-23 00:00:00 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& title (english translation) \\
\midrule
0 & none \\
1 & none \\
2 & none \\
3 & none \\
4 & none \\
5 & none \\
6 & none \\
7 & none \\
8 & none \\
9 & none \\
10 & none \\
11 & none \\
12 & none \\
13 & none \\
14 & none \\
15 & none \\
16 & none \\
17 & none \\
18 & none \\
19 & none \\
20 & none \\
21 & none \\
22 & none \\
23 & none \\
24 & none \\
25 & none \\
26 & none \\
27 & "our city" \\
28 & none \\
29 & none \\
30 & none \\
31 & none \\
32 & none \\
33 & none \\
34 & none \\
35 & none \\
36 & none \\
37 & none \\
\bottomrule
\end{tabular}
| select title (english translation) where no. > 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no.</th>
<th>title (latin)</th>
<th>title (english translation)</th>
<th>subject</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>qui pluribus</td>
<td>none</td>
<td>on faith and religion</td>
<td>1846-11-09 00:00:00</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>praedecessores nostros</td>
<td>none</td>
<td>on aid for ireland</td>
<td>1847-03-25 00:00:00</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>ubi primum</td>
<td>none</td>
<td>on discipline for religious</td>
<td>1847-06-17 00:00:00</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>ubi primum</td>
<td>none</td>
<td>on immaculate conception</td>
<td>1849-02-02 00:00:00</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>nostis et nobiscum</td>
<td>none</td>
<td>on the church in the papal states</td>
<td>1849-12-08 00:00:00</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>exultavit cor nostrum</td>
<td>none</td>
<td>on the effects of the jubilee</td>
<td>1851-11-21 00:00:00</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>nemo certe ignorat</td>
<td>none</td>
<td>on discipline for clergy</td>
<td>1852-03-25 00:00:00</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>probe noscitis venerabiles</td>
<td>none</td>
<td>on the discipline for clergy</td>
<td>1852-05-17 00:00:00</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>inter multiplices</td>
<td>none</td>
<td>pleading for unity of spirit</td>
<td>1853-03-21 00:00:00</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>neminem vestrum</td>
<td>none</td>
<td>on the persecution of armenians</td>
<td>1854-02-02 00:00:00</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>optime noscitis</td>
<td>none</td>
<td>on the proposed catholic university of ireland</td>
<td>1854-03-20 00:00:00</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>apostolicae nostrae caritatis</td>
<td>none</td>
<td>urging prayers of peace</td>
<td>1854-08-01 00:00:00</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>optime noscitis</td>
<td>none</td>
<td>on episcopal meetings</td>
<td>1855-11-05 00:00:00</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>singulari quidem</td>
<td>none</td>
<td>on the church in austria</td>
<td>1856-03-17 00:00:00</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>cum nuper</td>
<td>none</td>
<td>on care for clerics</td>
<td>1858-01-20 00:00:00</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>amantissimi redemptoris</td>
<td>none</td>
<td>on priests and the care of souls</td>
<td>1858-05-03 00:00:00</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>cum sancta mater ecclesia</td>
<td>none</td>
<td>pleading for public prayer</td>
<td>1859-04-27 00:00:00</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>qui nuper</td>
<td>none</td>
<td>on the pontifical states</td>
<td>1859-06-18 00:00:00</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>nullis certe verbis</td>
<td>none</td>
<td>on the need for civil sovereignty</td>
<td>1860-01-19 00:00:00</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>amantissimus</td>
<td>none</td>
<td>on the care of the churches</td>
<td>1862-04-08 00:00:00</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>quanto conficiamur moerore</td>
<td>none</td>
<td>on promotion of false doctrines</td>
<td>1863-08-10 00:00:00</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>incredibili</td>
<td>none</td>
<td>on the persecution in new granada</td>
<td>1863-09-17 00:00:00</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>maximae quidem</td>
<td>none</td>
<td>on the church in bavaria</td>
<td>1864-08-18 00:00:00</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>quanta cura</td>
<td>none</td>
<td>condemning current errors</td>
<td>1864-12-08 00:00:00</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>meridionali americae</td>
<td>none</td>
<td>on the seminary for the native clergy</td>
<td>1865-09-30 00:00:00</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>levate</td>
<td>none</td>
<td>on the affiliations of church</td>
<td>1867-10-27 00:00:00</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>respicientes</td>
<td>none</td>
<td>protesting the taking of the pontifical states</td>
<td>1870-11-01 00:00:00</td>
</tr>
<tr>
<th>27</th>
<td>28</td>
<td>ubi nos</td>
<td>"our city"</td>
<td>on the pontifical states</td>
<td>1871-05-15 00:00:00</td>
</tr>
<tr>
<th>28</th>
<td>29</td>
<td>beneficia dei</td>
<td>none</td>
<td>on the 25th anniversary of his pontificate</td>
<td>1871-06-04 00:00:00</td>
</tr>
<tr>
<th>29</th>
<td>30</td>
<td>saepe venerabiles fratres</td>
<td>none</td>
<td>thanksgiving for 25 years of pontificate</td>
<td>1871-08-05 00:00:00</td>
</tr>
<tr>
<th>30</th>
<td>31</td>
<td>quae in patriarchatu</td>
<td>none</td>
<td>on the church in chaldea</td>
<td>1872-11-16 00:00:00</td>
</tr>
<tr>
<th>31</th>
<td>32</td>
<td>quartus supra</td>
<td>none</td>
<td>on the church in armenia</td>
<td>1873-01-01 00:00:00</td>
</tr>
<tr>
<th>32</th>
<td>33</td>
<td>etsi multa</td>
<td>none</td>
<td>on the church in italy, germany and switzerland</td>
<td>1873-11-21 00:00:00</td>
</tr>
<tr>
<th>33</th>
<td>34</td>
<td>vix dum a nobis</td>
<td>none</td>
<td>on the church in austria</td>
<td>1874-03-07 00:00:00</td>
</tr>
<tr>
<th>34</th>
<td>35</td>
<td>omnem sollicitudinem</td>
<td>none</td>
<td>on the greek-ruthenian rite</td>
<td>1874-05-13 00:00:00</td>
</tr>
<tr>
<th>35</th>
<td>36</td>
<td>gravibus ecclesiae</td>
<td>none</td>
<td>proclaiming a jubilee</td>
<td>1874-12-24 00:00:00</td>
</tr>
<tr>
<th>36</th>
<td>37</td>
<td>quod nunquam</td>
<td>none</td>
<td>on the church in prussia</td>
<td>1875-02-05 00:00:00</td>
</tr>
<tr>
<th>37</th>
<td>38</td>
<td>graves ac diuturnae</td>
<td>none</td>
<td>on the church in switzerland</td>
<td>1875-03-23 00:00:00</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title (english translation)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>"our city"</td>
</tr>
<tr>
<th>28</th>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>none</td>
</tr>
<tr>
<th>33</th>
<td>none</td>
</tr>
<tr>
<th>34</th>
<td>none</td>
</tr>
<tr>
<th>35</th>
<td>none</td>
</tr>
<tr>
<th>36</th>
<td>none</td>
</tr>
<tr>
<th>37</th>
<td>none</td>
</tr>
</tbody>
</table> | select title (english translation) where no. > 0 <table_name> : table | | no. | title (latin) | title (english translation) | subject | date |
|---:|------:|:------------------------------|:------------------------------|:------------------------------------------------|:--------------------|
| 0 | 1 | qui pluribus | none | on faith and religion | 1846-11-09 00:00:00 |
| 1 | 2 | praedecessores nostros | none | on aid for ireland | 1847-03-25 00:00:00 |
| 2 | 3 | ubi primum | none | on discipline for religious | 1847-06-17 00:00:00 |
| 3 | 4 | ubi primum | none | on immaculate conception | 1849-02-02 00:00:00 |
| 4 | 5 | nostis et nobiscum | none | on the church in the papal states | 1849-12-08 00:00:00 |
| 5 | 6 | exultavit cor nostrum | none | on the effects of the jubilee | 1851-11-21 00:00:00 |
| 6 | 7 | nemo certe ignorat | none | on discipline for clergy | 1852-03-25 00:00:00 |
| 7 | 8 | probe noscitis venerabiles | none | on the discipline for clergy | 1852-05-17 00:00:00 |
| 8 | 9 | inter multiplices | none | pleading for unity of spirit | 1853-03-21 00:00:00 |
| 9 | 10 | neminem vestrum | none | on the persecution of armenians | 1854-02-02 00:00:00 |
| 10 | 11 | optime noscitis | none | on the proposed catholic university of ireland | 1854-03-20 00:00:00 |
| 11 | 12 | apostolicae nostrae caritatis | none | urging prayers of peace | 1854-08-01 00:00:00 |
| 12 | 13 | optime noscitis | none | on episcopal meetings | 1855-11-05 00:00:00 |
| 13 | 14 | singulari quidem | none | on the church in austria | 1856-03-17 00:00:00 |
| 14 | 15 | cum nuper | none | on care for clerics | 1858-01-20 00:00:00 |
| 15 | 16 | amantissimi redemptoris | none | on priests and the care of souls | 1858-05-03 00:00:00 |
| 16 | 17 | cum sancta mater ecclesia | none | pleading for public prayer | 1859-04-27 00:00:00 |
| 17 | 18 | qui nuper | none | on the pontifical states | 1859-06-18 00:00:00 |
| 18 | 19 | nullis certe verbis | none | on the need for civil sovereignty | 1860-01-19 00:00:00 |
| 19 | 20 | amantissimus | none | on the care of the churches | 1862-04-08 00:00:00 |
| 20 | 21 | quanto conficiamur moerore | none | on promotion of false doctrines | 1863-08-10 00:00:00 |
| 21 | 22 | incredibili | none | on the persecution in new granada | 1863-09-17 00:00:00 |
| 22 | 23 | maximae quidem | none | on the church in bavaria | 1864-08-18 00:00:00 |
| 23 | 24 | quanta cura | none | condemning current errors | 1864-12-08 00:00:00 |
| 24 | 25 | meridionali americae | none | on the seminary for the native clergy | 1865-09-30 00:00:00 |
| 25 | 26 | levate | none | on the affiliations of church | 1867-10-27 00:00:00 |
| 26 | 27 | respicientes | none | protesting the taking of the pontifical states | 1870-11-01 00:00:00 |
| 27 | 28 | ubi nos | "our city" | on the pontifical states | 1871-05-15 00:00:00 |
| 28 | 29 | beneficia dei | none | on the 25th anniversary of his pontificate | 1871-06-04 00:00:00 |
| 29 | 30 | saepe venerabiles fratres | none | thanksgiving for 25 years of pontificate | 1871-08-05 00:00:00 |
| 30 | 31 | quae in patriarchatu | none | on the church in chaldea | 1872-11-16 00:00:00 |
| 31 | 32 | quartus supra | none | on the church in armenia | 1873-01-01 00:00:00 |
| 32 | 33 | etsi multa | none | on the church in italy, germany and switzerland | 1873-11-21 00:00:00 |
| 33 | 34 | vix dum a nobis | none | on the church in austria | 1874-03-07 00:00:00 |
| 34 | 35 | omnem sollicitudinem | none | on the greek-ruthenian rite | 1874-05-13 00:00:00 |
| 35 | 36 | gravibus ecclesiae | none | proclaiming a jubilee | 1874-12-24 00:00:00 |
| 36 | 37 | quod nunquam | none | on the church in prussia | 1875-02-05 00:00:00 |
| 37 | 38 | graves ac diuturnae | none | on the church in switzerland | 1875-03-23 00:00:00 | | | | title (english translation) |
|---:|:------------------------------|
| 0 | none |
| 1 | none |
| 2 | none |
| 3 | none |
| 4 | none |
| 5 | none |
| 6 | none |
| 7 | none |
| 8 | none |
| 9 | none |
| 10 | none |
| 11 | none |
| 12 | none |
| 13 | none |
| 14 | none |
| 15 | none |
| 16 | none |
| 17 | none |
| 18 | none |
| 19 | none |
| 20 | none |
| 21 | none |
| 22 | none |
| 23 | none |
| 24 | none |
| 25 | none |
| 26 | none |
| 27 | "our city" |
| 28 | none |
| 29 | none |
| 30 | none |
| 31 | none |
| 32 | none |
| 33 | none |
| 34 | none |
| 35 | none |
| 36 | none |
| 37 | none | | [
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select peak chart positions uk - peak chart positions uk where album = 'anthem' col : year | single | peak chart positions us mod | peak chart positions uk | album row 1 : 1997 | "automatic" | none | none | losing streak row 2 : 1997 | "dopeman" | none | none | losing streak row 3 : 1997 | "dopeman" (remix) | none | none | non-album single row 4 : 1997 | "howie j. reynolds" | none | none | non-album single row 5 : 1998 | "history of a boring town" | 39 | none | hello rockview row 6 : 2000 | "all my best friends are metalheads" | none | 51 | hello rockview row 7 : 2000 | "all my best friends are metalheads" (remix) | none | none | non-album single row 8 : 2001 | "gainesville rock city" | none | 57 | borders & boundaries row 9 : 2003 | "she's gonna break soon" | none | 39 | anthem row 10 : 2003 | "the science of selling yourself short" | 36 | 78 | anthem row 11 : 2003 | "surrender" | none | none | anthem row 12 : 2006 | "overrated (everything is)" | none | 61 | in with the out crowd row 13 : 2006 | "the rest of my life" | none | 77 | in with the out crowd row 14 : 2008 | "does the lion city still roar?" | none | none | gnv fla row 15 : 2008 | "abandon ship" | none | none | gnv fla | col : "peak chart positions uk - peak chart positions uk" row 1 : peak chart positions uk - peak chart positions uk row 2 : peak chart positions uk - peak chart positions uk row 3 : peak chart positions uk - peak chart positions uk | select peak chart positions uk - peak chart positions uk where album = 'anthem' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & single & peak chart positions us mod & peak chart positions uk & album \\
\midrule
0 & 1997 & "automatic" & none & none & losing streak \\
1 & 1997 & "dopeman" & none & none & losing streak \\
2 & 1997 & "dopeman" (remix) & none & none & non-album single \\
3 & 1997 & "howie j. reynolds" & none & none & non-album single \\
4 & 1998 & "history of a boring town" & 39 & none & hello rockview \\
5 & 2000 & "all my best friends are metalheads" & none & 51 & hello rockview \\
6 & 2000 & "all my best friends are metalheads" (remix) & none & none & non-album single \\
7 & 2001 & "gainesville rock city" & none & 57 & borders & boundaries \\
8 & 2003 & "she's gonna break soon" & none & 39 & anthem \\
9 & 2003 & "the science of selling yourself short" & 36 & 78 & anthem \\
10 & 2003 & "surrender" & none & none & anthem \\
11 & 2006 & "overrated (everything is)" & none & 61 & in with the out crowd \\
12 & 2006 & "the rest of my life" & none & 77 & in with the out crowd \\
13 & 2008 & "does the lion city still roar?" & none & none & gnv fla \\
14 & 2008 & "abandon ship" & none & none & gnv fla \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "peak chart positions uk - peak chart positions uk" \\
\midrule
0 & peak chart positions uk - peak chart positions uk \\
1 & peak chart positions uk - peak chart positions uk \\
2 & peak chart positions uk - peak chart positions uk \\
\bottomrule
\end{tabular}
| select peak chart positions uk - peak chart positions uk where album = 'anthem' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>single</th>
<th>peak chart positions us mod</th>
<th>peak chart positions uk</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1997</td>
<td>"automatic"</td>
<td>none</td>
<td>none</td>
<td>losing streak</td>
</tr>
<tr>
<th>1</th>
<td>1997</td>
<td>"dopeman"</td>
<td>none</td>
<td>none</td>
<td>losing streak</td>
</tr>
<tr>
<th>2</th>
<td>1997</td>
<td>"dopeman" (remix)</td>
<td>none</td>
<td>none</td>
<td>non-album single</td>
</tr>
<tr>
<th>3</th>
<td>1997</td>
<td>"howie j. reynolds"</td>
<td>none</td>
<td>none</td>
<td>non-album single</td>
</tr>
<tr>
<th>4</th>
<td>1998</td>
<td>"history of a boring town"</td>
<td>39</td>
<td>none</td>
<td>hello rockview</td>
</tr>
<tr>
<th>5</th>
<td>2000</td>
<td>"all my best friends are metalheads"</td>
<td>none</td>
<td>51</td>
<td>hello rockview</td>
</tr>
<tr>
<th>6</th>
<td>2000</td>
<td>"all my best friends are metalheads" (remix)</td>
<td>none</td>
<td>none</td>
<td>non-album single</td>
</tr>
<tr>
<th>7</th>
<td>2001</td>
<td>"gainesville rock city"</td>
<td>none</td>
<td>57</td>
<td>borders & boundaries</td>
</tr>
<tr>
<th>8</th>
<td>2003</td>
<td>"she's gonna break soon"</td>
<td>none</td>
<td>39</td>
<td>anthem</td>
</tr>
<tr>
<th>9</th>
<td>2003</td>
<td>"the science of selling yourself short"</td>
<td>36</td>
<td>78</td>
<td>anthem</td>
</tr>
<tr>
<th>10</th>
<td>2003</td>
<td>"surrender"</td>
<td>none</td>
<td>none</td>
<td>anthem</td>
</tr>
<tr>
<th>11</th>
<td>2006</td>
<td>"overrated (everything is)"</td>
<td>none</td>
<td>61</td>
<td>in with the out crowd</td>
</tr>
<tr>
<th>12</th>
<td>2006</td>
<td>"the rest of my life"</td>
<td>none</td>
<td>77</td>
<td>in with the out crowd</td>
</tr>
<tr>
<th>13</th>
<td>2008</td>
<td>"does the lion city still roar?"</td>
<td>none</td>
<td>none</td>
<td>gnv fla</td>
</tr>
<tr>
<th>14</th>
<td>2008</td>
<td>"abandon ship"</td>
<td>none</td>
<td>none</td>
<td>gnv fla</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"peak chart positions uk - peak chart positions uk"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>peak chart positions uk - peak chart positions uk</td>
</tr>
<tr>
<th>1</th>
<td>peak chart positions uk - peak chart positions uk</td>
</tr>
<tr>
<th>2</th>
<td>peak chart positions uk - peak chart positions uk</td>
</tr>
</tbody>
</table> | select peak chart positions uk - peak chart positions uk where album = 'anthem' <table_name> : table | | year | single | peak chart positions us mod | peak chart positions uk | album |
|---:|-------:|:---------------------------------------------|:------------------------------|:--------------------------|:----------------------|
| 0 | 1997 | "automatic" | none | none | losing streak |
| 1 | 1997 | "dopeman" | none | none | losing streak |
| 2 | 1997 | "dopeman" (remix) | none | none | non-album single |
| 3 | 1997 | "howie j. reynolds" | none | none | non-album single |
| 4 | 1998 | "history of a boring town" | 39 | none | hello rockview |
| 5 | 2000 | "all my best friends are metalheads" | none | 51 | hello rockview |
| 6 | 2000 | "all my best friends are metalheads" (remix) | none | none | non-album single |
| 7 | 2001 | "gainesville rock city" | none | 57 | borders & boundaries |
| 8 | 2003 | "she's gonna break soon" | none | 39 | anthem |
| 9 | 2003 | "the science of selling yourself short" | 36 | 78 | anthem |
| 10 | 2003 | "surrender" | none | none | anthem |
| 11 | 2006 | "overrated (everything is)" | none | 61 | in with the out crowd |
| 12 | 2006 | "the rest of my life" | none | 77 | in with the out crowd |
| 13 | 2008 | "does the lion city still roar?" | none | none | gnv fla |
| 14 | 2008 | "abandon ship" | none | none | gnv fla | | | | "peak chart positions uk - peak chart positions uk" |
|---:|:------------------------------------------------------|
| 0 | peak chart positions uk - peak chart positions uk |
| 1 | peak chart positions uk - peak chart positions uk |
| 2 | peak chart positions uk - peak chart positions uk | | [
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select count ( coach ) where coach = 208 col : coach | years | seasons | wins | losses | ties | pct row 1 : o. b. "rip" sanderson | 1908 | 1 | 5 | 1 | 0 | 0.833 row 2 : ed sabre | 1920 | 1 | 3 | 1 | 0 | 0.75 row 3 : mack erwin | 1957-60 | 4 | 62 | 30 | 1 | 0.672 row 4 : chal port | 1965-91 | 27 | 641 | 386 | 2 | 0.624 row 5 : fred jordan | 1992-pres | 22 | 726 | 552 | 0 | 0.568 row 6 : john d. mcmillan | 1952-53 | 2 | 14 | 15 | 0 | 0.483 row 7 : jim newsome | 1961-64 | 4 | 37 | 43 | 0 | 0.463 row 8 : bunzy o'neal | 1948 | 1 | 6 | 7 | 0 | 0.462 row 9 : george c. rogers | 1914-15, 1921-24 | 6 | 26 | 33 | 1 | 0.441 row 10 : fred montsdeoca | 1954-56 | 2 | 22 | 31 | 0 | 0.415 row 11 : george a. schmick | 1910 | 1 | 4 | 6 | 0 | 0.4 row 12 : thomas s. mcmillan | 1916, 1919 | 2 | 8 | 12 | 0 | 0.4 row 13 : harold manley | 1954 | 1 | 5 | 9 | 0 | 0.357 row 14 : "barney" legge | 1911 | 1 | 2 | 5 | 1 | 0.286 row 15 : h. l. "matty" matthews | 1926-30, 37-38 | 3 | 10 | 25 | 1 | 0.286 row 16 : dusty rhodes | 1947 | 1 | 2 | 5 | 0 | 0.286 row 17 : "shorty" o'brien | 1918 | 1 | 3 | 9 | 0 | 0.25 row 18 : "bull dog" drummond | 1925 | 1 | 2 | 7 | 0 | 0.222 | col : count ( "coach" ) row 1 : 0 | select count ( coach ) where coach = 208 <table_name> : table \begin{tabular}{llllllll}
\toprule
& coach & years & seasons & wins & losses & ties & pct \\
\midrule
0 & o. b. "rip" sanderson & 1908 & 1 & 5 & 1 & 0 & 0.833 \\
1 & ed sabre & 1920 & 1 & 3 & 1 & 0 & 0.75 \\
2 & mack erwin & 1957-60 & 4 & 62 & 30 & 1 & 0.672 \\
3 & chal port & 1965-91 & 27 & 641 & 386 & 2 & 0.624 \\
4 & fred jordan & 1992-pres & 22 & 726 & 552 & 0 & 0.568 \\
5 & john d. mcmillan & 1952-53 & 2 & 14 & 15 & 0 & 0.483 \\
6 & jim newsome & 1961-64 & 4 & 37 & 43 & 0 & 0.463 \\
7 & bunzy o'neal & 1948 & 1 & 6 & 7 & 0 & 0.462 \\
8 & george c. rogers & 1914-15, 1921-24 & 6 & 26 & 33 & 1 & 0.441 \\
9 & fred montsdeoca & 1954-56 & 2 & 22 & 31 & 0 & 0.415 \\
10 & george a. schmick & 1910 & 1 & 4 & 6 & 0 & 0.4 \\
11 & thomas s. mcmillan & 1916, 1919 & 2 & 8 & 12 & 0 & 0.4 \\
12 & harold manley & 1954 & 1 & 5 & 9 & 0 & 0.357 \\
13 & "barney" legge & 1911 & 1 & 2 & 5 & 1 & 0.286 \\
14 & h. l. "matty" matthews & 1926-30, 37-38 & 3 & 10 & 25 & 1 & 0.286 \\
15 & dusty rhodes & 1947 & 1 & 2 & 5 & 0 & 0.286 \\
16 & "shorty" o'brien & 1918 & 1 & 3 & 9 & 0 & 0.25 \\
17 & "bull dog" drummond & 1925 & 1 & 2 & 7 & 0 & 0.222 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "coach" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( coach ) where coach = 208 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>coach</th>
<th>years</th>
<th>seasons</th>
<th>wins</th>
<th>losses</th>
<th>ties</th>
<th>pct</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>o. b. "rip" sanderson</td>
<td>1908</td>
<td>1</td>
<td>5</td>
<td>1</td>
<td>0</td>
<td>0.833</td>
</tr>
<tr>
<th>1</th>
<td>ed sabre</td>
<td>1920</td>
<td>1</td>
<td>3</td>
<td>1</td>
<td>0</td>
<td>0.75</td>
</tr>
<tr>
<th>2</th>
<td>mack erwin</td>
<td>1957-60</td>
<td>4</td>
<td>62</td>
<td>30</td>
<td>1</td>
<td>0.672</td>
</tr>
<tr>
<th>3</th>
<td>chal port</td>
<td>1965-91</td>
<td>27</td>
<td>641</td>
<td>386</td>
<td>2</td>
<td>0.624</td>
</tr>
<tr>
<th>4</th>
<td>fred jordan</td>
<td>1992-pres</td>
<td>22</td>
<td>726</td>
<td>552</td>
<td>0</td>
<td>0.568</td>
</tr>
<tr>
<th>5</th>
<td>john d. mcmillan</td>
<td>1952-53</td>
<td>2</td>
<td>14</td>
<td>15</td>
<td>0</td>
<td>0.483</td>
</tr>
<tr>
<th>6</th>
<td>jim newsome</td>
<td>1961-64</td>
<td>4</td>
<td>37</td>
<td>43</td>
<td>0</td>
<td>0.463</td>
</tr>
<tr>
<th>7</th>
<td>bunzy o'neal</td>
<td>1948</td>
<td>1</td>
<td>6</td>
<td>7</td>
<td>0</td>
<td>0.462</td>
</tr>
<tr>
<th>8</th>
<td>george c. rogers</td>
<td>1914-15, 1921-24</td>
<td>6</td>
<td>26</td>
<td>33</td>
<td>1</td>
<td>0.441</td>
</tr>
<tr>
<th>9</th>
<td>fred montsdeoca</td>
<td>1954-56</td>
<td>2</td>
<td>22</td>
<td>31</td>
<td>0</td>
<td>0.415</td>
</tr>
<tr>
<th>10</th>
<td>george a. schmick</td>
<td>1910</td>
<td>1</td>
<td>4</td>
<td>6</td>
<td>0</td>
<td>0.4</td>
</tr>
<tr>
<th>11</th>
<td>thomas s. mcmillan</td>
<td>1916, 1919</td>
<td>2</td>
<td>8</td>
<td>12</td>
<td>0</td>
<td>0.4</td>
</tr>
<tr>
<th>12</th>
<td>harold manley</td>
<td>1954</td>
<td>1</td>
<td>5</td>
<td>9</td>
<td>0</td>
<td>0.357</td>
</tr>
<tr>
<th>13</th>
<td>"barney" legge</td>
<td>1911</td>
<td>1</td>
<td>2</td>
<td>5</td>
<td>1</td>
<td>0.286</td>
</tr>
<tr>
<th>14</th>
<td>h. l. "matty" matthews</td>
<td>1926-30, 37-38</td>
<td>3</td>
<td>10</td>
<td>25</td>
<td>1</td>
<td>0.286</td>
</tr>
<tr>
<th>15</th>
<td>dusty rhodes</td>
<td>1947</td>
<td>1</td>
<td>2</td>
<td>5</td>
<td>0</td>
<td>0.286</td>
</tr>
<tr>
<th>16</th>
<td>"shorty" o'brien</td>
<td>1918</td>
<td>1</td>
<td>3</td>
<td>9</td>
<td>0</td>
<td>0.25</td>
</tr>
<tr>
<th>17</th>
<td>"bull dog" drummond</td>
<td>1925</td>
<td>1</td>
<td>2</td>
<td>7</td>
<td>0</td>
<td>0.222</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "coach" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( coach ) where coach = 208 <table_name> : table | | coach | years | seasons | wins | losses | ties | pct |
|---:|:-----------------------|:-----------------|----------:|-------:|---------:|-------:|------:|
| 0 | o. b. "rip" sanderson | 1908 | 1 | 5 | 1 | 0 | 0.833 |
| 1 | ed sabre | 1920 | 1 | 3 | 1 | 0 | 0.75 |
| 2 | mack erwin | 1957-60 | 4 | 62 | 30 | 1 | 0.672 |
| 3 | chal port | 1965-91 | 27 | 641 | 386 | 2 | 0.624 |
| 4 | fred jordan | 1992-pres | 22 | 726 | 552 | 0 | 0.568 |
| 5 | john d. mcmillan | 1952-53 | 2 | 14 | 15 | 0 | 0.483 |
| 6 | jim newsome | 1961-64 | 4 | 37 | 43 | 0 | 0.463 |
| 7 | bunzy o'neal | 1948 | 1 | 6 | 7 | 0 | 0.462 |
| 8 | george c. rogers | 1914-15, 1921-24 | 6 | 26 | 33 | 1 | 0.441 |
| 9 | fred montsdeoca | 1954-56 | 2 | 22 | 31 | 0 | 0.415 |
| 10 | george a. schmick | 1910 | 1 | 4 | 6 | 0 | 0.4 |
| 11 | thomas s. mcmillan | 1916, 1919 | 2 | 8 | 12 | 0 | 0.4 |
| 12 | harold manley | 1954 | 1 | 5 | 9 | 0 | 0.357 |
| 13 | "barney" legge | 1911 | 1 | 2 | 5 | 1 | 0.286 |
| 14 | h. l. "matty" matthews | 1926-30, 37-38 | 3 | 10 | 25 | 1 | 0.286 |
| 15 | dusty rhodes | 1947 | 1 | 2 | 5 | 0 | 0.286 |
| 16 | "shorty" o'brien | 1918 | 1 | 3 | 9 | 0 | 0.25 |
| 17 | "bull dog" drummond | 1925 | 1 | 2 | 7 | 0 | 0.222 | | | | count ( "coach" ) |
|---:|--------------------:|
| 0 | 0 | | [
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select count ( * ) where age = 11 col : fence | name | jockey | age | handicap (st-lb) | starting price | fate row 1 : 26 | rondetto | jeff king | 9 | 11-6 | 100/8 | fell row 2 : 6 | forgotten dreams | r coonan | 11 | 11-0 | 22/1 | fell row 3 : 22 | kapeno | david dick | 8 | 11-6 | 100/8 | fell row 4 : 1 | ayala | stan mellor | 11 | 10-13 | 50/1 | fell row 5 : none | time | mr brough scott | 10 | 10-13 | 40/1 | fell row 6 : 10 | dark venetian | jim renfree | 10 | 10-13 | 100/1 | fell row 7 : 4 | red tide | johnny haine | 8 | 10-13 | 33/1 | fell row 8 : 24 | pontin-go | johnny lehane | 13 | 10-13 | 50/1 | fell row 9 : 18 | leedsy | george robinson | 7 | 10-13 | 18/1 | fell row 10 : 3 | ronald's boy | mr gay kindersley | 8 | 11-1 | 100/1 | fell row 11 : 17 | bold biri | michael scudamore | 9 | 10-13 | 100/1 | fell row 12 : 9 | groomsman | beltran osorio | 10 | 10-13 | 100/1 | fell row 13 : none | blonde warrior | mr d crossley-cooke | 13 | 10-13 | 100/1 | fell row 14 : 6 | nedsmar | john hudson | 11 | 10-13 | 100/1 | fell row 15 : none | black spot | j gamble | 8 | 10-13 | 100/1 | fell row 16 : none | lizawake | mr george hartigan | 12 | 10-13 | 100/1 | pulled up row 17 : none | reproduction | robin langley | 12 | 10-13 | 40/1 | pulled-up row 18 : none | leslie | p jones | 9 | 10-13 | 33/1 | pulled up row 19 : none | sword flash | t ryan | 12 | 10-13 | 100/1 | pulled up row 20 : none | vulcano | tommy carberry | 7 | 10-13 | 50/1 | pulled up row 21 : none | quintin bay | pat taaffe | 9 | 10-13 | 25/1 | pulled up row 22 : none | solonace | rw jones | 13 | 10-13 | 100/1 | pulled up row 23 : 4 | cutlette | m roberts | 8 | 10-13 | 50/1 | pulled up row 24 : none | mr mctaffy | t jackson | 13 | 10-13 | 100/1 | pulled up row 25 : 6 | barleycroft | phil harvey | 10 | 10-13 | 100/1 | brought down row 26 : 13 | phebu | j morrissey | 8 | 10-13 | 33/1 | brought down row 27 : 6 | ruby glen | stephen davenport | 10 | 10-13 | 33/1 | brought down row 28 : 6 | sizzle-on | p hurley | 9 | 10/13 | 100/1 | brought down row 29 : 6 | crobeg | mr macer gifford | 12 | 10-13 | 100/1 | brought down row 30 : 8 | coleen star | johnny leech | 11 | 10-13 | 100/1 | refused row 31 : 22 | ballygowan | a redmond | 11 | 10-13 | 66/1 | refused row 32 : none | fearless cavalier | r west | 14 | 10-13 | 100/1 | refused row 33 : none | french cottage | mr wa tellwright | 13 | 10-13 | 100/1 | refused | col : count ( "*" ) row 1 : 5 | select count ( * ) where age = 11 <table_name> : table \begin{tabular}{llllllll}
\toprule
& fence & name & jockey & age & handicap (st-lb) & starting price & fate \\
\midrule
0 & 26 & rondetto & jeff king & 9 & 11-6 & 100/8 & fell \\
1 & 6 & forgotten dreams & r coonan & 11 & 11-0 & 22/1 & fell \\
2 & 22 & kapeno & david dick & 8 & 11-6 & 100/8 & fell \\
3 & 1 & ayala & stan mellor & 11 & 10-13 & 50/1 & fell \\
4 & none & time & mr brough scott & 10 & 10-13 & 40/1 & fell \\
5 & 10 & dark venetian & jim renfree & 10 & 10-13 & 100/1 & fell \\
6 & 4 & red tide & johnny haine & 8 & 10-13 & 33/1 & fell \\
7 & 24 & pontin-go & johnny lehane & 13 & 10-13 & 50/1 & fell \\
8 & 18 & leedsy & george robinson & 7 & 10-13 & 18/1 & fell \\
9 & 3 & ronald's boy & mr gay kindersley & 8 & 11-1 & 100/1 & fell \\
10 & 17 & bold biri & michael scudamore & 9 & 10-13 & 100/1 & fell \\
11 & 9 & groomsman & beltran osorio & 10 & 10-13 & 100/1 & fell \\
12 & none & blonde warrior & mr d crossley-cooke & 13 & 10-13 & 100/1 & fell \\
13 & 6 & nedsmar & john hudson & 11 & 10-13 & 100/1 & fell \\
14 & none & black spot & j gamble & 8 & 10-13 & 100/1 & fell \\
15 & none & lizawake & mr george hartigan & 12 & 10-13 & 100/1 & pulled up \\
16 & none & reproduction & robin langley & 12 & 10-13 & 40/1 & pulled-up \\
17 & none & leslie & p jones & 9 & 10-13 & 33/1 & pulled up \\
18 & none & sword flash & t ryan & 12 & 10-13 & 100/1 & pulled up \\
19 & none & vulcano & tommy carberry & 7 & 10-13 & 50/1 & pulled up \\
20 & none & quintin bay & pat taaffe & 9 & 10-13 & 25/1 & pulled up \\
21 & none & solonace & rw jones & 13 & 10-13 & 100/1 & pulled up \\
22 & 4 & cutlette & m roberts & 8 & 10-13 & 50/1 & pulled up \\
23 & none & mr mctaffy & t jackson & 13 & 10-13 & 100/1 & pulled up \\
24 & 6 & barleycroft & phil harvey & 10 & 10-13 & 100/1 & brought down \\
25 & 13 & phebu & j morrissey & 8 & 10-13 & 33/1 & brought down \\
26 & 6 & ruby glen & stephen davenport & 10 & 10-13 & 33/1 & brought down \\
27 & 6 & sizzle-on & p hurley & 9 & 10/13 & 100/1 & brought down \\
28 & 6 & crobeg & mr macer gifford & 12 & 10-13 & 100/1 & brought down \\
29 & 8 & coleen star & johnny leech & 11 & 10-13 & 100/1 & refused \\
30 & 22 & ballygowan & a redmond & 11 & 10-13 & 66/1 & refused \\
31 & none & fearless cavalier & r west & 14 & 10-13 & 100/1 & refused \\
32 & none & french cottage & mr wa tellwright & 13 & 10-13 & 100/1 & refused \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( * ) where age = 11 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>fence</th>
<th>name</th>
<th>jockey</th>
<th>age</th>
<th>handicap (st-lb)</th>
<th>starting price</th>
<th>fate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>26</td>
<td>rondetto</td>
<td>jeff king</td>
<td>9</td>
<td>11-6</td>
<td>100/8</td>
<td>fell</td>
</tr>
<tr>
<th>1</th>
<td>6</td>
<td>forgotten dreams</td>
<td>r coonan</td>
<td>11</td>
<td>11-0</td>
<td>22/1</td>
<td>fell</td>
</tr>
<tr>
<th>2</th>
<td>22</td>
<td>kapeno</td>
<td>david dick</td>
<td>8</td>
<td>11-6</td>
<td>100/8</td>
<td>fell</td>
</tr>
<tr>
<th>3</th>
<td>1</td>
<td>ayala</td>
<td>stan mellor</td>
<td>11</td>
<td>10-13</td>
<td>50/1</td>
<td>fell</td>
</tr>
<tr>
<th>4</th>
<td>none</td>
<td>time</td>
<td>mr brough scott</td>
<td>10</td>
<td>10-13</td>
<td>40/1</td>
<td>fell</td>
</tr>
<tr>
<th>5</th>
<td>10</td>
<td>dark venetian</td>
<td>jim renfree</td>
<td>10</td>
<td>10-13</td>
<td>100/1</td>
<td>fell</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>red tide</td>
<td>johnny haine</td>
<td>8</td>
<td>10-13</td>
<td>33/1</td>
<td>fell</td>
</tr>
<tr>
<th>7</th>
<td>24</td>
<td>pontin-go</td>
<td>johnny lehane</td>
<td>13</td>
<td>10-13</td>
<td>50/1</td>
<td>fell</td>
</tr>
<tr>
<th>8</th>
<td>18</td>
<td>leedsy</td>
<td>george robinson</td>
<td>7</td>
<td>10-13</td>
<td>18/1</td>
<td>fell</td>
</tr>
<tr>
<th>9</th>
<td>3</td>
<td>ronald's boy</td>
<td>mr gay kindersley</td>
<td>8</td>
<td>11-1</td>
<td>100/1</td>
<td>fell</td>
</tr>
<tr>
<th>10</th>
<td>17</td>
<td>bold biri</td>
<td>michael scudamore</td>
<td>9</td>
<td>10-13</td>
<td>100/1</td>
<td>fell</td>
</tr>
<tr>
<th>11</th>
<td>9</td>
<td>groomsman</td>
<td>beltran osorio</td>
<td>10</td>
<td>10-13</td>
<td>100/1</td>
<td>fell</td>
</tr>
<tr>
<th>12</th>
<td>none</td>
<td>blonde warrior</td>
<td>mr d crossley-cooke</td>
<td>13</td>
<td>10-13</td>
<td>100/1</td>
<td>fell</td>
</tr>
<tr>
<th>13</th>
<td>6</td>
<td>nedsmar</td>
<td>john hudson</td>
<td>11</td>
<td>10-13</td>
<td>100/1</td>
<td>fell</td>
</tr>
<tr>
<th>14</th>
<td>none</td>
<td>black spot</td>
<td>j gamble</td>
<td>8</td>
<td>10-13</td>
<td>100/1</td>
<td>fell</td>
</tr>
<tr>
<th>15</th>
<td>none</td>
<td>lizawake</td>
<td>mr george hartigan</td>
<td>12</td>
<td>10-13</td>
<td>100/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>16</th>
<td>none</td>
<td>reproduction</td>
<td>robin langley</td>
<td>12</td>
<td>10-13</td>
<td>40/1</td>
<td>pulled-up</td>
</tr>
<tr>
<th>17</th>
<td>none</td>
<td>leslie</td>
<td>p jones</td>
<td>9</td>
<td>10-13</td>
<td>33/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>18</th>
<td>none</td>
<td>sword flash</td>
<td>t ryan</td>
<td>12</td>
<td>10-13</td>
<td>100/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>19</th>
<td>none</td>
<td>vulcano</td>
<td>tommy carberry</td>
<td>7</td>
<td>10-13</td>
<td>50/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>20</th>
<td>none</td>
<td>quintin bay</td>
<td>pat taaffe</td>
<td>9</td>
<td>10-13</td>
<td>25/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>21</th>
<td>none</td>
<td>solonace</td>
<td>rw jones</td>
<td>13</td>
<td>10-13</td>
<td>100/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>22</th>
<td>4</td>
<td>cutlette</td>
<td>m roberts</td>
<td>8</td>
<td>10-13</td>
<td>50/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>23</th>
<td>none</td>
<td>mr mctaffy</td>
<td>t jackson</td>
<td>13</td>
<td>10-13</td>
<td>100/1</td>
<td>pulled up</td>
</tr>
<tr>
<th>24</th>
<td>6</td>
<td>barleycroft</td>
<td>phil harvey</td>
<td>10</td>
<td>10-13</td>
<td>100/1</td>
<td>brought down</td>
</tr>
<tr>
<th>25</th>
<td>13</td>
<td>phebu</td>
<td>j morrissey</td>
<td>8</td>
<td>10-13</td>
<td>33/1</td>
<td>brought down</td>
</tr>
<tr>
<th>26</th>
<td>6</td>
<td>ruby glen</td>
<td>stephen davenport</td>
<td>10</td>
<td>10-13</td>
<td>33/1</td>
<td>brought down</td>
</tr>
<tr>
<th>27</th>
<td>6</td>
<td>sizzle-on</td>
<td>p hurley</td>
<td>9</td>
<td>10/13</td>
<td>100/1</td>
<td>brought down</td>
</tr>
<tr>
<th>28</th>
<td>6</td>
<td>crobeg</td>
<td>mr macer gifford</td>
<td>12</td>
<td>10-13</td>
<td>100/1</td>
<td>brought down</td>
</tr>
<tr>
<th>29</th>
<td>8</td>
<td>coleen star</td>
<td>johnny leech</td>
<td>11</td>
<td>10-13</td>
<td>100/1</td>
<td>refused</td>
</tr>
<tr>
<th>30</th>
<td>22</td>
<td>ballygowan</td>
<td>a redmond</td>
<td>11</td>
<td>10-13</td>
<td>66/1</td>
<td>refused</td>
</tr>
<tr>
<th>31</th>
<td>none</td>
<td>fearless cavalier</td>
<td>r west</td>
<td>14</td>
<td>10-13</td>
<td>100/1</td>
<td>refused</td>
</tr>
<tr>
<th>32</th>
<td>none</td>
<td>french cottage</td>
<td>mr wa tellwright</td>
<td>13</td>
<td>10-13</td>
<td>100/1</td>
<td>refused</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( * ) where age = 11 <table_name> : table | | fence | name | jockey | age | handicap (st-lb) | starting price | fate |
|---:|:--------|:------------------|:--------------------|------:|:-------------------|:-----------------|:-------------|
| 0 | 26 | rondetto | jeff king | 9 | 11-6 | 100/8 | fell |
| 1 | 6 | forgotten dreams | r coonan | 11 | 11-0 | 22/1 | fell |
| 2 | 22 | kapeno | david dick | 8 | 11-6 | 100/8 | fell |
| 3 | 1 | ayala | stan mellor | 11 | 10-13 | 50/1 | fell |
| 4 | none | time | mr brough scott | 10 | 10-13 | 40/1 | fell |
| 5 | 10 | dark venetian | jim renfree | 10 | 10-13 | 100/1 | fell |
| 6 | 4 | red tide | johnny haine | 8 | 10-13 | 33/1 | fell |
| 7 | 24 | pontin-go | johnny lehane | 13 | 10-13 | 50/1 | fell |
| 8 | 18 | leedsy | george robinson | 7 | 10-13 | 18/1 | fell |
| 9 | 3 | ronald's boy | mr gay kindersley | 8 | 11-1 | 100/1 | fell |
| 10 | 17 | bold biri | michael scudamore | 9 | 10-13 | 100/1 | fell |
| 11 | 9 | groomsman | beltran osorio | 10 | 10-13 | 100/1 | fell |
| 12 | none | blonde warrior | mr d crossley-cooke | 13 | 10-13 | 100/1 | fell |
| 13 | 6 | nedsmar | john hudson | 11 | 10-13 | 100/1 | fell |
| 14 | none | black spot | j gamble | 8 | 10-13 | 100/1 | fell |
| 15 | none | lizawake | mr george hartigan | 12 | 10-13 | 100/1 | pulled up |
| 16 | none | reproduction | robin langley | 12 | 10-13 | 40/1 | pulled-up |
| 17 | none | leslie | p jones | 9 | 10-13 | 33/1 | pulled up |
| 18 | none | sword flash | t ryan | 12 | 10-13 | 100/1 | pulled up |
| 19 | none | vulcano | tommy carberry | 7 | 10-13 | 50/1 | pulled up |
| 20 | none | quintin bay | pat taaffe | 9 | 10-13 | 25/1 | pulled up |
| 21 | none | solonace | rw jones | 13 | 10-13 | 100/1 | pulled up |
| 22 | 4 | cutlette | m roberts | 8 | 10-13 | 50/1 | pulled up |
| 23 | none | mr mctaffy | t jackson | 13 | 10-13 | 100/1 | pulled up |
| 24 | 6 | barleycroft | phil harvey | 10 | 10-13 | 100/1 | brought down |
| 25 | 13 | phebu | j morrissey | 8 | 10-13 | 33/1 | brought down |
| 26 | 6 | ruby glen | stephen davenport | 10 | 10-13 | 33/1 | brought down |
| 27 | 6 | sizzle-on | p hurley | 9 | 10/13 | 100/1 | brought down |
| 28 | 6 | crobeg | mr macer gifford | 12 | 10-13 | 100/1 | brought down |
| 29 | 8 | coleen star | johnny leech | 11 | 10-13 | 100/1 | refused |
| 30 | 22 | ballygowan | a redmond | 11 | 10-13 | 66/1 | refused |
| 31 | none | fearless cavalier | r west | 14 | 10-13 | 100/1 | refused |
| 32 | none | french cottage | mr wa tellwright | 13 | 10-13 | 100/1 | refused | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 5 | | [
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] |
select count ( air/ground ) where status = 'destroyed' col : date | location | air/ground | number | type | status row 1 : 1944-03-08 00:00:00 | near steinhuder meer (lake), germany | air | 1.0 | me-109 | destroyed row 2 : 1944-03-16 00:00:00 | 20 miles south of stuttgart, germany | air | 1.0 | me-110 | destroyed row 3 : 1944-04-11 00:00:00 | 20 miles northeast of magdeburg, germany | air | 0.5 | me-109 | destroyed row 4 : 1944-04-13 00:00:00 | west of mannheim, germany | air | 1.0 | fw-190 | destroyed row 5 : 1944-04-24 00:00:00 | south of munich, germany | air | 3.0 | me-110 | destroyed row 6 : 1944-05-27 00:00:00 | north of strasbourg, france | air | 1.0 | me-109 | damaged row 7 : 1944-08-18 00:00:00 | 20 miles northeast of paris, france | air | 0.5 | me-109 | destroyed row 8 : 1944-09-13 00:00:00 | south of nordhausen, germany | air | 2.5 | me-109 | destroyed row 9 : 1944-10-06 00:00:00 | 20 miles northwest of berlin, germany | air | 1.0 | me-109 | damaged row 10 : 1944-10-06 00:00:00 | 20 miles northwest of berlin, germany | air | 2.0 | me-109 | destroyed row 11 : 1944-11-27 00:00:00 | south of magdeburg, germany | air | 4.0 | fw-190 | destroyed row 12 : 1945-01-14 00:00:00 | 20 miles northwest of berlin, germany | air | 1.0 | me-109 | destroyed row 13 : 1952-01-25 00:00:00 | korea | air | 1.0 | mig-15 | damaged | col : count ( "air/ground" ) row 1 : 10 | select count ( air/ground ) where status = 'destroyed' <table_name> : table \begin{tabular}{lllllll}
\toprule
& date & location & air/ground & number & type & status \\
\midrule
0 & 1944-03-08 00:00:00 & near steinhuder meer (lake), germany & air & 1.0 & me-109 & destroyed \\
1 & 1944-03-16 00:00:00 & 20 miles south of stuttgart, germany & air & 1.0 & me-110 & destroyed \\
2 & 1944-04-11 00:00:00 & 20 miles northeast of magdeburg, germany & air & 0.5 & me-109 & destroyed \\
3 & 1944-04-13 00:00:00 & west of mannheim, germany & air & 1.0 & fw-190 & destroyed \\
4 & 1944-04-24 00:00:00 & south of munich, germany & air & 3.0 & me-110 & destroyed \\
5 & 1944-05-27 00:00:00 & north of strasbourg, france & air & 1.0 & me-109 & damaged \\
6 & 1944-08-18 00:00:00 & 20 miles northeast of paris, france & air & 0.5 & me-109 & destroyed \\
7 & 1944-09-13 00:00:00 & south of nordhausen, germany & air & 2.5 & me-109 & destroyed \\
8 & 1944-10-06 00:00:00 & 20 miles northwest of berlin, germany & air & 1.0 & me-109 & damaged \\
9 & 1944-10-06 00:00:00 & 20 miles northwest of berlin, germany & air & 2.0 & me-109 & destroyed \\
10 & 1944-11-27 00:00:00 & south of magdeburg, germany & air & 4.0 & fw-190 & destroyed \\
11 & 1945-01-14 00:00:00 & 20 miles northwest of berlin, germany & air & 1.0 & me-109 & destroyed \\
12 & 1952-01-25 00:00:00 & korea & air & 1.0 & mig-15 & damaged \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "air/ground" ) \\
\midrule
0 & 10 \\
\bottomrule
\end{tabular}
| select count ( air/ground ) where status = 'destroyed' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>location</th>
<th>air/ground</th>
<th>number</th>
<th>type</th>
<th>status</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1944-03-08 00:00:00</td>
<td>near steinhuder meer (lake), germany</td>
<td>air</td>
<td>1.0</td>
<td>me-109</td>
<td>destroyed</td>
</tr>
<tr>
<th>1</th>
<td>1944-03-16 00:00:00</td>
<td>20 miles south of stuttgart, germany</td>
<td>air</td>
<td>1.0</td>
<td>me-110</td>
<td>destroyed</td>
</tr>
<tr>
<th>2</th>
<td>1944-04-11 00:00:00</td>
<td>20 miles northeast of magdeburg, germany</td>
<td>air</td>
<td>0.5</td>
<td>me-109</td>
<td>destroyed</td>
</tr>
<tr>
<th>3</th>
<td>1944-04-13 00:00:00</td>
<td>west of mannheim, germany</td>
<td>air</td>
<td>1.0</td>
<td>fw-190</td>
<td>destroyed</td>
</tr>
<tr>
<th>4</th>
<td>1944-04-24 00:00:00</td>
<td>south of munich, germany</td>
<td>air</td>
<td>3.0</td>
<td>me-110</td>
<td>destroyed</td>
</tr>
<tr>
<th>5</th>
<td>1944-05-27 00:00:00</td>
<td>north of strasbourg, france</td>
<td>air</td>
<td>1.0</td>
<td>me-109</td>
<td>damaged</td>
</tr>
<tr>
<th>6</th>
<td>1944-08-18 00:00:00</td>
<td>20 miles northeast of paris, france</td>
<td>air</td>
<td>0.5</td>
<td>me-109</td>
<td>destroyed</td>
</tr>
<tr>
<th>7</th>
<td>1944-09-13 00:00:00</td>
<td>south of nordhausen, germany</td>
<td>air</td>
<td>2.5</td>
<td>me-109</td>
<td>destroyed</td>
</tr>
<tr>
<th>8</th>
<td>1944-10-06 00:00:00</td>
<td>20 miles northwest of berlin, germany</td>
<td>air</td>
<td>1.0</td>
<td>me-109</td>
<td>damaged</td>
</tr>
<tr>
<th>9</th>
<td>1944-10-06 00:00:00</td>
<td>20 miles northwest of berlin, germany</td>
<td>air</td>
<td>2.0</td>
<td>me-109</td>
<td>destroyed</td>
</tr>
<tr>
<th>10</th>
<td>1944-11-27 00:00:00</td>
<td>south of magdeburg, germany</td>
<td>air</td>
<td>4.0</td>
<td>fw-190</td>
<td>destroyed</td>
</tr>
<tr>
<th>11</th>
<td>1945-01-14 00:00:00</td>
<td>20 miles northwest of berlin, germany</td>
<td>air</td>
<td>1.0</td>
<td>me-109</td>
<td>destroyed</td>
</tr>
<tr>
<th>12</th>
<td>1952-01-25 00:00:00</td>
<td>korea</td>
<td>air</td>
<td>1.0</td>
<td>mig-15</td>
<td>damaged</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "air/ground" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>10</td>
</tr>
</tbody>
</table> | select count ( air/ground ) where status = 'destroyed' <table_name> : table | | date | location | air/ground | number | type | status |
|---:|:--------------------|:-----------------------------------------|:-------------|---------:|:-------|:----------|
| 0 | 1944-03-08 00:00:00 | near steinhuder meer (lake), germany | air | 1 | me-109 | destroyed |
| 1 | 1944-03-16 00:00:00 | 20 miles south of stuttgart, germany | air | 1 | me-110 | destroyed |
| 2 | 1944-04-11 00:00:00 | 20 miles northeast of magdeburg, germany | air | 0.5 | me-109 | destroyed |
| 3 | 1944-04-13 00:00:00 | west of mannheim, germany | air | 1 | fw-190 | destroyed |
| 4 | 1944-04-24 00:00:00 | south of munich, germany | air | 3 | me-110 | destroyed |
| 5 | 1944-05-27 00:00:00 | north of strasbourg, france | air | 1 | me-109 | damaged |
| 6 | 1944-08-18 00:00:00 | 20 miles northeast of paris, france | air | 0.5 | me-109 | destroyed |
| 7 | 1944-09-13 00:00:00 | south of nordhausen, germany | air | 2.5 | me-109 | destroyed |
| 8 | 1944-10-06 00:00:00 | 20 miles northwest of berlin, germany | air | 1 | me-109 | damaged |
| 9 | 1944-10-06 00:00:00 | 20 miles northwest of berlin, germany | air | 2 | me-109 | destroyed |
| 10 | 1944-11-27 00:00:00 | south of magdeburg, germany | air | 4 | fw-190 | destroyed |
| 11 | 1945-01-14 00:00:00 | 20 miles northwest of berlin, germany | air | 1 | me-109 | destroyed |
| 12 | 1952-01-25 00:00:00 | korea | air | 1 | mig-15 | damaged | | | | count ( "air/ground" ) |
|---:|-------------------------:|
| 0 | 10 | | [
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] |
select count ( * ) where opponent = '8' col : game | november | opponent | score | record row 1 : 2 | 5 | @ detroit red wings | 12 - 5 | 0-2-0 row 2 : 3 | 7 | montreal canadiens | 4 - 3 ot | 1-2-0 row 3 : 4 | 8 | @ montreal canadiens | 10 - 4 | 1-3-0 row 4 : 5 | 10 | chicago black hawks | 5 - 3 ot | 2-3-0 row 5 : 6 | 14 | @ boston bruins | 5 - 3 | 2-4-0 row 6 : 7 | 15 | boston bruins | 4 - 3 | 2-5-0 row 7 : 8 | 19 | toronto maple leafs | 7 - 3 | 2-6-0 row 8 : 9 | 22 | detroit red wings | 4 - 4 | 2-6-1 row 9 : 10 | 26 | @ chicago black hawks | 2 - 1 | 3-6-1 row 10 : 11 | 28 | @ toronto maple leafs | 8 - 6 | 3-7-1 row 11 : 12 | 29 | boston bruins | 3 - 2 | 4-7-1 | col : count ( "*" ) row 1 : 0 | select count ( * ) where opponent = '8' <table_name> : table \begin{tabular}{llllll}
\toprule
& game & november & opponent & score & record \\
\midrule
0 & 2 & 5 & @ detroit red wings & 12 - 5 & 0-2-0 \\
1 & 3 & 7 & montreal canadiens & 4 - 3 ot & 1-2-0 \\
2 & 4 & 8 & @ montreal canadiens & 10 - 4 & 1-3-0 \\
3 & 5 & 10 & chicago black hawks & 5 - 3 ot & 2-3-0 \\
4 & 6 & 14 & @ boston bruins & 5 - 3 & 2-4-0 \\
5 & 7 & 15 & boston bruins & 4 - 3 & 2-5-0 \\
6 & 8 & 19 & toronto maple leafs & 7 - 3 & 2-6-0 \\
7 & 9 & 22 & detroit red wings & 4 - 4 & 2-6-1 \\
8 & 10 & 26 & @ chicago black hawks & 2 - 1 & 3-6-1 \\
9 & 11 & 28 & @ toronto maple leafs & 8 - 6 & 3-7-1 \\
10 & 12 & 29 & boston bruins & 3 - 2 & 4-7-1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where opponent = '8' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>november</th>
<th>opponent</th>
<th>score</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
<td>5</td>
<td>@ detroit red wings</td>
<td>12 - 5</td>
<td>0-2-0</td>
</tr>
<tr>
<th>1</th>
<td>3</td>
<td>7</td>
<td>montreal canadiens</td>
<td>4 - 3 ot</td>
<td>1-2-0</td>
</tr>
<tr>
<th>2</th>
<td>4</td>
<td>8</td>
<td>@ montreal canadiens</td>
<td>10 - 4</td>
<td>1-3-0</td>
</tr>
<tr>
<th>3</th>
<td>5</td>
<td>10</td>
<td>chicago black hawks</td>
<td>5 - 3 ot</td>
<td>2-3-0</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>14</td>
<td>@ boston bruins</td>
<td>5 - 3</td>
<td>2-4-0</td>
</tr>
<tr>
<th>5</th>
<td>7</td>
<td>15</td>
<td>boston bruins</td>
<td>4 - 3</td>
<td>2-5-0</td>
</tr>
<tr>
<th>6</th>
<td>8</td>
<td>19</td>
<td>toronto maple leafs</td>
<td>7 - 3</td>
<td>2-6-0</td>
</tr>
<tr>
<th>7</th>
<td>9</td>
<td>22</td>
<td>detroit red wings</td>
<td>4 - 4</td>
<td>2-6-1</td>
</tr>
<tr>
<th>8</th>
<td>10</td>
<td>26</td>
<td>@ chicago black hawks</td>
<td>2 - 1</td>
<td>3-6-1</td>
</tr>
<tr>
<th>9</th>
<td>11</td>
<td>28</td>
<td>@ toronto maple leafs</td>
<td>8 - 6</td>
<td>3-7-1</td>
</tr>
<tr>
<th>10</th>
<td>12</td>
<td>29</td>
<td>boston bruins</td>
<td>3 - 2</td>
<td>4-7-1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where opponent = '8' <table_name> : table | | game | november | opponent | score | record |
|---:|-------:|-----------:|:----------------------|:---------|:---------|
| 0 | 2 | 5 | @ detroit red wings | 12 - 5 | 0-2-0 |
| 1 | 3 | 7 | montreal canadiens | 4 - 3 ot | 1-2-0 |
| 2 | 4 | 8 | @ montreal canadiens | 10 - 4 | 1-3-0 |
| 3 | 5 | 10 | chicago black hawks | 5 - 3 ot | 2-3-0 |
| 4 | 6 | 14 | @ boston bruins | 5 - 3 | 2-4-0 |
| 5 | 7 | 15 | boston bruins | 4 - 3 | 2-5-0 |
| 6 | 8 | 19 | toronto maple leafs | 7 - 3 | 2-6-0 |
| 7 | 9 | 22 | detroit red wings | 4 - 4 | 2-6-1 |
| 8 | 10 | 26 | @ chicago black hawks | 2 - 1 | 3-6-1 |
| 9 | 11 | 28 | @ toronto maple leafs | 8 - 6 | 3-7-1 |
| 10 | 12 | 29 | boston bruins | 3 - 2 | 4-7-1 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select name where 2009-10 team = 'wisconsin badgers' order by weight desc limit 1 col : position | name | height | weight | birthdate | birthplace | 2009-10 team row 1 : g | brianne mclaughlin | 174 cm (5 ft 9 in) | 59 kg (130 lb) | june 20, 1987 | sheffield, ohio | robert morris colonials row 2 : g | molly schaus | 174 cm (5 ft 9 in) | 67 kg (148 lb) | july 29, 1988 | natick, massachusetts | boston eagles row 3 : g | jessie vetter | 174 cm (5 ft 9 in) | 77 kg (170 lb) | december 19, 1985 | cottage grove, wisconsin | wisconsin badgers row 4 : d | kacey bellamy | 174 cm (5 ft 9 in) | 65 kg (143 lb) | april 22, 1987 | westfield, massachusetts | new hampshire wildcats row 5 : d | caitlin cahow | 163 cm (5 ft 4 in) | 71 kg (157 lb) | may 20, 1985 | new haven, connecticut | harvard crimson row 6 : d | lisa chesson | 169 cm (5 ft 7 in) | 69 kg (152 lb) | august 18, 1986 | plainfield, illinois | ohio state buckeyes row 7 : d | molly engstrom | 175 cm (5 ft 9 in) | 81 kg (179 lb) | march 1, 1983 | siren, wisconsin | wisconsin badgers row 8 : d | angela ruggiero - a | 175 cm (5 ft 9 in) | 87 kg (192 lb) | january 3, 1980 | los angeles, california | harvard crimson row 9 : d | kerry weiland | 163 cm (5 ft 4 in) | 64 kg (141 lb) | october 18, 1980 | palmer, alaska | wisconsin badgers row 10 : f | julie chu - a | 174 cm (5 ft 9 in) | 67 kg (148 lb) | march 13, 1982 | bridgeport, connecticut | harvard crimson row 11 : f | natalie darwitz - c | 160 cm (5 ft 3 in) | 62 kg (137 lb) | october 13, 1983 | eagan, minnesota | minnesota golden gophers row 12 : f | meghan duggan | 175 cm (5 ft 9 in) | 74 kg (163 lb) | september 3, 1987 | danvers, massachusetts | wisconsin badgers row 13 : f | hilary knight | 178 cm (5 ft 10 in) | 78 kg (172 lb) | july 12, 1989 | hanover, new hampshire | wisconsin badgers row 14 : f | jocelyne lamoureux | 168 cm (5 ft 6 in) | 70 kg (150 lb) | july 3, 1989 | grand forks, north dakota | north dakota fighting sioux row 15 : f | monique lamoureux | 168 cm (5 ft 6 in) | 71 kg (157 lb) | july 3, 1989 | grand forks, north dakota | north dakota fighting sioux row 16 : f | erika lawler | 152 cm (5 ft 0 in) | 59 kg (130 lb) | february 5, 1987 | fitchburg, massachusetts | wisconsin badgers row 17 : f | gisele marvin | 174 cm (5 ft 9 in) | 75 kg (165 lb) | march 7, 1987 | warroad, minnesota | minnesota golden gophers row 18 : f | jenny potter - a | 163 cm (5 ft 4 in) | 66 kg (146 lb) | january 12, 1979 | edina, minnesota | minnesota golden gophers row 19 : f | kelli stack | 165 cm (5 ft 5 in) | 59 kg (130 lb) | january 13, 1988 | brooklyn heights, ohio | boston eagles row 20 : f | karen thatcher | 174 cm (5 ft 9 in) | 74 kg (163 lb) | february 29, 1984 | blaine, washington | providence friars row 21 : f | jinelle zaugg-siergiej | 183 cm (6 ft 0 in) | 82 kg (181 lb) | march 27, 1986 | eagle river, wisconsin | wisconsin badgers | col : name row 1 : jinelle zaugg-siergiej | select name where 2009-10 team = 'wisconsin badgers' order by weight desc limit 1 <table_name> : table \begin{tabular}{llllllll}
\toprule
& position & name & height & weight & birthdate & birthplace & 2009-10 team \\
\midrule
0 & g & brianne mclaughlin & 174 cm (5 ft 9 in) & 59 kg (130 lb) & june 20, 1987 & sheffield, ohio & robert morris colonials \\
1 & g & molly schaus & 174 cm (5 ft 9 in) & 67 kg (148 lb) & july 29, 1988 & natick, massachusetts & boston eagles \\
2 & g & jessie vetter & 174 cm (5 ft 9 in) & 77 kg (170 lb) & december 19, 1985 & cottage grove, wisconsin & wisconsin badgers \\
3 & d & kacey bellamy & 174 cm (5 ft 9 in) & 65 kg (143 lb) & april 22, 1987 & westfield, massachusetts & new hampshire wildcats \\
4 & d & caitlin cahow & 163 cm (5 ft 4 in) & 71 kg (157 lb) & may 20, 1985 & new haven, connecticut & harvard crimson \\
5 & d & lisa chesson & 169 cm (5 ft 7 in) & 69 kg (152 lb) & august 18, 1986 & plainfield, illinois & ohio state buckeyes \\
6 & d & molly engstrom & 175 cm (5 ft 9 in) & 81 kg (179 lb) & march 1, 1983 & siren, wisconsin & wisconsin badgers \\
7 & d & angela ruggiero - a & 175 cm (5 ft 9 in) & 87 kg (192 lb) & january 3, 1980 & los angeles, california & harvard crimson \\
8 & d & kerry weiland & 163 cm (5 ft 4 in) & 64 kg (141 lb) & october 18, 1980 & palmer, alaska & wisconsin badgers \\
9 & f & julie chu - a & 174 cm (5 ft 9 in) & 67 kg (148 lb) & march 13, 1982 & bridgeport, connecticut & harvard crimson \\
10 & f & natalie darwitz - c & 160 cm (5 ft 3 in) & 62 kg (137 lb) & october 13, 1983 & eagan, minnesota & minnesota golden gophers \\
11 & f & meghan duggan & 175 cm (5 ft 9 in) & 74 kg (163 lb) & september 3, 1987 & danvers, massachusetts & wisconsin badgers \\
12 & f & hilary knight & 178 cm (5 ft 10 in) & 78 kg (172 lb) & july 12, 1989 & hanover, new hampshire & wisconsin badgers \\
13 & f & jocelyne lamoureux & 168 cm (5 ft 6 in) & 70 kg (150 lb) & july 3, 1989 & grand forks, north dakota & north dakota fighting sioux \\
14 & f & monique lamoureux & 168 cm (5 ft 6 in) & 71 kg (157 lb) & july 3, 1989 & grand forks, north dakota & north dakota fighting sioux \\
15 & f & erika lawler & 152 cm (5 ft 0 in) & 59 kg (130 lb) & february 5, 1987 & fitchburg, massachusetts & wisconsin badgers \\
16 & f & gisele marvin & 174 cm (5 ft 9 in) & 75 kg (165 lb) & march 7, 1987 & warroad, minnesota & minnesota golden gophers \\
17 & f & jenny potter - a & 163 cm (5 ft 4 in) & 66 kg (146 lb) & january 12, 1979 & edina, minnesota & minnesota golden gophers \\
18 & f & kelli stack & 165 cm (5 ft 5 in) & 59 kg (130 lb) & january 13, 1988 & brooklyn heights, ohio & boston eagles \\
19 & f & karen thatcher & 174 cm (5 ft 9 in) & 74 kg (163 lb) & february 29, 1984 & blaine, washington & providence friars \\
20 & f & jinelle zaugg-siergiej & 183 cm (6 ft 0 in) & 82 kg (181 lb) & march 27, 1986 & eagle river, wisconsin & wisconsin badgers \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & jinelle zaugg-siergiej \\
\bottomrule
\end{tabular}
| select name where 2009-10 team = 'wisconsin badgers' order by weight desc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
<th>name</th>
<th>height</th>
<th>weight</th>
<th>birthdate</th>
<th>birthplace</th>
<th>2009-10 team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>g</td>
<td>brianne mclaughlin</td>
<td>174 cm (5 ft 9 in)</td>
<td>59 kg (130 lb)</td>
<td>june 20, 1987</td>
<td>sheffield, ohio</td>
<td>robert morris colonials</td>
</tr>
<tr>
<th>1</th>
<td>g</td>
<td>molly schaus</td>
<td>174 cm (5 ft 9 in)</td>
<td>67 kg (148 lb)</td>
<td>july 29, 1988</td>
<td>natick, massachusetts</td>
<td>boston eagles</td>
</tr>
<tr>
<th>2</th>
<td>g</td>
<td>jessie vetter</td>
<td>174 cm (5 ft 9 in)</td>
<td>77 kg (170 lb)</td>
<td>december 19, 1985</td>
<td>cottage grove, wisconsin</td>
<td>wisconsin badgers</td>
</tr>
<tr>
<th>3</th>
<td>d</td>
<td>kacey bellamy</td>
<td>174 cm (5 ft 9 in)</td>
<td>65 kg (143 lb)</td>
<td>april 22, 1987</td>
<td>westfield, massachusetts</td>
<td>new hampshire wildcats</td>
</tr>
<tr>
<th>4</th>
<td>d</td>
<td>caitlin cahow</td>
<td>163 cm (5 ft 4 in)</td>
<td>71 kg (157 lb)</td>
<td>may 20, 1985</td>
<td>new haven, connecticut</td>
<td>harvard crimson</td>
</tr>
<tr>
<th>5</th>
<td>d</td>
<td>lisa chesson</td>
<td>169 cm (5 ft 7 in)</td>
<td>69 kg (152 lb)</td>
<td>august 18, 1986</td>
<td>plainfield, illinois</td>
<td>ohio state buckeyes</td>
</tr>
<tr>
<th>6</th>
<td>d</td>
<td>molly engstrom</td>
<td>175 cm (5 ft 9 in)</td>
<td>81 kg (179 lb)</td>
<td>march 1, 1983</td>
<td>siren, wisconsin</td>
<td>wisconsin badgers</td>
</tr>
<tr>
<th>7</th>
<td>d</td>
<td>angela ruggiero - a</td>
<td>175 cm (5 ft 9 in)</td>
<td>87 kg (192 lb)</td>
<td>january 3, 1980</td>
<td>los angeles, california</td>
<td>harvard crimson</td>
</tr>
<tr>
<th>8</th>
<td>d</td>
<td>kerry weiland</td>
<td>163 cm (5 ft 4 in)</td>
<td>64 kg (141 lb)</td>
<td>october 18, 1980</td>
<td>palmer, alaska</td>
<td>wisconsin badgers</td>
</tr>
<tr>
<th>9</th>
<td>f</td>
<td>julie chu - a</td>
<td>174 cm (5 ft 9 in)</td>
<td>67 kg (148 lb)</td>
<td>march 13, 1982</td>
<td>bridgeport, connecticut</td>
<td>harvard crimson</td>
</tr>
<tr>
<th>10</th>
<td>f</td>
<td>natalie darwitz - c</td>
<td>160 cm (5 ft 3 in)</td>
<td>62 kg (137 lb)</td>
<td>october 13, 1983</td>
<td>eagan, minnesota</td>
<td>minnesota golden gophers</td>
</tr>
<tr>
<th>11</th>
<td>f</td>
<td>meghan duggan</td>
<td>175 cm (5 ft 9 in)</td>
<td>74 kg (163 lb)</td>
<td>september 3, 1987</td>
<td>danvers, massachusetts</td>
<td>wisconsin badgers</td>
</tr>
<tr>
<th>12</th>
<td>f</td>
<td>hilary knight</td>
<td>178 cm (5 ft 10 in)</td>
<td>78 kg (172 lb)</td>
<td>july 12, 1989</td>
<td>hanover, new hampshire</td>
<td>wisconsin badgers</td>
</tr>
<tr>
<th>13</th>
<td>f</td>
<td>jocelyne lamoureux</td>
<td>168 cm (5 ft 6 in)</td>
<td>70 kg (150 lb)</td>
<td>july 3, 1989</td>
<td>grand forks, north dakota</td>
<td>north dakota fighting sioux</td>
</tr>
<tr>
<th>14</th>
<td>f</td>
<td>monique lamoureux</td>
<td>168 cm (5 ft 6 in)</td>
<td>71 kg (157 lb)</td>
<td>july 3, 1989</td>
<td>grand forks, north dakota</td>
<td>north dakota fighting sioux</td>
</tr>
<tr>
<th>15</th>
<td>f</td>
<td>erika lawler</td>
<td>152 cm (5 ft 0 in)</td>
<td>59 kg (130 lb)</td>
<td>february 5, 1987</td>
<td>fitchburg, massachusetts</td>
<td>wisconsin badgers</td>
</tr>
<tr>
<th>16</th>
<td>f</td>
<td>gisele marvin</td>
<td>174 cm (5 ft 9 in)</td>
<td>75 kg (165 lb)</td>
<td>march 7, 1987</td>
<td>warroad, minnesota</td>
<td>minnesota golden gophers</td>
</tr>
<tr>
<th>17</th>
<td>f</td>
<td>jenny potter - a</td>
<td>163 cm (5 ft 4 in)</td>
<td>66 kg (146 lb)</td>
<td>january 12, 1979</td>
<td>edina, minnesota</td>
<td>minnesota golden gophers</td>
</tr>
<tr>
<th>18</th>
<td>f</td>
<td>kelli stack</td>
<td>165 cm (5 ft 5 in)</td>
<td>59 kg (130 lb)</td>
<td>january 13, 1988</td>
<td>brooklyn heights, ohio</td>
<td>boston eagles</td>
</tr>
<tr>
<th>19</th>
<td>f</td>
<td>karen thatcher</td>
<td>174 cm (5 ft 9 in)</td>
<td>74 kg (163 lb)</td>
<td>february 29, 1984</td>
<td>blaine, washington</td>
<td>providence friars</td>
</tr>
<tr>
<th>20</th>
<td>f</td>
<td>jinelle zaugg-siergiej</td>
<td>183 cm (6 ft 0 in)</td>
<td>82 kg (181 lb)</td>
<td>march 27, 1986</td>
<td>eagle river, wisconsin</td>
<td>wisconsin badgers</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>jinelle zaugg-siergiej</td>
</tr>
</tbody>
</table> | select name where 2009-10 team = 'wisconsin badgers' order by weight desc limit 1 <table_name> : table | | position | name | height | weight | birthdate | birthplace | 2009-10 team |
|---:|:-----------|:-----------------------|:--------------------|:---------------|:------------------|:--------------------------|:----------------------------|
| 0 | g | brianne mclaughlin | 174 cm (5 ft 9 in) | 59 kg (130 lb) | june 20, 1987 | sheffield, ohio | robert morris colonials |
| 1 | g | molly schaus | 174 cm (5 ft 9 in) | 67 kg (148 lb) | july 29, 1988 | natick, massachusetts | boston eagles |
| 2 | g | jessie vetter | 174 cm (5 ft 9 in) | 77 kg (170 lb) | december 19, 1985 | cottage grove, wisconsin | wisconsin badgers |
| 3 | d | kacey bellamy | 174 cm (5 ft 9 in) | 65 kg (143 lb) | april 22, 1987 | westfield, massachusetts | new hampshire wildcats |
| 4 | d | caitlin cahow | 163 cm (5 ft 4 in) | 71 kg (157 lb) | may 20, 1985 | new haven, connecticut | harvard crimson |
| 5 | d | lisa chesson | 169 cm (5 ft 7 in) | 69 kg (152 lb) | august 18, 1986 | plainfield, illinois | ohio state buckeyes |
| 6 | d | molly engstrom | 175 cm (5 ft 9 in) | 81 kg (179 lb) | march 1, 1983 | siren, wisconsin | wisconsin badgers |
| 7 | d | angela ruggiero - a | 175 cm (5 ft 9 in) | 87 kg (192 lb) | january 3, 1980 | los angeles, california | harvard crimson |
| 8 | d | kerry weiland | 163 cm (5 ft 4 in) | 64 kg (141 lb) | october 18, 1980 | palmer, alaska | wisconsin badgers |
| 9 | f | julie chu - a | 174 cm (5 ft 9 in) | 67 kg (148 lb) | march 13, 1982 | bridgeport, connecticut | harvard crimson |
| 10 | f | natalie darwitz - c | 160 cm (5 ft 3 in) | 62 kg (137 lb) | october 13, 1983 | eagan, minnesota | minnesota golden gophers |
| 11 | f | meghan duggan | 175 cm (5 ft 9 in) | 74 kg (163 lb) | september 3, 1987 | danvers, massachusetts | wisconsin badgers |
| 12 | f | hilary knight | 178 cm (5 ft 10 in) | 78 kg (172 lb) | july 12, 1989 | hanover, new hampshire | wisconsin badgers |
| 13 | f | jocelyne lamoureux | 168 cm (5 ft 6 in) | 70 kg (150 lb) | july 3, 1989 | grand forks, north dakota | north dakota fighting sioux |
| 14 | f | monique lamoureux | 168 cm (5 ft 6 in) | 71 kg (157 lb) | july 3, 1989 | grand forks, north dakota | north dakota fighting sioux |
| 15 | f | erika lawler | 152 cm (5 ft 0 in) | 59 kg (130 lb) | february 5, 1987 | fitchburg, massachusetts | wisconsin badgers |
| 16 | f | gisele marvin | 174 cm (5 ft 9 in) | 75 kg (165 lb) | march 7, 1987 | warroad, minnesota | minnesota golden gophers |
| 17 | f | jenny potter - a | 163 cm (5 ft 4 in) | 66 kg (146 lb) | january 12, 1979 | edina, minnesota | minnesota golden gophers |
| 18 | f | kelli stack | 165 cm (5 ft 5 in) | 59 kg (130 lb) | january 13, 1988 | brooklyn heights, ohio | boston eagles |
| 19 | f | karen thatcher | 174 cm (5 ft 9 in) | 74 kg (163 lb) | february 29, 1984 | blaine, washington | providence friars |
| 20 | f | jinelle zaugg-siergiej | 183 cm (6 ft 0 in) | 82 kg (181 lb) | march 27, 1986 | eagle river, wisconsin | wisconsin badgers | | | | name |
|---:|:-----------------------|
| 0 | jinelle zaugg-siergiej | | [
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]
] |
select count ( * ) where location = 'cambridge, massachusetts' col : result | record | opponent | method | date | round | location row 1 : loss | 31-3-0 | j.h. isbell | ko | 1934-03-31 00:00:00 | 2 | cambridge, massachusetts row 2 : loss | 31-2-0 | "modest" bill smith | ko | 1934-02-27 00:00:00 | 2 | cambridge, massachusetts row 3 : win | 31-1-0 | frankie hagen | ko | 1934-02-24 00:00:00 | 1 | cambridge, massachusetts row 4 : win | 30-1-0 | harry gardner | ko | 1934-02-21 00:00:00 | 1 | cambridge, massachusetts row 5 : win | 29-1-0 | sid stoneman | ko | 1934-02-14 00:00:00 | 1 | cambridge, massachusetts row 6 : win | 28-1-0 | frankie hagan | pts | 1934-01-30 00:00:00 | 3 | cambridge, massachusetts row 7 : win | 27-1-0 | basil barnett | ko | 1934-01-24 00:00:00 | 2 | cambridge, massachusetts row 8 : win | 26-1-0 | george krause | ko | 1934-01-16 00:00:00 | 1 | cambridge, massachusetts row 9 : win | 25-1-0 | bob delmont | ko | 1934-01-07 00:00:00 | 1 | cambridge, massachusetts row 10 : loss | 24-1-0 | brad simmons | ko | 1934-01-01 00:00:00 | 1 | cambridge, massachusetts row 11 : win | 24-0-0 | herman zeinman | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 12 : win | 23-0-0 | william beltran | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 13 : win | 22-0-0 | lloyd blake | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 14 : win | 21-0-0 | lawrence "larry" o'neil | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 15 : win | 20-0-0 | igg rosenberg | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 16 : win | 19-0-0 | melvin kenyon | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 17 : win | 18-0-0 | gary keers | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts row 18 : win | 17-0-0 | samuel rodgway | ko | 1933-05-28 00:00:00 | 1 | cambridge, massachusetts row 19 : exch | 16-0-0 | "irish" tommy mitchell | ko | 1933-05-21 00:00:00 | 1 | cambridge, massachusetts row 20 : win | 15-0-0 | jim crawford | ko | 1933-05-14 00:00:00 | 1 | cambridge, massachusetts row 21 : win | 14-0-0 | max levine | ko | 1933-05-07 00:00:00 | 1 | cambridge, massachusetts row 22 : win | 13-0-0 | leo hart | ko | 1933-05-01 00:00:00 | 1 | cambridge, massachusetts row 23 : win | 12-0-0 | paul benjamin | pts | 1932-01-01 00:00:00 | 3 | evanston, illinois row 24 : win | 11-0-0 | fred chapman | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois row 25 : win | 10-0-0 | paul benjamin | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois row 26 : win | 9-0-0 | rod conley | ko | 1932-01-01 00:00:00 | 2 | evanston, illinois row 27 : win | 8-0-0 | paul gilmore | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 28 : win | 7-0-0 | jack lewis | ko | 1932-01-01 00:00:00 | 3 | chicago, illinois row 29 : exch | 6-0-0 | eddie mitchell | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 30 : win | 5-0-0 | ernest brant | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 31 : win | 4-0-0 | karl brenner-eggers | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 32 : win | 3-0-0 | norman martin | pts | 1932-01-01 00:00:00 | 3 | chicago, illinois row 33 : win | 2-0-0 | albert leikman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois row 34 : win | 1-0-0 | keith newman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois | col : count ( "*" ) row 1 : 22 | select count ( * ) where location = 'cambridge, massachusetts' <table_name> : table \begin{tabular}{llllllll}
\toprule
& result & record & opponent & method & date & round & location \\
\midrule
0 & loss & 31-3-0 & j.h. isbell & ko & 1934-03-31 00:00:00 & 2 & cambridge, massachusetts \\
1 & loss & 31-2-0 & "modest" bill smith & ko & 1934-02-27 00:00:00 & 2 & cambridge, massachusetts \\
2 & win & 31-1-0 & frankie hagen & ko & 1934-02-24 00:00:00 & 1 & cambridge, massachusetts \\
3 & win & 30-1-0 & harry gardner & ko & 1934-02-21 00:00:00 & 1 & cambridge, massachusetts \\
4 & win & 29-1-0 & sid stoneman & ko & 1934-02-14 00:00:00 & 1 & cambridge, massachusetts \\
5 & win & 28-1-0 & frankie hagan & pts & 1934-01-30 00:00:00 & 3 & cambridge, massachusetts \\
6 & win & 27-1-0 & basil barnett & ko & 1934-01-24 00:00:00 & 2 & cambridge, massachusetts \\
7 & win & 26-1-0 & george krause & ko & 1934-01-16 00:00:00 & 1 & cambridge, massachusetts \\
8 & win & 25-1-0 & bob delmont & ko & 1934-01-07 00:00:00 & 1 & cambridge, massachusetts \\
9 & loss & 24-1-0 & brad simmons & ko & 1934-01-01 00:00:00 & 1 & cambridge, massachusetts \\
10 & win & 24-0-0 & herman zeinman & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
11 & win & 23-0-0 & william beltran & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
12 & win & 22-0-0 & lloyd blake & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
13 & win & 21-0-0 & lawrence "larry" o'neil & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
14 & win & 20-0-0 & igg rosenberg & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
15 & win & 19-0-0 & melvin kenyon & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
16 & win & 18-0-0 & gary keers & ko & 1933-01-01 00:00:00 & 1 & cambridge, massachusetts \\
17 & win & 17-0-0 & samuel rodgway & ko & 1933-05-28 00:00:00 & 1 & cambridge, massachusetts \\
18 & exch & 16-0-0 & "irish" tommy mitchell & ko & 1933-05-21 00:00:00 & 1 & cambridge, massachusetts \\
19 & win & 15-0-0 & jim crawford & ko & 1933-05-14 00:00:00 & 1 & cambridge, massachusetts \\
20 & win & 14-0-0 & max levine & ko & 1933-05-07 00:00:00 & 1 & cambridge, massachusetts \\
21 & win & 13-0-0 & leo hart & ko & 1933-05-01 00:00:00 & 1 & cambridge, massachusetts \\
22 & win & 12-0-0 & paul benjamin & pts & 1932-01-01 00:00:00 & 3 & evanston, illinois \\
23 & win & 11-0-0 & fred chapman & ko & 1932-01-01 00:00:00 & 3 & evanston, illinois \\
24 & win & 10-0-0 & paul benjamin & ko & 1932-01-01 00:00:00 & 3 & evanston, illinois \\
25 & win & 9-0-0 & rod conley & ko & 1932-01-01 00:00:00 & 2 & evanston, illinois \\
26 & win & 8-0-0 & paul gilmore & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
27 & win & 7-0-0 & jack lewis & ko & 1932-01-01 00:00:00 & 3 & chicago, illinois \\
28 & exch & 6-0-0 & eddie mitchell & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
29 & win & 5-0-0 & ernest brant & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
30 & win & 4-0-0 & karl brenner-eggers & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
31 & win & 3-0-0 & norman martin & pts & 1932-01-01 00:00:00 & 3 & chicago, illinois \\
32 & win & 2-0-0 & albert leikman & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
33 & win & 1-0-0 & keith newman & ko & 1932-01-01 00:00:00 & 1 & chicago, illinois \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 22 \\
\bottomrule
\end{tabular}
| select count ( * ) where location = 'cambridge, massachusetts' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>result</th>
<th>record</th>
<th>opponent</th>
<th>method</th>
<th>date</th>
<th>round</th>
<th>location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>loss</td>
<td>31-3-0</td>
<td>j.h. isbell</td>
<td>ko</td>
<td>1934-03-31 00:00:00</td>
<td>2</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>1</th>
<td>loss</td>
<td>31-2-0</td>
<td>"modest" bill smith</td>
<td>ko</td>
<td>1934-02-27 00:00:00</td>
<td>2</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>2</th>
<td>win</td>
<td>31-1-0</td>
<td>frankie hagen</td>
<td>ko</td>
<td>1934-02-24 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>3</th>
<td>win</td>
<td>30-1-0</td>
<td>harry gardner</td>
<td>ko</td>
<td>1934-02-21 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>4</th>
<td>win</td>
<td>29-1-0</td>
<td>sid stoneman</td>
<td>ko</td>
<td>1934-02-14 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>5</th>
<td>win</td>
<td>28-1-0</td>
<td>frankie hagan</td>
<td>pts</td>
<td>1934-01-30 00:00:00</td>
<td>3</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>6</th>
<td>win</td>
<td>27-1-0</td>
<td>basil barnett</td>
<td>ko</td>
<td>1934-01-24 00:00:00</td>
<td>2</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>7</th>
<td>win</td>
<td>26-1-0</td>
<td>george krause</td>
<td>ko</td>
<td>1934-01-16 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>8</th>
<td>win</td>
<td>25-1-0</td>
<td>bob delmont</td>
<td>ko</td>
<td>1934-01-07 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>9</th>
<td>loss</td>
<td>24-1-0</td>
<td>brad simmons</td>
<td>ko</td>
<td>1934-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>10</th>
<td>win</td>
<td>24-0-0</td>
<td>herman zeinman</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>11</th>
<td>win</td>
<td>23-0-0</td>
<td>william beltran</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>12</th>
<td>win</td>
<td>22-0-0</td>
<td>lloyd blake</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>13</th>
<td>win</td>
<td>21-0-0</td>
<td>lawrence "larry" o'neil</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>14</th>
<td>win</td>
<td>20-0-0</td>
<td>igg rosenberg</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>15</th>
<td>win</td>
<td>19-0-0</td>
<td>melvin kenyon</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>16</th>
<td>win</td>
<td>18-0-0</td>
<td>gary keers</td>
<td>ko</td>
<td>1933-01-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>17</th>
<td>win</td>
<td>17-0-0</td>
<td>samuel rodgway</td>
<td>ko</td>
<td>1933-05-28 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>18</th>
<td>exch</td>
<td>16-0-0</td>
<td>"irish" tommy mitchell</td>
<td>ko</td>
<td>1933-05-21 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>19</th>
<td>win</td>
<td>15-0-0</td>
<td>jim crawford</td>
<td>ko</td>
<td>1933-05-14 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>20</th>
<td>win</td>
<td>14-0-0</td>
<td>max levine</td>
<td>ko</td>
<td>1933-05-07 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>21</th>
<td>win</td>
<td>13-0-0</td>
<td>leo hart</td>
<td>ko</td>
<td>1933-05-01 00:00:00</td>
<td>1</td>
<td>cambridge, massachusetts</td>
</tr>
<tr>
<th>22</th>
<td>win</td>
<td>12-0-0</td>
<td>paul benjamin</td>
<td>pts</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>23</th>
<td>win</td>
<td>11-0-0</td>
<td>fred chapman</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>24</th>
<td>win</td>
<td>10-0-0</td>
<td>paul benjamin</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>25</th>
<td>win</td>
<td>9-0-0</td>
<td>rod conley</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>2</td>
<td>evanston, illinois</td>
</tr>
<tr>
<th>26</th>
<td>win</td>
<td>8-0-0</td>
<td>paul gilmore</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>27</th>
<td>win</td>
<td>7-0-0</td>
<td>jack lewis</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>28</th>
<td>exch</td>
<td>6-0-0</td>
<td>eddie mitchell</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>29</th>
<td>win</td>
<td>5-0-0</td>
<td>ernest brant</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>30</th>
<td>win</td>
<td>4-0-0</td>
<td>karl brenner-eggers</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>31</th>
<td>win</td>
<td>3-0-0</td>
<td>norman martin</td>
<td>pts</td>
<td>1932-01-01 00:00:00</td>
<td>3</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>32</th>
<td>win</td>
<td>2-0-0</td>
<td>albert leikman</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
<tr>
<th>33</th>
<td>win</td>
<td>1-0-0</td>
<td>keith newman</td>
<td>ko</td>
<td>1932-01-01 00:00:00</td>
<td>1</td>
<td>chicago, illinois</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>22</td>
</tr>
</tbody>
</table> | select count ( * ) where location = 'cambridge, massachusetts' <table_name> : table | | result | record | opponent | method | date | round | location |
|---:|:---------|:---------|:------------------------|:---------|:--------------------|--------:|:-------------------------|
| 0 | loss | 31-3-0 | j.h. isbell | ko | 1934-03-31 00:00:00 | 2 | cambridge, massachusetts |
| 1 | loss | 31-2-0 | "modest" bill smith | ko | 1934-02-27 00:00:00 | 2 | cambridge, massachusetts |
| 2 | win | 31-1-0 | frankie hagen | ko | 1934-02-24 00:00:00 | 1 | cambridge, massachusetts |
| 3 | win | 30-1-0 | harry gardner | ko | 1934-02-21 00:00:00 | 1 | cambridge, massachusetts |
| 4 | win | 29-1-0 | sid stoneman | ko | 1934-02-14 00:00:00 | 1 | cambridge, massachusetts |
| 5 | win | 28-1-0 | frankie hagan | pts | 1934-01-30 00:00:00 | 3 | cambridge, massachusetts |
| 6 | win | 27-1-0 | basil barnett | ko | 1934-01-24 00:00:00 | 2 | cambridge, massachusetts |
| 7 | win | 26-1-0 | george krause | ko | 1934-01-16 00:00:00 | 1 | cambridge, massachusetts |
| 8 | win | 25-1-0 | bob delmont | ko | 1934-01-07 00:00:00 | 1 | cambridge, massachusetts |
| 9 | loss | 24-1-0 | brad simmons | ko | 1934-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 10 | win | 24-0-0 | herman zeinman | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 11 | win | 23-0-0 | william beltran | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 12 | win | 22-0-0 | lloyd blake | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 13 | win | 21-0-0 | lawrence "larry" o'neil | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 14 | win | 20-0-0 | igg rosenberg | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 15 | win | 19-0-0 | melvin kenyon | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 16 | win | 18-0-0 | gary keers | ko | 1933-01-01 00:00:00 | 1 | cambridge, massachusetts |
| 17 | win | 17-0-0 | samuel rodgway | ko | 1933-05-28 00:00:00 | 1 | cambridge, massachusetts |
| 18 | exch | 16-0-0 | "irish" tommy mitchell | ko | 1933-05-21 00:00:00 | 1 | cambridge, massachusetts |
| 19 | win | 15-0-0 | jim crawford | ko | 1933-05-14 00:00:00 | 1 | cambridge, massachusetts |
| 20 | win | 14-0-0 | max levine | ko | 1933-05-07 00:00:00 | 1 | cambridge, massachusetts |
| 21 | win | 13-0-0 | leo hart | ko | 1933-05-01 00:00:00 | 1 | cambridge, massachusetts |
| 22 | win | 12-0-0 | paul benjamin | pts | 1932-01-01 00:00:00 | 3 | evanston, illinois |
| 23 | win | 11-0-0 | fred chapman | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois |
| 24 | win | 10-0-0 | paul benjamin | ko | 1932-01-01 00:00:00 | 3 | evanston, illinois |
| 25 | win | 9-0-0 | rod conley | ko | 1932-01-01 00:00:00 | 2 | evanston, illinois |
| 26 | win | 8-0-0 | paul gilmore | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 27 | win | 7-0-0 | jack lewis | ko | 1932-01-01 00:00:00 | 3 | chicago, illinois |
| 28 | exch | 6-0-0 | eddie mitchell | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 29 | win | 5-0-0 | ernest brant | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 30 | win | 4-0-0 | karl brenner-eggers | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 31 | win | 3-0-0 | norman martin | pts | 1932-01-01 00:00:00 | 3 | chicago, illinois |
| 32 | win | 2-0-0 | albert leikman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois |
| 33 | win | 1-0-0 | keith newman | ko | 1932-01-01 00:00:00 | 1 | chicago, illinois | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 22 | | [
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]
] | [
[
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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1,
1,
1,
1,
1,
1,
1,
1,
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select rider where manufacturer = 'aprilia' order by grid desc limit 1 col : pos | rider | manufacturer | laps | time/retired | grid | points row 1 : 1 | manuel poggiali | gilera | 25 | 41:18.211 | 1 | 25 row 2 : 2 | dani pedrosa | honda | 25 | 0.019 | 4 | 20 row 3 : 3 | steve jenkner | aprilia | 25 | 9.888 | 3 | 16 row 4 : 4 | lucio cecchinello | aprilia | 25 | 15.397 | 5 | 13 row 5 : 5 | simone sanna | aprilia | 25 | 15.452 | 8 | 11 row 6 : 6 | joan olive | honda | 25 | 15.486 | 20 | 10 row 7 : 7 | stefano bianco | aprilia | 25 | 15.549 | 11 | 9 row 8 : 8 | pablo nieto | aprilia | 25 | 16.218 | 2 | 8 row 9 : 9 | mika kallio | honda | 25 | 22.762 | 10 | 7 row 10 : 10 | mirko giansanti | honda | 25 | 22.839 | 16 | 6 row 11 : 11 | arnaud vincent | aprilia | 25 | 23.067 | 23 | 5 row 12 : 12 | andrea ballerini | honda | 25 | 23.134 | 18 | 4 row 13 : 13 | stefano perugini | italjet | 25 | 43.345 | 17 | 3 row 14 : 14 | jorge lorenzo | derbi | 25 | 43.973 | 7 | 2 row 15 : 15 | masao azuma | honda | 25 | 47.189 | 13 | 1 row 16 : 16 | jakub smrz | honda | 25 | 47.333 | 24 | none row 17 : 17 | gianluigi scalvini | aprilia | 25 | 52 | 22 | none row 18 : 18 | hector barbera | aprilia | 25 | +1:11.358 | 27 | none row 19 : 19 | mattia angeloni | gilera | 25 | +1:11.488 | 29 | none row 20 : 20 | alex baldolini | aprilia | 25 | +1:21.603 | 32 | none row 21 : 21 | jaroslav hules | aprilia | 25 | +1:21.681 | 15 | none row 22 : 22 | julian simon | honda | 25 | +1:31.723 | 26 | none row 23 : 23 | imre toth | honda | 25 | +1:31.794 | 31 | none row 24 : 24 | leon camier | italjet | 24 | +1 lap | 33 | none row 25 : ret | chaz davies | aprilia | 18 | retirement | 21 | none row 26 : ret | michel fabrizio | gilera | 14 | accident | 19 | none row 27 : ret | youichi ui | derbi | 13 | accident | 6 | none row 28 : ret | alex de angelis | aprilia | 13 | accident | 12 | none row 29 : ret | angel rodriguez | aprilia | 4 | retirement | 25 | none row 30 : ret | gino borsoi | aprilia | 0 | accident | 9 | none row 31 : ret | andrea dovizioso | honda | 0 | accident | 14 | none row 32 : ret | alessandro brannetti | honda | 0 | accident | 30 | none row 33 : ret | alvaro bautista | aprilia | 0 | accident | 28 | none row 34 : dnq | javier machado | honda | none | none | none | none | col : rider row 1 : gino borsoi | select rider where manufacturer = 'aprilia' order by grid desc limit 1 <table_name> : table \begin{tabular}{llllllll}
\toprule
& pos & rider & manufacturer & laps & time/retired & grid & points \\
\midrule
0 & 1 & manuel poggiali & gilera & 25 & 41:18.211 & 1 & 25 \\
1 & 2 & dani pedrosa & honda & 25 & 0.019 & 4 & 20 \\
2 & 3 & steve jenkner & aprilia & 25 & 9.888 & 3 & 16 \\
3 & 4 & lucio cecchinello & aprilia & 25 & 15.397 & 5 & 13 \\
4 & 5 & simone sanna & aprilia & 25 & 15.452 & 8 & 11 \\
5 & 6 & joan olive & honda & 25 & 15.486 & 20 & 10 \\
6 & 7 & stefano bianco & aprilia & 25 & 15.549 & 11 & 9 \\
7 & 8 & pablo nieto & aprilia & 25 & 16.218 & 2 & 8 \\
8 & 9 & mika kallio & honda & 25 & 22.762 & 10 & 7 \\
9 & 10 & mirko giansanti & honda & 25 & 22.839 & 16 & 6 \\
10 & 11 & arnaud vincent & aprilia & 25 & 23.067 & 23 & 5 \\
11 & 12 & andrea ballerini & honda & 25 & 23.134 & 18 & 4 \\
12 & 13 & stefano perugini & italjet & 25 & 43.345 & 17 & 3 \\
13 & 14 & jorge lorenzo & derbi & 25 & 43.973 & 7 & 2 \\
14 & 15 & masao azuma & honda & 25 & 47.189 & 13 & 1 \\
15 & 16 & jakub smrz & honda & 25 & 47.333 & 24 & none \\
16 & 17 & gianluigi scalvini & aprilia & 25 & 52 & 22 & none \\
17 & 18 & hector barbera & aprilia & 25 & +1:11.358 & 27 & none \\
18 & 19 & mattia angeloni & gilera & 25 & +1:11.488 & 29 & none \\
19 & 20 & alex baldolini & aprilia & 25 & +1:21.603 & 32 & none \\
20 & 21 & jaroslav hules & aprilia & 25 & +1:21.681 & 15 & none \\
21 & 22 & julian simon & honda & 25 & +1:31.723 & 26 & none \\
22 & 23 & imre toth & honda & 25 & +1:31.794 & 31 & none \\
23 & 24 & leon camier & italjet & 24 & +1 lap & 33 & none \\
24 & ret & chaz davies & aprilia & 18 & retirement & 21 & none \\
25 & ret & michel fabrizio & gilera & 14 & accident & 19 & none \\
26 & ret & youichi ui & derbi & 13 & accident & 6 & none \\
27 & ret & alex de angelis & aprilia & 13 & accident & 12 & none \\
28 & ret & angel rodriguez & aprilia & 4 & retirement & 25 & none \\
29 & ret & gino borsoi & aprilia & 0 & accident & 9 & none \\
30 & ret & andrea dovizioso & honda & 0 & accident & 14 & none \\
31 & ret & alessandro brannetti & honda & 0 & accident & 30 & none \\
32 & ret & alvaro bautista & aprilia & 0 & accident & 28 & none \\
33 & dnq & javier machado & honda & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& rider \\
\midrule
0 & gino borsoi \\
\bottomrule
\end{tabular}
| select rider where manufacturer = 'aprilia' order by grid desc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>rider</th>
<th>manufacturer</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>manuel poggiali</td>
<td>gilera</td>
<td>25</td>
<td>41:18.211</td>
<td>1</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>dani pedrosa</td>
<td>honda</td>
<td>25</td>
<td>0.019</td>
<td>4</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>steve jenkner</td>
<td>aprilia</td>
<td>25</td>
<td>9.888</td>
<td>3</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>lucio cecchinello</td>
<td>aprilia</td>
<td>25</td>
<td>15.397</td>
<td>5</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>simone sanna</td>
<td>aprilia</td>
<td>25</td>
<td>15.452</td>
<td>8</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>joan olive</td>
<td>honda</td>
<td>25</td>
<td>15.486</td>
<td>20</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>stefano bianco</td>
<td>aprilia</td>
<td>25</td>
<td>15.549</td>
<td>11</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>pablo nieto</td>
<td>aprilia</td>
<td>25</td>
<td>16.218</td>
<td>2</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>mika kallio</td>
<td>honda</td>
<td>25</td>
<td>22.762</td>
<td>10</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>mirko giansanti</td>
<td>honda</td>
<td>25</td>
<td>22.839</td>
<td>16</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>arnaud vincent</td>
<td>aprilia</td>
<td>25</td>
<td>23.067</td>
<td>23</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>andrea ballerini</td>
<td>honda</td>
<td>25</td>
<td>23.134</td>
<td>18</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>stefano perugini</td>
<td>italjet</td>
<td>25</td>
<td>43.345</td>
<td>17</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>jorge lorenzo</td>
<td>derbi</td>
<td>25</td>
<td>43.973</td>
<td>7</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>masao azuma</td>
<td>honda</td>
<td>25</td>
<td>47.189</td>
<td>13</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>jakub smrz</td>
<td>honda</td>
<td>25</td>
<td>47.333</td>
<td>24</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>gianluigi scalvini</td>
<td>aprilia</td>
<td>25</td>
<td>52</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>hector barbera</td>
<td>aprilia</td>
<td>25</td>
<td>+1:11.358</td>
<td>27</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>mattia angeloni</td>
<td>gilera</td>
<td>25</td>
<td>+1:11.488</td>
<td>29</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>alex baldolini</td>
<td>aprilia</td>
<td>25</td>
<td>+1:21.603</td>
<td>32</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>jaroslav hules</td>
<td>aprilia</td>
<td>25</td>
<td>+1:21.681</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>julian simon</td>
<td>honda</td>
<td>25</td>
<td>+1:31.723</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>imre toth</td>
<td>honda</td>
<td>25</td>
<td>+1:31.794</td>
<td>31</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>leon camier</td>
<td>italjet</td>
<td>24</td>
<td>+1 lap</td>
<td>33</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>chaz davies</td>
<td>aprilia</td>
<td>18</td>
<td>retirement</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>michel fabrizio</td>
<td>gilera</td>
<td>14</td>
<td>accident</td>
<td>19</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>ret</td>
<td>youichi ui</td>
<td>derbi</td>
<td>13</td>
<td>accident</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>ret</td>
<td>alex de angelis</td>
<td>aprilia</td>
<td>13</td>
<td>accident</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>ret</td>
<td>angel rodriguez</td>
<td>aprilia</td>
<td>4</td>
<td>retirement</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>ret</td>
<td>gino borsoi</td>
<td>aprilia</td>
<td>0</td>
<td>accident</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>ret</td>
<td>andrea dovizioso</td>
<td>honda</td>
<td>0</td>
<td>accident</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>ret</td>
<td>alessandro brannetti</td>
<td>honda</td>
<td>0</td>
<td>accident</td>
<td>30</td>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>ret</td>
<td>alvaro bautista</td>
<td>aprilia</td>
<td>0</td>
<td>accident</td>
<td>28</td>
<td>none</td>
</tr>
<tr>
<th>33</th>
<td>dnq</td>
<td>javier machado</td>
<td>honda</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rider</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>gino borsoi</td>
</tr>
</tbody>
</table> | select rider where manufacturer = 'aprilia' order by grid desc limit 1 <table_name> : table | | pos | rider | manufacturer | laps | time/retired | grid | points |
|---:|:------|:---------------------|:---------------|:-------|:---------------|:-------|:---------|
| 0 | 1 | manuel poggiali | gilera | 25 | 41:18.211 | 1 | 25 |
| 1 | 2 | dani pedrosa | honda | 25 | 0.019 | 4 | 20 |
| 2 | 3 | steve jenkner | aprilia | 25 | 9.888 | 3 | 16 |
| 3 | 4 | lucio cecchinello | aprilia | 25 | 15.397 | 5 | 13 |
| 4 | 5 | simone sanna | aprilia | 25 | 15.452 | 8 | 11 |
| 5 | 6 | joan olive | honda | 25 | 15.486 | 20 | 10 |
| 6 | 7 | stefano bianco | aprilia | 25 | 15.549 | 11 | 9 |
| 7 | 8 | pablo nieto | aprilia | 25 | 16.218 | 2 | 8 |
| 8 | 9 | mika kallio | honda | 25 | 22.762 | 10 | 7 |
| 9 | 10 | mirko giansanti | honda | 25 | 22.839 | 16 | 6 |
| 10 | 11 | arnaud vincent | aprilia | 25 | 23.067 | 23 | 5 |
| 11 | 12 | andrea ballerini | honda | 25 | 23.134 | 18 | 4 |
| 12 | 13 | stefano perugini | italjet | 25 | 43.345 | 17 | 3 |
| 13 | 14 | jorge lorenzo | derbi | 25 | 43.973 | 7 | 2 |
| 14 | 15 | masao azuma | honda | 25 | 47.189 | 13 | 1 |
| 15 | 16 | jakub smrz | honda | 25 | 47.333 | 24 | none |
| 16 | 17 | gianluigi scalvini | aprilia | 25 | 52 | 22 | none |
| 17 | 18 | hector barbera | aprilia | 25 | +1:11.358 | 27 | none |
| 18 | 19 | mattia angeloni | gilera | 25 | +1:11.488 | 29 | none |
| 19 | 20 | alex baldolini | aprilia | 25 | +1:21.603 | 32 | none |
| 20 | 21 | jaroslav hules | aprilia | 25 | +1:21.681 | 15 | none |
| 21 | 22 | julian simon | honda | 25 | +1:31.723 | 26 | none |
| 22 | 23 | imre toth | honda | 25 | +1:31.794 | 31 | none |
| 23 | 24 | leon camier | italjet | 24 | +1 lap | 33 | none |
| 24 | ret | chaz davies | aprilia | 18 | retirement | 21 | none |
| 25 | ret | michel fabrizio | gilera | 14 | accident | 19 | none |
| 26 | ret | youichi ui | derbi | 13 | accident | 6 | none |
| 27 | ret | alex de angelis | aprilia | 13 | accident | 12 | none |
| 28 | ret | angel rodriguez | aprilia | 4 | retirement | 25 | none |
| 29 | ret | gino borsoi | aprilia | 0 | accident | 9 | none |
| 30 | ret | andrea dovizioso | honda | 0 | accident | 14 | none |
| 31 | ret | alessandro brannetti | honda | 0 | accident | 30 | none |
| 32 | ret | alvaro bautista | aprilia | 0 | accident | 28 | none |
| 33 | dnq | javier machado | honda | none | none | none | none | | | | rider |
|---:|:------------|
| 0 | gino borsoi | | [
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select count ( red vs. blue ) where weight > 450 col : name | red vs. blue | couples team | status | weight | total votes row 1 : valerica marin 47, bucharest | none | none | eliminated week 1 | 142 kg | 0 row 2 : tatiana musat 25, bucharest | none | none | eliminated week 1 | 150 kg | 0 row 3 : gige state 47, bucharest | none | none | eliminated week 1 | 200 kg | 0 row 4 : alex ionescu returned week 5 | none | none | eliminated week 1 | 196 kg | 0 row 5 : catalin chiriac 23, bucharest | blue team | none | 1st voted out week 1 | 146, 4 kg | 6 row 6 : dana mocanu 34, ploiesti | red team | none | 2nd voted out week 2 | 111, 5 kg | 6 row 7 : daniela gheorghe 21, pitesti | red team | none | 3rd voted out week 3 | 112, 8 kg | 5 row 8 : alexandra patrascu 37, bucharest | red team | none | eliminated week 4 | 118, 4 kg | 0 row 9 : mihai florescu 35, bucharest | red team | none | 4th voted out week 4 | 175, 8 kg | 0 row 10 : alexandru briscu 26, bacau | blue team | gray team | 5th voted out week 5 | 158, 1 kg | 0 row 11 : daniel sulugiu 34, bucharest | blue team | yellow team | 5th voted out week 6 | 158, 1 kg | 0 row 12 : irina gur 39, bucharest | blue team | lightgreen team | 6th voted out week7 | 129,4 kg | 1 row 13 : dragos holeac 30, bucharest | blue team | lightgreen team | 6th voted out week7 | 129,4 kg | 1 | col : count ( "red vs. blue" ) row 1 : 0 | select count ( red vs. blue ) where weight > 450 <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & red vs. blue & couples team & status & weight & total votes \\
\midrule
0 & valerica marin 47, bucharest & none & none & eliminated week 1 & 142 kg & 0 \\
1 & tatiana musat 25, bucharest & none & none & eliminated week 1 & 150 kg & 0 \\
2 & gige state 47, bucharest & none & none & eliminated week 1 & 200 kg & 0 \\
3 & alex ionescu returned week 5 & none & none & eliminated week 1 & 196 kg & 0 \\
4 & catalin chiriac 23, bucharest & blue team & none & 1st voted out week 1 & 146, 4 kg & 6 \\
5 & dana mocanu 34, ploiesti & red team & none & 2nd voted out week 2 & 111, 5 kg & 6 \\
6 & daniela gheorghe 21, pitesti & red team & none & 3rd voted out week 3 & 112, 8 kg & 5 \\
7 & alexandra patrascu 37, bucharest & red team & none & eliminated week 4 & 118, 4 kg & 0 \\
8 & mihai florescu 35, bucharest & red team & none & 4th voted out week 4 & 175, 8 kg & 0 \\
9 & alexandru briscu 26, bacau & blue team & gray team & 5th voted out week 5 & 158, 1 kg & 0 \\
10 & daniel sulugiu 34, bucharest & blue team & yellow team & 5th voted out week 6 & 158, 1 kg & 0 \\
11 & irina gur 39, bucharest & blue team & lightgreen team & 6th voted out week7 & 129,4 kg & 1 \\
12 & dragos holeac 30, bucharest & blue team & lightgreen team & 6th voted out week7 & 129,4 kg & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "red vs. blue" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( red vs. blue ) where weight > 450 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>red vs. blue</th>
<th>couples team</th>
<th>status</th>
<th>weight</th>
<th>total votes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>valerica marin 47, bucharest</td>
<td>none</td>
<td>none</td>
<td>eliminated week 1</td>
<td>142 kg</td>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>tatiana musat 25, bucharest</td>
<td>none</td>
<td>none</td>
<td>eliminated week 1</td>
<td>150 kg</td>
<td>0</td>
</tr>
<tr>
<th>2</th>
<td>gige state 47, bucharest</td>
<td>none</td>
<td>none</td>
<td>eliminated week 1</td>
<td>200 kg</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>alex ionescu returned week 5</td>
<td>none</td>
<td>none</td>
<td>eliminated week 1</td>
<td>196 kg</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>catalin chiriac 23, bucharest</td>
<td>blue team</td>
<td>none</td>
<td>1st voted out week 1</td>
<td>146, 4 kg</td>
<td>6</td>
</tr>
<tr>
<th>5</th>
<td>dana mocanu 34, ploiesti</td>
<td>red team</td>
<td>none</td>
<td>2nd voted out week 2</td>
<td>111, 5 kg</td>
<td>6</td>
</tr>
<tr>
<th>6</th>
<td>daniela gheorghe 21, pitesti</td>
<td>red team</td>
<td>none</td>
<td>3rd voted out week 3</td>
<td>112, 8 kg</td>
<td>5</td>
</tr>
<tr>
<th>7</th>
<td>alexandra patrascu 37, bucharest</td>
<td>red team</td>
<td>none</td>
<td>eliminated week 4</td>
<td>118, 4 kg</td>
<td>0</td>
</tr>
<tr>
<th>8</th>
<td>mihai florescu 35, bucharest</td>
<td>red team</td>
<td>none</td>
<td>4th voted out week 4</td>
<td>175, 8 kg</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>alexandru briscu 26, bacau</td>
<td>blue team</td>
<td>gray team</td>
<td>5th voted out week 5</td>
<td>158, 1 kg</td>
<td>0</td>
</tr>
<tr>
<th>10</th>
<td>daniel sulugiu 34, bucharest</td>
<td>blue team</td>
<td>yellow team</td>
<td>5th voted out week 6</td>
<td>158, 1 kg</td>
<td>0</td>
</tr>
<tr>
<th>11</th>
<td>irina gur 39, bucharest</td>
<td>blue team</td>
<td>lightgreen team</td>
<td>6th voted out week7</td>
<td>129,4 kg</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>dragos holeac 30, bucharest</td>
<td>blue team</td>
<td>lightgreen team</td>
<td>6th voted out week7</td>
<td>129,4 kg</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "red vs. blue" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( red vs. blue ) where weight > 450 <table_name> : table | | name | red vs. blue | couples team | status | weight | total votes |
|---:|:---------------------------------|:---------------|:----------------|:---------------------|:----------|--------------:|
| 0 | valerica marin 47, bucharest | none | none | eliminated week 1 | 142 kg | 0 |
| 1 | tatiana musat 25, bucharest | none | none | eliminated week 1 | 150 kg | 0 |
| 2 | gige state 47, bucharest | none | none | eliminated week 1 | 200 kg | 0 |
| 3 | alex ionescu returned week 5 | none | none | eliminated week 1 | 196 kg | 0 |
| 4 | catalin chiriac 23, bucharest | blue team | none | 1st voted out week 1 | 146, 4 kg | 6 |
| 5 | dana mocanu 34, ploiesti | red team | none | 2nd voted out week 2 | 111, 5 kg | 6 |
| 6 | daniela gheorghe 21, pitesti | red team | none | 3rd voted out week 3 | 112, 8 kg | 5 |
| 7 | alexandra patrascu 37, bucharest | red team | none | eliminated week 4 | 118, 4 kg | 0 |
| 8 | mihai florescu 35, bucharest | red team | none | 4th voted out week 4 | 175, 8 kg | 0 |
| 9 | alexandru briscu 26, bacau | blue team | gray team | 5th voted out week 5 | 158, 1 kg | 0 |
| 10 | daniel sulugiu 34, bucharest | blue team | yellow team | 5th voted out week 6 | 158, 1 kg | 0 |
| 11 | irina gur 39, bucharest | blue team | lightgreen team | 6th voted out week7 | 129,4 kg | 1 |
| 12 | dragos holeac 30, bucharest | blue team | lightgreen team | 6th voted out week7 | 129,4 kg | 1 | | | | count ( "red vs. blue" ) |
|---:|---------------------------:|
| 0 | 0 | | [
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select nation - nation where nation = 'south korea (kor)' col : rank | nation | gold | silver | bronze | total row 1 : 1 | china (chn) | 14 | 14 | 13 | 41 row 2 : 2 | india (ind) | 7 | 6 | 4 | 17 row 3 : 3 | saudi arabia (ksa) | 7 | 1 | 0 | 8 row 4 : 4 | kazakhstan (kaz) | 3 | 4 | 5 | 12 row 5 : 5 | south korea (kor) | 3 | 2 | 1 | 6 row 6 : 6 | japan (jpn) | 2 | 13 | 8 | 23 row 7 : 7 | bahrain (brn) | 2 | 1 | 1 | 4 row 8 : 8 | sri lanka (sri) | 2 | 0 | 2 | 4 row 9 : 9 | qatar (qat) | 1 | 4 | 3 | 8 row 10 : 10 | thailand (tha) | 1 | 1 | 2 | 4 row 11 : 11 | kyrgyzstan (kgz) | 1 | 1 | 0 | 2 row 12 : 12 | kuwait (kuw) | 1 | 0 | 0 | 1 row 13 : 12 | north korea (prk) | 1 | 0 | 0 | 1 row 14 : 14 | uzbekistan (uzb) | 0 | 1 | 3 | 4 row 15 : 15 | iran (iri) | 0 | 1 | 0 | 1 row 16 : total | total | 45 | 49 | 42 | 136 | col : "nation - nation" row 1 : nation - nation | select nation - nation where nation = 'south korea (kor)' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & china (chn) & 14 & 14 & 13 & 41 \\
1 & 2 & india (ind) & 7 & 6 & 4 & 17 \\
2 & 3 & saudi arabia (ksa) & 7 & 1 & 0 & 8 \\
3 & 4 & kazakhstan (kaz) & 3 & 4 & 5 & 12 \\
4 & 5 & south korea (kor) & 3 & 2 & 1 & 6 \\
5 & 6 & japan (jpn) & 2 & 13 & 8 & 23 \\
6 & 7 & bahrain (brn) & 2 & 1 & 1 & 4 \\
7 & 8 & sri lanka (sri) & 2 & 0 & 2 & 4 \\
8 & 9 & qatar (qat) & 1 & 4 & 3 & 8 \\
9 & 10 & thailand (tha) & 1 & 1 & 2 & 4 \\
10 & 11 & kyrgyzstan (kgz) & 1 & 1 & 0 & 2 \\
11 & 12 & kuwait (kuw) & 1 & 0 & 0 & 1 \\
12 & 12 & north korea (prk) & 1 & 0 & 0 & 1 \\
13 & 14 & uzbekistan (uzb) & 0 & 1 & 3 & 4 \\
14 & 15 & iran (iri) & 0 & 1 & 0 & 1 \\
15 & total & total & 45 & 49 & 42 & 136 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "nation - nation" \\
\midrule
0 & nation - nation \\
\bottomrule
\end{tabular}
| select nation - nation where nation = 'south korea (kor)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>china (chn)</td>
<td>14</td>
<td>14</td>
<td>13</td>
<td>41</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>india (ind)</td>
<td>7</td>
<td>6</td>
<td>4</td>
<td>17</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>saudi arabia (ksa)</td>
<td>7</td>
<td>1</td>
<td>0</td>
<td>8</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>kazakhstan (kaz)</td>
<td>3</td>
<td>4</td>
<td>5</td>
<td>12</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>south korea (kor)</td>
<td>3</td>
<td>2</td>
<td>1</td>
<td>6</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>japan (jpn)</td>
<td>2</td>
<td>13</td>
<td>8</td>
<td>23</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>bahrain (brn)</td>
<td>2</td>
<td>1</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>sri lanka (sri)</td>
<td>2</td>
<td>0</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>qatar (qat)</td>
<td>1</td>
<td>4</td>
<td>3</td>
<td>8</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>thailand (tha)</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>kyrgyzstan (kgz)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>kuwait (kuw)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>12</td>
<td>north korea (prk)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>uzbekistan (uzb)</td>
<td>0</td>
<td>1</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>iran (iri)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>total</td>
<td>total</td>
<td>45</td>
<td>49</td>
<td>42</td>
<td>136</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"nation - nation"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>nation - nation</td>
</tr>
</tbody>
</table> | select nation - nation where nation = 'south korea (kor)' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:-------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | china (chn) | 14 | 14 | 13 | 41 |
| 1 | 2 | india (ind) | 7 | 6 | 4 | 17 |
| 2 | 3 | saudi arabia (ksa) | 7 | 1 | 0 | 8 |
| 3 | 4 | kazakhstan (kaz) | 3 | 4 | 5 | 12 |
| 4 | 5 | south korea (kor) | 3 | 2 | 1 | 6 |
| 5 | 6 | japan (jpn) | 2 | 13 | 8 | 23 |
| 6 | 7 | bahrain (brn) | 2 | 1 | 1 | 4 |
| 7 | 8 | sri lanka (sri) | 2 | 0 | 2 | 4 |
| 8 | 9 | qatar (qat) | 1 | 4 | 3 | 8 |
| 9 | 10 | thailand (tha) | 1 | 1 | 2 | 4 |
| 10 | 11 | kyrgyzstan (kgz) | 1 | 1 | 0 | 2 |
| 11 | 12 | kuwait (kuw) | 1 | 0 | 0 | 1 |
| 12 | 12 | north korea (prk) | 1 | 0 | 0 | 1 |
| 13 | 14 | uzbekistan (uzb) | 0 | 1 | 3 | 4 |
| 14 | 15 | iran (iri) | 0 | 1 | 0 | 1 |
| 15 | total | total | 45 | 49 | 42 | 136 | | | | "nation - nation" |
|---:|:--------------------|
| 0 | nation - nation | | [
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select rank where advocate = 'paul gross' col : rank | name | notability | birthplace | advocate row 1 : 10 | wayne gretzky | hockey player, holder of numerous nhl records | brantford, ontario | deborah grey row 2 : 9 | alexander graham bell | scientist, inventor, founder of the bell telephone company | edinburgh, scotland | evan solomon row 3 : 8 | sir john a. macdonald | first prime minister of canada | glasgow, scotland | charlotte gray row 4 : 7 | don cherry | hockey coach and commentator | kingston, ontario | bret hart row 5 : 6 | lester b. pearson | fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate | toronto, ontario | paul gross row 6 : 5 | david suzuki | environmentalist | vancouver, british columbia | melissa auf der maur row 7 : 4 | sir frederick banting | medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine | alliston, ontario | mary walsh row 8 : 3 | pierre trudeau | fifteenth prime minister of canada | montreal, quebec | rex murphy row 9 : 2 | terry fox | athlete, activist, humanitarian | winnipeg, manitoba | sook-yin lee row 10 : 1 | tommy douglas | father of medicare, premier of saskatchewan | falkirk, scotland | george stroumboulopoulos | col : rank row 1 : 6 | select rank where advocate = 'paul gross' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & notability & birthplace & advocate \\
\midrule
0 & 10 & wayne gretzky & hockey player, holder of numerous nhl records & brantford, ontario & deborah grey \\
1 & 9 & alexander graham bell & scientist, inventor, founder of the bell telephone company & edinburgh, scotland & evan solomon \\
2 & 8 & sir john a. macdonald & first prime minister of canada & glasgow, scotland & charlotte gray \\
3 & 7 & don cherry & hockey coach and commentator & kingston, ontario & bret hart \\
4 & 6 & lester b. pearson & fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate & toronto, ontario & paul gross \\
5 & 5 & david suzuki & environmentalist & vancouver, british columbia & melissa auf der maur \\
6 & 4 & sir frederick banting & medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine & alliston, ontario & mary walsh \\
7 & 3 & pierre trudeau & fifteenth prime minister of canada & montreal, quebec & rex murphy \\
8 & 2 & terry fox & athlete, activist, humanitarian & winnipeg, manitoba & sook-yin lee \\
9 & 1 & tommy douglas & father of medicare, premier of saskatchewan & falkirk, scotland & george stroumboulopoulos \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& rank \\
\midrule
0 & 6 \\
\bottomrule
\end{tabular}
| select rank where advocate = 'paul gross' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>notability</th>
<th>birthplace</th>
<th>advocate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>10</td>
<td>wayne gretzky</td>
<td>hockey player, holder of numerous nhl records</td>
<td>brantford, ontario</td>
<td>deborah grey</td>
</tr>
<tr>
<th>1</th>
<td>9</td>
<td>alexander graham bell</td>
<td>scientist, inventor, founder of the bell telephone company</td>
<td>edinburgh, scotland</td>
<td>evan solomon</td>
</tr>
<tr>
<th>2</th>
<td>8</td>
<td>sir john a. macdonald</td>
<td>first prime minister of canada</td>
<td>glasgow, scotland</td>
<td>charlotte gray</td>
</tr>
<tr>
<th>3</th>
<td>7</td>
<td>don cherry</td>
<td>hockey coach and commentator</td>
<td>kingston, ontario</td>
<td>bret hart</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>lester b. pearson</td>
<td>fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate</td>
<td>toronto, ontario</td>
<td>paul gross</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>david suzuki</td>
<td>environmentalist</td>
<td>vancouver, british columbia</td>
<td>melissa auf der maur</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>sir frederick banting</td>
<td>medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine</td>
<td>alliston, ontario</td>
<td>mary walsh</td>
</tr>
<tr>
<th>7</th>
<td>3</td>
<td>pierre trudeau</td>
<td>fifteenth prime minister of canada</td>
<td>montreal, quebec</td>
<td>rex murphy</td>
</tr>
<tr>
<th>8</th>
<td>2</td>
<td>terry fox</td>
<td>athlete, activist, humanitarian</td>
<td>winnipeg, manitoba</td>
<td>sook-yin lee</td>
</tr>
<tr>
<th>9</th>
<td>1</td>
<td>tommy douglas</td>
<td>father of medicare, premier of saskatchewan</td>
<td>falkirk, scotland</td>
<td>george stroumboulopoulos</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>6</td>
</tr>
</tbody>
</table> | select rank where advocate = 'paul gross' <table_name> : table | | rank | name | notability | birthplace | advocate |
|---:|-------:|:----------------------|:-----------------------------------------------------------------------------------------------------------|:----------------------------|:-------------------------|
| 0 | 10 | wayne gretzky | hockey player, holder of numerous nhl records | brantford, ontario | deborah grey |
| 1 | 9 | alexander graham bell | scientist, inventor, founder of the bell telephone company | edinburgh, scotland | evan solomon |
| 2 | 8 | sir john a. macdonald | first prime minister of canada | glasgow, scotland | charlotte gray |
| 3 | 7 | don cherry | hockey coach and commentator | kingston, ontario | bret hart |
| 4 | 6 | lester b. pearson | fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate | toronto, ontario | paul gross |
| 5 | 5 | david suzuki | environmentalist | vancouver, british columbia | melissa auf der maur |
| 6 | 4 | sir frederick banting | medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine | alliston, ontario | mary walsh |
| 7 | 3 | pierre trudeau | fifteenth prime minister of canada | montreal, quebec | rex murphy |
| 8 | 2 | terry fox | athlete, activist, humanitarian | winnipeg, manitoba | sook-yin lee |
| 9 | 1 | tommy douglas | father of medicare, premier of saskatchewan | falkirk, scotland | george stroumboulopoulos | | | | rank |
|---:|-------:|
| 0 | 6 | | [
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select nation where nation = 'czechoslovakia (tch)' order by total asc limit 515 col : rank | nation | gold | silver | bronze | total row 1 : 1 | united states (usa) | 5 | 0 | 0 | 5 row 2 : 2 | italy (ita) | 1 | 1 | 1 | 3 row 3 : 3 | poland (pol) | 1 | 1 | 0 | 2 row 4 : 4 | finland (fin) | 1 | 0 | 4 | 5 row 5 : 5 | czechoslovakia (tch) | 1 | 0 | 0 | 1 row 6 : 5 | hungary (hun) | 1 | 0 | 0 | 1 row 7 : 7 | soviet union (urs) | 0 | 2 | 4 | 6 row 8 : 8 | south africa (rsa) | 0 | 1 | 3 | 4 row 9 : 9 | argentina (arg) | 0 | 1 | 1 | 2 row 10 : 9 | germany (ger) | 0 | 1 | 1 | 2 row 11 : 9 | romania (rou) | 0 | 1 | 1 | 2 row 12 : 9 | sweden (swe) | 0 | 1 | 1 | 2 row 13 : 13 | ireland (irl) | 0 | 1 | 0 | 1 row 14 : 14 | bulgaria (bul) | 0 | 0 | 1 | 1 row 15 : 14 | denmark (den) | 0 | 0 | 1 | 1 row 16 : 14 | france (fra) | 0 | 0 | 1 | 1 row 17 : 14 | south korea (kor) | 0 | 0 | 1 | 1 | col : nation row 1 : czechoslovakia (tch) | select nation where nation = 'czechoslovakia (tch)' order by total asc limit 515 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & united states (usa) & 5 & 0 & 0 & 5 \\
1 & 2 & italy (ita) & 1 & 1 & 1 & 3 \\
2 & 3 & poland (pol) & 1 & 1 & 0 & 2 \\
3 & 4 & finland (fin) & 1 & 0 & 4 & 5 \\
4 & 5 & czechoslovakia (tch) & 1 & 0 & 0 & 1 \\
5 & 5 & hungary (hun) & 1 & 0 & 0 & 1 \\
6 & 7 & soviet union (urs) & 0 & 2 & 4 & 6 \\
7 & 8 & south africa (rsa) & 0 & 1 & 3 & 4 \\
8 & 9 & argentina (arg) & 0 & 1 & 1 & 2 \\
9 & 9 & germany (ger) & 0 & 1 & 1 & 2 \\
10 & 9 & romania (rou) & 0 & 1 & 1 & 2 \\
11 & 9 & sweden (swe) & 0 & 1 & 1 & 2 \\
12 & 13 & ireland (irl) & 0 & 1 & 0 & 1 \\
13 & 14 & bulgaria (bul) & 0 & 0 & 1 & 1 \\
14 & 14 & denmark (den) & 0 & 0 & 1 & 1 \\
15 & 14 & france (fra) & 0 & 0 & 1 & 1 \\
16 & 14 & south korea (kor) & 0 & 0 & 1 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & czechoslovakia (tch) \\
\bottomrule
\end{tabular}
| select nation where nation = 'czechoslovakia (tch)' order by total asc limit 515 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>united states (usa)</td>
<td>5</td>
<td>0</td>
<td>0</td>
<td>5</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>italy (ita)</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>poland (pol)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>finland (fin)</td>
<td>1</td>
<td>0</td>
<td>4</td>
<td>5</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>czechoslovakia (tch)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>hungary (hun)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>soviet union (urs)</td>
<td>0</td>
<td>2</td>
<td>4</td>
<td>6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>south africa (rsa)</td>
<td>0</td>
<td>1</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>argentina (arg)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>germany (ger)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>10</th>
<td>9</td>
<td>romania (rou)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>9</td>
<td>sweden (swe)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>ireland (irl)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>bulgaria (bul)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>14</td>
<td>denmark (den)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>14</td>
<td>france (fra)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>14</td>
<td>south korea (kor)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>czechoslovakia (tch)</td>
</tr>
</tbody>
</table> | select nation where nation = 'czechoslovakia (tch)' order by total asc limit 515 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|-------:|:---------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | united states (usa) | 5 | 0 | 0 | 5 |
| 1 | 2 | italy (ita) | 1 | 1 | 1 | 3 |
| 2 | 3 | poland (pol) | 1 | 1 | 0 | 2 |
| 3 | 4 | finland (fin) | 1 | 0 | 4 | 5 |
| 4 | 5 | czechoslovakia (tch) | 1 | 0 | 0 | 1 |
| 5 | 5 | hungary (hun) | 1 | 0 | 0 | 1 |
| 6 | 7 | soviet union (urs) | 0 | 2 | 4 | 6 |
| 7 | 8 | south africa (rsa) | 0 | 1 | 3 | 4 |
| 8 | 9 | argentina (arg) | 0 | 1 | 1 | 2 |
| 9 | 9 | germany (ger) | 0 | 1 | 1 | 2 |
| 10 | 9 | romania (rou) | 0 | 1 | 1 | 2 |
| 11 | 9 | sweden (swe) | 0 | 1 | 1 | 2 |
| 12 | 13 | ireland (irl) | 0 | 1 | 0 | 1 |
| 13 | 14 | bulgaria (bul) | 0 | 0 | 1 | 1 |
| 14 | 14 | denmark (den) | 0 | 0 | 1 | 1 |
| 15 | 14 | france (fra) | 0 | 0 | 1 | 1 |
| 16 | 14 | south korea (kor) | 0 | 0 | 1 | 1 | | | | nation |
|---:|:---------------------|
| 0 | czechoslovakia (tch) | | [
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select winner where trainer = 'laz barrera' col : year | winner | jockey | trainer | owner | breeder row 1 : 1919 | sir barton | johnny loftus | h. guy bedwell | j. k. l. ross | none row 2 : 1930 | gallant fox | earl sande | jim fitzsimmons | belair stud | belair stud row 3 : 1935 | omaha | willie saunders | jim fitzsimmons | belair stud | belair stud row 4 : 1937 | war admiral | charley kurtsinger | george h. conway | samuel d. riddle | samuel d. riddle row 5 : 1941 | whirlaway | eddie arcaro | ben a. jones | calumet farm | calumet farm row 6 : 1943 | count fleet | johnny longden | don cameron | fannie hertz | fannie hertz row 7 : 1946 | assault | warren mehrtens | max hirsch | king ranch | king ranch row 8 : 1948 | citation | eddie arcaro | horace a. jones | calumet farm | calumet farm row 9 : 1973 | secretariat | ron turcotte | lucien laurin | meadow stable | meadow stud row 10 : 1977 | seattle slew | jean cruguet | william h. turner, jr | karen l. taylor | ben s. castleman row 11 : 1978 | affirmed | steve cauthen | laz barrera | harbor view farm | harbor view farm | col : winner row 1 : affirmed | select winner where trainer = 'laz barrera' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & winner & jockey & trainer & owner & breeder \\
\midrule
0 & 1919 & sir barton & johnny loftus & h. guy bedwell & j. k. l. ross & none \\
1 & 1930 & gallant fox & earl sande & jim fitzsimmons & belair stud & belair stud \\
2 & 1935 & omaha & willie saunders & jim fitzsimmons & belair stud & belair stud \\
3 & 1937 & war admiral & charley kurtsinger & george h. conway & samuel d. riddle & samuel d. riddle \\
4 & 1941 & whirlaway & eddie arcaro & ben a. jones & calumet farm & calumet farm \\
5 & 1943 & count fleet & johnny longden & don cameron & fannie hertz & fannie hertz \\
6 & 1946 & assault & warren mehrtens & max hirsch & king ranch & king ranch \\
7 & 1948 & citation & eddie arcaro & horace a. jones & calumet farm & calumet farm \\
8 & 1973 & secretariat & ron turcotte & lucien laurin & meadow stable & meadow stud \\
9 & 1977 & seattle slew & jean cruguet & william h. turner, jr & karen l. taylor & ben s. castleman \\
10 & 1978 & affirmed & steve cauthen & laz barrera & harbor view farm & harbor view farm \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& winner \\
\midrule
0 & affirmed \\
\bottomrule
\end{tabular}
| select winner where trainer = 'laz barrera' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>winner</th>
<th>jockey</th>
<th>trainer</th>
<th>owner</th>
<th>breeder</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1919</td>
<td>sir barton</td>
<td>johnny loftus</td>
<td>h. guy bedwell</td>
<td>j. k. l. ross</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1930</td>
<td>gallant fox</td>
<td>earl sande</td>
<td>jim fitzsimmons</td>
<td>belair stud</td>
<td>belair stud</td>
</tr>
<tr>
<th>2</th>
<td>1935</td>
<td>omaha</td>
<td>willie saunders</td>
<td>jim fitzsimmons</td>
<td>belair stud</td>
<td>belair stud</td>
</tr>
<tr>
<th>3</th>
<td>1937</td>
<td>war admiral</td>
<td>charley kurtsinger</td>
<td>george h. conway</td>
<td>samuel d. riddle</td>
<td>samuel d. riddle</td>
</tr>
<tr>
<th>4</th>
<td>1941</td>
<td>whirlaway</td>
<td>eddie arcaro</td>
<td>ben a. jones</td>
<td>calumet farm</td>
<td>calumet farm</td>
</tr>
<tr>
<th>5</th>
<td>1943</td>
<td>count fleet</td>
<td>johnny longden</td>
<td>don cameron</td>
<td>fannie hertz</td>
<td>fannie hertz</td>
</tr>
<tr>
<th>6</th>
<td>1946</td>
<td>assault</td>
<td>warren mehrtens</td>
<td>max hirsch</td>
<td>king ranch</td>
<td>king ranch</td>
</tr>
<tr>
<th>7</th>
<td>1948</td>
<td>citation</td>
<td>eddie arcaro</td>
<td>horace a. jones</td>
<td>calumet farm</td>
<td>calumet farm</td>
</tr>
<tr>
<th>8</th>
<td>1973</td>
<td>secretariat</td>
<td>ron turcotte</td>
<td>lucien laurin</td>
<td>meadow stable</td>
<td>meadow stud</td>
</tr>
<tr>
<th>9</th>
<td>1977</td>
<td>seattle slew</td>
<td>jean cruguet</td>
<td>william h. turner, jr</td>
<td>karen l. taylor</td>
<td>ben s. castleman</td>
</tr>
<tr>
<th>10</th>
<td>1978</td>
<td>affirmed</td>
<td>steve cauthen</td>
<td>laz barrera</td>
<td>harbor view farm</td>
<td>harbor view farm</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>winner</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>affirmed</td>
</tr>
</tbody>
</table> | select winner where trainer = 'laz barrera' <table_name> : table | | year | winner | jockey | trainer | owner | breeder |
|---:|-------:|:-------------|:-------------------|:----------------------|:-----------------|:-----------------|
| 0 | 1919 | sir barton | johnny loftus | h. guy bedwell | j. k. l. ross | none |
| 1 | 1930 | gallant fox | earl sande | jim fitzsimmons | belair stud | belair stud |
| 2 | 1935 | omaha | willie saunders | jim fitzsimmons | belair stud | belair stud |
| 3 | 1937 | war admiral | charley kurtsinger | george h. conway | samuel d. riddle | samuel d. riddle |
| 4 | 1941 | whirlaway | eddie arcaro | ben a. jones | calumet farm | calumet farm |
| 5 | 1943 | count fleet | johnny longden | don cameron | fannie hertz | fannie hertz |
| 6 | 1946 | assault | warren mehrtens | max hirsch | king ranch | king ranch |
| 7 | 1948 | citation | eddie arcaro | horace a. jones | calumet farm | calumet farm |
| 8 | 1973 | secretariat | ron turcotte | lucien laurin | meadow stable | meadow stud |
| 9 | 1977 | seattle slew | jean cruguet | william h. turner, jr | karen l. taylor | ben s. castleman |
| 10 | 1978 | affirmed | steve cauthen | laz barrera | harbor view farm | harbor view farm | | | | winner |
|---:|:---------|
| 0 | affirmed | | [
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select club where competition = 'regionalliga sud' col : season | club | country | competition | apps. | goals row 1 : 1997/98 | rapide club lebbeke | belgium | fourth division | none | none row 2 : 1998/99 | ksc eendracht aalst | belgium | jupiler league | 30 | 7 row 3 : 1999/00 | ksc eendracht aalst | belgium | jupiler league | 31 | 7 row 4 : 2000/01 | ksc eendracht aalst | belgium | jupiler league | 30 | 6 row 5 : 2001/02 | omonia nicosia | cyprus | cypriot first division | 22 | 8 row 6 : 2002/03 | fc denderleeuw | belgium | belgian second division | 32 | 23 row 7 : 2003/04 | 1. fc saarbrucken | germany | regionalliga sud | 33 | 16 row 8 : 2004/05 | 1. fc saarbrucken | germany | 2. bundesliga | 14 | 7 row 9 : 2005/06 | 1. fc saarbrucken | germany | 2. bundesliga | 10 | 0 row 10 : 2005/06 | s.v. zulte waregem | belgium | jupiler league | 14 | 1 row 11 : 2006/07 | fcv dender eh | belgium | belgian second division | 33 | 21 row 12 : 2007/08 | mvv | netherlands | eerste divisie | 33 | 22 row 13 : 2008/09 | mvv | netherlands | eerste divisie | 32 | 20 row 14 : total | none | none | none | 302 | 132 | col : club row 1 : 1. fc saarbrucken | select club where competition = 'regionalliga sud' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & club & country & competition & apps. & goals \\
\midrule
0 & 1997/98 & rapide club lebbeke & belgium & fourth division & none & none \\
1 & 1998/99 & ksc eendracht aalst & belgium & jupiler league & 30 & 7 \\
2 & 1999/00 & ksc eendracht aalst & belgium & jupiler league & 31 & 7 \\
3 & 2000/01 & ksc eendracht aalst & belgium & jupiler league & 30 & 6 \\
4 & 2001/02 & omonia nicosia & cyprus & cypriot first division & 22 & 8 \\
5 & 2002/03 & fc denderleeuw & belgium & belgian second division & 32 & 23 \\
6 & 2003/04 & 1. fc saarbrucken & germany & regionalliga sud & 33 & 16 \\
7 & 2004/05 & 1. fc saarbrucken & germany & 2. bundesliga & 14 & 7 \\
8 & 2005/06 & 1. fc saarbrucken & germany & 2. bundesliga & 10 & 0 \\
9 & 2005/06 & s.v. zulte waregem & belgium & jupiler league & 14 & 1 \\
10 & 2006/07 & fcv dender eh & belgium & belgian second division & 33 & 21 \\
11 & 2007/08 & mvv & netherlands & eerste divisie & 33 & 22 \\
12 & 2008/09 & mvv & netherlands & eerste divisie & 32 & 20 \\
13 & total & none & none & none & 302 & 132 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& club \\
\midrule
0 & 1. fc saarbrucken \\
\bottomrule
\end{tabular}
| select club where competition = 'regionalliga sud' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>club</th>
<th>country</th>
<th>competition</th>
<th>apps.</th>
<th>goals</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1997/98</td>
<td>rapide club lebbeke</td>
<td>belgium</td>
<td>fourth division</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1998/99</td>
<td>ksc eendracht aalst</td>
<td>belgium</td>
<td>jupiler league</td>
<td>30</td>
<td>7</td>
</tr>
<tr>
<th>2</th>
<td>1999/00</td>
<td>ksc eendracht aalst</td>
<td>belgium</td>
<td>jupiler league</td>
<td>31</td>
<td>7</td>
</tr>
<tr>
<th>3</th>
<td>2000/01</td>
<td>ksc eendracht aalst</td>
<td>belgium</td>
<td>jupiler league</td>
<td>30</td>
<td>6</td>
</tr>
<tr>
<th>4</th>
<td>2001/02</td>
<td>omonia nicosia</td>
<td>cyprus</td>
<td>cypriot first division</td>
<td>22</td>
<td>8</td>
</tr>
<tr>
<th>5</th>
<td>2002/03</td>
<td>fc denderleeuw</td>
<td>belgium</td>
<td>belgian second division</td>
<td>32</td>
<td>23</td>
</tr>
<tr>
<th>6</th>
<td>2003/04</td>
<td>1. fc saarbrucken</td>
<td>germany</td>
<td>regionalliga sud</td>
<td>33</td>
<td>16</td>
</tr>
<tr>
<th>7</th>
<td>2004/05</td>
<td>1. fc saarbrucken</td>
<td>germany</td>
<td>2. bundesliga</td>
<td>14</td>
<td>7</td>
</tr>
<tr>
<th>8</th>
<td>2005/06</td>
<td>1. fc saarbrucken</td>
<td>germany</td>
<td>2. bundesliga</td>
<td>10</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>2005/06</td>
<td>s.v. zulte waregem</td>
<td>belgium</td>
<td>jupiler league</td>
<td>14</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>2006/07</td>
<td>fcv dender eh</td>
<td>belgium</td>
<td>belgian second division</td>
<td>33</td>
<td>21</td>
</tr>
<tr>
<th>11</th>
<td>2007/08</td>
<td>mvv</td>
<td>netherlands</td>
<td>eerste divisie</td>
<td>33</td>
<td>22</td>
</tr>
<tr>
<th>12</th>
<td>2008/09</td>
<td>mvv</td>
<td>netherlands</td>
<td>eerste divisie</td>
<td>32</td>
<td>20</td>
</tr>
<tr>
<th>13</th>
<td>total</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>302</td>
<td>132</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>club</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1. fc saarbrucken</td>
</tr>
</tbody>
</table> | select club where competition = 'regionalliga sud' <table_name> : table | | season | club | country | competition | apps. | goals |
|---:|:---------|:--------------------|:------------|:------------------------|:--------|:--------|
| 0 | 1997/98 | rapide club lebbeke | belgium | fourth division | none | none |
| 1 | 1998/99 | ksc eendracht aalst | belgium | jupiler league | 30 | 7 |
| 2 | 1999/00 | ksc eendracht aalst | belgium | jupiler league | 31 | 7 |
| 3 | 2000/01 | ksc eendracht aalst | belgium | jupiler league | 30 | 6 |
| 4 | 2001/02 | omonia nicosia | cyprus | cypriot first division | 22 | 8 |
| 5 | 2002/03 | fc denderleeuw | belgium | belgian second division | 32 | 23 |
| 6 | 2003/04 | 1. fc saarbrucken | germany | regionalliga sud | 33 | 16 |
| 7 | 2004/05 | 1. fc saarbrucken | germany | 2. bundesliga | 14 | 7 |
| 8 | 2005/06 | 1. fc saarbrucken | germany | 2. bundesliga | 10 | 0 |
| 9 | 2005/06 | s.v. zulte waregem | belgium | jupiler league | 14 | 1 |
| 10 | 2006/07 | fcv dender eh | belgium | belgian second division | 33 | 21 |
| 11 | 2007/08 | mvv | netherlands | eerste divisie | 33 | 22 |
| 12 | 2008/09 | mvv | netherlands | eerste divisie | 32 | 20 |
| 13 | total | none | none | none | 302 | 132 | | | | club |
|---:|:------------------|
| 0 | 1. fc saarbrucken | | [
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] |
select college/junior/club team where pick # = 137 col : pick # | player | position | nationality | nhl team | college/junior/club team row 1 : 123 | paul ames | defence | united states | pittsburgh penguins | billerica high school (ushs-ma) row 2 : 124 | joe reekie | defence | canada | hartford whalers | north bay centennials (ohl) row 3 : 125 | greg evtushevski | right wing | canada | new jersey devils | kamloops blazers (whl) row 4 : 126 | bob pierson | left wing | canada | detroit red wings | london knights (ohl) row 5 : 127 | tim burgess | defence | canada | los angeles kings | oshawa generals (ohl) row 6 : 128 | cam plante | defence | canada | toronto maple leafs | brandon wheat kings (whl) row 7 : 129 | iain duncan | left wing | canada | winnipeg jets | north york rangers (ojhl) row 8 : 130 | terry maki | left wing | canada | vancouver canucks | brantford alexanders (ohl) row 9 : 131 | jeff hogg | goaltender | canada | calgary flames | oshawa generals (ohl) row 10 : 132 | craig mack | defence | united states | quebec nordiques | east grand forks high school (ushs-mn) row 11 : 133 | steve orth | centre | united states | new york rangers | st. cloud state university (wcha) row 12 : 134 | christian ruuttu | centre | finland | buffalo sabres | pori (finland) row 13 : 135 | dwaine hutton | centre | canada | washington capitals | kelowna wings (whl) row 14 : 136 | sean toomey | left wing | united states | minnesota north stars | cretin-derham hall high school (ushs-mn) row 15 : 137 | jim sprenger | defence | united states | new york islanders | cloquet high school (ushs-mn) row 16 : 138 | vladislav tretiak | goaltender | soviet union | montreal canadiens | moscow cska (ussr) row 17 : 139 | scott birnie | rignt wing | canada | chicago black hawks | cornwall royals (ohl) row 18 : 140 | dale derkatch | centre | canada | edmonton oilers | regina pats (whl) row 19 : 141 | bob mormina | right wing | canada | philadelphia flyers | longueuil chevaliers (qmjhl) row 20 : 142 | ian armstrong | defence | canada | boston bruins | peterborough petes (ohl) | col : college/junior/club team row 1 : cloquet high school (ushs-mn) | select college/junior/club team where pick # = 137 <table_name> : table \begin{tabular}{lllllll}
\toprule
& pick # & player & position & nationality & nhl team & college/junior/club team \\
\midrule
0 & 123 & paul ames & defence & united states & pittsburgh penguins & billerica high school (ushs-ma) \\
1 & 124 & joe reekie & defence & canada & hartford whalers & north bay centennials (ohl) \\
2 & 125 & greg evtushevski & right wing & canada & new jersey devils & kamloops blazers (whl) \\
3 & 126 & bob pierson & left wing & canada & detroit red wings & london knights (ohl) \\
4 & 127 & tim burgess & defence & canada & los angeles kings & oshawa generals (ohl) \\
5 & 128 & cam plante & defence & canada & toronto maple leafs & brandon wheat kings (whl) \\
6 & 129 & iain duncan & left wing & canada & winnipeg jets & north york rangers (ojhl) \\
7 & 130 & terry maki & left wing & canada & vancouver canucks & brantford alexanders (ohl) \\
8 & 131 & jeff hogg & goaltender & canada & calgary flames & oshawa generals (ohl) \\
9 & 132 & craig mack & defence & united states & quebec nordiques & east grand forks high school (ushs-mn) \\
10 & 133 & steve orth & centre & united states & new york rangers & st. cloud state university (wcha) \\
11 & 134 & christian ruuttu & centre & finland & buffalo sabres & pori (finland) \\
12 & 135 & dwaine hutton & centre & canada & washington capitals & kelowna wings (whl) \\
13 & 136 & sean toomey & left wing & united states & minnesota north stars & cretin-derham hall high school (ushs-mn) \\
14 & 137 & jim sprenger & defence & united states & new york islanders & cloquet high school (ushs-mn) \\
15 & 138 & vladislav tretiak & goaltender & soviet union & montreal canadiens & moscow cska (ussr) \\
16 & 139 & scott birnie & rignt wing & canada & chicago black hawks & cornwall royals (ohl) \\
17 & 140 & dale derkatch & centre & canada & edmonton oilers & regina pats (whl) \\
18 & 141 & bob mormina & right wing & canada & philadelphia flyers & longueuil chevaliers (qmjhl) \\
19 & 142 & ian armstrong & defence & canada & boston bruins & peterborough petes (ohl) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& college/junior/club team \\
\midrule
0 & cloquet high school (ushs-mn) \\
\bottomrule
\end{tabular}
| select college/junior/club team where pick # = 137 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pick #</th>
<th>player</th>
<th>position</th>
<th>nationality</th>
<th>nhl team</th>
<th>college/junior/club team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>123</td>
<td>paul ames</td>
<td>defence</td>
<td>united states</td>
<td>pittsburgh penguins</td>
<td>billerica high school (ushs-ma)</td>
</tr>
<tr>
<th>1</th>
<td>124</td>
<td>joe reekie</td>
<td>defence</td>
<td>canada</td>
<td>hartford whalers</td>
<td>north bay centennials (ohl)</td>
</tr>
<tr>
<th>2</th>
<td>125</td>
<td>greg evtushevski</td>
<td>right wing</td>
<td>canada</td>
<td>new jersey devils</td>
<td>kamloops blazers (whl)</td>
</tr>
<tr>
<th>3</th>
<td>126</td>
<td>bob pierson</td>
<td>left wing</td>
<td>canada</td>
<td>detroit red wings</td>
<td>london knights (ohl)</td>
</tr>
<tr>
<th>4</th>
<td>127</td>
<td>tim burgess</td>
<td>defence</td>
<td>canada</td>
<td>los angeles kings</td>
<td>oshawa generals (ohl)</td>
</tr>
<tr>
<th>5</th>
<td>128</td>
<td>cam plante</td>
<td>defence</td>
<td>canada</td>
<td>toronto maple leafs</td>
<td>brandon wheat kings (whl)</td>
</tr>
<tr>
<th>6</th>
<td>129</td>
<td>iain duncan</td>
<td>left wing</td>
<td>canada</td>
<td>winnipeg jets</td>
<td>north york rangers (ojhl)</td>
</tr>
<tr>
<th>7</th>
<td>130</td>
<td>terry maki</td>
<td>left wing</td>
<td>canada</td>
<td>vancouver canucks</td>
<td>brantford alexanders (ohl)</td>
</tr>
<tr>
<th>8</th>
<td>131</td>
<td>jeff hogg</td>
<td>goaltender</td>
<td>canada</td>
<td>calgary flames</td>
<td>oshawa generals (ohl)</td>
</tr>
<tr>
<th>9</th>
<td>132</td>
<td>craig mack</td>
<td>defence</td>
<td>united states</td>
<td>quebec nordiques</td>
<td>east grand forks high school (ushs-mn)</td>
</tr>
<tr>
<th>10</th>
<td>133</td>
<td>steve orth</td>
<td>centre</td>
<td>united states</td>
<td>new york rangers</td>
<td>st. cloud state university (wcha)</td>
</tr>
<tr>
<th>11</th>
<td>134</td>
<td>christian ruuttu</td>
<td>centre</td>
<td>finland</td>
<td>buffalo sabres</td>
<td>pori (finland)</td>
</tr>
<tr>
<th>12</th>
<td>135</td>
<td>dwaine hutton</td>
<td>centre</td>
<td>canada</td>
<td>washington capitals</td>
<td>kelowna wings (whl)</td>
</tr>
<tr>
<th>13</th>
<td>136</td>
<td>sean toomey</td>
<td>left wing</td>
<td>united states</td>
<td>minnesota north stars</td>
<td>cretin-derham hall high school (ushs-mn)</td>
</tr>
<tr>
<th>14</th>
<td>137</td>
<td>jim sprenger</td>
<td>defence</td>
<td>united states</td>
<td>new york islanders</td>
<td>cloquet high school (ushs-mn)</td>
</tr>
<tr>
<th>15</th>
<td>138</td>
<td>vladislav tretiak</td>
<td>goaltender</td>
<td>soviet union</td>
<td>montreal canadiens</td>
<td>moscow cska (ussr)</td>
</tr>
<tr>
<th>16</th>
<td>139</td>
<td>scott birnie</td>
<td>rignt wing</td>
<td>canada</td>
<td>chicago black hawks</td>
<td>cornwall royals (ohl)</td>
</tr>
<tr>
<th>17</th>
<td>140</td>
<td>dale derkatch</td>
<td>centre</td>
<td>canada</td>
<td>edmonton oilers</td>
<td>regina pats (whl)</td>
</tr>
<tr>
<th>18</th>
<td>141</td>
<td>bob mormina</td>
<td>right wing</td>
<td>canada</td>
<td>philadelphia flyers</td>
<td>longueuil chevaliers (qmjhl)</td>
</tr>
<tr>
<th>19</th>
<td>142</td>
<td>ian armstrong</td>
<td>defence</td>
<td>canada</td>
<td>boston bruins</td>
<td>peterborough petes (ohl)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>college/junior/club team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cloquet high school (ushs-mn)</td>
</tr>
</tbody>
</table> | select college/junior/club team where pick # = 137 <table_name> : table | | pick # | player | position | nationality | nhl team | college/junior/club team |
|---:|---------:|:------------------|:-----------|:--------------|:----------------------|:-----------------------------------------|
| 0 | 123 | paul ames | defence | united states | pittsburgh penguins | billerica high school (ushs-ma) |
| 1 | 124 | joe reekie | defence | canada | hartford whalers | north bay centennials (ohl) |
| 2 | 125 | greg evtushevski | right wing | canada | new jersey devils | kamloops blazers (whl) |
| 3 | 126 | bob pierson | left wing | canada | detroit red wings | london knights (ohl) |
| 4 | 127 | tim burgess | defence | canada | los angeles kings | oshawa generals (ohl) |
| 5 | 128 | cam plante | defence | canada | toronto maple leafs | brandon wheat kings (whl) |
| 6 | 129 | iain duncan | left wing | canada | winnipeg jets | north york rangers (ojhl) |
| 7 | 130 | terry maki | left wing | canada | vancouver canucks | brantford alexanders (ohl) |
| 8 | 131 | jeff hogg | goaltender | canada | calgary flames | oshawa generals (ohl) |
| 9 | 132 | craig mack | defence | united states | quebec nordiques | east grand forks high school (ushs-mn) |
| 10 | 133 | steve orth | centre | united states | new york rangers | st. cloud state university (wcha) |
| 11 | 134 | christian ruuttu | centre | finland | buffalo sabres | pori (finland) |
| 12 | 135 | dwaine hutton | centre | canada | washington capitals | kelowna wings (whl) |
| 13 | 136 | sean toomey | left wing | united states | minnesota north stars | cretin-derham hall high school (ushs-mn) |
| 14 | 137 | jim sprenger | defence | united states | new york islanders | cloquet high school (ushs-mn) |
| 15 | 138 | vladislav tretiak | goaltender | soviet union | montreal canadiens | moscow cska (ussr) |
| 16 | 139 | scott birnie | rignt wing | canada | chicago black hawks | cornwall royals (ohl) |
| 17 | 140 | dale derkatch | centre | canada | edmonton oilers | regina pats (whl) |
| 18 | 141 | bob mormina | right wing | canada | philadelphia flyers | longueuil chevaliers (qmjhl) |
| 19 | 142 | ian armstrong | defence | canada | boston bruins | peterborough petes (ohl) | | | | college/junior/club team |
|---:|:------------------------------|
| 0 | cloquet high school (ushs-mn) | | [
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select attendance - attendance where result = 'w 24-21' col : date | opponent# | rank# | site | result | attendance row 1 : september 12 | #1 michigan | none | camp randall stadium • madison, wi | w 21-14 | 68733 row 2 : september 19 | #9 ucla | #20 | camp randall stadium • madison, wi | l 13-31 | 71496 row 3 : september 26 | western michigan | none | camp randall stadium • madison, wi | w 21-10 | 67196 row 4 : october 3 | purdue | none | camp randall stadium • madison, wi | w 20-14 | 68603 row 5 : october 10 | #18 ohio state | none | camp randall stadium • madison, wi | w 24-21 | 78973 row 6 : october 17 | at michigan state | #14 | spartan stadium • east lansing, mi | l 14-33 | 67352 row 7 : october 24 | at illinois | none | memorial stadium • champaign, il | l 21-23 | 67413 row 8 : october 31 | northwestern | none | camp randall stadium • madison, wi | w 52-0 | 70035 row 9 : november 7 | at indiana | none | memorial stadium • bloomington, in | w 28-7 | 44218 row 10 : november 14 | iowa | none | camp randall stadium • madison, wi | l 7-17 | 78731 row 11 : november 21 | at minnesota | none | memorial stadium • minneapolis, mn (paul bunyan's axe) | w 26-21 | 47125 row 12 : december 13 | vs. tennessee | none | giants stadium • east rutherford, nj (garden state bowl) | l 21-28 | 53220 | col : "attendance - attendance" row 1 : attendance - attendance | select attendance - attendance where result = 'w 24-21' <table_name> : table \begin{tabular}{lllllll}
\toprule
& date & opponent# & rank# & site & result & attendance \\
\midrule
0 & september 12 & #1 michigan & none & camp randall stadium • madison, wi & w 21-14 & 68733 \\
1 & september 19 & #9 ucla & #20 & camp randall stadium • madison, wi & l 13-31 & 71496 \\
2 & september 26 & western michigan & none & camp randall stadium • madison, wi & w 21-10 & 67196 \\
3 & october 3 & purdue & none & camp randall stadium • madison, wi & w 20-14 & 68603 \\
4 & october 10 & #18 ohio state & none & camp randall stadium • madison, wi & w 24-21 & 78973 \\
5 & october 17 & at michigan state & #14 & spartan stadium • east lansing, mi & l 14-33 & 67352 \\
6 & october 24 & at illinois & none & memorial stadium • champaign, il & l 21-23 & 67413 \\
7 & october 31 & northwestern & none & camp randall stadium • madison, wi & w 52-0 & 70035 \\
8 & november 7 & at indiana & none & memorial stadium • bloomington, in & w 28-7 & 44218 \\
9 & november 14 & iowa & none & camp randall stadium • madison, wi & l 7-17 & 78731 \\
10 & november 21 & at minnesota & none & memorial stadium • minneapolis, mn (paul bunyan's axe) & w 26-21 & 47125 \\
11 & december 13 & vs. tennessee & none & giants stadium • east rutherford, nj (garden state bowl) & l 21-28 & 53220 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "attendance - attendance" \\
\midrule
0 & attendance - attendance \\
\bottomrule
\end{tabular}
| select attendance - attendance where result = 'w 24-21' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>opponent#</th>
<th>rank#</th>
<th>site</th>
<th>result</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>september 12</td>
<td>#1 michigan</td>
<td>none</td>
<td>camp randall stadium • madison, wi</td>
<td>w 21-14</td>
<td>68733</td>
</tr>
<tr>
<th>1</th>
<td>september 19</td>
<td>#9 ucla</td>
<td>#20</td>
<td>camp randall stadium • madison, wi</td>
<td>l 13-31</td>
<td>71496</td>
</tr>
<tr>
<th>2</th>
<td>september 26</td>
<td>western michigan</td>
<td>none</td>
<td>camp randall stadium • madison, wi</td>
<td>w 21-10</td>
<td>67196</td>
</tr>
<tr>
<th>3</th>
<td>october 3</td>
<td>purdue</td>
<td>none</td>
<td>camp randall stadium • madison, wi</td>
<td>w 20-14</td>
<td>68603</td>
</tr>
<tr>
<th>4</th>
<td>october 10</td>
<td>#18 ohio state</td>
<td>none</td>
<td>camp randall stadium • madison, wi</td>
<td>w 24-21</td>
<td>78973</td>
</tr>
<tr>
<th>5</th>
<td>october 17</td>
<td>at michigan state</td>
<td>#14</td>
<td>spartan stadium • east lansing, mi</td>
<td>l 14-33</td>
<td>67352</td>
</tr>
<tr>
<th>6</th>
<td>october 24</td>
<td>at illinois</td>
<td>none</td>
<td>memorial stadium • champaign, il</td>
<td>l 21-23</td>
<td>67413</td>
</tr>
<tr>
<th>7</th>
<td>october 31</td>
<td>northwestern</td>
<td>none</td>
<td>camp randall stadium • madison, wi</td>
<td>w 52-0</td>
<td>70035</td>
</tr>
<tr>
<th>8</th>
<td>november 7</td>
<td>at indiana</td>
<td>none</td>
<td>memorial stadium • bloomington, in</td>
<td>w 28-7</td>
<td>44218</td>
</tr>
<tr>
<th>9</th>
<td>november 14</td>
<td>iowa</td>
<td>none</td>
<td>camp randall stadium • madison, wi</td>
<td>l 7-17</td>
<td>78731</td>
</tr>
<tr>
<th>10</th>
<td>november 21</td>
<td>at minnesota</td>
<td>none</td>
<td>memorial stadium • minneapolis, mn (paul bunyan's axe)</td>
<td>w 26-21</td>
<td>47125</td>
</tr>
<tr>
<th>11</th>
<td>december 13</td>
<td>vs. tennessee</td>
<td>none</td>
<td>giants stadium • east rutherford, nj (garden state bowl)</td>
<td>l 21-28</td>
<td>53220</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"attendance - attendance"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>attendance - attendance</td>
</tr>
</tbody>
</table> | select attendance - attendance where result = 'w 24-21' <table_name> : table | | date | opponent# | rank# | site | result | attendance |
|---:|:-------------|:------------------|:--------|:---------------------------------------------------------|:---------|-------------:|
| 0 | september 12 | #1 michigan | none | camp randall stadium • madison, wi | w 21-14 | 68733 |
| 1 | september 19 | #9 ucla | #20 | camp randall stadium • madison, wi | l 13-31 | 71496 |
| 2 | september 26 | western michigan | none | camp randall stadium • madison, wi | w 21-10 | 67196 |
| 3 | october 3 | purdue | none | camp randall stadium • madison, wi | w 20-14 | 68603 |
| 4 | october 10 | #18 ohio state | none | camp randall stadium • madison, wi | w 24-21 | 78973 |
| 5 | october 17 | at michigan state | #14 | spartan stadium • east lansing, mi | l 14-33 | 67352 |
| 6 | october 24 | at illinois | none | memorial stadium • champaign, il | l 21-23 | 67413 |
| 7 | october 31 | northwestern | none | camp randall stadium • madison, wi | w 52-0 | 70035 |
| 8 | november 7 | at indiana | none | memorial stadium • bloomington, in | w 28-7 | 44218 |
| 9 | november 14 | iowa | none | camp randall stadium • madison, wi | l 7-17 | 78731 |
| 10 | november 21 | at minnesota | none | memorial stadium • minneapolis, mn (paul bunyan's axe) | w 26-21 | 47125 |
| 11 | december 13 | vs. tennessee | none | giants stadium • east rutherford, nj (garden state bowl) | l 21-28 | 53220 | | | | "attendance - attendance" |
|---:|:----------------------------|
| 0 | attendance - attendance | | [
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select count ( team ) where lost < 342 col : pos | team | played | won | draw | lost | goals for | goals against | goal difference | points | notes row 1 : 1 | fh | 18 | 14 | 2 | 2 | 47 | 20 | 27 | 44 | promoted to 1989 urvalsdeild row 2 : 2 | fylkir | 18 | 9 | 6 | 3 | 39 | 30 | 9 | 33 | promoted to 1989 urvalsdeild row 3 : 3 | viðir | 18 | 8 | 3 | 7 | 38 | 31 | 7 | 27 | none row 4 : 4 | ir | 18 | 8 | 2 | 8 | 31 | 35 | -4 | 26 | none row 5 : 5 | selfoss | 18 | 7 | 4 | 7 | 27 | 26 | 1 | 25 | none row 6 : 6 | tindastoll | 18 | 7 | 2 | 9 | 27 | 31 | -4 | 23 | none row 7 : 7 | breiðablik | 18 | 6 | 5 | 7 | 27 | 33 | -6 | 23 | none row 8 : 8 | ibv | 18 | 6 | 2 | 10 | 29 | 36 | -7 | 20 | none row 9 : 9 | ks | 18 | 5 | 4 | 9 | 38 | 46 | -8 | 19 | relegated to 1989 2. deild row 10 : 10 | þrottur r | 18 | 2 | 6 | 10 | 27 | 42 | -15 | 12 | relegated to 1989 2. deild | col : count ( "team" ) row 1 : 4 | select count ( team ) where lost < 342 <table_name> : table \begin{tabular}{llllllllllll}
\toprule
& pos & team & played & won & draw & lost & goals for & goals against & goal difference & points & notes \\
\midrule
0 & 1 & fh & 18 & 14 & 2 & 2 & 47 & 20 & 27 & 44 & promoted to 1989 urvalsdeild \\
1 & 2 & fylkir & 18 & 9 & 6 & 3 & 39 & 30 & 9 & 33 & promoted to 1989 urvalsdeild \\
2 & 3 & viðir & 18 & 8 & 3 & 7 & 38 & 31 & 7 & 27 & none \\
3 & 4 & ir & 18 & 8 & 2 & 8 & 31 & 35 & -4 & 26 & none \\
4 & 5 & selfoss & 18 & 7 & 4 & 7 & 27 & 26 & 1 & 25 & none \\
5 & 6 & tindastoll & 18 & 7 & 2 & 9 & 27 & 31 & -4 & 23 & none \\
6 & 7 & breiðablik & 18 & 6 & 5 & 7 & 27 & 33 & -6 & 23 & none \\
7 & 8 & ibv & 18 & 6 & 2 & 10 & 29 & 36 & -7 & 20 & none \\
8 & 9 & ks & 18 & 5 & 4 & 9 & 38 & 46 & -8 & 19 & relegated to 1989 2. deild \\
9 & 10 & þrottur r & 18 & 2 & 6 & 10 & 27 & 42 & -15 & 12 & relegated to 1989 2. deild \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "team" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( team ) where lost < 342 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>team</th>
<th>played</th>
<th>won</th>
<th>draw</th>
<th>lost</th>
<th>goals for</th>
<th>goals against</th>
<th>goal difference</th>
<th>points</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>fh</td>
<td>18</td>
<td>14</td>
<td>2</td>
<td>2</td>
<td>47</td>
<td>20</td>
<td>27</td>
<td>44</td>
<td>promoted to 1989 urvalsdeild</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>fylkir</td>
<td>18</td>
<td>9</td>
<td>6</td>
<td>3</td>
<td>39</td>
<td>30</td>
<td>9</td>
<td>33</td>
<td>promoted to 1989 urvalsdeild</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>viðir</td>
<td>18</td>
<td>8</td>
<td>3</td>
<td>7</td>
<td>38</td>
<td>31</td>
<td>7</td>
<td>27</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>ir</td>
<td>18</td>
<td>8</td>
<td>2</td>
<td>8</td>
<td>31</td>
<td>35</td>
<td>-4</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>selfoss</td>
<td>18</td>
<td>7</td>
<td>4</td>
<td>7</td>
<td>27</td>
<td>26</td>
<td>1</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>tindastoll</td>
<td>18</td>
<td>7</td>
<td>2</td>
<td>9</td>
<td>27</td>
<td>31</td>
<td>-4</td>
<td>23</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>breiðablik</td>
<td>18</td>
<td>6</td>
<td>5</td>
<td>7</td>
<td>27</td>
<td>33</td>
<td>-6</td>
<td>23</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>ibv</td>
<td>18</td>
<td>6</td>
<td>2</td>
<td>10</td>
<td>29</td>
<td>36</td>
<td>-7</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>ks</td>
<td>18</td>
<td>5</td>
<td>4</td>
<td>9</td>
<td>38</td>
<td>46</td>
<td>-8</td>
<td>19</td>
<td>relegated to 1989 2. deild</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>þrottur r</td>
<td>18</td>
<td>2</td>
<td>6</td>
<td>10</td>
<td>27</td>
<td>42</td>
<td>-15</td>
<td>12</td>
<td>relegated to 1989 2. deild</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "team" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select count ( team ) where lost < 342 <table_name> : table | | pos | team | played | won | draw | lost | goals for | goals against | goal difference | points | notes |
|---:|------:|:-----------|---------:|------:|-------:|-------:|------------:|----------------:|------------------:|---------:|:-----------------------------|
| 0 | 1 | fh | 18 | 14 | 2 | 2 | 47 | 20 | 27 | 44 | promoted to 1989 urvalsdeild |
| 1 | 2 | fylkir | 18 | 9 | 6 | 3 | 39 | 30 | 9 | 33 | promoted to 1989 urvalsdeild |
| 2 | 3 | viðir | 18 | 8 | 3 | 7 | 38 | 31 | 7 | 27 | none |
| 3 | 4 | ir | 18 | 8 | 2 | 8 | 31 | 35 | -4 | 26 | none |
| 4 | 5 | selfoss | 18 | 7 | 4 | 7 | 27 | 26 | 1 | 25 | none |
| 5 | 6 | tindastoll | 18 | 7 | 2 | 9 | 27 | 31 | -4 | 23 | none |
| 6 | 7 | breiðablik | 18 | 6 | 5 | 7 | 27 | 33 | -6 | 23 | none |
| 7 | 8 | ibv | 18 | 6 | 2 | 10 | 29 | 36 | -7 | 20 | none |
| 8 | 9 | ks | 18 | 5 | 4 | 9 | 38 | 46 | -8 | 19 | relegated to 1989 2. deild |
| 9 | 10 | þrottur r | 18 | 2 | 6 | 10 | 27 | 42 | -15 | 12 | relegated to 1989 2. deild | | | | count ( "team" ) |
|---:|-------------------:|
| 0 | 4 | | [
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] |
select school where runners-up = 0 col : school | location | outright titles | shared titles | runners-up | total finals | last title | last final row 1 : methodist college belfast | belfast | 35 | 2 | 25 | 62 | 2014 | 2014 row 2 : royal belfast academical institution | belfast | 29 | 4 | 21 | 54 | 2007 | 2013 row 3 : campbell college | belfast | 23 | 4 | 12 | 39 | 2011 | 2011 row 4 : coleraine academical institution | coleraine | 9 | 0 | 24 | 33 | 1992 | 1998 row 5 : the royal school, armagh | armagh | 9 | 0 | 3 | 12 | 2004 | 2004 row 6 : portora royal school | enniskillen | 6 | 1 | 5 | 12 | 1942 | 1942 row 7 : bangor grammar school | bangor | 5 | 0 | 4 | 9 | 1988 | 1995 row 8 : ballymena academy | ballymena | 3 | 0 | 6 | 9 | 2010 | 2010 row 9 : rainey endowed school | magherafelt | 2 | 1 | 2 | 5 | 1982 | 1982 row 10 : foyle college | londonderry | 2 | 0 | 4 | 6 | 1915 | 1915 row 11 : belfast royal academy | belfast | 1 | 3 | 5 | 9 | 1997 | 2010 row 12 : regent house grammar school | newtownards | 1 | 1 | 2 | 4 | 1996 | 2008 row 13 : royal school dungannon | dungannon | 1 | 0 | 4 | 5 | 1907 | 1975 row 14 : annadale grammar school (now wellington college) | belfast | 1 | 0 | 1 | 2 | 1958 | 1978 row 15 : ballyclare high school | ballyclare | 1 | 0 | 1 | 2 | 1973 | 2012 row 16 : belfast boys' model school | belfast | 1 | 0 | 0 | 1 | 1971 | 1971 row 17 : grosvenor high school | belfast | 1 | 0 | 0 | 1 | 1983 | 1983 row 18 : wallace high school | lisburn | 0 | 0 | 4 | 4 | none | 2007 row 19 : derry academy | derry | 0 | 0 | 2 | 2 | none | 1896 row 20 : dalriada school | ballymoney | 0 | 0 | 1 | 1 | none | 1993 row 21 : galway grammar school | galway | 0 | 0 | 1 | 1 | none | 1887 row 22 : lurgan college | lurgan | 0 | 0 | 1 | 1 | none | 1934 row 23 : omagh academy | omagh | 0 | 0 | 1 | 1 | none | 1985 row 24 : sullivan upper school | holywood | 0 | 0 | 1 | 1 | none | 2014 | col : school row 1 : belfast boys' model school row 2 : grosvenor high school | select school where runners-up = 0 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& school & location & outright titles & shared titles & runners-up & total finals & last title & last final \\
\midrule
0 & methodist college belfast & belfast & 35 & 2 & 25 & 62 & 2014 & 2014 \\
1 & royal belfast academical institution & belfast & 29 & 4 & 21 & 54 & 2007 & 2013 \\
2 & campbell college & belfast & 23 & 4 & 12 & 39 & 2011 & 2011 \\
3 & coleraine academical institution & coleraine & 9 & 0 & 24 & 33 & 1992 & 1998 \\
4 & the royal school, armagh & armagh & 9 & 0 & 3 & 12 & 2004 & 2004 \\
5 & portora royal school & enniskillen & 6 & 1 & 5 & 12 & 1942 & 1942 \\
6 & bangor grammar school & bangor & 5 & 0 & 4 & 9 & 1988 & 1995 \\
7 & ballymena academy & ballymena & 3 & 0 & 6 & 9 & 2010 & 2010 \\
8 & rainey endowed school & magherafelt & 2 & 1 & 2 & 5 & 1982 & 1982 \\
9 & foyle college & londonderry & 2 & 0 & 4 & 6 & 1915 & 1915 \\
10 & belfast royal academy & belfast & 1 & 3 & 5 & 9 & 1997 & 2010 \\
11 & regent house grammar school & newtownards & 1 & 1 & 2 & 4 & 1996 & 2008 \\
12 & royal school dungannon & dungannon & 1 & 0 & 4 & 5 & 1907 & 1975 \\
13 & annadale grammar school (now wellington college) & belfast & 1 & 0 & 1 & 2 & 1958 & 1978 \\
14 & ballyclare high school & ballyclare & 1 & 0 & 1 & 2 & 1973 & 2012 \\
15 & belfast boys' model school & belfast & 1 & 0 & 0 & 1 & 1971 & 1971 \\
16 & grosvenor high school & belfast & 1 & 0 & 0 & 1 & 1983 & 1983 \\
17 & wallace high school & lisburn & 0 & 0 & 4 & 4 & none & 2007 \\
18 & derry academy & derry & 0 & 0 & 2 & 2 & none & 1896 \\
19 & dalriada school & ballymoney & 0 & 0 & 1 & 1 & none & 1993 \\
20 & galway grammar school & galway & 0 & 0 & 1 & 1 & none & 1887 \\
21 & lurgan college & lurgan & 0 & 0 & 1 & 1 & none & 1934 \\
22 & omagh academy & omagh & 0 & 0 & 1 & 1 & none & 1985 \\
23 & sullivan upper school & holywood & 0 & 0 & 1 & 1 & none & 2014 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& school \\
\midrule
0 & belfast boys' model school \\
1 & grosvenor high school \\
\bottomrule
\end{tabular}
| select school where runners-up = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>school</th>
<th>location</th>
<th>outright titles</th>
<th>shared titles</th>
<th>runners-up</th>
<th>total finals</th>
<th>last title</th>
<th>last final</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>methodist college belfast</td>
<td>belfast</td>
<td>35</td>
<td>2</td>
<td>25</td>
<td>62</td>
<td>2014</td>
<td>2014</td>
</tr>
<tr>
<th>1</th>
<td>royal belfast academical institution</td>
<td>belfast</td>
<td>29</td>
<td>4</td>
<td>21</td>
<td>54</td>
<td>2007</td>
<td>2013</td>
</tr>
<tr>
<th>2</th>
<td>campbell college</td>
<td>belfast</td>
<td>23</td>
<td>4</td>
<td>12</td>
<td>39</td>
<td>2011</td>
<td>2011</td>
</tr>
<tr>
<th>3</th>
<td>coleraine academical institution</td>
<td>coleraine</td>
<td>9</td>
<td>0</td>
<td>24</td>
<td>33</td>
<td>1992</td>
<td>1998</td>
</tr>
<tr>
<th>4</th>
<td>the royal school, armagh</td>
<td>armagh</td>
<td>9</td>
<td>0</td>
<td>3</td>
<td>12</td>
<td>2004</td>
<td>2004</td>
</tr>
<tr>
<th>5</th>
<td>portora royal school</td>
<td>enniskillen</td>
<td>6</td>
<td>1</td>
<td>5</td>
<td>12</td>
<td>1942</td>
<td>1942</td>
</tr>
<tr>
<th>6</th>
<td>bangor grammar school</td>
<td>bangor</td>
<td>5</td>
<td>0</td>
<td>4</td>
<td>9</td>
<td>1988</td>
<td>1995</td>
</tr>
<tr>
<th>7</th>
<td>ballymena academy</td>
<td>ballymena</td>
<td>3</td>
<td>0</td>
<td>6</td>
<td>9</td>
<td>2010</td>
<td>2010</td>
</tr>
<tr>
<th>8</th>
<td>rainey endowed school</td>
<td>magherafelt</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>5</td>
<td>1982</td>
<td>1982</td>
</tr>
<tr>
<th>9</th>
<td>foyle college</td>
<td>londonderry</td>
<td>2</td>
<td>0</td>
<td>4</td>
<td>6</td>
<td>1915</td>
<td>1915</td>
</tr>
<tr>
<th>10</th>
<td>belfast royal academy</td>
<td>belfast</td>
<td>1</td>
<td>3</td>
<td>5</td>
<td>9</td>
<td>1997</td>
<td>2010</td>
</tr>
<tr>
<th>11</th>
<td>regent house grammar school</td>
<td>newtownards</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>4</td>
<td>1996</td>
<td>2008</td>
</tr>
<tr>
<th>12</th>
<td>royal school dungannon</td>
<td>dungannon</td>
<td>1</td>
<td>0</td>
<td>4</td>
<td>5</td>
<td>1907</td>
<td>1975</td>
</tr>
<tr>
<th>13</th>
<td>annadale grammar school (now wellington college)</td>
<td>belfast</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
<td>1958</td>
<td>1978</td>
</tr>
<tr>
<th>14</th>
<td>ballyclare high school</td>
<td>ballyclare</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
<td>1973</td>
<td>2012</td>
</tr>
<tr>
<th>15</th>
<td>belfast boys' model school</td>
<td>belfast</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1971</td>
<td>1971</td>
</tr>
<tr>
<th>16</th>
<td>grosvenor high school</td>
<td>belfast</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1983</td>
<td>1983</td>
</tr>
<tr>
<th>17</th>
<td>wallace high school</td>
<td>lisburn</td>
<td>0</td>
<td>0</td>
<td>4</td>
<td>4</td>
<td>none</td>
<td>2007</td>
</tr>
<tr>
<th>18</th>
<td>derry academy</td>
<td>derry</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
<td>none</td>
<td>1896</td>
</tr>
<tr>
<th>19</th>
<td>dalriada school</td>
<td>ballymoney</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1993</td>
</tr>
<tr>
<th>20</th>
<td>galway grammar school</td>
<td>galway</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1887</td>
</tr>
<tr>
<th>21</th>
<td>lurgan college</td>
<td>lurgan</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1934</td>
</tr>
<tr>
<th>22</th>
<td>omagh academy</td>
<td>omagh</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1985</td>
</tr>
<tr>
<th>23</th>
<td>sullivan upper school</td>
<td>holywood</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>2014</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>school</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>belfast boys' model school</td>
</tr>
<tr>
<th>1</th>
<td>grosvenor high school</td>
</tr>
</tbody>
</table> | select school where runners-up = 0 <table_name> : table | | school | location | outright titles | shared titles | runners-up | total finals | last title | last final |
|---:|:-------------------------------------------------|:------------|------------------:|----------------:|-------------:|---------------:|:-------------|-------------:|
| 0 | methodist college belfast | belfast | 35 | 2 | 25 | 62 | 2014 | 2014 |
| 1 | royal belfast academical institution | belfast | 29 | 4 | 21 | 54 | 2007 | 2013 |
| 2 | campbell college | belfast | 23 | 4 | 12 | 39 | 2011 | 2011 |
| 3 | coleraine academical institution | coleraine | 9 | 0 | 24 | 33 | 1992 | 1998 |
| 4 | the royal school, armagh | armagh | 9 | 0 | 3 | 12 | 2004 | 2004 |
| 5 | portora royal school | enniskillen | 6 | 1 | 5 | 12 | 1942 | 1942 |
| 6 | bangor grammar school | bangor | 5 | 0 | 4 | 9 | 1988 | 1995 |
| 7 | ballymena academy | ballymena | 3 | 0 | 6 | 9 | 2010 | 2010 |
| 8 | rainey endowed school | magherafelt | 2 | 1 | 2 | 5 | 1982 | 1982 |
| 9 | foyle college | londonderry | 2 | 0 | 4 | 6 | 1915 | 1915 |
| 10 | belfast royal academy | belfast | 1 | 3 | 5 | 9 | 1997 | 2010 |
| 11 | regent house grammar school | newtownards | 1 | 1 | 2 | 4 | 1996 | 2008 |
| 12 | royal school dungannon | dungannon | 1 | 0 | 4 | 5 | 1907 | 1975 |
| 13 | annadale grammar school (now wellington college) | belfast | 1 | 0 | 1 | 2 | 1958 | 1978 |
| 14 | ballyclare high school | ballyclare | 1 | 0 | 1 | 2 | 1973 | 2012 |
| 15 | belfast boys' model school | belfast | 1 | 0 | 0 | 1 | 1971 | 1971 |
| 16 | grosvenor high school | belfast | 1 | 0 | 0 | 1 | 1983 | 1983 |
| 17 | wallace high school | lisburn | 0 | 0 | 4 | 4 | none | 2007 |
| 18 | derry academy | derry | 0 | 0 | 2 | 2 | none | 1896 |
| 19 | dalriada school | ballymoney | 0 | 0 | 1 | 1 | none | 1993 |
| 20 | galway grammar school | galway | 0 | 0 | 1 | 1 | none | 1887 |
| 21 | lurgan college | lurgan | 0 | 0 | 1 | 1 | none | 1934 |
| 22 | omagh academy | omagh | 0 | 0 | 1 | 1 | none | 1985 |
| 23 | sullivan upper school | holywood | 0 | 0 | 1 | 1 | none | 2014 | | | | school |
|---:|:---------------------------|
| 0 | belfast boys' model school |
| 1 | grosvenor high school | | [
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] |
select count ( * ) where winning vehicle (ta2) = '2' col : round | date | circuit | winning driver (ta2) | winning vehicle (ta2) | winning driver (ta1) | winning vehicle (ta1) row 1 : 1 | may 21 | sears point | greg pickett | chevrolet corvette | gene bothello | chevrolet corvette row 2 : 2 | june 4 | westwood | ludwig heimrath | porsche 935 | nick engels | chevrolet corvette row 3 : 3 | june 11 | portland | tuck thomas | chevrolet monza | bob matkowitch | chevrolet corvette row 4 : 4 | june 25 | mont-tremblant | monte sheldon | porsche 935 | bob tullius | jaguar xjs row 5 : 5 | july 8 | watkins glen | hal shaw, jr. monte shelton | porsche 935 | brian fuerstenau bob tullius | jaguar xjs row 6 : 6 | august 13 | brainerd | jerry hansen | chevrolet monza | bob tullius | jaguar xjs row 7 : 7 | august 19 | mosport | greg pickett | chevrolet corvette | bob tullius | jaguar xjs row 8 : 8 | september 4 | road america | greg pickett | chevrolet corvette | bob tullius | jaguar xjs row 9 : 9 | october 8 | laguna seca | greg pickett | chevrolet corvette | bob tullius | jaguar xjs row 10 : 10 | november 5 | mexico city | ludwig heimrath | porsche 935 | bob tullius | jaguar xjs | col : count ( "*" ) row 1 : 0 | select count ( * ) where winning vehicle (ta2) = '2' <table_name> : table \begin{tabular}{llllllll}
\toprule
& round & date & circuit & winning driver (ta2) & winning vehicle (ta2) & winning driver (ta1) & winning vehicle (ta1) \\
\midrule
0 & 1 & may 21 & sears point & greg pickett & chevrolet corvette & gene bothello & chevrolet corvette \\
1 & 2 & june 4 & westwood & ludwig heimrath & porsche 935 & nick engels & chevrolet corvette \\
2 & 3 & june 11 & portland & tuck thomas & chevrolet monza & bob matkowitch & chevrolet corvette \\
3 & 4 & june 25 & mont-tremblant & monte sheldon & porsche 935 & bob tullius & jaguar xjs \\
4 & 5 & july 8 & watkins glen & hal shaw, jr. monte shelton & porsche 935 & brian fuerstenau bob tullius & jaguar xjs \\
5 & 6 & august 13 & brainerd & jerry hansen & chevrolet monza & bob tullius & jaguar xjs \\
6 & 7 & august 19 & mosport & greg pickett & chevrolet corvette & bob tullius & jaguar xjs \\
7 & 8 & september 4 & road america & greg pickett & chevrolet corvette & bob tullius & jaguar xjs \\
8 & 9 & october 8 & laguna seca & greg pickett & chevrolet corvette & bob tullius & jaguar xjs \\
9 & 10 & november 5 & mexico city & ludwig heimrath & porsche 935 & bob tullius & jaguar xjs \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where winning vehicle (ta2) = '2' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>round</th>
<th>date</th>
<th>circuit</th>
<th>winning driver (ta2)</th>
<th>winning vehicle (ta2)</th>
<th>winning driver (ta1)</th>
<th>winning vehicle (ta1)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>may 21</td>
<td>sears point</td>
<td>greg pickett</td>
<td>chevrolet corvette</td>
<td>gene bothello</td>
<td>chevrolet corvette</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>june 4</td>
<td>westwood</td>
<td>ludwig heimrath</td>
<td>porsche 935</td>
<td>nick engels</td>
<td>chevrolet corvette</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>june 11</td>
<td>portland</td>
<td>tuck thomas</td>
<td>chevrolet monza</td>
<td>bob matkowitch</td>
<td>chevrolet corvette</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>june 25</td>
<td>mont-tremblant</td>
<td>monte sheldon</td>
<td>porsche 935</td>
<td>bob tullius</td>
<td>jaguar xjs</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>july 8</td>
<td>watkins glen</td>
<td>hal shaw, jr. monte shelton</td>
<td>porsche 935</td>
<td>brian fuerstenau bob tullius</td>
<td>jaguar xjs</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>august 13</td>
<td>brainerd</td>
<td>jerry hansen</td>
<td>chevrolet monza</td>
<td>bob tullius</td>
<td>jaguar xjs</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>august 19</td>
<td>mosport</td>
<td>greg pickett</td>
<td>chevrolet corvette</td>
<td>bob tullius</td>
<td>jaguar xjs</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>september 4</td>
<td>road america</td>
<td>greg pickett</td>
<td>chevrolet corvette</td>
<td>bob tullius</td>
<td>jaguar xjs</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>october 8</td>
<td>laguna seca</td>
<td>greg pickett</td>
<td>chevrolet corvette</td>
<td>bob tullius</td>
<td>jaguar xjs</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>november 5</td>
<td>mexico city</td>
<td>ludwig heimrath</td>
<td>porsche 935</td>
<td>bob tullius</td>
<td>jaguar xjs</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where winning vehicle (ta2) = '2' <table_name> : table | | round | date | circuit | winning driver (ta2) | winning vehicle (ta2) | winning driver (ta1) | winning vehicle (ta1) |
|---:|--------:|:------------|:---------------|:----------------------------|:------------------------|:-----------------------------|:------------------------|
| 0 | 1 | may 21 | sears point | greg pickett | chevrolet corvette | gene bothello | chevrolet corvette |
| 1 | 2 | june 4 | westwood | ludwig heimrath | porsche 935 | nick engels | chevrolet corvette |
| 2 | 3 | june 11 | portland | tuck thomas | chevrolet monza | bob matkowitch | chevrolet corvette |
| 3 | 4 | june 25 | mont-tremblant | monte sheldon | porsche 935 | bob tullius | jaguar xjs |
| 4 | 5 | july 8 | watkins glen | hal shaw, jr. monte shelton | porsche 935 | brian fuerstenau bob tullius | jaguar xjs |
| 5 | 6 | august 13 | brainerd | jerry hansen | chevrolet monza | bob tullius | jaguar xjs |
| 6 | 7 | august 19 | mosport | greg pickett | chevrolet corvette | bob tullius | jaguar xjs |
| 7 | 8 | september 4 | road america | greg pickett | chevrolet corvette | bob tullius | jaguar xjs |
| 8 | 9 | october 8 | laguna seca | greg pickett | chevrolet corvette | bob tullius | jaguar xjs |
| 9 | 10 | november 5 | mexico city | ludwig heimrath | porsche 935 | bob tullius | jaguar xjs | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select time where tv = 'espn' col : date | time | opponent | site | tv | result | attendance row 1 : september 5 | 2:30 p.m | jackson state | davis wade stadium • starkville, ms | espnu | w 45-7 | 54232 row 2 : september 12 | 6:00 p.m | at auburn | jordan-hare stadium • auburn, al | secrn | l 24-49 | 85269 row 3 : september 19 | 6:00 p.m | at vanderbilt | vanderbilt stadium • nashville, tn | secrn | w 15-3 | 31840 row 4 : september 26 | 11:21 a.m | #7 lsu | davis wade stadium • starkville, ms | secn | l 26-30 | 53612 row 5 : october 3 | 6:30 p.m | #25 georgia tech | davis wade stadium • starkville, ms | css | l 31-42 | 50035 row 6 : october 10 | 11:30 a.m | houston | davis wade stadium • starkville, ms | espnu | l 24-31 | 48019 row 7 : october 17 | 11:30 a.m | at middle tennessee | johnny "red" floyd stadium • murfreesboro, tn | espnu | w 27-6 | 23882 row 8 : october 24 | 6:30 p.m | #1 florida | davis wade stadium • starkville, ms | espn | l 19-29 | 57178 row 9 : october 31 | 6:00 p.m | at kentucky | commonwealth stadium • lexington, ky | secrn | w 31-24 | 67953 row 10 : november 14 | 6:00 p.m | #2 alabama | davis wade stadium • starkville, ms (rivalry) | espn | l 3-31 | 58103 row 11 : november 21 | 11:21 a.m | at arkansas | war memorial stadium • little rock, ar | secn | l 21-42 | 55634 row 12 : november 28 | 11:21 a.m | #25 ole miss | davis wade stadium • starkville, ms (egg bowl) | secn | w 41-27 | 55365 | col : time row 1 : 6:30 p.m row 2 : 6:00 p.m | select time where tv = 'espn' <table_name> : table \begin{tabular}{llllllll}
\toprule
& date & time & opponent & site & tv & result & attendance \\
\midrule
0 & september 5 & 2:30 p.m & jackson state & davis wade stadium • starkville, ms & espnu & w 45-7 & 54232 \\
1 & september 12 & 6:00 p.m & at auburn & jordan-hare stadium • auburn, al & secrn & l 24-49 & 85269 \\
2 & september 19 & 6:00 p.m & at vanderbilt & vanderbilt stadium • nashville, tn & secrn & w 15-3 & 31840 \\
3 & september 26 & 11:21 a.m & #7 lsu & davis wade stadium • starkville, ms & secn & l 26-30 & 53612 \\
4 & october 3 & 6:30 p.m & #25 georgia tech & davis wade stadium • starkville, ms & css & l 31-42 & 50035 \\
5 & october 10 & 11:30 a.m & houston & davis wade stadium • starkville, ms & espnu & l 24-31 & 48019 \\
6 & october 17 & 11:30 a.m & at middle tennessee & johnny "red" floyd stadium • murfreesboro, tn & espnu & w 27-6 & 23882 \\
7 & october 24 & 6:30 p.m & #1 florida & davis wade stadium • starkville, ms & espn & l 19-29 & 57178 \\
8 & october 31 & 6:00 p.m & at kentucky & commonwealth stadium • lexington, ky & secrn & w 31-24 & 67953 \\
9 & november 14 & 6:00 p.m & #2 alabama & davis wade stadium • starkville, ms (rivalry) & espn & l 3-31 & 58103 \\
10 & november 21 & 11:21 a.m & at arkansas & war memorial stadium • little rock, ar & secn & l 21-42 & 55634 \\
11 & november 28 & 11:21 a.m & #25 ole miss & davis wade stadium • starkville, ms (egg bowl) & secn & w 41-27 & 55365 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& time \\
\midrule
0 & 6:30 p.m \\
1 & 6:00 p.m \\
\bottomrule
\end{tabular}
| select time where tv = 'espn' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>time</th>
<th>opponent</th>
<th>site</th>
<th>tv</th>
<th>result</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>september 5</td>
<td>2:30 p.m</td>
<td>jackson state</td>
<td>davis wade stadium • starkville, ms</td>
<td>espnu</td>
<td>w 45-7</td>
<td>54232</td>
</tr>
<tr>
<th>1</th>
<td>september 12</td>
<td>6:00 p.m</td>
<td>at auburn</td>
<td>jordan-hare stadium • auburn, al</td>
<td>secrn</td>
<td>l 24-49</td>
<td>85269</td>
</tr>
<tr>
<th>2</th>
<td>september 19</td>
<td>6:00 p.m</td>
<td>at vanderbilt</td>
<td>vanderbilt stadium • nashville, tn</td>
<td>secrn</td>
<td>w 15-3</td>
<td>31840</td>
</tr>
<tr>
<th>3</th>
<td>september 26</td>
<td>11:21 a.m</td>
<td>#7 lsu</td>
<td>davis wade stadium • starkville, ms</td>
<td>secn</td>
<td>l 26-30</td>
<td>53612</td>
</tr>
<tr>
<th>4</th>
<td>october 3</td>
<td>6:30 p.m</td>
<td>#25 georgia tech</td>
<td>davis wade stadium • starkville, ms</td>
<td>css</td>
<td>l 31-42</td>
<td>50035</td>
</tr>
<tr>
<th>5</th>
<td>october 10</td>
<td>11:30 a.m</td>
<td>houston</td>
<td>davis wade stadium • starkville, ms</td>
<td>espnu</td>
<td>l 24-31</td>
<td>48019</td>
</tr>
<tr>
<th>6</th>
<td>october 17</td>
<td>11:30 a.m</td>
<td>at middle tennessee</td>
<td>johnny "red" floyd stadium • murfreesboro, tn</td>
<td>espnu</td>
<td>w 27-6</td>
<td>23882</td>
</tr>
<tr>
<th>7</th>
<td>october 24</td>
<td>6:30 p.m</td>
<td>#1 florida</td>
<td>davis wade stadium • starkville, ms</td>
<td>espn</td>
<td>l 19-29</td>
<td>57178</td>
</tr>
<tr>
<th>8</th>
<td>october 31</td>
<td>6:00 p.m</td>
<td>at kentucky</td>
<td>commonwealth stadium • lexington, ky</td>
<td>secrn</td>
<td>w 31-24</td>
<td>67953</td>
</tr>
<tr>
<th>9</th>
<td>november 14</td>
<td>6:00 p.m</td>
<td>#2 alabama</td>
<td>davis wade stadium • starkville, ms (rivalry)</td>
<td>espn</td>
<td>l 3-31</td>
<td>58103</td>
</tr>
<tr>
<th>10</th>
<td>november 21</td>
<td>11:21 a.m</td>
<td>at arkansas</td>
<td>war memorial stadium • little rock, ar</td>
<td>secn</td>
<td>l 21-42</td>
<td>55634</td>
</tr>
<tr>
<th>11</th>
<td>november 28</td>
<td>11:21 a.m</td>
<td>#25 ole miss</td>
<td>davis wade stadium • starkville, ms (egg bowl)</td>
<td>secn</td>
<td>w 41-27</td>
<td>55365</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>6:30 p.m</td>
</tr>
<tr>
<th>1</th>
<td>6:00 p.m</td>
</tr>
</tbody>
</table> | select time where tv = 'espn' <table_name> : table | | date | time | opponent | site | tv | result | attendance |
|---:|:-------------|:----------|:--------------------|:-----------------------------------------------|:------|:---------|-------------:|
| 0 | september 5 | 2:30 p.m | jackson state | davis wade stadium • starkville, ms | espnu | w 45-7 | 54232 |
| 1 | september 12 | 6:00 p.m | at auburn | jordan-hare stadium • auburn, al | secrn | l 24-49 | 85269 |
| 2 | september 19 | 6:00 p.m | at vanderbilt | vanderbilt stadium • nashville, tn | secrn | w 15-3 | 31840 |
| 3 | september 26 | 11:21 a.m | #7 lsu | davis wade stadium • starkville, ms | secn | l 26-30 | 53612 |
| 4 | october 3 | 6:30 p.m | #25 georgia tech | davis wade stadium • starkville, ms | css | l 31-42 | 50035 |
| 5 | october 10 | 11:30 a.m | houston | davis wade stadium • starkville, ms | espnu | l 24-31 | 48019 |
| 6 | october 17 | 11:30 a.m | at middle tennessee | johnny "red" floyd stadium • murfreesboro, tn | espnu | w 27-6 | 23882 |
| 7 | october 24 | 6:30 p.m | #1 florida | davis wade stadium • starkville, ms | espn | l 19-29 | 57178 |
| 8 | october 31 | 6:00 p.m | at kentucky | commonwealth stadium • lexington, ky | secrn | w 31-24 | 67953 |
| 9 | november 14 | 6:00 p.m | #2 alabama | davis wade stadium • starkville, ms (rivalry) | espn | l 3-31 | 58103 |
| 10 | november 21 | 11:21 a.m | at arkansas | war memorial stadium • little rock, ar | secn | l 21-42 | 55634 |
| 11 | november 28 | 11:21 a.m | #25 ole miss | davis wade stadium • starkville, ms (egg bowl) | secn | w 41-27 | 55365 | | | | time |
|---:|:---------|
| 0 | 6:30 p.m |
| 1 | 6:00 p.m | | [
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select nation where gold = 9 col : rank | nation | gold | silver | bronze | total row 1 : 1 | japan | 5 | 2 | 0 | 7 row 2 : 2 | china | 4 | 3 | 2 | 9 row 3 : 3 | south korea | 0 | 3 | 1 | 4 row 4 : 4 | north korea | 0 | 1 | 0 | 1 row 5 : 5 | chinese taipei | 0 | 0 | 3 | 3 row 6 : 5 | thailand | 0 | 0 | 3 | 3 row 7 : total | total | 9 | 9 | 9 | 27 | col : nation row 1 : total | select nation where gold = 9 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & japan & 5 & 2 & 0 & 7 \\
1 & 2 & china & 4 & 3 & 2 & 9 \\
2 & 3 & south korea & 0 & 3 & 1 & 4 \\
3 & 4 & north korea & 0 & 1 & 0 & 1 \\
4 & 5 & chinese taipei & 0 & 0 & 3 & 3 \\
5 & 5 & thailand & 0 & 0 & 3 & 3 \\
6 & total & total & 9 & 9 & 9 & 27 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & total \\
\bottomrule
\end{tabular}
| select nation where gold = 9 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>japan</td>
<td>5</td>
<td>2</td>
<td>0</td>
<td>7</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>china</td>
<td>4</td>
<td>3</td>
<td>2</td>
<td>9</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>south korea</td>
<td>0</td>
<td>3</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>north korea</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>chinese taipei</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>thailand</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>total</td>
<td>total</td>
<td>9</td>
<td>9</td>
<td>9</td>
<td>27</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>total</td>
</tr>
</tbody>
</table> | select nation where gold = 9 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------|-------:|---------:|---------:|--------:|
| 0 | 1 | japan | 5 | 2 | 0 | 7 |
| 1 | 2 | china | 4 | 3 | 2 | 9 |
| 2 | 3 | south korea | 0 | 3 | 1 | 4 |
| 3 | 4 | north korea | 0 | 1 | 0 | 1 |
| 4 | 5 | chinese taipei | 0 | 0 | 3 | 3 |
| 5 | 5 | thailand | 0 | 0 | 3 | 3 |
| 6 | total | total | 9 | 9 | 9 | 27 | | | | nation |
|---:|:---------|
| 0 | total | | [
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select count ( team ) where winners = 3 col : team | winners | runners-up | years won | years runner-up row 1 : liverpool | 8 | 3 | 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 | 1978, 1987, 2005 row 2 : aston villa | 5 | 3 | 1961, 1975, 1977, 1994, 1996 | 1963, 1971, 2010 row 3 : manchester united | 4 | 4 | 1992, 2006, 2009, 2010 | 1983, 1991, 1994, 2003 row 4 : tottenham hotspur | 4 | 3 | 1971, 1973, 1999, 2008 | 1982, 2002, 2009 row 5 : chelsea | 4 | 2 | 1965, 1998, 2005, 2007 | 1972, 2008 row 6 : nottingham forest | 4 | 2 | 1978, 1979, 1989, 1990 | 1980, 1992 row 7 : leicester city | 3 | 2 | 1964, 1997, 2000 | 1965, 1999 row 8 : manchester city | 3 | 1 | 1970, 1976, 2014 | 1974 row 9 : arsenal | 2 | 5 | 1987, 1993 | 1968, 1969, 1988, 2007, 2011 row 10 : norwich city | 2 | 2 | 1962, 1985 | 1973, 1975 row 11 : birmingham city | 2 | 1 | 1963, 2011 | 2001 row 12 : wolverhampton wanderers | 2 | 0 | 1974, 1980 | none row 13 : west bromwich albion | 1 | 2 | 1966 | 1967, 1970 row 14 : middlesbrough | 1 | 2 | 2004 | 1997, 1998 row 15 : queens park rangers | 1 | 1 | 1967 | 1986 row 16 : leeds united | 1 | 1 | 1968 | 1996 row 17 : stoke city | 1 | 1 | 1972 | 1964 row 18 : luton town | 1 | 1 | 1988 | 1989 row 19 : sheffield wednesday | 1 | 1 | 1991 | 1993 row 20 : swindon town | 1 | 0 | 1969 | none row 21 : oxford united | 1 | 0 | 1986 | none row 22 : blackburn rovers | 1 | 0 | 2002 | none row 23 : swansea city | 1 | 0 | 2013 | none row 24 : west ham united | 0 | 2 | none | 1966, 1981 row 25 : everton | 0 | 2 | none | 1977, 1984 row 26 : bolton wanderers | 0 | 2 | none | 1995, 2004 row 27 : sunderland | 0 | 2 | none | 1985, 2014 row 28 : rotherham united | 0 | 1 | none | 1961 row 29 : rochdale | 0 | 1 | none | 1962 row 30 : newcastle united | 0 | 1 | none | 1976 row 31 : southampton | 0 | 1 | none | 1979 row 32 : oldham athletic | 0 | 1 | none | 1990 row 33 : tranmere rovers | 0 | 1 | none | 2000 row 34 : wigan athletic | 0 | 1 | none | 2006 row 35 : cardiff city | 0 | 1 | none | 2012 row 36 : bradford city | 0 | 1 | none | 2013 | col : count ( "team" ) row 1 : 2 | select count ( team ) where winners = 3 <table_name> : table \begin{tabular}{llllll}
\toprule
& team & winners & runners-up & years won & years runner-up \\
\midrule
0 & liverpool & 8 & 3 & 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 & 1978, 1987, 2005 \\
1 & aston villa & 5 & 3 & 1961, 1975, 1977, 1994, 1996 & 1963, 1971, 2010 \\
2 & manchester united & 4 & 4 & 1992, 2006, 2009, 2010 & 1983, 1991, 1994, 2003 \\
3 & tottenham hotspur & 4 & 3 & 1971, 1973, 1999, 2008 & 1982, 2002, 2009 \\
4 & chelsea & 4 & 2 & 1965, 1998, 2005, 2007 & 1972, 2008 \\
5 & nottingham forest & 4 & 2 & 1978, 1979, 1989, 1990 & 1980, 1992 \\
6 & leicester city & 3 & 2 & 1964, 1997, 2000 & 1965, 1999 \\
7 & manchester city & 3 & 1 & 1970, 1976, 2014 & 1974 \\
8 & arsenal & 2 & 5 & 1987, 1993 & 1968, 1969, 1988, 2007, 2011 \\
9 & norwich city & 2 & 2 & 1962, 1985 & 1973, 1975 \\
10 & birmingham city & 2 & 1 & 1963, 2011 & 2001 \\
11 & wolverhampton wanderers & 2 & 0 & 1974, 1980 & none \\
12 & west bromwich albion & 1 & 2 & 1966 & 1967, 1970 \\
13 & middlesbrough & 1 & 2 & 2004 & 1997, 1998 \\
14 & queens park rangers & 1 & 1 & 1967 & 1986 \\
15 & leeds united & 1 & 1 & 1968 & 1996 \\
16 & stoke city & 1 & 1 & 1972 & 1964 \\
17 & luton town & 1 & 1 & 1988 & 1989 \\
18 & sheffield wednesday & 1 & 1 & 1991 & 1993 \\
19 & swindon town & 1 & 0 & 1969 & none \\
20 & oxford united & 1 & 0 & 1986 & none \\
21 & blackburn rovers & 1 & 0 & 2002 & none \\
22 & swansea city & 1 & 0 & 2013 & none \\
23 & west ham united & 0 & 2 & none & 1966, 1981 \\
24 & everton & 0 & 2 & none & 1977, 1984 \\
25 & bolton wanderers & 0 & 2 & none & 1995, 2004 \\
26 & sunderland & 0 & 2 & none & 1985, 2014 \\
27 & rotherham united & 0 & 1 & none & 1961 \\
28 & rochdale & 0 & 1 & none & 1962 \\
29 & newcastle united & 0 & 1 & none & 1976 \\
30 & southampton & 0 & 1 & none & 1979 \\
31 & oldham athletic & 0 & 1 & none & 1990 \\
32 & tranmere rovers & 0 & 1 & none & 2000 \\
33 & wigan athletic & 0 & 1 & none & 2006 \\
34 & cardiff city & 0 & 1 & none & 2012 \\
35 & bradford city & 0 & 1 & none & 2013 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "team" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( team ) where winners = 3 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>team</th>
<th>winners</th>
<th>runners-up</th>
<th>years won</th>
<th>years runner-up</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>liverpool</td>
<td>8</td>
<td>3</td>
<td>1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012</td>
<td>1978, 1987, 2005</td>
</tr>
<tr>
<th>1</th>
<td>aston villa</td>
<td>5</td>
<td>3</td>
<td>1961, 1975, 1977, 1994, 1996</td>
<td>1963, 1971, 2010</td>
</tr>
<tr>
<th>2</th>
<td>manchester united</td>
<td>4</td>
<td>4</td>
<td>1992, 2006, 2009, 2010</td>
<td>1983, 1991, 1994, 2003</td>
</tr>
<tr>
<th>3</th>
<td>tottenham hotspur</td>
<td>4</td>
<td>3</td>
<td>1971, 1973, 1999, 2008</td>
<td>1982, 2002, 2009</td>
</tr>
<tr>
<th>4</th>
<td>chelsea</td>
<td>4</td>
<td>2</td>
<td>1965, 1998, 2005, 2007</td>
<td>1972, 2008</td>
</tr>
<tr>
<th>5</th>
<td>nottingham forest</td>
<td>4</td>
<td>2</td>
<td>1978, 1979, 1989, 1990</td>
<td>1980, 1992</td>
</tr>
<tr>
<th>6</th>
<td>leicester city</td>
<td>3</td>
<td>2</td>
<td>1964, 1997, 2000</td>
<td>1965, 1999</td>
</tr>
<tr>
<th>7</th>
<td>manchester city</td>
<td>3</td>
<td>1</td>
<td>1970, 1976, 2014</td>
<td>1974</td>
</tr>
<tr>
<th>8</th>
<td>arsenal</td>
<td>2</td>
<td>5</td>
<td>1987, 1993</td>
<td>1968, 1969, 1988, 2007, 2011</td>
</tr>
<tr>
<th>9</th>
<td>norwich city</td>
<td>2</td>
<td>2</td>
<td>1962, 1985</td>
<td>1973, 1975</td>
</tr>
<tr>
<th>10</th>
<td>birmingham city</td>
<td>2</td>
<td>1</td>
<td>1963, 2011</td>
<td>2001</td>
</tr>
<tr>
<th>11</th>
<td>wolverhampton wanderers</td>
<td>2</td>
<td>0</td>
<td>1974, 1980</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>west bromwich albion</td>
<td>1</td>
<td>2</td>
<td>1966</td>
<td>1967, 1970</td>
</tr>
<tr>
<th>13</th>
<td>middlesbrough</td>
<td>1</td>
<td>2</td>
<td>2004</td>
<td>1997, 1998</td>
</tr>
<tr>
<th>14</th>
<td>queens park rangers</td>
<td>1</td>
<td>1</td>
<td>1967</td>
<td>1986</td>
</tr>
<tr>
<th>15</th>
<td>leeds united</td>
<td>1</td>
<td>1</td>
<td>1968</td>
<td>1996</td>
</tr>
<tr>
<th>16</th>
<td>stoke city</td>
<td>1</td>
<td>1</td>
<td>1972</td>
<td>1964</td>
</tr>
<tr>
<th>17</th>
<td>luton town</td>
<td>1</td>
<td>1</td>
<td>1988</td>
<td>1989</td>
</tr>
<tr>
<th>18</th>
<td>sheffield wednesday</td>
<td>1</td>
<td>1</td>
<td>1991</td>
<td>1993</td>
</tr>
<tr>
<th>19</th>
<td>swindon town</td>
<td>1</td>
<td>0</td>
<td>1969</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>oxford united</td>
<td>1</td>
<td>0</td>
<td>1986</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>blackburn rovers</td>
<td>1</td>
<td>0</td>
<td>2002</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>swansea city</td>
<td>1</td>
<td>0</td>
<td>2013</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>west ham united</td>
<td>0</td>
<td>2</td>
<td>none</td>
<td>1966, 1981</td>
</tr>
<tr>
<th>24</th>
<td>everton</td>
<td>0</td>
<td>2</td>
<td>none</td>
<td>1977, 1984</td>
</tr>
<tr>
<th>25</th>
<td>bolton wanderers</td>
<td>0</td>
<td>2</td>
<td>none</td>
<td>1995, 2004</td>
</tr>
<tr>
<th>26</th>
<td>sunderland</td>
<td>0</td>
<td>2</td>
<td>none</td>
<td>1985, 2014</td>
</tr>
<tr>
<th>27</th>
<td>rotherham united</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1961</td>
</tr>
<tr>
<th>28</th>
<td>rochdale</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1962</td>
</tr>
<tr>
<th>29</th>
<td>newcastle united</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1976</td>
</tr>
<tr>
<th>30</th>
<td>southampton</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1979</td>
</tr>
<tr>
<th>31</th>
<td>oldham athletic</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1990</td>
</tr>
<tr>
<th>32</th>
<td>tranmere rovers</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>2000</td>
</tr>
<tr>
<th>33</th>
<td>wigan athletic</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>2006</td>
</tr>
<tr>
<th>34</th>
<td>cardiff city</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>2012</td>
</tr>
<tr>
<th>35</th>
<td>bradford city</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>2013</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "team" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( team ) where winners = 3 <table_name> : table | | team | winners | runners-up | years won | years runner-up |
|---:|:------------------------|----------:|-------------:|:-----------------------------------------------|:-----------------------------|
| 0 | liverpool | 8 | 3 | 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 | 1978, 1987, 2005 |
| 1 | aston villa | 5 | 3 | 1961, 1975, 1977, 1994, 1996 | 1963, 1971, 2010 |
| 2 | manchester united | 4 | 4 | 1992, 2006, 2009, 2010 | 1983, 1991, 1994, 2003 |
| 3 | tottenham hotspur | 4 | 3 | 1971, 1973, 1999, 2008 | 1982, 2002, 2009 |
| 4 | chelsea | 4 | 2 | 1965, 1998, 2005, 2007 | 1972, 2008 |
| 5 | nottingham forest | 4 | 2 | 1978, 1979, 1989, 1990 | 1980, 1992 |
| 6 | leicester city | 3 | 2 | 1964, 1997, 2000 | 1965, 1999 |
| 7 | manchester city | 3 | 1 | 1970, 1976, 2014 | 1974 |
| 8 | arsenal | 2 | 5 | 1987, 1993 | 1968, 1969, 1988, 2007, 2011 |
| 9 | norwich city | 2 | 2 | 1962, 1985 | 1973, 1975 |
| 10 | birmingham city | 2 | 1 | 1963, 2011 | 2001 |
| 11 | wolverhampton wanderers | 2 | 0 | 1974, 1980 | none |
| 12 | west bromwich albion | 1 | 2 | 1966 | 1967, 1970 |
| 13 | middlesbrough | 1 | 2 | 2004 | 1997, 1998 |
| 14 | queens park rangers | 1 | 1 | 1967 | 1986 |
| 15 | leeds united | 1 | 1 | 1968 | 1996 |
| 16 | stoke city | 1 | 1 | 1972 | 1964 |
| 17 | luton town | 1 | 1 | 1988 | 1989 |
| 18 | sheffield wednesday | 1 | 1 | 1991 | 1993 |
| 19 | swindon town | 1 | 0 | 1969 | none |
| 20 | oxford united | 1 | 0 | 1986 | none |
| 21 | blackburn rovers | 1 | 0 | 2002 | none |
| 22 | swansea city | 1 | 0 | 2013 | none |
| 23 | west ham united | 0 | 2 | none | 1966, 1981 |
| 24 | everton | 0 | 2 | none | 1977, 1984 |
| 25 | bolton wanderers | 0 | 2 | none | 1995, 2004 |
| 26 | sunderland | 0 | 2 | none | 1985, 2014 |
| 27 | rotherham united | 0 | 1 | none | 1961 |
| 28 | rochdale | 0 | 1 | none | 1962 |
| 29 | newcastle united | 0 | 1 | none | 1976 |
| 30 | southampton | 0 | 1 | none | 1979 |
| 31 | oldham athletic | 0 | 1 | none | 1990 |
| 32 | tranmere rovers | 0 | 1 | none | 2000 |
| 33 | wigan athletic | 0 | 1 | none | 2006 |
| 34 | cardiff city | 0 | 1 | none | 2012 |
| 35 | bradford city | 0 | 1 | none | 2013 | | | | count ( "team" ) |
|---:|-------------------:|
| 0 | 2 | | [
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select title where us r&b = 74 col : year | title | album | us r&b | us pop | us dance row 1 : 1989 | "talk to myself"/sweet memories | adventures in paradise a | 4 | 49 | 18 row 2 : 1989 | "promises, promises"/lover come back | adventures in paradise a | 7 | none | none row 3 : 1990 | "one girl"/lover come back | adventures in paradise a | 31 | none | none row 4 : 1991 | "i'm dreamin'" | new jack city soundtrack | 1 | 89 | 16 row 5 : 1991 | "i wanna b ure lover" | f.s. effect featuring christopher williams | 52 | none | none row 6 : 1992 | "all i see" | changes | 19 | none | 46 row 7 : 1993 | "every little thing u do" | changes | 7 | 75 | none row 8 : 1993 | "come go with me" | changes | 74 | none | none row 9 : 1995 | "dance 4 me" | not a perfect man | 25 | none | none row 10 : 1995 | "if you say" | not a perfect man | 91 | none | none | col : title row 1 : "come go with me" | select title where us r&b = 74 <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & title & album & us r&b & us pop & us dance \\
\midrule
0 & 1989 & "talk to myself"/sweet memories & adventures in paradise a & 4 & 49 & 18 \\
1 & 1989 & "promises, promises"/lover come back & adventures in paradise a & 7 & none & none \\
2 & 1990 & "one girl"/lover come back & adventures in paradise a & 31 & none & none \\
3 & 1991 & "i'm dreamin'" & new jack city soundtrack & 1 & 89 & 16 \\
4 & 1991 & "i wanna b ure lover" & f.s. effect featuring christopher williams & 52 & none & none \\
5 & 1992 & "all i see" & changes & 19 & none & 46 \\
6 & 1993 & "every little thing u do" & changes & 7 & 75 & none \\
7 & 1993 & "come go with me" & changes & 74 & none & none \\
8 & 1995 & "dance 4 me" & not a perfect man & 25 & none & none \\
9 & 1995 & "if you say" & not a perfect man & 91 & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& title \\
\midrule
0 & "come go with me" \\
\bottomrule
\end{tabular}
| select title where us r&b = 74 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>album</th>
<th>us r&b</th>
<th>us pop</th>
<th>us dance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1989</td>
<td>"talk to myself"/sweet memories</td>
<td>adventures in paradise a</td>
<td>4</td>
<td>49</td>
<td>18</td>
</tr>
<tr>
<th>1</th>
<td>1989</td>
<td>"promises, promises"/lover come back</td>
<td>adventures in paradise a</td>
<td>7</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1990</td>
<td>"one girl"/lover come back</td>
<td>adventures in paradise a</td>
<td>31</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1991</td>
<td>"i'm dreamin'"</td>
<td>new jack city soundtrack</td>
<td>1</td>
<td>89</td>
<td>16</td>
</tr>
<tr>
<th>4</th>
<td>1991</td>
<td>"i wanna b ure lover"</td>
<td>f.s. effect featuring christopher williams</td>
<td>52</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1992</td>
<td>"all i see"</td>
<td>changes</td>
<td>19</td>
<td>none</td>
<td>46</td>
</tr>
<tr>
<th>6</th>
<td>1993</td>
<td>"every little thing u do"</td>
<td>changes</td>
<td>7</td>
<td>75</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1993</td>
<td>"come go with me"</td>
<td>changes</td>
<td>74</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1995</td>
<td>"dance 4 me"</td>
<td>not a perfect man</td>
<td>25</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1995</td>
<td>"if you say"</td>
<td>not a perfect man</td>
<td>91</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>"come go with me"</td>
</tr>
</tbody>
</table> | select title where us r&b = 74 <table_name> : table | | year | title | album | us r&b | us pop | us dance |
|---:|-------:|:-------------------------------------|:-------------------------------------------|---------:|:---------|:-----------|
| 0 | 1989 | "talk to myself"/sweet memories | adventures in paradise a | 4 | 49 | 18 |
| 1 | 1989 | "promises, promises"/lover come back | adventures in paradise a | 7 | none | none |
| 2 | 1990 | "one girl"/lover come back | adventures in paradise a | 31 | none | none |
| 3 | 1991 | "i'm dreamin'" | new jack city soundtrack | 1 | 89 | 16 |
| 4 | 1991 | "i wanna b ure lover" | f.s. effect featuring christopher williams | 52 | none | none |
| 5 | 1992 | "all i see" | changes | 19 | none | 46 |
| 6 | 1993 | "every little thing u do" | changes | 7 | 75 | none |
| 7 | 1993 | "come go with me" | changes | 74 | none | none |
| 8 | 1995 | "dance 4 me" | not a perfect man | 25 | none | none |
| 9 | 1995 | "if you say" | not a perfect man | 91 | none | none | | | | title |
|---:|:------------------|
| 0 | "come go with me" | | [
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select count ( school ) where pick < 626 col : pick | player | team | position | school row 1 : 1 | ben mcdonald | baltimore orioles | rhp | louisiana state university row 2 : 2 | tyler houston | atlanta braves | c | valley hs (las vegas, nv) row 3 : 3 | roger salkeld | seattle mariners | rhp | saugus (ca) hs row 4 : 4 | jeff jackson | philadelphia phillies | of | simeon hs (chicago, il) row 5 : 5 | donald harris | texas rangers | of | texas tech university row 6 : 6 | paul coleman | saint louis cardinals | of | frankston (tx) hs row 7 : 7 | frank thomas | chicago white sox | 1b | auburn university row 8 : 8 | earl cunningham | chicago cubs | of | lancaster (sc) hs row 9 : 9 | kyle abbott | california angels | lhp | long beach state university row 10 : 10 | charles johnson | montreal expos | c | westwood hs (fort pierce, fl) row 11 : 11 | calvin murray | cleveland indians | 3b | w.t. white high school (dallas, tx) row 12 : 12 | jeff juden | houston astros | rhp | salem (ma) hs row 13 : 13 | brent mayne | kansas city royals | c | cal state fullerton row 14 : 14 | steve hosey | san francisco giants | of | fresno state university row 15 : 15 | kiki jones | los angeles dodgers | rhp | hillsborough hs (tampa, fl) row 16 : 16 | greg blosser | boston red sox | of | sarasota (fl) hs row 17 : 17 | cal eldred | milwaukee brewers | rhp | university of iowa row 18 : 18 | willie greene | pittsburgh pirates | ss | jones county hs (gray, ga) row 19 : 19 | eddie zosky | toronto blue jays | ss | fresno state university row 20 : 20 | scott bryant | cincinnati reds | of | university of texas row 21 : 21 | greg gohr | detroit tigers | rhp | santa clara university row 22 : 22 | tom goodwin | los angeles dodgers | of | fresno state university row 23 : 23 | mo vaughn | boston red sox | 1b | seton hall university row 24 : 24 | alan zinter | new york mets | c | university of arizona row 25 : 25 | chuck knoblauch | minnesota twins | 2b | texas a&m university row 26 : 26 | scott burrell | seattle mariners | rhp | hamden (ct) hs | col : count ( "school" ) row 1 : 23 | select count ( school ) where pick < 626 <table_name> : table \begin{tabular}{llllll}
\toprule
& pick & player & team & position & school \\
\midrule
0 & 1 & ben mcdonald & baltimore orioles & rhp & louisiana state university \\
1 & 2 & tyler houston & atlanta braves & c & valley hs (las vegas, nv) \\
2 & 3 & roger salkeld & seattle mariners & rhp & saugus (ca) hs \\
3 & 4 & jeff jackson & philadelphia phillies & of & simeon hs (chicago, il) \\
4 & 5 & donald harris & texas rangers & of & texas tech university \\
5 & 6 & paul coleman & saint louis cardinals & of & frankston (tx) hs \\
6 & 7 & frank thomas & chicago white sox & 1b & auburn university \\
7 & 8 & earl cunningham & chicago cubs & of & lancaster (sc) hs \\
8 & 9 & kyle abbott & california angels & lhp & long beach state university \\
9 & 10 & charles johnson & montreal expos & c & westwood hs (fort pierce, fl) \\
10 & 11 & calvin murray & cleveland indians & 3b & w.t. white high school (dallas, tx) \\
11 & 12 & jeff juden & houston astros & rhp & salem (ma) hs \\
12 & 13 & brent mayne & kansas city royals & c & cal state fullerton \\
13 & 14 & steve hosey & san francisco giants & of & fresno state university \\
14 & 15 & kiki jones & los angeles dodgers & rhp & hillsborough hs (tampa, fl) \\
15 & 16 & greg blosser & boston red sox & of & sarasota (fl) hs \\
16 & 17 & cal eldred & milwaukee brewers & rhp & university of iowa \\
17 & 18 & willie greene & pittsburgh pirates & ss & jones county hs (gray, ga) \\
18 & 19 & eddie zosky & toronto blue jays & ss & fresno state university \\
19 & 20 & scott bryant & cincinnati reds & of & university of texas \\
20 & 21 & greg gohr & detroit tigers & rhp & santa clara university \\
21 & 22 & tom goodwin & los angeles dodgers & of & fresno state university \\
22 & 23 & mo vaughn & boston red sox & 1b & seton hall university \\
23 & 24 & alan zinter & new york mets & c & university of arizona \\
24 & 25 & chuck knoblauch & minnesota twins & 2b & texas a&m university \\
25 & 26 & scott burrell & seattle mariners & rhp & hamden (ct) hs \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "school" ) \\
\midrule
0 & 23 \\
\bottomrule
\end{tabular}
| select count ( school ) where pick < 626 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pick</th>
<th>player</th>
<th>team</th>
<th>position</th>
<th>school</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>ben mcdonald</td>
<td>baltimore orioles</td>
<td>rhp</td>
<td>louisiana state university</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>tyler houston</td>
<td>atlanta braves</td>
<td>c</td>
<td>valley hs (las vegas, nv)</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>roger salkeld</td>
<td>seattle mariners</td>
<td>rhp</td>
<td>saugus (ca) hs</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>jeff jackson</td>
<td>philadelphia phillies</td>
<td>of</td>
<td>simeon hs (chicago, il)</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>donald harris</td>
<td>texas rangers</td>
<td>of</td>
<td>texas tech university</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>paul coleman</td>
<td>saint louis cardinals</td>
<td>of</td>
<td>frankston (tx) hs</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>frank thomas</td>
<td>chicago white sox</td>
<td>1b</td>
<td>auburn university</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>earl cunningham</td>
<td>chicago cubs</td>
<td>of</td>
<td>lancaster (sc) hs</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>kyle abbott</td>
<td>california angels</td>
<td>lhp</td>
<td>long beach state university</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>charles johnson</td>
<td>montreal expos</td>
<td>c</td>
<td>westwood hs (fort pierce, fl)</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>calvin murray</td>
<td>cleveland indians</td>
<td>3b</td>
<td>w.t. white high school (dallas, tx)</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>jeff juden</td>
<td>houston astros</td>
<td>rhp</td>
<td>salem (ma) hs</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>brent mayne</td>
<td>kansas city royals</td>
<td>c</td>
<td>cal state fullerton</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>steve hosey</td>
<td>san francisco giants</td>
<td>of</td>
<td>fresno state university</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>kiki jones</td>
<td>los angeles dodgers</td>
<td>rhp</td>
<td>hillsborough hs (tampa, fl)</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>greg blosser</td>
<td>boston red sox</td>
<td>of</td>
<td>sarasota (fl) hs</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>cal eldred</td>
<td>milwaukee brewers</td>
<td>rhp</td>
<td>university of iowa</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>willie greene</td>
<td>pittsburgh pirates</td>
<td>ss</td>
<td>jones county hs (gray, ga)</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>eddie zosky</td>
<td>toronto blue jays</td>
<td>ss</td>
<td>fresno state university</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>scott bryant</td>
<td>cincinnati reds</td>
<td>of</td>
<td>university of texas</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>greg gohr</td>
<td>detroit tigers</td>
<td>rhp</td>
<td>santa clara university</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>tom goodwin</td>
<td>los angeles dodgers</td>
<td>of</td>
<td>fresno state university</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>mo vaughn</td>
<td>boston red sox</td>
<td>1b</td>
<td>seton hall university</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>alan zinter</td>
<td>new york mets</td>
<td>c</td>
<td>university of arizona</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>chuck knoblauch</td>
<td>minnesota twins</td>
<td>2b</td>
<td>texas a&m university</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>scott burrell</td>
<td>seattle mariners</td>
<td>rhp</td>
<td>hamden (ct) hs</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "school" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>23</td>
</tr>
</tbody>
</table> | select count ( school ) where pick < 626 <table_name> : table | | pick | player | team | position | school |
|---:|-------:|:----------------|:----------------------|:-----------|:------------------------------------|
| 0 | 1 | ben mcdonald | baltimore orioles | rhp | louisiana state university |
| 1 | 2 | tyler houston | atlanta braves | c | valley hs (las vegas, nv) |
| 2 | 3 | roger salkeld | seattle mariners | rhp | saugus (ca) hs |
| 3 | 4 | jeff jackson | philadelphia phillies | of | simeon hs (chicago, il) |
| 4 | 5 | donald harris | texas rangers | of | texas tech university |
| 5 | 6 | paul coleman | saint louis cardinals | of | frankston (tx) hs |
| 6 | 7 | frank thomas | chicago white sox | 1b | auburn university |
| 7 | 8 | earl cunningham | chicago cubs | of | lancaster (sc) hs |
| 8 | 9 | kyle abbott | california angels | lhp | long beach state university |
| 9 | 10 | charles johnson | montreal expos | c | westwood hs (fort pierce, fl) |
| 10 | 11 | calvin murray | cleveland indians | 3b | w.t. white high school (dallas, tx) |
| 11 | 12 | jeff juden | houston astros | rhp | salem (ma) hs |
| 12 | 13 | brent mayne | kansas city royals | c | cal state fullerton |
| 13 | 14 | steve hosey | san francisco giants | of | fresno state university |
| 14 | 15 | kiki jones | los angeles dodgers | rhp | hillsborough hs (tampa, fl) |
| 15 | 16 | greg blosser | boston red sox | of | sarasota (fl) hs |
| 16 | 17 | cal eldred | milwaukee brewers | rhp | university of iowa |
| 17 | 18 | willie greene | pittsburgh pirates | ss | jones county hs (gray, ga) |
| 18 | 19 | eddie zosky | toronto blue jays | ss | fresno state university |
| 19 | 20 | scott bryant | cincinnati reds | of | university of texas |
| 20 | 21 | greg gohr | detroit tigers | rhp | santa clara university |
| 21 | 22 | tom goodwin | los angeles dodgers | of | fresno state university |
| 22 | 23 | mo vaughn | boston red sox | 1b | seton hall university |
| 23 | 24 | alan zinter | new york mets | c | university of arizona |
| 24 | 25 | chuck knoblauch | minnesota twins | 2b | texas a&m university |
| 25 | 26 | scott burrell | seattle mariners | rhp | hamden (ct) hs | | | | count ( "school" ) |
|---:|---------------------:|
| 0 | 23 | | [
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select attendance where result = '0-0' col : date | opponents | venue | result | scorers | attendance | report 1 | report 2 row 1 : 2068-01-27 00:00:00 | bournemouth | a | 0-0 | none | 24388 | report | report row 2 : 2068-01-30 00:00:00 | bournemouth | h | 4-1 | hateley 33' thompson 44' hunt 51' lawler 73' | 54075 | report | report row 3 : 2068-02-17 00:00:00 | walsall | a | 0-0 | none | 21066 | report | report row 4 : 2068-02-19 00:00:00 | walsall | h | 5-2 | hateley 24', 33', 64', 71' strong 34' | 39113 | report | report row 5 : 2068-03-09 00:00:00 | tottenham hotspur | a | 1-1 | hateley 54' | 54005 | report | report row 6 : 2068-03-12 00:00:00 | tottenham hotspur | h | 2-1 | hunt 23' smith 78 pen' | 53658 | report | report row 7 : 2068-03-30 00:00:00 | west bromwich albion | a | 0-0 | none | 53062 | report | report row 8 : 2068-04-08 00:00:00 | west bromwich albion | h | 1-1 | hateley 24' | 54273 | report | report row 9 : 2068-04-18 00:00:00 | west bromwich albion | n | 1-2 | hateley 39' | 56000 | report | report | col : attendance row 1 : 24388 row 2 : 21066 row 3 : 53062 | select attendance where result = '0-0' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& date & opponents & venue & result & scorers & attendance & report 1 & report 2 \\
\midrule
0 & 2068-01-27 00:00:00 & bournemouth & a & 0-0 & none & 24388 & report & report \\
1 & 2068-01-30 00:00:00 & bournemouth & h & 4-1 & hateley 33' thompson 44' hunt 51' lawler 73' & 54075 & report & report \\
2 & 2068-02-17 00:00:00 & walsall & a & 0-0 & none & 21066 & report & report \\
3 & 2068-02-19 00:00:00 & walsall & h & 5-2 & hateley 24', 33', 64', 71' strong 34' & 39113 & report & report \\
4 & 2068-03-09 00:00:00 & tottenham hotspur & a & 1-1 & hateley 54' & 54005 & report & report \\
5 & 2068-03-12 00:00:00 & tottenham hotspur & h & 2-1 & hunt 23' smith 78 pen' & 53658 & report & report \\
6 & 2068-03-30 00:00:00 & west bromwich albion & a & 0-0 & none & 53062 & report & report \\
7 & 2068-04-08 00:00:00 & west bromwich albion & h & 1-1 & hateley 24' & 54273 & report & report \\
8 & 2068-04-18 00:00:00 & west bromwich albion & n & 1-2 & hateley 39' & 56000 & report & report \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& attendance \\
\midrule
0 & 24388 \\
1 & 21066 \\
2 & 53062 \\
\bottomrule
\end{tabular}
| select attendance where result = '0-0' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>opponents</th>
<th>venue</th>
<th>result</th>
<th>scorers</th>
<th>attendance</th>
<th>report 1</th>
<th>report 2</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2068-01-27 00:00:00</td>
<td>bournemouth</td>
<td>a</td>
<td>0-0</td>
<td>none</td>
<td>24388</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>1</th>
<td>2068-01-30 00:00:00</td>
<td>bournemouth</td>
<td>h</td>
<td>4-1</td>
<td>hateley 33' thompson 44' hunt 51' lawler 73'</td>
<td>54075</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>2</th>
<td>2068-02-17 00:00:00</td>
<td>walsall</td>
<td>a</td>
<td>0-0</td>
<td>none</td>
<td>21066</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>3</th>
<td>2068-02-19 00:00:00</td>
<td>walsall</td>
<td>h</td>
<td>5-2</td>
<td>hateley 24', 33', 64', 71' strong 34'</td>
<td>39113</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>4</th>
<td>2068-03-09 00:00:00</td>
<td>tottenham hotspur</td>
<td>a</td>
<td>1-1</td>
<td>hateley 54'</td>
<td>54005</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>5</th>
<td>2068-03-12 00:00:00</td>
<td>tottenham hotspur</td>
<td>h</td>
<td>2-1</td>
<td>hunt 23' smith 78 pen'</td>
<td>53658</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>6</th>
<td>2068-03-30 00:00:00</td>
<td>west bromwich albion</td>
<td>a</td>
<td>0-0</td>
<td>none</td>
<td>53062</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>7</th>
<td>2068-04-08 00:00:00</td>
<td>west bromwich albion</td>
<td>h</td>
<td>1-1</td>
<td>hateley 24'</td>
<td>54273</td>
<td>report</td>
<td>report</td>
</tr>
<tr>
<th>8</th>
<td>2068-04-18 00:00:00</td>
<td>west bromwich albion</td>
<td>n</td>
<td>1-2</td>
<td>hateley 39'</td>
<td>56000</td>
<td>report</td>
<td>report</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>24388</td>
</tr>
<tr>
<th>1</th>
<td>21066</td>
</tr>
<tr>
<th>2</th>
<td>53062</td>
</tr>
</tbody>
</table> | select attendance where result = '0-0' <table_name> : table | | date | opponents | venue | result | scorers | attendance | report 1 | report 2 |
|---:|:--------------------|:---------------------|:--------|:---------|:---------------------------------------------|-------------:|:-----------|:-----------|
| 0 | 2068-01-27 00:00:00 | bournemouth | a | 0-0 | none | 24388 | report | report |
| 1 | 2068-01-30 00:00:00 | bournemouth | h | 4-1 | hateley 33' thompson 44' hunt 51' lawler 73' | 54075 | report | report |
| 2 | 2068-02-17 00:00:00 | walsall | a | 0-0 | none | 21066 | report | report |
| 3 | 2068-02-19 00:00:00 | walsall | h | 5-2 | hateley 24', 33', 64', 71' strong 34' | 39113 | report | report |
| 4 | 2068-03-09 00:00:00 | tottenham hotspur | a | 1-1 | hateley 54' | 54005 | report | report |
| 5 | 2068-03-12 00:00:00 | tottenham hotspur | h | 2-1 | hunt 23' smith 78 pen' | 53658 | report | report |
| 6 | 2068-03-30 00:00:00 | west bromwich albion | a | 0-0 | none | 53062 | report | report |
| 7 | 2068-04-08 00:00:00 | west bromwich albion | h | 1-1 | hateley 24' | 54273 | report | report |
| 8 | 2068-04-18 00:00:00 | west bromwich albion | n | 1-2 | hateley 39' | 56000 | report | report | | | | attendance |
|---:|-------------:|
| 0 | 24388 |
| 1 | 21066 |
| 2 | 53062 | | [
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select count ( name ) where fa cup = 0 col : place | position | number | name | league one | fa cup | league cup | football league trophy | total row 1 : 1 | mf | 4 | luke summerfield | 5 | 0 | 0 | 0 | 5 row 2 : 2 | mf | 17 | paul parry | 3 | 0 | 1 | 0 | 4 row 3 : 3 | fw | 24 | tom eaves | 3 | 0 | 0 | 0 | 3 row 4 : 4 | mf | 11 | jon taylor | 1 | 0 | 0 | 1 | 2 row 5 : 4 | df | 5 | darren jones | 2 | 0 | 0 | 0 | 2 row 6 : 4 | mf | 23 | adam reach | 2 | 0 | 0 | 0 | 2 row 7 : 4 | mf | 22 | ryan woods | 2 | 0 | 0 | 0 | 2 row 8 : 4 | fw | 26 | curtis main | 2 | 0 | 0 | 0 | 2 row 9 : 5 | mf | 2 | jermaine grandison | 1 | 0 | 0 | 0 | 1 row 10 : 5 | mf | 8 | dave mcallister | 1 | 0 | 0 | 0 | 1 row 11 : 5 | fw | 15 | aaron wildig | 1 | 0 | 0 | 0 | 1 row 12 : 5 | fw | 29 | asa hall | 1 | 0 | 0 | 0 | 1 row 13 : 5 | fw | 7 | gozie ugwu | 1 | 0 | 0 | 0 | 1 row 14 : 5 | df | 18 | connor goldson | 1 | 0 | 0 | 0 | 1 row 15 : 5 | mf | 10 | nicky wroe | 1 | 0 | 0 | 0 | 1 row 16 : 5 | fw | 9 | tom bradshaw | 1 | 0 | 0 | 0 | 1 | col : count ( "name" ) row 1 : 16 | select count ( name ) where fa cup = 0 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& place & position & number & name & league one & fa cup & league cup & football league trophy & total \\
\midrule
0 & 1 & mf & 4 & luke summerfield & 5 & 0 & 0 & 0 & 5 \\
1 & 2 & mf & 17 & paul parry & 3 & 0 & 1 & 0 & 4 \\
2 & 3 & fw & 24 & tom eaves & 3 & 0 & 0 & 0 & 3 \\
3 & 4 & mf & 11 & jon taylor & 1 & 0 & 0 & 1 & 2 \\
4 & 4 & df & 5 & darren jones & 2 & 0 & 0 & 0 & 2 \\
5 & 4 & mf & 23 & adam reach & 2 & 0 & 0 & 0 & 2 \\
6 & 4 & mf & 22 & ryan woods & 2 & 0 & 0 & 0 & 2 \\
7 & 4 & fw & 26 & curtis main & 2 & 0 & 0 & 0 & 2 \\
8 & 5 & mf & 2 & jermaine grandison & 1 & 0 & 0 & 0 & 1 \\
9 & 5 & mf & 8 & dave mcallister & 1 & 0 & 0 & 0 & 1 \\
10 & 5 & fw & 15 & aaron wildig & 1 & 0 & 0 & 0 & 1 \\
11 & 5 & fw & 29 & asa hall & 1 & 0 & 0 & 0 & 1 \\
12 & 5 & fw & 7 & gozie ugwu & 1 & 0 & 0 & 0 & 1 \\
13 & 5 & df & 18 & connor goldson & 1 & 0 & 0 & 0 & 1 \\
14 & 5 & mf & 10 & nicky wroe & 1 & 0 & 0 & 0 & 1 \\
15 & 5 & fw & 9 & tom bradshaw & 1 & 0 & 0 & 0 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "name" ) \\
\midrule
0 & 16 \\
\bottomrule
\end{tabular}
| select count ( name ) where fa cup = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>position</th>
<th>number</th>
<th>name</th>
<th>league one</th>
<th>fa cup</th>
<th>league cup</th>
<th>football league trophy</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>mf</td>
<td>4</td>
<td>luke summerfield</td>
<td>5</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>5</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>mf</td>
<td>17</td>
<td>paul parry</td>
<td>3</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>4</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>fw</td>
<td>24</td>
<td>tom eaves</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>mf</td>
<td>11</td>
<td>jon taylor</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>df</td>
<td>5</td>
<td>darren jones</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>mf</td>
<td>23</td>
<td>adam reach</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>mf</td>
<td>22</td>
<td>ryan woods</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>4</td>
<td>fw</td>
<td>26</td>
<td>curtis main</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>5</td>
<td>mf</td>
<td>2</td>
<td>jermaine grandison</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>5</td>
<td>mf</td>
<td>8</td>
<td>dave mcallister</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>5</td>
<td>fw</td>
<td>15</td>
<td>aaron wildig</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>5</td>
<td>fw</td>
<td>29</td>
<td>asa hall</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>5</td>
<td>fw</td>
<td>7</td>
<td>gozie ugwu</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>5</td>
<td>df</td>
<td>18</td>
<td>connor goldson</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>5</td>
<td>mf</td>
<td>10</td>
<td>nicky wroe</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>5</td>
<td>fw</td>
<td>9</td>
<td>tom bradshaw</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "name" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16</td>
</tr>
</tbody>
</table> | select count ( name ) where fa cup = 0 <table_name> : table | | place | position | number | name | league one | fa cup | league cup | football league trophy | total |
|---:|--------:|:-----------|---------:|:-------------------|-------------:|---------:|-------------:|-------------------------:|--------:|
| 0 | 1 | mf | 4 | luke summerfield | 5 | 0 | 0 | 0 | 5 |
| 1 | 2 | mf | 17 | paul parry | 3 | 0 | 1 | 0 | 4 |
| 2 | 3 | fw | 24 | tom eaves | 3 | 0 | 0 | 0 | 3 |
| 3 | 4 | mf | 11 | jon taylor | 1 | 0 | 0 | 1 | 2 |
| 4 | 4 | df | 5 | darren jones | 2 | 0 | 0 | 0 | 2 |
| 5 | 4 | mf | 23 | adam reach | 2 | 0 | 0 | 0 | 2 |
| 6 | 4 | mf | 22 | ryan woods | 2 | 0 | 0 | 0 | 2 |
| 7 | 4 | fw | 26 | curtis main | 2 | 0 | 0 | 0 | 2 |
| 8 | 5 | mf | 2 | jermaine grandison | 1 | 0 | 0 | 0 | 1 |
| 9 | 5 | mf | 8 | dave mcallister | 1 | 0 | 0 | 0 | 1 |
| 10 | 5 | fw | 15 | aaron wildig | 1 | 0 | 0 | 0 | 1 |
| 11 | 5 | fw | 29 | asa hall | 1 | 0 | 0 | 0 | 1 |
| 12 | 5 | fw | 7 | gozie ugwu | 1 | 0 | 0 | 0 | 1 |
| 13 | 5 | df | 18 | connor goldson | 1 | 0 | 0 | 0 | 1 |
| 14 | 5 | mf | 10 | nicky wroe | 1 | 0 | 0 | 0 | 1 |
| 15 | 5 | fw | 9 | tom bradshaw | 1 | 0 | 0 | 0 | 1 | | | | count ( "name" ) |
|---:|-------------------:|
| 0 | 16 | | [
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select count ( * ) where playoffs = 'no playoff' col : year | division | league | reg. season | playoffs | national cup row 1 : 1934/35 | | asl | 6th | no playoff | none row 2 : 1935/36 | | asl | 2nd | no playoff | none row 3 : 1936/37 | | asl | 2nd, american | 1st round | none row 4 : 1937/38 | | asl | 4th, american | did not qualify | none row 5 : 1938/39 | | asl | 5th, american | did not qualify | none row 6 : 1939/40 | | asl | 2nd(t) | no playoff | co-champion row 7 : 1940/41 | | asl | 3rd | no playoff | none row 8 : 1941/42 | | asl | 5th | no playoff | none row 9 : 1942/43 | | asl | 5th | no playoff | none row 10 : 1943/44 | | asl | 3rd | no playoff | none row 11 : 1944/45 | | asl | 4th | no playoff | none row 12 : 1945/46 | | asl | 1st | champion (no playoff) | none row 13 : 1946/47 | | asl | 4th | no playoff | none row 14 : 1947/48 | | asl | 4th | no playoff | none row 15 : 1948/49 | | asl | withdrew after 3 games | none | none | col : count ( "*" ) row 1 : 10 | select count ( * ) where playoffs = 'no playoff' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & division & league & reg. season & playoffs & national cup \\
\midrule
0 & 1934/35 & & asl & 6th & no playoff & none \\
1 & 1935/36 & & asl & 2nd & no playoff & none \\
2 & 1936/37 & & asl & 2nd, american & 1st round & none \\
3 & 1937/38 & & asl & 4th, american & did not qualify & none \\
4 & 1938/39 & & asl & 5th, american & did not qualify & none \\
5 & 1939/40 & & asl & 2nd(t) & no playoff & co-champion \\
6 & 1940/41 & & asl & 3rd & no playoff & none \\
7 & 1941/42 & & asl & 5th & no playoff & none \\
8 & 1942/43 & & asl & 5th & no playoff & none \\
9 & 1943/44 & & asl & 3rd & no playoff & none \\
10 & 1944/45 & & asl & 4th & no playoff & none \\
11 & 1945/46 & & asl & 1st & champion (no playoff) & none \\
12 & 1946/47 & & asl & 4th & no playoff & none \\
13 & 1947/48 & & asl & 4th & no playoff & none \\
14 & 1948/49 & & asl & withdrew after 3 games & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 10 \\
\bottomrule
\end{tabular}
| select count ( * ) where playoffs = 'no playoff' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>division</th>
<th>league</th>
<th>reg. season</th>
<th>playoffs</th>
<th>national cup</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1934/35</td>
<td></td>
<td>asl</td>
<td>6th</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1935/36</td>
<td></td>
<td>asl</td>
<td>2nd</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1936/37</td>
<td></td>
<td>asl</td>
<td>2nd, american</td>
<td>1st round</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1937/38</td>
<td></td>
<td>asl</td>
<td>4th, american</td>
<td>did not qualify</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1938/39</td>
<td></td>
<td>asl</td>
<td>5th, american</td>
<td>did not qualify</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1939/40</td>
<td></td>
<td>asl</td>
<td>2nd(t)</td>
<td>no playoff</td>
<td>co-champion</td>
</tr>
<tr>
<th>6</th>
<td>1940/41</td>
<td></td>
<td>asl</td>
<td>3rd</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1941/42</td>
<td></td>
<td>asl</td>
<td>5th</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1942/43</td>
<td></td>
<td>asl</td>
<td>5th</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1943/44</td>
<td></td>
<td>asl</td>
<td>3rd</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>1944/45</td>
<td></td>
<td>asl</td>
<td>4th</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>1945/46</td>
<td></td>
<td>asl</td>
<td>1st</td>
<td>champion (no playoff)</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>1946/47</td>
<td></td>
<td>asl</td>
<td>4th</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1947/48</td>
<td></td>
<td>asl</td>
<td>4th</td>
<td>no playoff</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>1948/49</td>
<td></td>
<td>asl</td>
<td>withdrew after 3 games</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>10</td>
</tr>
</tbody>
</table> | select count ( * ) where playoffs = 'no playoff' <table_name> : table | | year | division | league | reg. season | playoffs | national cup |
|---:|:--------|:-----------|:---------|:-----------------------|:----------------------|:---------------|
| 0 | 1934/35 | | asl | 6th | no playoff | none |
| 1 | 1935/36 | | asl | 2nd | no playoff | none |
| 2 | 1936/37 | | asl | 2nd, american | 1st round | none |
| 3 | 1937/38 | | asl | 4th, american | did not qualify | none |
| 4 | 1938/39 | | asl | 5th, american | did not qualify | none |
| 5 | 1939/40 | | asl | 2nd(t) | no playoff | co-champion |
| 6 | 1940/41 | | asl | 3rd | no playoff | none |
| 7 | 1941/42 | | asl | 5th | no playoff | none |
| 8 | 1942/43 | | asl | 5th | no playoff | none |
| 9 | 1943/44 | | asl | 3rd | no playoff | none |
| 10 | 1944/45 | | asl | 4th | no playoff | none |
| 11 | 1945/46 | | asl | 1st | champion (no playoff) | none |
| 12 | 1946/47 | | asl | 4th | no playoff | none |
| 13 | 1947/48 | | asl | 4th | no playoff | none |
| 14 | 1948/49 | | asl | withdrew after 3 games | none | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 10 | | [
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select count ( opponent ) where location = 'lanxess arena, cologne, germany' col : record | date | result | opponent | location | method | round row 1 : 13-0 | 2013-07-12 00:00:00 | win | igor pylypenko | porsche arena, stuttgart, germany | unanimous decision | 6 row 2 : 12-0 | 2013-10-27 00:00:00 | win | alphonce mchumiatumbo | sarajevo, bosnia and herzegovina | decision | 8 row 3 : 11-0 | 2013-06-07 00:00:00 | win | alexander vasiliev | westfalenhalle, dortmund, germany | tko | 2 row 4 : 10-0 | 2013-02-02 00:00:00 | win | niko falin | iss dome, dusseldorf, germany | unanimous decision | 6 row 5 : 9-0 | 2012-02-12 00:00:00 | win | ladislav kovarik | esprit arena, dusseldorf, germany | unanimous decision | 6 row 6 : 8-0 | 2012-06-08 00:00:00 | win | ivica perkovic | sarajevo, bosnia and herzegovina | unanimous decision | 12 row 7 : 7-0 | 2012-04-13 00:00:00 | win | aliaksandr makaranka | lanxess arena, cologne, germany | ko | 1 row 8 : 6-0 | 2011-12-17 00:00:00 | win | ferenc zsalek | sarajevo, bosnia and herzegovina | ko | 3 row 9 : 5-0 | 2011-12-02 00:00:00 | win | liridon memishi | sap arena, mannheim, germany | unanimous decision | 6 row 10 : 4-0 | 2011-06-25 00:00:00 | win | werner kreiskott | lanxess arena, cologne, germany | unanimous decision | 6 row 11 : 3-0 | 2011-02-19 00:00:00 | win | ergin solmaz | porsche arena, stuttgart, germany | unanimous decision | 4 row 12 : 2-0 | 2004-09-03 00:00:00 | win | tomasz zeprzalka | gorazde, bosnia and herzegovina | tko | 2 row 13 : 1-0 | 2004-02-07 00:00:00 | win | ergin solmaz | sarajevo, bosnia and herzegovina | unanimous decision | 4 | col : count ( "opponent" ) row 1 : 2 | select count ( opponent ) where location = 'lanxess arena, cologne, germany' <table_name> : table \begin{tabular}{llllllll}
\toprule
& record & date & result & opponent & location & method & round \\
\midrule
0 & 13-0 & 2013-07-12 00:00:00 & win & igor pylypenko & porsche arena, stuttgart, germany & unanimous decision & 6 \\
1 & 12-0 & 2013-10-27 00:00:00 & win & alphonce mchumiatumbo & sarajevo, bosnia and herzegovina & decision & 8 \\
2 & 11-0 & 2013-06-07 00:00:00 & win & alexander vasiliev & westfalenhalle, dortmund, germany & tko & 2 \\
3 & 10-0 & 2013-02-02 00:00:00 & win & niko falin & iss dome, dusseldorf, germany & unanimous decision & 6 \\
4 & 9-0 & 2012-02-12 00:00:00 & win & ladislav kovarik & esprit arena, dusseldorf, germany & unanimous decision & 6 \\
5 & 8-0 & 2012-06-08 00:00:00 & win & ivica perkovic & sarajevo, bosnia and herzegovina & unanimous decision & 12 \\
6 & 7-0 & 2012-04-13 00:00:00 & win & aliaksandr makaranka & lanxess arena, cologne, germany & ko & 1 \\
7 & 6-0 & 2011-12-17 00:00:00 & win & ferenc zsalek & sarajevo, bosnia and herzegovina & ko & 3 \\
8 & 5-0 & 2011-12-02 00:00:00 & win & liridon memishi & sap arena, mannheim, germany & unanimous decision & 6 \\
9 & 4-0 & 2011-06-25 00:00:00 & win & werner kreiskott & lanxess arena, cologne, germany & unanimous decision & 6 \\
10 & 3-0 & 2011-02-19 00:00:00 & win & ergin solmaz & porsche arena, stuttgart, germany & unanimous decision & 4 \\
11 & 2-0 & 2004-09-03 00:00:00 & win & tomasz zeprzalka & gorazde, bosnia and herzegovina & tko & 2 \\
12 & 1-0 & 2004-02-07 00:00:00 & win & ergin solmaz & sarajevo, bosnia and herzegovina & unanimous decision & 4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "opponent" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( opponent ) where location = 'lanxess arena, cologne, germany' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>record</th>
<th>date</th>
<th>result</th>
<th>opponent</th>
<th>location</th>
<th>method</th>
<th>round</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13-0</td>
<td>2013-07-12 00:00:00</td>
<td>win</td>
<td>igor pylypenko</td>
<td>porsche arena, stuttgart, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>1</th>
<td>12-0</td>
<td>2013-10-27 00:00:00</td>
<td>win</td>
<td>alphonce mchumiatumbo</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>decision</td>
<td>8</td>
</tr>
<tr>
<th>2</th>
<td>11-0</td>
<td>2013-06-07 00:00:00</td>
<td>win</td>
<td>alexander vasiliev</td>
<td>westfalenhalle, dortmund, germany</td>
<td>tko</td>
<td>2</td>
</tr>
<tr>
<th>3</th>
<td>10-0</td>
<td>2013-02-02 00:00:00</td>
<td>win</td>
<td>niko falin</td>
<td>iss dome, dusseldorf, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>4</th>
<td>9-0</td>
<td>2012-02-12 00:00:00</td>
<td>win</td>
<td>ladislav kovarik</td>
<td>esprit arena, dusseldorf, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>5</th>
<td>8-0</td>
<td>2012-06-08 00:00:00</td>
<td>win</td>
<td>ivica perkovic</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>unanimous decision</td>
<td>12</td>
</tr>
<tr>
<th>6</th>
<td>7-0</td>
<td>2012-04-13 00:00:00</td>
<td>win</td>
<td>aliaksandr makaranka</td>
<td>lanxess arena, cologne, germany</td>
<td>ko</td>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>6-0</td>
<td>2011-12-17 00:00:00</td>
<td>win</td>
<td>ferenc zsalek</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>ko</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>5-0</td>
<td>2011-12-02 00:00:00</td>
<td>win</td>
<td>liridon memishi</td>
<td>sap arena, mannheim, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>9</th>
<td>4-0</td>
<td>2011-06-25 00:00:00</td>
<td>win</td>
<td>werner kreiskott</td>
<td>lanxess arena, cologne, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>3-0</td>
<td>2011-02-19 00:00:00</td>
<td>win</td>
<td>ergin solmaz</td>
<td>porsche arena, stuttgart, germany</td>
<td>unanimous decision</td>
<td>4</td>
</tr>
<tr>
<th>11</th>
<td>2-0</td>
<td>2004-09-03 00:00:00</td>
<td>win</td>
<td>tomasz zeprzalka</td>
<td>gorazde, bosnia and herzegovina</td>
<td>tko</td>
<td>2</td>
</tr>
<tr>
<th>12</th>
<td>1-0</td>
<td>2004-02-07 00:00:00</td>
<td>win</td>
<td>ergin solmaz</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>unanimous decision</td>
<td>4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "opponent" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( opponent ) where location = 'lanxess arena, cologne, germany' <table_name> : table | | record | date | result | opponent | location | method | round |
|---:|:---------|:--------------------|:---------|:----------------------|:----------------------------------|:-------------------|--------:|
| 0 | 13-0 | 2013-07-12 00:00:00 | win | igor pylypenko | porsche arena, stuttgart, germany | unanimous decision | 6 |
| 1 | 12-0 | 2013-10-27 00:00:00 | win | alphonce mchumiatumbo | sarajevo, bosnia and herzegovina | decision | 8 |
| 2 | 11-0 | 2013-06-07 00:00:00 | win | alexander vasiliev | westfalenhalle, dortmund, germany | tko | 2 |
| 3 | 10-0 | 2013-02-02 00:00:00 | win | niko falin | iss dome, dusseldorf, germany | unanimous decision | 6 |
| 4 | 9-0 | 2012-02-12 00:00:00 | win | ladislav kovarik | esprit arena, dusseldorf, germany | unanimous decision | 6 |
| 5 | 8-0 | 2012-06-08 00:00:00 | win | ivica perkovic | sarajevo, bosnia and herzegovina | unanimous decision | 12 |
| 6 | 7-0 | 2012-04-13 00:00:00 | win | aliaksandr makaranka | lanxess arena, cologne, germany | ko | 1 |
| 7 | 6-0 | 2011-12-17 00:00:00 | win | ferenc zsalek | sarajevo, bosnia and herzegovina | ko | 3 |
| 8 | 5-0 | 2011-12-02 00:00:00 | win | liridon memishi | sap arena, mannheim, germany | unanimous decision | 6 |
| 9 | 4-0 | 2011-06-25 00:00:00 | win | werner kreiskott | lanxess arena, cologne, germany | unanimous decision | 6 |
| 10 | 3-0 | 2011-02-19 00:00:00 | win | ergin solmaz | porsche arena, stuttgart, germany | unanimous decision | 4 |
| 11 | 2-0 | 2004-09-03 00:00:00 | win | tomasz zeprzalka | gorazde, bosnia and herzegovina | tko | 2 |
| 12 | 1-0 | 2004-02-07 00:00:00 | win | ergin solmaz | sarajevo, bosnia and herzegovina | unanimous decision | 4 | | | | count ( "opponent" ) |
|---:|-----------------------:|
| 0 | 2 | | [
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select count ( * ) where airdate = '13 june 2013' col : episode no. | airdate | viewers | bbc three weekly ranking | multichannels rank row 1 : 1 | 25 april 2013 | 979,000 | 2 | 9 row 2 : 2 | 2 may 2013 | 978,000 | 1 | 11 row 3 : 3 | 9 may 2013 | 885,000 | 1 | 11 row 4 : 4 | 16 may 2013 | 880,000 | 1 | 13 row 5 : 5 | 23 may 2013 | 1,092,000 | 1 | 5 row 6 : 6 | 30 may 2013 | 1,094,000 | 1 | 3 row 7 : 7 | 6 june 2013 | 975,000 | 2 | 6 row 8 : 8 | 13 june 2013 | 840,000 | 5 | 19 row 9 : 9 | 20 june 2013 | 1,204,000 | 6 | 9 row 10 : 10 | 27 june 2013 | 730,000 | none | 28 row 11 : 11 | 4 july 2013 | none | none | none row 12 : 12 | 11 july 2013 | none | none | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where airdate = '13 june 2013' <table_name> : table \begin{tabular}{llllll}
\toprule
& episode no. & airdate & viewers & bbc three weekly ranking & multichannels rank \\
\midrule
0 & 1 & 25 april 2013 & 979,000 & 2 & 9 \\
1 & 2 & 2 may 2013 & 978,000 & 1 & 11 \\
2 & 3 & 9 may 2013 & 885,000 & 1 & 11 \\
3 & 4 & 16 may 2013 & 880,000 & 1 & 13 \\
4 & 5 & 23 may 2013 & 1,092,000 & 1 & 5 \\
5 & 6 & 30 may 2013 & 1,094,000 & 1 & 3 \\
6 & 7 & 6 june 2013 & 975,000 & 2 & 6 \\
7 & 8 & 13 june 2013 & 840,000 & 5 & 19 \\
8 & 9 & 20 june 2013 & 1,204,000 & 6 & 9 \\
9 & 10 & 27 june 2013 & 730,000 & none & 28 \\
10 & 11 & 4 july 2013 & none & none & none \\
11 & 12 & 11 july 2013 & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where airdate = '13 june 2013' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>episode no.</th>
<th>airdate</th>
<th>viewers</th>
<th>bbc three weekly ranking</th>
<th>multichannels rank</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>25 april 2013</td>
<td>979,000</td>
<td>2</td>
<td>9</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2 may 2013</td>
<td>978,000</td>
<td>1</td>
<td>11</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>9 may 2013</td>
<td>885,000</td>
<td>1</td>
<td>11</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>16 may 2013</td>
<td>880,000</td>
<td>1</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>23 may 2013</td>
<td>1,092,000</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>30 may 2013</td>
<td>1,094,000</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>6 june 2013</td>
<td>975,000</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>13 june 2013</td>
<td>840,000</td>
<td>5</td>
<td>19</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>20 june 2013</td>
<td>1,204,000</td>
<td>6</td>
<td>9</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>27 june 2013</td>
<td>730,000</td>
<td>none</td>
<td>28</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>4 july 2013</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>11 july 2013</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where airdate = '13 june 2013' <table_name> : table | | episode no. | airdate | viewers | bbc three weekly ranking | multichannels rank |
|---:|--------------:|:--------------|:----------|:---------------------------|:---------------------|
| 0 | 1 | 25 april 2013 | 979,000 | 2 | 9 |
| 1 | 2 | 2 may 2013 | 978,000 | 1 | 11 |
| 2 | 3 | 9 may 2013 | 885,000 | 1 | 11 |
| 3 | 4 | 16 may 2013 | 880,000 | 1 | 13 |
| 4 | 5 | 23 may 2013 | 1,092,000 | 1 | 5 |
| 5 | 6 | 30 may 2013 | 1,094,000 | 1 | 3 |
| 6 | 7 | 6 june 2013 | 975,000 | 2 | 6 |
| 7 | 8 | 13 june 2013 | 840,000 | 5 | 19 |
| 8 | 9 | 20 june 2013 | 1,204,000 | 6 | 9 |
| 9 | 10 | 27 june 2013 | 730,000 | none | 28 |
| 10 | 11 | 4 july 2013 | none | none | none |
| 11 | 12 | 11 july 2013 | none | none | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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] |
select count ( notes ) where rank < 0 col : rank | name | nationality | time | notes row 1 : none | jill sterkel | united states | 1:00.53 | nr, gr row 2 : none | lisa buese | united states | 1:00.59 | none row 3 : none | nancy garapick | canada | 1:02.96 | none row 4 : 4 | shelley cramer | u.s. virgin islands | 1:03.51 | nr row 5 : 5 | susan sloan | canada | 1:03.52 | none row 6 : 6 | maria paris | costa rica | 1:03.58 | none row 7 : 7 | rosanna juncos | argentina | 1:04.75 | none row 8 : 8 | adriana pereira | brazil | 1:06.79 | none | col : count ( "notes" ) row 1 : 0 | select count ( notes ) where rank < 0 <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & nationality & time & notes \\
\midrule
0 & none & jill sterkel & united states & 1:00.53 & nr, gr \\
1 & none & lisa buese & united states & 1:00.59 & none \\
2 & none & nancy garapick & canada & 1:02.96 & none \\
3 & 4 & shelley cramer & u.s. virgin islands & 1:03.51 & nr \\
4 & 5 & susan sloan & canada & 1:03.52 & none \\
5 & 6 & maria paris & costa rica & 1:03.58 & none \\
6 & 7 & rosanna juncos & argentina & 1:04.75 & none \\
7 & 8 & adriana pereira & brazil & 1:06.79 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "notes" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( notes ) where rank < 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>time</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>jill sterkel</td>
<td>united states</td>
<td>1:00.53</td>
<td>nr, gr</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>lisa buese</td>
<td>united states</td>
<td>1:00.59</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>nancy garapick</td>
<td>canada</td>
<td>1:02.96</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>shelley cramer</td>
<td>u.s. virgin islands</td>
<td>1:03.51</td>
<td>nr</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>susan sloan</td>
<td>canada</td>
<td>1:03.52</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>maria paris</td>
<td>costa rica</td>
<td>1:03.58</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>rosanna juncos</td>
<td>argentina</td>
<td>1:04.75</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>adriana pereira</td>
<td>brazil</td>
<td>1:06.79</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "notes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( notes ) where rank < 0 <table_name> : table | | rank | name | nationality | time | notes |
|---:|:-------|:----------------|:--------------------|:--------|:--------|
| 0 | none | jill sterkel | united states | 1:00.53 | nr, gr |
| 1 | none | lisa buese | united states | 1:00.59 | none |
| 2 | none | nancy garapick | canada | 1:02.96 | none |
| 3 | 4 | shelley cramer | u.s. virgin islands | 1:03.51 | nr |
| 4 | 5 | susan sloan | canada | 1:03.52 | none |
| 5 | 6 | maria paris | costa rica | 1:03.58 | none |
| 6 | 7 | rosanna juncos | argentina | 1:04.75 | none |
| 7 | 8 | adriana pereira | brazil | 1:06.79 | none | | | | count ( "notes" ) |
|---:|--------------------:|
| 0 | 0 | | [
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select count ( * ) where term (french) > 1091 col : term (french) | description | temperature range -1 | temperature range -2 | usda recommended row 1 : extra-rare or blue (bleu) | very red and cold | 46-49 °c | 115-120 °f | none row 2 : rare (saignant) | cold red center; soft | 52-55 °c | 125-130 °f | none row 3 : medium rare (a point) | warm red center; firmer | 55-60 °c | 130-140 °f | 145 °f row 4 : medium (demi-anglais) | pink and firm | 60-65 °c | 140-150 °f | 160 °f row 5 : medium well (cuit) | small amount of pink in the center | 65-69 °c | 150-155 °f | none row 6 : well done (bien cuit) | gray-brown throughout; firm | 71-100 °c | 160-212 °f | 170 °f row 7 : over cooked (trop cuit, carbonise")' | blacken throughout; hard | > 100 °c | > 212 °f | 300 °f | col : count ( "*" ) row 1 : 7 | select count ( * ) where term (french) > 1091 <table_name> : table \begin{tabular}{llllll}
\toprule
& term (french) & description & temperature range -1 & temperature range -2 & usda recommended \\
\midrule
0 & extra-rare or blue (bleu) & very red and cold & 46-49 °c & 115-120 °f & none \\
1 & rare (saignant) & cold red center; soft & 52-55 °c & 125-130 °f & none \\
2 & medium rare (a point) & warm red center; firmer & 55-60 °c & 130-140 °f & 145 °f \\
3 & medium (demi-anglais) & pink and firm & 60-65 °c & 140-150 °f & 160 °f \\
4 & medium well (cuit) & small amount of pink in the center & 65-69 °c & 150-155 °f & none \\
5 & well done (bien cuit) & gray-brown throughout; firm & 71-100 °c & 160-212 °f & 170 °f \\
6 & over cooked (trop cuit, carbonise")' & blacken throughout; hard & > 100 °c & > 212 °f & 300 °f \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select count ( * ) where term (french) > 1091 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>term (french)</th>
<th>description</th>
<th>temperature range -1</th>
<th>temperature range -2</th>
<th>usda recommended</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>extra-rare or blue (bleu)</td>
<td>very red and cold</td>
<td>46-49 °c</td>
<td>115-120 °f</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>rare (saignant)</td>
<td>cold red center; soft</td>
<td>52-55 °c</td>
<td>125-130 °f</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>medium rare (a point)</td>
<td>warm red center; firmer</td>
<td>55-60 °c</td>
<td>130-140 °f</td>
<td>145 °f</td>
</tr>
<tr>
<th>3</th>
<td>medium (demi-anglais)</td>
<td>pink and firm</td>
<td>60-65 °c</td>
<td>140-150 °f</td>
<td>160 °f</td>
</tr>
<tr>
<th>4</th>
<td>medium well (cuit)</td>
<td>small amount of pink in the center</td>
<td>65-69 °c</td>
<td>150-155 °f</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>well done (bien cuit)</td>
<td>gray-brown throughout; firm</td>
<td>71-100 °c</td>
<td>160-212 °f</td>
<td>170 °f</td>
</tr>
<tr>
<th>6</th>
<td>over cooked (trop cuit, carbonise")'</td>
<td>blacken throughout; hard</td>
<td>> 100 °c</td>
<td>> 212 °f</td>
<td>300 °f</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select count ( * ) where term (french) > 1091 <table_name> : table | | term (french) | description | temperature range -1 | temperature range -2 | usda recommended |
|---:|:-------------------------------------|:-----------------------------------|:-----------------------|:-----------------------|:-------------------|
| 0 | extra-rare or blue (bleu) | very red and cold | 46-49 °c | 115-120 °f | none |
| 1 | rare (saignant) | cold red center; soft | 52-55 °c | 125-130 °f | none |
| 2 | medium rare (a point) | warm red center; firmer | 55-60 °c | 130-140 °f | 145 °f |
| 3 | medium (demi-anglais) | pink and firm | 60-65 °c | 140-150 °f | 160 °f |
| 4 | medium well (cuit) | small amount of pink in the center | 65-69 °c | 150-155 °f | none |
| 5 | well done (bien cuit) | gray-brown throughout; firm | 71-100 °c | 160-212 °f | 170 °f |
| 6 | over cooked (trop cuit, carbonise")' | blacken throughout; hard | > 100 °c | > 212 °f | 300 °f | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 7 | | [
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select match play where country = 'australia' col : golfer | country | wins | match play | championship | invitational | champions row 1 : tiger woods | united states | 18 | 2003, 2004, 2008 | 1999, 2002, 2003, 2005, 2006, 2007, 2013 | 1999, 2000, 2001, 2005, 2006, 2007, 2009, 2013 | none row 2 : geoff ogilvy | australia | 3 | 2006, 2009 | 2008 | none | none row 3 : darren clarke | northern ireland | 2 | 2000 | none | 2003 | none row 4 : ernie els | south africa | 2 | none | 2004, 2010 | none | none row 5 : hunter mahan | united states | 2 | 2012 | none | 2010 | none row 6 : phil mickelson | united states | 2 | none | 2009 | none | 2009 row 7 : ian poulter | england | 2 | 2010 | none | none | 2012 | col : match play row 1 : 2006, 2009 | select match play where country = 'australia' <table_name> : table \begin{tabular}{llllllll}
\toprule
& golfer & country & wins & match play & championship & invitational & champions \\
\midrule
0 & tiger woods & united states & 18 & 2003, 2004, 2008 & 1999, 2002, 2003, 2005, 2006, 2007, 2013 & 1999, 2000, 2001, 2005, 2006, 2007, 2009, 2013 & none \\
1 & geoff ogilvy & australia & 3 & 2006, 2009 & 2008 & none & none \\
2 & darren clarke & northern ireland & 2 & 2000 & none & 2003 & none \\
3 & ernie els & south africa & 2 & none & 2004, 2010 & none & none \\
4 & hunter mahan & united states & 2 & 2012 & none & 2010 & none \\
5 & phil mickelson & united states & 2 & none & 2009 & none & 2009 \\
6 & ian poulter & england & 2 & 2010 & none & none & 2012 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& match play \\
\midrule
0 & 2006, 2009 \\
\bottomrule
\end{tabular}
| select match play where country = 'australia' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>golfer</th>
<th>country</th>
<th>wins</th>
<th>match play</th>
<th>championship</th>
<th>invitational</th>
<th>champions</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>tiger woods</td>
<td>united states</td>
<td>18</td>
<td>2003, 2004, 2008</td>
<td>1999, 2002, 2003, 2005, 2006, 2007, 2013</td>
<td>1999, 2000, 2001, 2005, 2006, 2007, 2009, 2013</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>geoff ogilvy</td>
<td>australia</td>
<td>3</td>
<td>2006, 2009</td>
<td>2008</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>darren clarke</td>
<td>northern ireland</td>
<td>2</td>
<td>2000</td>
<td>none</td>
<td>2003</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>ernie els</td>
<td>south africa</td>
<td>2</td>
<td>none</td>
<td>2004, 2010</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>hunter mahan</td>
<td>united states</td>
<td>2</td>
<td>2012</td>
<td>none</td>
<td>2010</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>phil mickelson</td>
<td>united states</td>
<td>2</td>
<td>none</td>
<td>2009</td>
<td>none</td>
<td>2009</td>
</tr>
<tr>
<th>6</th>
<td>ian poulter</td>
<td>england</td>
<td>2</td>
<td>2010</td>
<td>none</td>
<td>none</td>
<td>2012</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>match play</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2006, 2009</td>
</tr>
</tbody>
</table> | select match play where country = 'australia' <table_name> : table | | golfer | country | wins | match play | championship | invitational | champions |
|---:|:---------------|:-----------------|-------:|:-----------------|:-----------------------------------------|:-----------------------------------------------|:------------|
| 0 | tiger woods | united states | 18 | 2003, 2004, 2008 | 1999, 2002, 2003, 2005, 2006, 2007, 2013 | 1999, 2000, 2001, 2005, 2006, 2007, 2009, 2013 | none |
| 1 | geoff ogilvy | australia | 3 | 2006, 2009 | 2008 | none | none |
| 2 | darren clarke | northern ireland | 2 | 2000 | none | 2003 | none |
| 3 | ernie els | south africa | 2 | none | 2004, 2010 | none | none |
| 4 | hunter mahan | united states | 2 | 2012 | none | 2010 | none |
| 5 | phil mickelson | united states | 2 | none | 2009 | none | 2009 |
| 6 | ian poulter | england | 2 | 2010 | none | none | 2012 | | | | match play |
|---:|:-------------|
| 0 | 2006, 2009 | | [
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select count ( * ) where date = '14 february 1976' col : tie no | home team | score | away team | date row 1 : 1 | leicester city | 1-2 | manchester united | 1976-02-14 00:00:00 row 2 : 2 | bolton wanderers | 3-3 | newcastle united | 1976-02-14 00:00:00 row 3 : replay | newcastle united | 0-0 | bolton wanderers | 1976-02-18 00:00:00 row 4 : replay | bolton wanderers | 1-2 | newcastle united | 1976-02-23 00:00:00 row 5 : 3 | wolverhampton wanderers | 3-0 | charlton athletic | 1976-02-14 00:00:00 row 6 : 4 | west bromwich albion | 1-1 | southampton | 1976-02-14 00:00:00 row 7 : replay | southampton | 4-0 | west bromwich albion | 1976-02-17 00:00:00 row 8 : 5 | derby county | 1-0 | southend united | 1976-02-14 00:00:00 row 9 : 6 | norwich city | 1-2 | bradford city | 1976-02-23 00:00:00 row 10 : 7 | chelsea | 2-3 | crystal palace | 1976-02-14 00:00:00 row 11 : 8 | stoke city | 0-0 | sunderland | 1976-02-14 00:00:00 row 12 : replay | sunderland | 2-1 | stoke city | 1976-02-17 00:00:00 | col : count ( "*" ) row 1 : 7 | select count ( * ) where date = '14 february 1976' <table_name> : table \begin{tabular}{llllll}
\toprule
& tie no & home team & score & away team & date \\
\midrule
0 & 1 & leicester city & 1-2 & manchester united & 1976-02-14 00:00:00 \\
1 & 2 & bolton wanderers & 3-3 & newcastle united & 1976-02-14 00:00:00 \\
2 & replay & newcastle united & 0-0 & bolton wanderers & 1976-02-18 00:00:00 \\
3 & replay & bolton wanderers & 1-2 & newcastle united & 1976-02-23 00:00:00 \\
4 & 3 & wolverhampton wanderers & 3-0 & charlton athletic & 1976-02-14 00:00:00 \\
5 & 4 & west bromwich albion & 1-1 & southampton & 1976-02-14 00:00:00 \\
6 & replay & southampton & 4-0 & west bromwich albion & 1976-02-17 00:00:00 \\
7 & 5 & derby county & 1-0 & southend united & 1976-02-14 00:00:00 \\
8 & 6 & norwich city & 1-2 & bradford city & 1976-02-23 00:00:00 \\
9 & 7 & chelsea & 2-3 & crystal palace & 1976-02-14 00:00:00 \\
10 & 8 & stoke city & 0-0 & sunderland & 1976-02-14 00:00:00 \\
11 & replay & sunderland & 2-1 & stoke city & 1976-02-17 00:00:00 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select count ( * ) where date = '14 february 1976' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>tie no</th>
<th>home team</th>
<th>score</th>
<th>away team</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>leicester city</td>
<td>1-2</td>
<td>manchester united</td>
<td>1976-02-14 00:00:00</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>bolton wanderers</td>
<td>3-3</td>
<td>newcastle united</td>
<td>1976-02-14 00:00:00</td>
</tr>
<tr>
<th>2</th>
<td>replay</td>
<td>newcastle united</td>
<td>0-0</td>
<td>bolton wanderers</td>
<td>1976-02-18 00:00:00</td>
</tr>
<tr>
<th>3</th>
<td>replay</td>
<td>bolton wanderers</td>
<td>1-2</td>
<td>newcastle united</td>
<td>1976-02-23 00:00:00</td>
</tr>
<tr>
<th>4</th>
<td>3</td>
<td>wolverhampton wanderers</td>
<td>3-0</td>
<td>charlton athletic</td>
<td>1976-02-14 00:00:00</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>west bromwich albion</td>
<td>1-1</td>
<td>southampton</td>
<td>1976-02-14 00:00:00</td>
</tr>
<tr>
<th>6</th>
<td>replay</td>
<td>southampton</td>
<td>4-0</td>
<td>west bromwich albion</td>
<td>1976-02-17 00:00:00</td>
</tr>
<tr>
<th>7</th>
<td>5</td>
<td>derby county</td>
<td>1-0</td>
<td>southend united</td>
<td>1976-02-14 00:00:00</td>
</tr>
<tr>
<th>8</th>
<td>6</td>
<td>norwich city</td>
<td>1-2</td>
<td>bradford city</td>
<td>1976-02-23 00:00:00</td>
</tr>
<tr>
<th>9</th>
<td>7</td>
<td>chelsea</td>
<td>2-3</td>
<td>crystal palace</td>
<td>1976-02-14 00:00:00</td>
</tr>
<tr>
<th>10</th>
<td>8</td>
<td>stoke city</td>
<td>0-0</td>
<td>sunderland</td>
<td>1976-02-14 00:00:00</td>
</tr>
<tr>
<th>11</th>
<td>replay</td>
<td>sunderland</td>
<td>2-1</td>
<td>stoke city</td>
<td>1976-02-17 00:00:00</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select count ( * ) where date = '14 february 1976' <table_name> : table | | tie no | home team | score | away team | date |
|---:|:---------|:------------------------|:--------|:---------------------|:--------------------|
| 0 | 1 | leicester city | 1-2 | manchester united | 1976-02-14 00:00:00 |
| 1 | 2 | bolton wanderers | 3-3 | newcastle united | 1976-02-14 00:00:00 |
| 2 | replay | newcastle united | 0-0 | bolton wanderers | 1976-02-18 00:00:00 |
| 3 | replay | bolton wanderers | 1-2 | newcastle united | 1976-02-23 00:00:00 |
| 4 | 3 | wolverhampton wanderers | 3-0 | charlton athletic | 1976-02-14 00:00:00 |
| 5 | 4 | west bromwich albion | 1-1 | southampton | 1976-02-14 00:00:00 |
| 6 | replay | southampton | 4-0 | west bromwich albion | 1976-02-17 00:00:00 |
| 7 | 5 | derby county | 1-0 | southend united | 1976-02-14 00:00:00 |
| 8 | 6 | norwich city | 1-2 | bradford city | 1976-02-23 00:00:00 |
| 9 | 7 | chelsea | 2-3 | crystal palace | 1976-02-14 00:00:00 |
| 10 | 8 | stoke city | 0-0 | sunderland | 1976-02-14 00:00:00 |
| 11 | replay | sunderland | 2-1 | stoke city | 1976-02-17 00:00:00 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 7 | | [
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select opponent where result = 'win' col : week | date | opponent | score | result | record row 1 : 1 | aug 28 | at toronto argonauts | 13-6 | loss | 0-1 row 2 : 2 | sept 4 | at montreal alouettes | 21-2 | loss | 0-2 row 3 : 2 | sept 6 | vs. montreal alouettes | 20-11 | loss | 0-3 row 4 : 3 | sept 11 | at toronto argonauts | 12-5 | win | 1-3 row 5 : 4 | sept 18 | vs. toronto argonauts | 34-6 | loss | 1-4 row 6 : 5 | sept 25 | vs. hamilton tiger-cats | 38-12 | loss | 1-5 row 7 : 6 | oct 2 | at hamilton tiger-cats | 45-0 | loss | 1-6 row 8 : 7 | oct 9 | vs. montreal alouettes | 25-11 | loss | 1-7 row 9 : 7 | oct 11 | at montreal alouettes | 24-6 | loss | 1-8 row 10 : 8 | oct 16 | vs. toronto argonauts | 27-11 | loss | 1-9 row 11 : 9 | oct 23 | at hamilton tiger-cats | 25-17 | loss | 1-10 row 12 : 10 | oct 30 | vs. hamilton tiger-cats | 30-9 | loss | 1-11 row 13 : 11 | nov 6 | at toronto argonauts | 18-12 | loss | 1-12 row 14 : 12 | nov 13 | vs. montreal alouettes | 14-12 | win | 2-12 | col : opponent row 1 : at toronto argonauts row 2 : vs. montreal alouettes | select opponent where result = 'win' <table_name> : table \begin{tabular}{lllllll}
\toprule
& week & date & opponent & score & result & record \\
\midrule
0 & 1 & aug 28 & at toronto argonauts & 13-6 & loss & 0-1 \\
1 & 2 & sept 4 & at montreal alouettes & 21-2 & loss & 0-2 \\
2 & 2 & sept 6 & vs. montreal alouettes & 20-11 & loss & 0-3 \\
3 & 3 & sept 11 & at toronto argonauts & 12-5 & win & 1-3 \\
4 & 4 & sept 18 & vs. toronto argonauts & 34-6 & loss & 1-4 \\
5 & 5 & sept 25 & vs. hamilton tiger-cats & 38-12 & loss & 1-5 \\
6 & 6 & oct 2 & at hamilton tiger-cats & 45-0 & loss & 1-6 \\
7 & 7 & oct 9 & vs. montreal alouettes & 25-11 & loss & 1-7 \\
8 & 7 & oct 11 & at montreal alouettes & 24-6 & loss & 1-8 \\
9 & 8 & oct 16 & vs. toronto argonauts & 27-11 & loss & 1-9 \\
10 & 9 & oct 23 & at hamilton tiger-cats & 25-17 & loss & 1-10 \\
11 & 10 & oct 30 & vs. hamilton tiger-cats & 30-9 & loss & 1-11 \\
12 & 11 & nov 6 & at toronto argonauts & 18-12 & loss & 1-12 \\
13 & 12 & nov 13 & vs. montreal alouettes & 14-12 & win & 2-12 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& opponent \\
\midrule
0 & at toronto argonauts \\
1 & vs. montreal alouettes \\
\bottomrule
\end{tabular}
| select opponent where result = 'win' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>opponent</th>
<th>score</th>
<th>result</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>aug 28</td>
<td>at toronto argonauts</td>
<td>13-6</td>
<td>loss</td>
<td>0-1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>sept 4</td>
<td>at montreal alouettes</td>
<td>21-2</td>
<td>loss</td>
<td>0-2</td>
</tr>
<tr>
<th>2</th>
<td>2</td>
<td>sept 6</td>
<td>vs. montreal alouettes</td>
<td>20-11</td>
<td>loss</td>
<td>0-3</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>sept 11</td>
<td>at toronto argonauts</td>
<td>12-5</td>
<td>win</td>
<td>1-3</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>sept 18</td>
<td>vs. toronto argonauts</td>
<td>34-6</td>
<td>loss</td>
<td>1-4</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>sept 25</td>
<td>vs. hamilton tiger-cats</td>
<td>38-12</td>
<td>loss</td>
<td>1-5</td>
</tr>
<tr>
<th>6</th>
<td>6</td>
<td>oct 2</td>
<td>at hamilton tiger-cats</td>
<td>45-0</td>
<td>loss</td>
<td>1-6</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>oct 9</td>
<td>vs. montreal alouettes</td>
<td>25-11</td>
<td>loss</td>
<td>1-7</td>
</tr>
<tr>
<th>8</th>
<td>7</td>
<td>oct 11</td>
<td>at montreal alouettes</td>
<td>24-6</td>
<td>loss</td>
<td>1-8</td>
</tr>
<tr>
<th>9</th>
<td>8</td>
<td>oct 16</td>
<td>vs. toronto argonauts</td>
<td>27-11</td>
<td>loss</td>
<td>1-9</td>
</tr>
<tr>
<th>10</th>
<td>9</td>
<td>oct 23</td>
<td>at hamilton tiger-cats</td>
<td>25-17</td>
<td>loss</td>
<td>1-10</td>
</tr>
<tr>
<th>11</th>
<td>10</td>
<td>oct 30</td>
<td>vs. hamilton tiger-cats</td>
<td>30-9</td>
<td>loss</td>
<td>1-11</td>
</tr>
<tr>
<th>12</th>
<td>11</td>
<td>nov 6</td>
<td>at toronto argonauts</td>
<td>18-12</td>
<td>loss</td>
<td>1-12</td>
</tr>
<tr>
<th>13</th>
<td>12</td>
<td>nov 13</td>
<td>vs. montreal alouettes</td>
<td>14-12</td>
<td>win</td>
<td>2-12</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>opponent</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>at toronto argonauts</td>
</tr>
<tr>
<th>1</th>
<td>vs. montreal alouettes</td>
</tr>
</tbody>
</table> | select opponent where result = 'win' <table_name> : table | | week | date | opponent | score | result | record |
|---:|-------:|:--------|:------------------------|:--------|:---------|:---------|
| 0 | 1 | aug 28 | at toronto argonauts | 13-6 | loss | 0-1 |
| 1 | 2 | sept 4 | at montreal alouettes | 21-2 | loss | 0-2 |
| 2 | 2 | sept 6 | vs. montreal alouettes | 20-11 | loss | 0-3 |
| 3 | 3 | sept 11 | at toronto argonauts | 12-5 | win | 1-3 |
| 4 | 4 | sept 18 | vs. toronto argonauts | 34-6 | loss | 1-4 |
| 5 | 5 | sept 25 | vs. hamilton tiger-cats | 38-12 | loss | 1-5 |
| 6 | 6 | oct 2 | at hamilton tiger-cats | 45-0 | loss | 1-6 |
| 7 | 7 | oct 9 | vs. montreal alouettes | 25-11 | loss | 1-7 |
| 8 | 7 | oct 11 | at montreal alouettes | 24-6 | loss | 1-8 |
| 9 | 8 | oct 16 | vs. toronto argonauts | 27-11 | loss | 1-9 |
| 10 | 9 | oct 23 | at hamilton tiger-cats | 25-17 | loss | 1-10 |
| 11 | 10 | oct 30 | vs. hamilton tiger-cats | 30-9 | loss | 1-11 |
| 12 | 11 | nov 6 | at toronto argonauts | 18-12 | loss | 1-12 |
| 13 | 12 | nov 13 | vs. montreal alouettes | 14-12 | win | 2-12 | | | | opponent |
|---:|:-----------------------|
| 0 | at toronto argonauts |
| 1 | vs. montreal alouettes | | [
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] |
select avg ( alumni chapters and clubs + location ) where founding date = 2 col : alumni chapters and clubs | location | founding date | years active | province row 1 : zeta alpha | detroit, mi | 1925 | none | beta row 2 : zeta beta | columbus, oh | december 14, 1926 | none | alpha north row 3 : zeta gamma | cincinnati, oh | december 14, 1926 | none | alpha south row 4 : zeta delta | milwaukee, wi | february 7, 1927 | 1927-present | mu row 5 : zeta epsilon | chicago, il | may 21, 1928 | none | none row 6 : zeta zeta | denver, co | november 23, 1940 | none | gamma row 7 : zeta eta | bloomington-normal, il | december 13, 1941 | none | delta row 8 : zeta theta | los angeles, ca | 1943 | none | none row 9 : zeta iota | louisville, ky | 1944 | none | alpha south row 10 : zeta kappa | cincinnati, oh | may 16, 1946 | none | none row 11 : zeta lambda | baton rouge, la | 1946 | none | none row 12 : zeta mu | lincoln, ne | february 22, 1947 | none | none row 13 : zeta nu | ann arbor, mi | december 1948 | none | none row 14 : zeta xi | oakland county, mi | july 7, 1953 | none | none row 15 : zeta omicron | akron-kent, oh | may 27, 1956 | 1956-present | alpha north row 16 : zeta pi | columbia, sc | december 7, 1958 | none | none row 17 : zeta rho | kearney, ne | march 7, 1959 | none | none row 18 : zeta sigma | cleveland, oh | may 15, 1960 | none | alpha north row 19 : zeta tau | st. petersburg, fl | december 10, 1960 | none | none row 20 : zeta upsilon | washington, d.c | december 18, 1961 | none | none row 21 : zeta phi | beaumont, tx | march 25, 1962 | none | none row 22 : zeta chi | dayton, oh | february 14, 1967 | 1967-present | alpha south row 23 : zeta psi | philadelphia, pa | june 4, 1967 | none | none row 24 : zeta omega | spartanburg-greenville, sc | april 12, 1969 | none | none row 25 : eta alpha | pueblo, co | may 25, 1969 | none | none row 26 : eta beta | brownwood, tx | november 14, 1969 | none | none row 27 : eta gamma | ft. collins, co | march 7, 1970 | none | none row 28 : eta delta | san antonio, tx | february 20, 1971 | none | none row 29 : eta epsilon | atlanta, ga | february 23, 1971 | none | none row 30 : eta zeta | buffalo, ny | may 2, 1971 | none | none row 31 : eta eta | jacksonville, al | may 13, 1972 | none | none row 32 : eta theta | dallas, tx | november 9, 1975 | none | none row 33 : eta iota | huntsville, al | september 24, 1978 | none | none row 34 : eta kappa | phoenix, az | january 26, 1980 | none | none row 35 : eta lambda | lithonia, ga | may 18, 2003 | 2004-2011 | iota row 36 : eta mu | atlanta, ga | july 18, 2004 | 2004-2011 | iota row 37 : champaign-urbana alumni club | chambaign-urbana, il | none | none | delta row 38 : lincoln alumni club | lincoln, ne | none | none | theta row 39 : kearney alumni club | kearney, ne | none | none | theta row 40 : georgia alumni club | decatur, ga | none | none | iota row 41 : frostburg alumni club | frostburg, md | none | none | lambda row 42 : cincinnati alumni club | cincinnati, oh | none | none | eta south row 43 : atlanta alumni club | atlanta, ga | none | none | iota row 44 : middle tennessee alumni club | murfreesboro, tn | 2013 | 2013-present | zeta west | col : avg ( "alumni chapters and clubs + location" ) row 1 : | select avg ( alumni chapters and clubs + location ) where founding date = 2 <table_name> : table \begin{tabular}{llllll}
\toprule
& alumni chapters and clubs & location & founding date & years active & province \\
\midrule
0 & zeta alpha & detroit, mi & 1925 & none & beta \\
1 & zeta beta & columbus, oh & december 14, 1926 & none & alpha north \\
2 & zeta gamma & cincinnati, oh & december 14, 1926 & none & alpha south \\
3 & zeta delta & milwaukee, wi & february 7, 1927 & 1927-present & mu \\
4 & zeta epsilon & chicago, il & may 21, 1928 & none & none \\
5 & zeta zeta & denver, co & november 23, 1940 & none & gamma \\
6 & zeta eta & bloomington-normal, il & december 13, 1941 & none & delta \\
7 & zeta theta & los angeles, ca & 1943 & none & none \\
8 & zeta iota & louisville, ky & 1944 & none & alpha south \\
9 & zeta kappa & cincinnati, oh & may 16, 1946 & none & none \\
10 & zeta lambda & baton rouge, la & 1946 & none & none \\
11 & zeta mu & lincoln, ne & february 22, 1947 & none & none \\
12 & zeta nu & ann arbor, mi & december 1948 & none & none \\
13 & zeta xi & oakland county, mi & july 7, 1953 & none & none \\
14 & zeta omicron & akron-kent, oh & may 27, 1956 & 1956-present & alpha north \\
15 & zeta pi & columbia, sc & december 7, 1958 & none & none \\
16 & zeta rho & kearney, ne & march 7, 1959 & none & none \\
17 & zeta sigma & cleveland, oh & may 15, 1960 & none & alpha north \\
18 & zeta tau & st. petersburg, fl & december 10, 1960 & none & none \\
19 & zeta upsilon & washington, d.c & december 18, 1961 & none & none \\
20 & zeta phi & beaumont, tx & march 25, 1962 & none & none \\
21 & zeta chi & dayton, oh & february 14, 1967 & 1967-present & alpha south \\
22 & zeta psi & philadelphia, pa & june 4, 1967 & none & none \\
23 & zeta omega & spartanburg-greenville, sc & april 12, 1969 & none & none \\
24 & eta alpha & pueblo, co & may 25, 1969 & none & none \\
25 & eta beta & brownwood, tx & november 14, 1969 & none & none \\
26 & eta gamma & ft. collins, co & march 7, 1970 & none & none \\
27 & eta delta & san antonio, tx & february 20, 1971 & none & none \\
28 & eta epsilon & atlanta, ga & february 23, 1971 & none & none \\
29 & eta zeta & buffalo, ny & may 2, 1971 & none & none \\
30 & eta eta & jacksonville, al & may 13, 1972 & none & none \\
31 & eta theta & dallas, tx & november 9, 1975 & none & none \\
32 & eta iota & huntsville, al & september 24, 1978 & none & none \\
33 & eta kappa & phoenix, az & january 26, 1980 & none & none \\
34 & eta lambda & lithonia, ga & may 18, 2003 & 2004-2011 & iota \\
35 & eta mu & atlanta, ga & july 18, 2004 & 2004-2011 & iota \\
36 & champaign-urbana alumni club & chambaign-urbana, il & none & none & delta \\
37 & lincoln alumni club & lincoln, ne & none & none & theta \\
38 & kearney alumni club & kearney, ne & none & none & theta \\
39 & georgia alumni club & decatur, ga & none & none & iota \\
40 & frostburg alumni club & frostburg, md & none & none & lambda \\
41 & cincinnati alumni club & cincinnati, oh & none & none & eta south \\
42 & atlanta alumni club & atlanta, ga & none & none & iota \\
43 & middle tennessee alumni club & murfreesboro, tn & 2013 & 2013-present & zeta west \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& avg ( "alumni chapters and clubs + location" ) \\
\midrule
0 & \\
\bottomrule
\end{tabular}
| select avg ( alumni chapters and clubs + location ) where founding date = 2 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>alumni chapters and clubs</th>
<th>location</th>
<th>founding date</th>
<th>years active</th>
<th>province</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>zeta alpha</td>
<td>detroit, mi</td>
<td>1925</td>
<td>none</td>
<td>beta</td>
</tr>
<tr>
<th>1</th>
<td>zeta beta</td>
<td>columbus, oh</td>
<td>december 14, 1926</td>
<td>none</td>
<td>alpha north</td>
</tr>
<tr>
<th>2</th>
<td>zeta gamma</td>
<td>cincinnati, oh</td>
<td>december 14, 1926</td>
<td>none</td>
<td>alpha south</td>
</tr>
<tr>
<th>3</th>
<td>zeta delta</td>
<td>milwaukee, wi</td>
<td>february 7, 1927</td>
<td>1927-present</td>
<td>mu</td>
</tr>
<tr>
<th>4</th>
<td>zeta epsilon</td>
<td>chicago, il</td>
<td>may 21, 1928</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>zeta zeta</td>
<td>denver, co</td>
<td>november 23, 1940</td>
<td>none</td>
<td>gamma</td>
</tr>
<tr>
<th>6</th>
<td>zeta eta</td>
<td>bloomington-normal, il</td>
<td>december 13, 1941</td>
<td>none</td>
<td>delta</td>
</tr>
<tr>
<th>7</th>
<td>zeta theta</td>
<td>los angeles, ca</td>
<td>1943</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>zeta iota</td>
<td>louisville, ky</td>
<td>1944</td>
<td>none</td>
<td>alpha south</td>
</tr>
<tr>
<th>9</th>
<td>zeta kappa</td>
<td>cincinnati, oh</td>
<td>may 16, 1946</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>zeta lambda</td>
<td>baton rouge, la</td>
<td>1946</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>zeta mu</td>
<td>lincoln, ne</td>
<td>february 22, 1947</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>zeta nu</td>
<td>ann arbor, mi</td>
<td>december 1948</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>zeta xi</td>
<td>oakland county, mi</td>
<td>july 7, 1953</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>zeta omicron</td>
<td>akron-kent, oh</td>
<td>may 27, 1956</td>
<td>1956-present</td>
<td>alpha north</td>
</tr>
<tr>
<th>15</th>
<td>zeta pi</td>
<td>columbia, sc</td>
<td>december 7, 1958</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>zeta rho</td>
<td>kearney, ne</td>
<td>march 7, 1959</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>zeta sigma</td>
<td>cleveland, oh</td>
<td>may 15, 1960</td>
<td>none</td>
<td>alpha north</td>
</tr>
<tr>
<th>18</th>
<td>zeta tau</td>
<td>st. petersburg, fl</td>
<td>december 10, 1960</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>zeta upsilon</td>
<td>washington, d.c</td>
<td>december 18, 1961</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>zeta phi</td>
<td>beaumont, tx</td>
<td>march 25, 1962</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>zeta chi</td>
<td>dayton, oh</td>
<td>february 14, 1967</td>
<td>1967-present</td>
<td>alpha south</td>
</tr>
<tr>
<th>22</th>
<td>zeta psi</td>
<td>philadelphia, pa</td>
<td>june 4, 1967</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>zeta omega</td>
<td>spartanburg-greenville, sc</td>
<td>april 12, 1969</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>eta alpha</td>
<td>pueblo, co</td>
<td>may 25, 1969</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>eta beta</td>
<td>brownwood, tx</td>
<td>november 14, 1969</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>eta gamma</td>
<td>ft. collins, co</td>
<td>march 7, 1970</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>eta delta</td>
<td>san antonio, tx</td>
<td>february 20, 1971</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>eta epsilon</td>
<td>atlanta, ga</td>
<td>february 23, 1971</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>eta zeta</td>
<td>buffalo, ny</td>
<td>may 2, 1971</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>eta eta</td>
<td>jacksonville, al</td>
<td>may 13, 1972</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>eta theta</td>
<td>dallas, tx</td>
<td>november 9, 1975</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>eta iota</td>
<td>huntsville, al</td>
<td>september 24, 1978</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>33</th>
<td>eta kappa</td>
<td>phoenix, az</td>
<td>january 26, 1980</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>34</th>
<td>eta lambda</td>
<td>lithonia, ga</td>
<td>may 18, 2003</td>
<td>2004-2011</td>
<td>iota</td>
</tr>
<tr>
<th>35</th>
<td>eta mu</td>
<td>atlanta, ga</td>
<td>july 18, 2004</td>
<td>2004-2011</td>
<td>iota</td>
</tr>
<tr>
<th>36</th>
<td>champaign-urbana alumni club</td>
<td>chambaign-urbana, il</td>
<td>none</td>
<td>none</td>
<td>delta</td>
</tr>
<tr>
<th>37</th>
<td>lincoln alumni club</td>
<td>lincoln, ne</td>
<td>none</td>
<td>none</td>
<td>theta</td>
</tr>
<tr>
<th>38</th>
<td>kearney alumni club</td>
<td>kearney, ne</td>
<td>none</td>
<td>none</td>
<td>theta</td>
</tr>
<tr>
<th>39</th>
<td>georgia alumni club</td>
<td>decatur, ga</td>
<td>none</td>
<td>none</td>
<td>iota</td>
</tr>
<tr>
<th>40</th>
<td>frostburg alumni club</td>
<td>frostburg, md</td>
<td>none</td>
<td>none</td>
<td>lambda</td>
</tr>
<tr>
<th>41</th>
<td>cincinnati alumni club</td>
<td>cincinnati, oh</td>
<td>none</td>
<td>none</td>
<td>eta south</td>
</tr>
<tr>
<th>42</th>
<td>atlanta alumni club</td>
<td>atlanta, ga</td>
<td>none</td>
<td>none</td>
<td>iota</td>
</tr>
<tr>
<th>43</th>
<td>middle tennessee alumni club</td>
<td>murfreesboro, tn</td>
<td>2013</td>
<td>2013-present</td>
<td>zeta west</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>avg ( "alumni chapters and clubs + location" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td></td>
</tr>
</tbody>
</table> | select avg ( alumni chapters and clubs + location ) where founding date = 2 <table_name> : table | | alumni chapters and clubs | location | founding date | years active | province |
|---:|:-----------------------------|:---------------------------|:-------------------|:---------------|:------------|
| 0 | zeta alpha | detroit, mi | 1925 | none | beta |
| 1 | zeta beta | columbus, oh | december 14, 1926 | none | alpha north |
| 2 | zeta gamma | cincinnati, oh | december 14, 1926 | none | alpha south |
| 3 | zeta delta | milwaukee, wi | february 7, 1927 | 1927-present | mu |
| 4 | zeta epsilon | chicago, il | may 21, 1928 | none | none |
| 5 | zeta zeta | denver, co | november 23, 1940 | none | gamma |
| 6 | zeta eta | bloomington-normal, il | december 13, 1941 | none | delta |
| 7 | zeta theta | los angeles, ca | 1943 | none | none |
| 8 | zeta iota | louisville, ky | 1944 | none | alpha south |
| 9 | zeta kappa | cincinnati, oh | may 16, 1946 | none | none |
| 10 | zeta lambda | baton rouge, la | 1946 | none | none |
| 11 | zeta mu | lincoln, ne | february 22, 1947 | none | none |
| 12 | zeta nu | ann arbor, mi | december 1948 | none | none |
| 13 | zeta xi | oakland county, mi | july 7, 1953 | none | none |
| 14 | zeta omicron | akron-kent, oh | may 27, 1956 | 1956-present | alpha north |
| 15 | zeta pi | columbia, sc | december 7, 1958 | none | none |
| 16 | zeta rho | kearney, ne | march 7, 1959 | none | none |
| 17 | zeta sigma | cleveland, oh | may 15, 1960 | none | alpha north |
| 18 | zeta tau | st. petersburg, fl | december 10, 1960 | none | none |
| 19 | zeta upsilon | washington, d.c | december 18, 1961 | none | none |
| 20 | zeta phi | beaumont, tx | march 25, 1962 | none | none |
| 21 | zeta chi | dayton, oh | february 14, 1967 | 1967-present | alpha south |
| 22 | zeta psi | philadelphia, pa | june 4, 1967 | none | none |
| 23 | zeta omega | spartanburg-greenville, sc | april 12, 1969 | none | none |
| 24 | eta alpha | pueblo, co | may 25, 1969 | none | none |
| 25 | eta beta | brownwood, tx | november 14, 1969 | none | none |
| 26 | eta gamma | ft. collins, co | march 7, 1970 | none | none |
| 27 | eta delta | san antonio, tx | february 20, 1971 | none | none |
| 28 | eta epsilon | atlanta, ga | february 23, 1971 | none | none |
| 29 | eta zeta | buffalo, ny | may 2, 1971 | none | none |
| 30 | eta eta | jacksonville, al | may 13, 1972 | none | none |
| 31 | eta theta | dallas, tx | november 9, 1975 | none | none |
| 32 | eta iota | huntsville, al | september 24, 1978 | none | none |
| 33 | eta kappa | phoenix, az | january 26, 1980 | none | none |
| 34 | eta lambda | lithonia, ga | may 18, 2003 | 2004-2011 | iota |
| 35 | eta mu | atlanta, ga | july 18, 2004 | 2004-2011 | iota |
| 36 | champaign-urbana alumni club | chambaign-urbana, il | none | none | delta |
| 37 | lincoln alumni club | lincoln, ne | none | none | theta |
| 38 | kearney alumni club | kearney, ne | none | none | theta |
| 39 | georgia alumni club | decatur, ga | none | none | iota |
| 40 | frostburg alumni club | frostburg, md | none | none | lambda |
| 41 | cincinnati alumni club | cincinnati, oh | none | none | eta south |
| 42 | atlanta alumni club | atlanta, ga | none | none | iota |
| 43 | middle tennessee alumni club | murfreesboro, tn | 2013 | 2013-present | zeta west | | | | avg ( "alumni chapters and clubs + location" ) |
|---:|:-------------------------------------------------|
| 0 | | | [
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select count ( * ) where match no. = 28 col : match no. | match type | team europe | score | team usa | progressive total row 1 : 25 | singles | mika koivuniemi | 217 - 279 | chris barnes | 14 - 11 row 2 : 26 | singles | osku palermaa | 217 - 244 | tommy jones | 14 - 12 row 3 : 27 | singles | paul moor | 210 - 199 | tim mack | 15 - 12 row 4 : 28 | singles | tore torgersen | 206 - 275 | doug kent | 15 - 13 row 5 : 29 | singles | tomas leandersson | 176 - 258 | bill hoffman | 15 - 14 row 6 : 30 | baker | team europe | 202 - 203 | team usa | 15 - 15 row 7 : 31 | singles | tore torgersen | 202 - 264 | chris barnes | 15 - 16 row 8 : 32 | singles | osku palermaa | 196 - 235 | tommy jones | 15 - 17 | col : count ( "*" ) row 1 : 1 | select count ( * ) where match no. = 28 <table_name> : table \begin{tabular}{lllllll}
\toprule
& match no. & match type & team europe & score & team usa & progressive total \\
\midrule
0 & 25 & singles & mika koivuniemi & 217 - 279 & chris barnes & 14 - 11 \\
1 & 26 & singles & osku palermaa & 217 - 244 & tommy jones & 14 - 12 \\
2 & 27 & singles & paul moor & 210 - 199 & tim mack & 15 - 12 \\
3 & 28 & singles & tore torgersen & 206 - 275 & doug kent & 15 - 13 \\
4 & 29 & singles & tomas leandersson & 176 - 258 & bill hoffman & 15 - 14 \\
5 & 30 & baker & team europe & 202 - 203 & team usa & 15 - 15 \\
6 & 31 & singles & tore torgersen & 202 - 264 & chris barnes & 15 - 16 \\
7 & 32 & singles & osku palermaa & 196 - 235 & tommy jones & 15 - 17 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where match no. = 28 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>match no.</th>
<th>match type</th>
<th>team europe</th>
<th>score</th>
<th>team usa</th>
<th>progressive total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>25</td>
<td>singles</td>
<td>mika koivuniemi</td>
<td>217 - 279</td>
<td>chris barnes</td>
<td>14 - 11</td>
</tr>
<tr>
<th>1</th>
<td>26</td>
<td>singles</td>
<td>osku palermaa</td>
<td>217 - 244</td>
<td>tommy jones</td>
<td>14 - 12</td>
</tr>
<tr>
<th>2</th>
<td>27</td>
<td>singles</td>
<td>paul moor</td>
<td>210 - 199</td>
<td>tim mack</td>
<td>15 - 12</td>
</tr>
<tr>
<th>3</th>
<td>28</td>
<td>singles</td>
<td>tore torgersen</td>
<td>206 - 275</td>
<td>doug kent</td>
<td>15 - 13</td>
</tr>
<tr>
<th>4</th>
<td>29</td>
<td>singles</td>
<td>tomas leandersson</td>
<td>176 - 258</td>
<td>bill hoffman</td>
<td>15 - 14</td>
</tr>
<tr>
<th>5</th>
<td>30</td>
<td>baker</td>
<td>team europe</td>
<td>202 - 203</td>
<td>team usa</td>
<td>15 - 15</td>
</tr>
<tr>
<th>6</th>
<td>31</td>
<td>singles</td>
<td>tore torgersen</td>
<td>202 - 264</td>
<td>chris barnes</td>
<td>15 - 16</td>
</tr>
<tr>
<th>7</th>
<td>32</td>
<td>singles</td>
<td>osku palermaa</td>
<td>196 - 235</td>
<td>tommy jones</td>
<td>15 - 17</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where match no. = 28 <table_name> : table | | match no. | match type | team europe | score | team usa | progressive total |
|---:|------------:|:-------------|:------------------|:----------|:-------------|:--------------------|
| 0 | 25 | singles | mika koivuniemi | 217 - 279 | chris barnes | 14 - 11 |
| 1 | 26 | singles | osku palermaa | 217 - 244 | tommy jones | 14 - 12 |
| 2 | 27 | singles | paul moor | 210 - 199 | tim mack | 15 - 12 |
| 3 | 28 | singles | tore torgersen | 206 - 275 | doug kent | 15 - 13 |
| 4 | 29 | singles | tomas leandersson | 176 - 258 | bill hoffman | 15 - 14 |
| 5 | 30 | baker | team europe | 202 - 203 | team usa | 15 - 15 |
| 6 | 31 | singles | tore torgersen | 202 - 264 | chris barnes | 15 - 16 |
| 7 | 32 | singles | osku palermaa | 196 - 235 | tommy jones | 15 - 17 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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] |
select count ( * ) where nationality = 385 col : rank | name | nationality | time row 1 : none | joanne malar | canada | 4:43.64 row 2 : none | alison fealey | united states | 4:48.31 row 3 : none | jenny kurth | united states | 4:57.24 row 4 : 4 | sonia fonseca | puerto rico | 5:03.15 row 5 : 5 | fabiola molina | brazil | 5:03.43 row 6 : 6 | isabel rojas | colombia | 5:11.58 row 7 : 7 | carolyn adel | suriname | 5:13.24 row 8 : 8 | edith arraspide | argentina | 5:13.95 | col : count ( "*" ) row 1 : 0 | select count ( * ) where nationality = 385 <table_name> : table \begin{tabular}{lllll}
\toprule
& rank & name & nationality & time \\
\midrule
0 & none & joanne malar & canada & 4:43.64 \\
1 & none & alison fealey & united states & 4:48.31 \\
2 & none & jenny kurth & united states & 4:57.24 \\
3 & 4 & sonia fonseca & puerto rico & 5:03.15 \\
4 & 5 & fabiola molina & brazil & 5:03.43 \\
5 & 6 & isabel rojas & colombia & 5:11.58 \\
6 & 7 & carolyn adel & suriname & 5:13.24 \\
7 & 8 & edith arraspide & argentina & 5:13.95 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where nationality = 385 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>joanne malar</td>
<td>canada</td>
<td>4:43.64</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>alison fealey</td>
<td>united states</td>
<td>4:48.31</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>jenny kurth</td>
<td>united states</td>
<td>4:57.24</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>sonia fonseca</td>
<td>puerto rico</td>
<td>5:03.15</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>fabiola molina</td>
<td>brazil</td>
<td>5:03.43</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>isabel rojas</td>
<td>colombia</td>
<td>5:11.58</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>carolyn adel</td>
<td>suriname</td>
<td>5:13.24</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>edith arraspide</td>
<td>argentina</td>
<td>5:13.95</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where nationality = 385 <table_name> : table | | rank | name | nationality | time |
|---:|:-------|:----------------|:--------------|:--------|
| 0 | none | joanne malar | canada | 4:43.64 |
| 1 | none | alison fealey | united states | 4:48.31 |
| 2 | none | jenny kurth | united states | 4:57.24 |
| 3 | 4 | sonia fonseca | puerto rico | 5:03.15 |
| 4 | 5 | fabiola molina | brazil | 5:03.43 |
| 5 | 6 | isabel rojas | colombia | 5:11.58 |
| 6 | 7 | carolyn adel | suriname | 5:13.24 |
| 7 | 8 | edith arraspide | argentina | 5:13.95 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select rank where advocate = 'sook-yin lee' col : rank | name | notability | birthplace | advocate row 1 : 10 | wayne gretzky | hockey player, holder of numerous nhl records | brantford, ontario | deborah grey row 2 : 9 | alexander graham bell | scientist, inventor, founder of the bell telephone company | edinburgh, scotland | evan solomon row 3 : 8 | sir john a. macdonald | first prime minister of canada | glasgow, scotland | charlotte gray row 4 : 7 | don cherry | hockey coach and commentator | kingston, ontario | bret hart row 5 : 6 | lester b. pearson | fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate | toronto, ontario | paul gross row 6 : 5 | david suzuki | environmentalist | vancouver, british columbia | melissa auf der maur row 7 : 4 | sir frederick banting | medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine | alliston, ontario | mary walsh row 8 : 3 | pierre trudeau | fifteenth prime minister of canada | montreal, quebec | rex murphy row 9 : 2 | terry fox | athlete, activist, humanitarian | winnipeg, manitoba | sook-yin lee row 10 : 1 | tommy douglas | father of medicare, premier of saskatchewan | falkirk, scotland | george stroumboulopoulos | col : rank row 1 : 2 | select rank where advocate = 'sook-yin lee' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & notability & birthplace & advocate \\
\midrule
0 & 10 & wayne gretzky & hockey player, holder of numerous nhl records & brantford, ontario & deborah grey \\
1 & 9 & alexander graham bell & scientist, inventor, founder of the bell telephone company & edinburgh, scotland & evan solomon \\
2 & 8 & sir john a. macdonald & first prime minister of canada & glasgow, scotland & charlotte gray \\
3 & 7 & don cherry & hockey coach and commentator & kingston, ontario & bret hart \\
4 & 6 & lester b. pearson & fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate & toronto, ontario & paul gross \\
5 & 5 & david suzuki & environmentalist & vancouver, british columbia & melissa auf der maur \\
6 & 4 & sir frederick banting & medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine & alliston, ontario & mary walsh \\
7 & 3 & pierre trudeau & fifteenth prime minister of canada & montreal, quebec & rex murphy \\
8 & 2 & terry fox & athlete, activist, humanitarian & winnipeg, manitoba & sook-yin lee \\
9 & 1 & tommy douglas & father of medicare, premier of saskatchewan & falkirk, scotland & george stroumboulopoulos \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& rank \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select rank where advocate = 'sook-yin lee' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>notability</th>
<th>birthplace</th>
<th>advocate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>10</td>
<td>wayne gretzky</td>
<td>hockey player, holder of numerous nhl records</td>
<td>brantford, ontario</td>
<td>deborah grey</td>
</tr>
<tr>
<th>1</th>
<td>9</td>
<td>alexander graham bell</td>
<td>scientist, inventor, founder of the bell telephone company</td>
<td>edinburgh, scotland</td>
<td>evan solomon</td>
</tr>
<tr>
<th>2</th>
<td>8</td>
<td>sir john a. macdonald</td>
<td>first prime minister of canada</td>
<td>glasgow, scotland</td>
<td>charlotte gray</td>
</tr>
<tr>
<th>3</th>
<td>7</td>
<td>don cherry</td>
<td>hockey coach and commentator</td>
<td>kingston, ontario</td>
<td>bret hart</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>lester b. pearson</td>
<td>fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate</td>
<td>toronto, ontario</td>
<td>paul gross</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>david suzuki</td>
<td>environmentalist</td>
<td>vancouver, british columbia</td>
<td>melissa auf der maur</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>sir frederick banting</td>
<td>medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine</td>
<td>alliston, ontario</td>
<td>mary walsh</td>
</tr>
<tr>
<th>7</th>
<td>3</td>
<td>pierre trudeau</td>
<td>fifteenth prime minister of canada</td>
<td>montreal, quebec</td>
<td>rex murphy</td>
</tr>
<tr>
<th>8</th>
<td>2</td>
<td>terry fox</td>
<td>athlete, activist, humanitarian</td>
<td>winnipeg, manitoba</td>
<td>sook-yin lee</td>
</tr>
<tr>
<th>9</th>
<td>1</td>
<td>tommy douglas</td>
<td>father of medicare, premier of saskatchewan</td>
<td>falkirk, scotland</td>
<td>george stroumboulopoulos</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select rank where advocate = 'sook-yin lee' <table_name> : table | | rank | name | notability | birthplace | advocate |
|---:|-------:|:----------------------|:-----------------------------------------------------------------------------------------------------------|:----------------------------|:-------------------------|
| 0 | 10 | wayne gretzky | hockey player, holder of numerous nhl records | brantford, ontario | deborah grey |
| 1 | 9 | alexander graham bell | scientist, inventor, founder of the bell telephone company | edinburgh, scotland | evan solomon |
| 2 | 8 | sir john a. macdonald | first prime minister of canada | glasgow, scotland | charlotte gray |
| 3 | 7 | don cherry | hockey coach and commentator | kingston, ontario | bret hart |
| 4 | 6 | lester b. pearson | fourteenth prime minister of canada, united nations general assembly president, nobel peace prize laureate | toronto, ontario | paul gross |
| 5 | 5 | david suzuki | environmentalist | vancouver, british columbia | melissa auf der maur |
| 6 | 4 | sir frederick banting | medical scientist, co-discoverer of insulin, winner of the nobel prize in physiology or medicine | alliston, ontario | mary walsh |
| 7 | 3 | pierre trudeau | fifteenth prime minister of canada | montreal, quebec | rex murphy |
| 8 | 2 | terry fox | athlete, activist, humanitarian | winnipeg, manitoba | sook-yin lee |
| 9 | 1 | tommy douglas | father of medicare, premier of saskatchewan | falkirk, scotland | george stroumboulopoulos | | | | rank |
|---:|-------:|
| 0 | 2 | | [
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select county where tally = '3-0' col : rank | player | county | tally | total | opposition row 1 : 1 | eamonn flynn | dublin | 3-5 | 14 | wexford row 2 : 1 | charlie mccarthy | cork | 2-8 | 14 | galway row 3 : 3 | paddy fahy | galway | 2-7 | 13 | kildare row 4 : 3 | t. morrissey | wicklow | 2-7 | 13 | laois row 5 : 5 | charlie mccarthy | cork | 3-3 | 12 | offaly row 6 : 5 | michael moroney | clare | 2-6 | 12 | dublin row 7 : 5 | declan lovett | kerry | 1-9 | 12 | galway row 8 : 5 | charlie mccarthy | cork | 1-9 | 12 | tipperary row 9 : 9 | ger cuddy | laois | 3-2 | 11 | wicklow row 10 : 9 | pat enright | waterford | 2-5 | 11 | kerry row 11 : 9 | pat enright | waterford | 1-8 | 11 | laois row 12 : 9 | johnny walsh | kildare | 0-11 | 11 | waterford row 13 : 9 | eddie keher | kilkenny | 0-11 | 11 | wexford row 14 : 14 | brendan cummins | cork | 3-1 | 10 | wexford row 15 : 14 | p. j. molloy | galway | 3-1 | 10 | kerry row 16 : 14 | nick behan | kildare | 3-1 | 10 | kerry row 17 : 14 | seanie o'leary | cork | 3-1 | 10 | limerick row 18 : 14 | michael keating | tipperary | 2-4 | 10 | wexford row 19 : 14 | seamus richmond | antrim | 2-4 | 10 | westmeath row 20 : 14 | declan lovett | kerry | 2-4 | 10 | waterford row 21 : 14 | michael keating | tipperary | 2-4 | 10 | dublin row 22 : 14 | eddie keher | kilkenny | 2-4 | 10 | dublin row 23 : 14 | mick dwan | kildare | 2-4 | 10 | antrim row 24 : 14 | charlie mccarthy | cork | 1-7 | 10 | kilkenny row 25 : 14 | paddy fahy | galway | 0-10 | 10 | kerry row 26 : 14 | johnny walsh | kildare | 0-10 | 10 | westmeath row 27 : 27 | p flynn | wexford | 3-0 | 9 | offaly row 28 : 27 | n casey | clare | 3-0 | 9 | cork row 29 : 27 | willie moore | limerick | 3-0 | 9 | cork row 30 : 27 | ger cuddy | laois | 3-0 | 9 | westmeath row 31 : 27 | tom ryan | galway | 3-0 | 9 | laois row 32 : 27 | seanie o'leary | cork | 3-0 | 9 | offaly row 33 : 27 | p flynn | wexford | 2-3 | 9 | cork row 34 : 27 | eddie keher | kilkenny | 2-3 | 9 | limerick row 35 : 27 | johnny walsh | kildare | 1-6 | 9 | galway row 36 : 27 | francis loughnane | tipperary | 1-6 | 9 | cork row 37 : 27 | richie bennis | limerick | 1-6 | 9 | cork row 38 : 27 | pat enright | waterford | 0-9 | 9 | kildare row 39 : 27 | johnny walsh | kildare | 0-9 | 9 | kerry | col : count ( "county" ) row 1 : 6 | select county where tally = '3-0' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & player & county & tally & total & opposition \\
\midrule
0 & 1 & eamonn flynn & dublin & 3-5 & 14 & wexford \\
1 & 1 & charlie mccarthy & cork & 2-8 & 14 & galway \\
2 & 3 & paddy fahy & galway & 2-7 & 13 & kildare \\
3 & 3 & t. morrissey & wicklow & 2-7 & 13 & laois \\
4 & 5 & charlie mccarthy & cork & 3-3 & 12 & offaly \\
5 & 5 & michael moroney & clare & 2-6 & 12 & dublin \\
6 & 5 & declan lovett & kerry & 1-9 & 12 & galway \\
7 & 5 & charlie mccarthy & cork & 1-9 & 12 & tipperary \\
8 & 9 & ger cuddy & laois & 3-2 & 11 & wicklow \\
9 & 9 & pat enright & waterford & 2-5 & 11 & kerry \\
10 & 9 & pat enright & waterford & 1-8 & 11 & laois \\
11 & 9 & johnny walsh & kildare & 0-11 & 11 & waterford \\
12 & 9 & eddie keher & kilkenny & 0-11 & 11 & wexford \\
13 & 14 & brendan cummins & cork & 3-1 & 10 & wexford \\
14 & 14 & p. j. molloy & galway & 3-1 & 10 & kerry \\
15 & 14 & nick behan & kildare & 3-1 & 10 & kerry \\
16 & 14 & seanie o'leary & cork & 3-1 & 10 & limerick \\
17 & 14 & michael keating & tipperary & 2-4 & 10 & wexford \\
18 & 14 & seamus richmond & antrim & 2-4 & 10 & westmeath \\
19 & 14 & declan lovett & kerry & 2-4 & 10 & waterford \\
20 & 14 & michael keating & tipperary & 2-4 & 10 & dublin \\
21 & 14 & eddie keher & kilkenny & 2-4 & 10 & dublin \\
22 & 14 & mick dwan & kildare & 2-4 & 10 & antrim \\
23 & 14 & charlie mccarthy & cork & 1-7 & 10 & kilkenny \\
24 & 14 & paddy fahy & galway & 0-10 & 10 & kerry \\
25 & 14 & johnny walsh & kildare & 0-10 & 10 & westmeath \\
26 & 27 & p flynn & wexford & 3-0 & 9 & offaly \\
27 & 27 & n casey & clare & 3-0 & 9 & cork \\
28 & 27 & willie moore & limerick & 3-0 & 9 & cork \\
29 & 27 & ger cuddy & laois & 3-0 & 9 & westmeath \\
30 & 27 & tom ryan & galway & 3-0 & 9 & laois \\
31 & 27 & seanie o'leary & cork & 3-0 & 9 & offaly \\
32 & 27 & p flynn & wexford & 2-3 & 9 & cork \\
33 & 27 & eddie keher & kilkenny & 2-3 & 9 & limerick \\
34 & 27 & johnny walsh & kildare & 1-6 & 9 & galway \\
35 & 27 & francis loughnane & tipperary & 1-6 & 9 & cork \\
36 & 27 & richie bennis & limerick & 1-6 & 9 & cork \\
37 & 27 & pat enright & waterford & 0-9 & 9 & kildare \\
38 & 27 & johnny walsh & kildare & 0-9 & 9 & kerry \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "county" ) \\
\midrule
0 & 6 \\
\bottomrule
\end{tabular}
| select county where tally = '3-0' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>player</th>
<th>county</th>
<th>tally</th>
<th>total</th>
<th>opposition</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>eamonn flynn</td>
<td>dublin</td>
<td>3-5</td>
<td>14</td>
<td>wexford</td>
</tr>
<tr>
<th>1</th>
<td>1</td>
<td>charlie mccarthy</td>
<td>cork</td>
<td>2-8</td>
<td>14</td>
<td>galway</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>paddy fahy</td>
<td>galway</td>
<td>2-7</td>
<td>13</td>
<td>kildare</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>t. morrissey</td>
<td>wicklow</td>
<td>2-7</td>
<td>13</td>
<td>laois</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>charlie mccarthy</td>
<td>cork</td>
<td>3-3</td>
<td>12</td>
<td>offaly</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>michael moroney</td>
<td>clare</td>
<td>2-6</td>
<td>12</td>
<td>dublin</td>
</tr>
<tr>
<th>6</th>
<td>5</td>
<td>declan lovett</td>
<td>kerry</td>
<td>1-9</td>
<td>12</td>
<td>galway</td>
</tr>
<tr>
<th>7</th>
<td>5</td>
<td>charlie mccarthy</td>
<td>cork</td>
<td>1-9</td>
<td>12</td>
<td>tipperary</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>ger cuddy</td>
<td>laois</td>
<td>3-2</td>
<td>11</td>
<td>wicklow</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>pat enright</td>
<td>waterford</td>
<td>2-5</td>
<td>11</td>
<td>kerry</td>
</tr>
<tr>
<th>10</th>
<td>9</td>
<td>pat enright</td>
<td>waterford</td>
<td>1-8</td>
<td>11</td>
<td>laois</td>
</tr>
<tr>
<th>11</th>
<td>9</td>
<td>johnny walsh</td>
<td>kildare</td>
<td>0-11</td>
<td>11</td>
<td>waterford</td>
</tr>
<tr>
<th>12</th>
<td>9</td>
<td>eddie keher</td>
<td>kilkenny</td>
<td>0-11</td>
<td>11</td>
<td>wexford</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>brendan cummins</td>
<td>cork</td>
<td>3-1</td>
<td>10</td>
<td>wexford</td>
</tr>
<tr>
<th>14</th>
<td>14</td>
<td>p. j. molloy</td>
<td>galway</td>
<td>3-1</td>
<td>10</td>
<td>kerry</td>
</tr>
<tr>
<th>15</th>
<td>14</td>
<td>nick behan</td>
<td>kildare</td>
<td>3-1</td>
<td>10</td>
<td>kerry</td>
</tr>
<tr>
<th>16</th>
<td>14</td>
<td>seanie o'leary</td>
<td>cork</td>
<td>3-1</td>
<td>10</td>
<td>limerick</td>
</tr>
<tr>
<th>17</th>
<td>14</td>
<td>michael keating</td>
<td>tipperary</td>
<td>2-4</td>
<td>10</td>
<td>wexford</td>
</tr>
<tr>
<th>18</th>
<td>14</td>
<td>seamus richmond</td>
<td>antrim</td>
<td>2-4</td>
<td>10</td>
<td>westmeath</td>
</tr>
<tr>
<th>19</th>
<td>14</td>
<td>declan lovett</td>
<td>kerry</td>
<td>2-4</td>
<td>10</td>
<td>waterford</td>
</tr>
<tr>
<th>20</th>
<td>14</td>
<td>michael keating</td>
<td>tipperary</td>
<td>2-4</td>
<td>10</td>
<td>dublin</td>
</tr>
<tr>
<th>21</th>
<td>14</td>
<td>eddie keher</td>
<td>kilkenny</td>
<td>2-4</td>
<td>10</td>
<td>dublin</td>
</tr>
<tr>
<th>22</th>
<td>14</td>
<td>mick dwan</td>
<td>kildare</td>
<td>2-4</td>
<td>10</td>
<td>antrim</td>
</tr>
<tr>
<th>23</th>
<td>14</td>
<td>charlie mccarthy</td>
<td>cork</td>
<td>1-7</td>
<td>10</td>
<td>kilkenny</td>
</tr>
<tr>
<th>24</th>
<td>14</td>
<td>paddy fahy</td>
<td>galway</td>
<td>0-10</td>
<td>10</td>
<td>kerry</td>
</tr>
<tr>
<th>25</th>
<td>14</td>
<td>johnny walsh</td>
<td>kildare</td>
<td>0-10</td>
<td>10</td>
<td>westmeath</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>p flynn</td>
<td>wexford</td>
<td>3-0</td>
<td>9</td>
<td>offaly</td>
</tr>
<tr>
<th>27</th>
<td>27</td>
<td>n casey</td>
<td>clare</td>
<td>3-0</td>
<td>9</td>
<td>cork</td>
</tr>
<tr>
<th>28</th>
<td>27</td>
<td>willie moore</td>
<td>limerick</td>
<td>3-0</td>
<td>9</td>
<td>cork</td>
</tr>
<tr>
<th>29</th>
<td>27</td>
<td>ger cuddy</td>
<td>laois</td>
<td>3-0</td>
<td>9</td>
<td>westmeath</td>
</tr>
<tr>
<th>30</th>
<td>27</td>
<td>tom ryan</td>
<td>galway</td>
<td>3-0</td>
<td>9</td>
<td>laois</td>
</tr>
<tr>
<th>31</th>
<td>27</td>
<td>seanie o'leary</td>
<td>cork</td>
<td>3-0</td>
<td>9</td>
<td>offaly</td>
</tr>
<tr>
<th>32</th>
<td>27</td>
<td>p flynn</td>
<td>wexford</td>
<td>2-3</td>
<td>9</td>
<td>cork</td>
</tr>
<tr>
<th>33</th>
<td>27</td>
<td>eddie keher</td>
<td>kilkenny</td>
<td>2-3</td>
<td>9</td>
<td>limerick</td>
</tr>
<tr>
<th>34</th>
<td>27</td>
<td>johnny walsh</td>
<td>kildare</td>
<td>1-6</td>
<td>9</td>
<td>galway</td>
</tr>
<tr>
<th>35</th>
<td>27</td>
<td>francis loughnane</td>
<td>tipperary</td>
<td>1-6</td>
<td>9</td>
<td>cork</td>
</tr>
<tr>
<th>36</th>
<td>27</td>
<td>richie bennis</td>
<td>limerick</td>
<td>1-6</td>
<td>9</td>
<td>cork</td>
</tr>
<tr>
<th>37</th>
<td>27</td>
<td>pat enright</td>
<td>waterford</td>
<td>0-9</td>
<td>9</td>
<td>kildare</td>
</tr>
<tr>
<th>38</th>
<td>27</td>
<td>johnny walsh</td>
<td>kildare</td>
<td>0-9</td>
<td>9</td>
<td>kerry</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "county" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>6</td>
</tr>
</tbody>
</table> | select county where tally = '3-0' <table_name> : table | | rank | player | county | tally | total | opposition |
|---:|-------:|:------------------|:----------|:--------|--------:|:-------------|
| 0 | 1 | eamonn flynn | dublin | 3-5 | 14 | wexford |
| 1 | 1 | charlie mccarthy | cork | 2-8 | 14 | galway |
| 2 | 3 | paddy fahy | galway | 2-7 | 13 | kildare |
| 3 | 3 | t. morrissey | wicklow | 2-7 | 13 | laois |
| 4 | 5 | charlie mccarthy | cork | 3-3 | 12 | offaly |
| 5 | 5 | michael moroney | clare | 2-6 | 12 | dublin |
| 6 | 5 | declan lovett | kerry | 1-9 | 12 | galway |
| 7 | 5 | charlie mccarthy | cork | 1-9 | 12 | tipperary |
| 8 | 9 | ger cuddy | laois | 3-2 | 11 | wicklow |
| 9 | 9 | pat enright | waterford | 2-5 | 11 | kerry |
| 10 | 9 | pat enright | waterford | 1-8 | 11 | laois |
| 11 | 9 | johnny walsh | kildare | 0-11 | 11 | waterford |
| 12 | 9 | eddie keher | kilkenny | 0-11 | 11 | wexford |
| 13 | 14 | brendan cummins | cork | 3-1 | 10 | wexford |
| 14 | 14 | p. j. molloy | galway | 3-1 | 10 | kerry |
| 15 | 14 | nick behan | kildare | 3-1 | 10 | kerry |
| 16 | 14 | seanie o'leary | cork | 3-1 | 10 | limerick |
| 17 | 14 | michael keating | tipperary | 2-4 | 10 | wexford |
| 18 | 14 | seamus richmond | antrim | 2-4 | 10 | westmeath |
| 19 | 14 | declan lovett | kerry | 2-4 | 10 | waterford |
| 20 | 14 | michael keating | tipperary | 2-4 | 10 | dublin |
| 21 | 14 | eddie keher | kilkenny | 2-4 | 10 | dublin |
| 22 | 14 | mick dwan | kildare | 2-4 | 10 | antrim |
| 23 | 14 | charlie mccarthy | cork | 1-7 | 10 | kilkenny |
| 24 | 14 | paddy fahy | galway | 0-10 | 10 | kerry |
| 25 | 14 | johnny walsh | kildare | 0-10 | 10 | westmeath |
| 26 | 27 | p flynn | wexford | 3-0 | 9 | offaly |
| 27 | 27 | n casey | clare | 3-0 | 9 | cork |
| 28 | 27 | willie moore | limerick | 3-0 | 9 | cork |
| 29 | 27 | ger cuddy | laois | 3-0 | 9 | westmeath |
| 30 | 27 | tom ryan | galway | 3-0 | 9 | laois |
| 31 | 27 | seanie o'leary | cork | 3-0 | 9 | offaly |
| 32 | 27 | p flynn | wexford | 2-3 | 9 | cork |
| 33 | 27 | eddie keher | kilkenny | 2-3 | 9 | limerick |
| 34 | 27 | johnny walsh | kildare | 1-6 | 9 | galway |
| 35 | 27 | francis loughnane | tipperary | 1-6 | 9 | cork |
| 36 | 27 | richie bennis | limerick | 1-6 | 9 | cork |
| 37 | 27 | pat enright | waterford | 0-9 | 9 | kildare |
| 38 | 27 | johnny walsh | kildare | 0-9 | 9 | kerry | | | | count ( "county" ) |
|---:|---------------------:|
| 0 | 6 | | [
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select count ( * ) where french language group electoral district (as of 2012) = 'liege' col : dutch language group electoral district (as of 2012) | dutch language group seats | french language group electoral district (as of 2012) | french language group seats row 1 : antwerp | 24 | brussels capital region | 13/14 row 2 : brussels capital region | 1/2 | hainaut | 18 row 3 : east flanders | 20 | liege | 15 row 4 : flemish brabant | 15 | luxembourg | 4 row 5 : limburg | 12 | namur | 6 row 6 : west flanders | 16 | walloon brabant | 5 row 7 : total | 88 | total | 62 | col : count ( "*" ) row 1 : 1 | select count ( * ) where french language group electoral district (as of 2012) = 'liege' <table_name> : table \begin{tabular}{lllll}
\toprule
& dutch language group electoral district (as of 2012) & dutch language group seats & french language group electoral district (as of 2012) & french language group seats \\
\midrule
0 & antwerp & 24 & brussels capital region & 13/14 \\
1 & brussels capital region & 1/2 & hainaut & 18 \\
2 & east flanders & 20 & liege & 15 \\
3 & flemish brabant & 15 & luxembourg & 4 \\
4 & limburg & 12 & namur & 6 \\
5 & west flanders & 16 & walloon brabant & 5 \\
6 & total & 88 & total & 62 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where french language group electoral district (as of 2012) = 'liege' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>dutch language group electoral district (as of 2012)</th>
<th>dutch language group seats</th>
<th>french language group electoral district (as of 2012)</th>
<th>french language group seats</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>antwerp</td>
<td>24</td>
<td>brussels capital region</td>
<td>13/14</td>
</tr>
<tr>
<th>1</th>
<td>brussels capital region</td>
<td>1/2</td>
<td>hainaut</td>
<td>18</td>
</tr>
<tr>
<th>2</th>
<td>east flanders</td>
<td>20</td>
<td>liege</td>
<td>15</td>
</tr>
<tr>
<th>3</th>
<td>flemish brabant</td>
<td>15</td>
<td>luxembourg</td>
<td>4</td>
</tr>
<tr>
<th>4</th>
<td>limburg</td>
<td>12</td>
<td>namur</td>
<td>6</td>
</tr>
<tr>
<th>5</th>
<td>west flanders</td>
<td>16</td>
<td>walloon brabant</td>
<td>5</td>
</tr>
<tr>
<th>6</th>
<td>total</td>
<td>88</td>
<td>total</td>
<td>62</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where french language group electoral district (as of 2012) = 'liege' <table_name> : table | | dutch language group electoral district (as of 2012) | dutch language group seats | french language group electoral district (as of 2012) | french language group seats |
|---:|:-------------------------------------------------------|:-----------------------------|:--------------------------------------------------------|:------------------------------|
| 0 | antwerp | 24 | brussels capital region | 13/14 |
| 1 | brussels capital region | 1/2 | hainaut | 18 |
| 2 | east flanders | 20 | liege | 15 |
| 3 | flemish brabant | 15 | luxembourg | 4 |
| 4 | limburg | 12 | namur | 6 |
| 5 | west flanders | 16 | walloon brabant | 5 |
| 6 | total | 88 | total | 62 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where 2nd leg = '1-2' col : team 1 | agg. | team 2 | 1st leg | 2nd leg row 1 : valladolid promesas | 1-3 | elche | 0-2 | 1-1 row 2 : pena sport | 0-4 | valladolid | 0-2 | 0-2 row 3 : algeciras | 2-10 | real madrid | 0-6 | 2-4 row 4 : real madrid castilla | 5-5 (3-4 p) | sabadell | 4-3 | 1-2 row 5 : leganes | 1-5 | eldense | 1-2 | 0-3 row 6 : ciempozuelos | 3-2 | lleida | 2-1 | 1-1 row 7 : alcala | 1-10 | valencia | 1-3 | 0-7 row 8 : burgos | 4-1 | huesca | 2-0 | 2-1 row 9 : ceuta | 1-6 | espanyol | 1-1 | 0-5 row 10 : atletico baleares | 2-3 | cadiz | 1-0 | 1-3 row 11 : tudelano | 3-6 | sporting gijon | 2-1 | 1-5 row 12 : figueres | 3-4 | racing santander | 1-2 | 2-2 row 13 : carabanchel | 5-2 | calvo sotelo | 4-1 | 1-1 row 14 : almansa | 1-4 | rayo vallecano | 0-2 | 1-2 row 15 : osasuna | 4-1 | guadalajara | 2-0 | 2-1 row 16 : deportivo | 5-1 | plasencia | 3-0 | 2-1 row 17 : europa | 3-8 | malaga | 3-3 | 0-5 row 18 : jaen | 1-4 | real union | 1-1 | 0-3 row 19 : ontinyent | 1-0 | torrejon | 1-0 | 0-0 row 20 : girona | 5-1 | alcoyano | 3-0 | 2-1 row 21 : valencia mestalla | 4-2 | sevilla atletico | 3-0 | 1-2 row 22 : espanol raspeig | 0-1 | mirandes | 0-0 | 0-1 row 23 : toledo | 3-3 (4-3 p) | badajoz | 2-0 | 1-3 row 24 : talavera | 2-0 | arosa | 2-0 | 0-0 row 25 : sarinena | 1-5 | rayo cantabria | 0-2 | 1-3 row 26 : san fernando | 5-1 | nastic tarragona | 4-1 | 1-0 row 27 : sevilla | 4-1 | sant andreu | 2-0 | 2-1 row 28 : orihuela | 0-3 | alaves | 0-1 | 0-2 row 29 : oviedo | 4-1 | cultural leonesa | 2-0 | 2-1 row 30 : langreo | 1-3 | granada | 1-0 | 0-3 row 31 : racing ferrol | 3-5 | real murcia | 2-0 | 1-5 row 32 : levante | 9-2 | moscardo | 5-0 | 4-2 row 33 : real sociedad | 3-3 (8-7 p) | xerez | 1-1 | 2-2 row 34 : marbella | 4-3 | gimnastica torrelavega | 4-1 | 0-2 row 35 : cordoba | 3-1 | bilbao athletic | 1-0 | 2-1 row 36 : recreativo | 4-2 | linense | 2-0 | 2-2 row 37 : reus | 0-5 | zaragoza | 0-0 | 0-5 row 38 : celta | 2-1 | cartagena | 2-0 | 0-1 row 39 : tenerife | 2-1 | malgrat | 2-0 | 0-1 row 40 : la cava | 2-5 | linares | 1-3 | 1-2 row 41 : gava | 2-3 | castellon | 1-1 | 1-2 row 42 : fabril | 0-7 | hercules | 0-3 | 0-4 | col : count ( "*" ) row 1 : 5 | select count ( * ) where 2nd leg = '1-2' <table_name> : table \begin{tabular}{llllll}
\toprule
& team 1 & agg. & team 2 & 1st leg & 2nd leg \\
\midrule
0 & valladolid promesas & 1-3 & elche & 0-2 & 1-1 \\
1 & pena sport & 0-4 & valladolid & 0-2 & 0-2 \\
2 & algeciras & 2-10 & real madrid & 0-6 & 2-4 \\
3 & real madrid castilla & 5-5 (3-4 p) & sabadell & 4-3 & 1-2 \\
4 & leganes & 1-5 & eldense & 1-2 & 0-3 \\
5 & ciempozuelos & 3-2 & lleida & 2-1 & 1-1 \\
6 & alcala & 1-10 & valencia & 1-3 & 0-7 \\
7 & burgos & 4-1 & huesca & 2-0 & 2-1 \\
8 & ceuta & 1-6 & espanyol & 1-1 & 0-5 \\
9 & atletico baleares & 2-3 & cadiz & 1-0 & 1-3 \\
10 & tudelano & 3-6 & sporting gijon & 2-1 & 1-5 \\
11 & figueres & 3-4 & racing santander & 1-2 & 2-2 \\
12 & carabanchel & 5-2 & calvo sotelo & 4-1 & 1-1 \\
13 & almansa & 1-4 & rayo vallecano & 0-2 & 1-2 \\
14 & osasuna & 4-1 & guadalajara & 2-0 & 2-1 \\
15 & deportivo & 5-1 & plasencia & 3-0 & 2-1 \\
16 & europa & 3-8 & malaga & 3-3 & 0-5 \\
17 & jaen & 1-4 & real union & 1-1 & 0-3 \\
18 & ontinyent & 1-0 & torrejon & 1-0 & 0-0 \\
19 & girona & 5-1 & alcoyano & 3-0 & 2-1 \\
20 & valencia mestalla & 4-2 & sevilla atletico & 3-0 & 1-2 \\
21 & espanol raspeig & 0-1 & mirandes & 0-0 & 0-1 \\
22 & toledo & 3-3 (4-3 p) & badajoz & 2-0 & 1-3 \\
23 & talavera & 2-0 & arosa & 2-0 & 0-0 \\
24 & sarinena & 1-5 & rayo cantabria & 0-2 & 1-3 \\
25 & san fernando & 5-1 & nastic tarragona & 4-1 & 1-0 \\
26 & sevilla & 4-1 & sant andreu & 2-0 & 2-1 \\
27 & orihuela & 0-3 & alaves & 0-1 & 0-2 \\
28 & oviedo & 4-1 & cultural leonesa & 2-0 & 2-1 \\
29 & langreo & 1-3 & granada & 1-0 & 0-3 \\
30 & racing ferrol & 3-5 & real murcia & 2-0 & 1-5 \\
31 & levante & 9-2 & moscardo & 5-0 & 4-2 \\
32 & real sociedad & 3-3 (8-7 p) & xerez & 1-1 & 2-2 \\
33 & marbella & 4-3 & gimnastica torrelavega & 4-1 & 0-2 \\
34 & cordoba & 3-1 & bilbao athletic & 1-0 & 2-1 \\
35 & recreativo & 4-2 & linense & 2-0 & 2-2 \\
36 & reus & 0-5 & zaragoza & 0-0 & 0-5 \\
37 & celta & 2-1 & cartagena & 2-0 & 0-1 \\
38 & tenerife & 2-1 & malgrat & 2-0 & 0-1 \\
39 & la cava & 2-5 & linares & 1-3 & 1-2 \\
40 & gava & 2-3 & castellon & 1-1 & 1-2 \\
41 & fabril & 0-7 & hercules & 0-3 & 0-4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( * ) where 2nd leg = '1-2' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>team 1</th>
<th>agg.</th>
<th>team 2</th>
<th>1st leg</th>
<th>2nd leg</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>valladolid promesas</td>
<td>1-3</td>
<td>elche</td>
<td>0-2</td>
<td>1-1</td>
</tr>
<tr>
<th>1</th>
<td>pena sport</td>
<td>0-4</td>
<td>valladolid</td>
<td>0-2</td>
<td>0-2</td>
</tr>
<tr>
<th>2</th>
<td>algeciras</td>
<td>2-10</td>
<td>real madrid</td>
<td>0-6</td>
<td>2-4</td>
</tr>
<tr>
<th>3</th>
<td>real madrid castilla</td>
<td>5-5 (3-4 p)</td>
<td>sabadell</td>
<td>4-3</td>
<td>1-2</td>
</tr>
<tr>
<th>4</th>
<td>leganes</td>
<td>1-5</td>
<td>eldense</td>
<td>1-2</td>
<td>0-3</td>
</tr>
<tr>
<th>5</th>
<td>ciempozuelos</td>
<td>3-2</td>
<td>lleida</td>
<td>2-1</td>
<td>1-1</td>
</tr>
<tr>
<th>6</th>
<td>alcala</td>
<td>1-10</td>
<td>valencia</td>
<td>1-3</td>
<td>0-7</td>
</tr>
<tr>
<th>7</th>
<td>burgos</td>
<td>4-1</td>
<td>huesca</td>
<td>2-0</td>
<td>2-1</td>
</tr>
<tr>
<th>8</th>
<td>ceuta</td>
<td>1-6</td>
<td>espanyol</td>
<td>1-1</td>
<td>0-5</td>
</tr>
<tr>
<th>9</th>
<td>atletico baleares</td>
<td>2-3</td>
<td>cadiz</td>
<td>1-0</td>
<td>1-3</td>
</tr>
<tr>
<th>10</th>
<td>tudelano</td>
<td>3-6</td>
<td>sporting gijon</td>
<td>2-1</td>
<td>1-5</td>
</tr>
<tr>
<th>11</th>
<td>figueres</td>
<td>3-4</td>
<td>racing santander</td>
<td>1-2</td>
<td>2-2</td>
</tr>
<tr>
<th>12</th>
<td>carabanchel</td>
<td>5-2</td>
<td>calvo sotelo</td>
<td>4-1</td>
<td>1-1</td>
</tr>
<tr>
<th>13</th>
<td>almansa</td>
<td>1-4</td>
<td>rayo vallecano</td>
<td>0-2</td>
<td>1-2</td>
</tr>
<tr>
<th>14</th>
<td>osasuna</td>
<td>4-1</td>
<td>guadalajara</td>
<td>2-0</td>
<td>2-1</td>
</tr>
<tr>
<th>15</th>
<td>deportivo</td>
<td>5-1</td>
<td>plasencia</td>
<td>3-0</td>
<td>2-1</td>
</tr>
<tr>
<th>16</th>
<td>europa</td>
<td>3-8</td>
<td>malaga</td>
<td>3-3</td>
<td>0-5</td>
</tr>
<tr>
<th>17</th>
<td>jaen</td>
<td>1-4</td>
<td>real union</td>
<td>1-1</td>
<td>0-3</td>
</tr>
<tr>
<th>18</th>
<td>ontinyent</td>
<td>1-0</td>
<td>torrejon</td>
<td>1-0</td>
<td>0-0</td>
</tr>
<tr>
<th>19</th>
<td>girona</td>
<td>5-1</td>
<td>alcoyano</td>
<td>3-0</td>
<td>2-1</td>
</tr>
<tr>
<th>20</th>
<td>valencia mestalla</td>
<td>4-2</td>
<td>sevilla atletico</td>
<td>3-0</td>
<td>1-2</td>
</tr>
<tr>
<th>21</th>
<td>espanol raspeig</td>
<td>0-1</td>
<td>mirandes</td>
<td>0-0</td>
<td>0-1</td>
</tr>
<tr>
<th>22</th>
<td>toledo</td>
<td>3-3 (4-3 p)</td>
<td>badajoz</td>
<td>2-0</td>
<td>1-3</td>
</tr>
<tr>
<th>23</th>
<td>talavera</td>
<td>2-0</td>
<td>arosa</td>
<td>2-0</td>
<td>0-0</td>
</tr>
<tr>
<th>24</th>
<td>sarinena</td>
<td>1-5</td>
<td>rayo cantabria</td>
<td>0-2</td>
<td>1-3</td>
</tr>
<tr>
<th>25</th>
<td>san fernando</td>
<td>5-1</td>
<td>nastic tarragona</td>
<td>4-1</td>
<td>1-0</td>
</tr>
<tr>
<th>26</th>
<td>sevilla</td>
<td>4-1</td>
<td>sant andreu</td>
<td>2-0</td>
<td>2-1</td>
</tr>
<tr>
<th>27</th>
<td>orihuela</td>
<td>0-3</td>
<td>alaves</td>
<td>0-1</td>
<td>0-2</td>
</tr>
<tr>
<th>28</th>
<td>oviedo</td>
<td>4-1</td>
<td>cultural leonesa</td>
<td>2-0</td>
<td>2-1</td>
</tr>
<tr>
<th>29</th>
<td>langreo</td>
<td>1-3</td>
<td>granada</td>
<td>1-0</td>
<td>0-3</td>
</tr>
<tr>
<th>30</th>
<td>racing ferrol</td>
<td>3-5</td>
<td>real murcia</td>
<td>2-0</td>
<td>1-5</td>
</tr>
<tr>
<th>31</th>
<td>levante</td>
<td>9-2</td>
<td>moscardo</td>
<td>5-0</td>
<td>4-2</td>
</tr>
<tr>
<th>32</th>
<td>real sociedad</td>
<td>3-3 (8-7 p)</td>
<td>xerez</td>
<td>1-1</td>
<td>2-2</td>
</tr>
<tr>
<th>33</th>
<td>marbella</td>
<td>4-3</td>
<td>gimnastica torrelavega</td>
<td>4-1</td>
<td>0-2</td>
</tr>
<tr>
<th>34</th>
<td>cordoba</td>
<td>3-1</td>
<td>bilbao athletic</td>
<td>1-0</td>
<td>2-1</td>
</tr>
<tr>
<th>35</th>
<td>recreativo</td>
<td>4-2</td>
<td>linense</td>
<td>2-0</td>
<td>2-2</td>
</tr>
<tr>
<th>36</th>
<td>reus</td>
<td>0-5</td>
<td>zaragoza</td>
<td>0-0</td>
<td>0-5</td>
</tr>
<tr>
<th>37</th>
<td>celta</td>
<td>2-1</td>
<td>cartagena</td>
<td>2-0</td>
<td>0-1</td>
</tr>
<tr>
<th>38</th>
<td>tenerife</td>
<td>2-1</td>
<td>malgrat</td>
<td>2-0</td>
<td>0-1</td>
</tr>
<tr>
<th>39</th>
<td>la cava</td>
<td>2-5</td>
<td>linares</td>
<td>1-3</td>
<td>1-2</td>
</tr>
<tr>
<th>40</th>
<td>gava</td>
<td>2-3</td>
<td>castellon</td>
<td>1-1</td>
<td>1-2</td>
</tr>
<tr>
<th>41</th>
<td>fabril</td>
<td>0-7</td>
<td>hercules</td>
<td>0-3</td>
<td>0-4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( * ) where 2nd leg = '1-2' <table_name> : table | | team 1 | agg. | team 2 | 1st leg | 2nd leg |
|---:|:---------------------|:------------|:-----------------------|:----------|:----------|
| 0 | valladolid promesas | 1-3 | elche | 0-2 | 1-1 |
| 1 | pena sport | 0-4 | valladolid | 0-2 | 0-2 |
| 2 | algeciras | 2-10 | real madrid | 0-6 | 2-4 |
| 3 | real madrid castilla | 5-5 (3-4 p) | sabadell | 4-3 | 1-2 |
| 4 | leganes | 1-5 | eldense | 1-2 | 0-3 |
| 5 | ciempozuelos | 3-2 | lleida | 2-1 | 1-1 |
| 6 | alcala | 1-10 | valencia | 1-3 | 0-7 |
| 7 | burgos | 4-1 | huesca | 2-0 | 2-1 |
| 8 | ceuta | 1-6 | espanyol | 1-1 | 0-5 |
| 9 | atletico baleares | 2-3 | cadiz | 1-0 | 1-3 |
| 10 | tudelano | 3-6 | sporting gijon | 2-1 | 1-5 |
| 11 | figueres | 3-4 | racing santander | 1-2 | 2-2 |
| 12 | carabanchel | 5-2 | calvo sotelo | 4-1 | 1-1 |
| 13 | almansa | 1-4 | rayo vallecano | 0-2 | 1-2 |
| 14 | osasuna | 4-1 | guadalajara | 2-0 | 2-1 |
| 15 | deportivo | 5-1 | plasencia | 3-0 | 2-1 |
| 16 | europa | 3-8 | malaga | 3-3 | 0-5 |
| 17 | jaen | 1-4 | real union | 1-1 | 0-3 |
| 18 | ontinyent | 1-0 | torrejon | 1-0 | 0-0 |
| 19 | girona | 5-1 | alcoyano | 3-0 | 2-1 |
| 20 | valencia mestalla | 4-2 | sevilla atletico | 3-0 | 1-2 |
| 21 | espanol raspeig | 0-1 | mirandes | 0-0 | 0-1 |
| 22 | toledo | 3-3 (4-3 p) | badajoz | 2-0 | 1-3 |
| 23 | talavera | 2-0 | arosa | 2-0 | 0-0 |
| 24 | sarinena | 1-5 | rayo cantabria | 0-2 | 1-3 |
| 25 | san fernando | 5-1 | nastic tarragona | 4-1 | 1-0 |
| 26 | sevilla | 4-1 | sant andreu | 2-0 | 2-1 |
| 27 | orihuela | 0-3 | alaves | 0-1 | 0-2 |
| 28 | oviedo | 4-1 | cultural leonesa | 2-0 | 2-1 |
| 29 | langreo | 1-3 | granada | 1-0 | 0-3 |
| 30 | racing ferrol | 3-5 | real murcia | 2-0 | 1-5 |
| 31 | levante | 9-2 | moscardo | 5-0 | 4-2 |
| 32 | real sociedad | 3-3 (8-7 p) | xerez | 1-1 | 2-2 |
| 33 | marbella | 4-3 | gimnastica torrelavega | 4-1 | 0-2 |
| 34 | cordoba | 3-1 | bilbao athletic | 1-0 | 2-1 |
| 35 | recreativo | 4-2 | linense | 2-0 | 2-2 |
| 36 | reus | 0-5 | zaragoza | 0-0 | 0-5 |
| 37 | celta | 2-1 | cartagena | 2-0 | 0-1 |
| 38 | tenerife | 2-1 | malgrat | 2-0 | 0-1 |
| 39 | la cava | 2-5 | linares | 1-3 | 1-2 |
| 40 | gava | 2-3 | castellon | 1-1 | 1-2 |
| 41 | fabril | 0-7 | hercules | 0-3 | 0-4 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 5 | | [
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select score where result = 'loss' col : week | date | opponent | score | result | attendance | record row 1 : 1 | thursday, aug 11 | vs. winnipeg blue bombers | 35-21 | loss | 31837 | 0-1 row 2 : 2 | monday, aug 15 | at edmonton eskimos | 33-14 | loss | 17500 | 0-2 row 3 : 3 | saturday, aug 20 | vs. saskatchewan roughriders | 27-12 | win | 29532 | 1-2 row 4 : 4 | monday, aug 22 | at calgary stampeders | 26-19 | win | none | 2-2 row 5 : 5 | monday, aug 29 | vs. edmonton eskimos | 26-0 | loss | 28420 | 2-3 row 6 : 6 | thursday, sept 1 | at winnipeg blue bombers | 19-14 | loss | 18297 | 2-4 row 7 : 7 | monday, sept 5 | at saskatchewan roughriders | 31-21 | win | 14105 | 3-4 row 8 : 8 | monday, sept 12 | vs. calgary stampeders | 21-21 | tie | 27759 | 3-4-1 row 9 : 9 | saturday, sept 17 | vs. winnipeg blue bombers | 26-14 | loss | 30292 | 3-5-1 row 10 : 10 | monday, sept 19 | at edmonton eskimos | 18-10 | loss | none | 3-6-1 row 11 : 11 | saturday, sept 24 | at calgary stampeders | 28-14 | loss | 13000 | 3-7-1 row 12 : 12 | thursday, oct 6 | vs. edmonton eskimos | 21-13 | win | 21707 | 4-7-1 row 13 : 13 | thursday, oct 13 | at winnipeg blue bombers | 49-21 | loss | 16773 | 4-8-1 row 14 : 14 | saturday, oct 15 | at saskatchewan roughriders | 14-14 | tie | 7255 | 4-8-2 row 15 : 15 | saturday, oct 22 | vs. calgary stampeders | 22-10 | loss | 29599 | 4-9-2 row 16 : 16 | saturday, oct 29 | vs. saskatchewan roughriders | 38-0 | win | 21114 | 5-9-2 | col : score row 1 : 35-21 row 2 : 33-14 row 3 : 26-0 row 4 : 19-14 row 5 : 26-14 row 6 : 18-10 row 7 : 28-14 row 8 : 49-21 row 9 : 22-10 | select score where result = 'loss' <table_name> : table \begin{tabular}{llllllll}
\toprule
& week & date & opponent & score & result & attendance & record \\
\midrule
0 & 1 & thursday, aug 11 & vs. winnipeg blue bombers & 35-21 & loss & 31837 & 0-1 \\
1 & 2 & monday, aug 15 & at edmonton eskimos & 33-14 & loss & 17500 & 0-2 \\
2 & 3 & saturday, aug 20 & vs. saskatchewan roughriders & 27-12 & win & 29532 & 1-2 \\
3 & 4 & monday, aug 22 & at calgary stampeders & 26-19 & win & none & 2-2 \\
4 & 5 & monday, aug 29 & vs. edmonton eskimos & 26-0 & loss & 28420 & 2-3 \\
5 & 6 & thursday, sept 1 & at winnipeg blue bombers & 19-14 & loss & 18297 & 2-4 \\
6 & 7 & monday, sept 5 & at saskatchewan roughriders & 31-21 & win & 14105 & 3-4 \\
7 & 8 & monday, sept 12 & vs. calgary stampeders & 21-21 & tie & 27759 & 3-4-1 \\
8 & 9 & saturday, sept 17 & vs. winnipeg blue bombers & 26-14 & loss & 30292 & 3-5-1 \\
9 & 10 & monday, sept 19 & at edmonton eskimos & 18-10 & loss & none & 3-6-1 \\
10 & 11 & saturday, sept 24 & at calgary stampeders & 28-14 & loss & 13000 & 3-7-1 \\
11 & 12 & thursday, oct 6 & vs. edmonton eskimos & 21-13 & win & 21707 & 4-7-1 \\
12 & 13 & thursday, oct 13 & at winnipeg blue bombers & 49-21 & loss & 16773 & 4-8-1 \\
13 & 14 & saturday, oct 15 & at saskatchewan roughriders & 14-14 & tie & 7255 & 4-8-2 \\
14 & 15 & saturday, oct 22 & vs. calgary stampeders & 22-10 & loss & 29599 & 4-9-2 \\
15 & 16 & saturday, oct 29 & vs. saskatchewan roughriders & 38-0 & win & 21114 & 5-9-2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& score \\
\midrule
0 & 35-21 \\
1 & 33-14 \\
2 & 26-0 \\
3 & 19-14 \\
4 & 26-14 \\
5 & 18-10 \\
6 & 28-14 \\
7 & 49-21 \\
8 & 22-10 \\
\bottomrule
\end{tabular}
| select score where result = 'loss' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>opponent</th>
<th>score</th>
<th>result</th>
<th>attendance</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>thursday, aug 11</td>
<td>vs. winnipeg blue bombers</td>
<td>35-21</td>
<td>loss</td>
<td>31837</td>
<td>0-1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>monday, aug 15</td>
<td>at edmonton eskimos</td>
<td>33-14</td>
<td>loss</td>
<td>17500</td>
<td>0-2</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>saturday, aug 20</td>
<td>vs. saskatchewan roughriders</td>
<td>27-12</td>
<td>win</td>
<td>29532</td>
<td>1-2</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>monday, aug 22</td>
<td>at calgary stampeders</td>
<td>26-19</td>
<td>win</td>
<td>none</td>
<td>2-2</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>monday, aug 29</td>
<td>vs. edmonton eskimos</td>
<td>26-0</td>
<td>loss</td>
<td>28420</td>
<td>2-3</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>thursday, sept 1</td>
<td>at winnipeg blue bombers</td>
<td>19-14</td>
<td>loss</td>
<td>18297</td>
<td>2-4</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>monday, sept 5</td>
<td>at saskatchewan roughriders</td>
<td>31-21</td>
<td>win</td>
<td>14105</td>
<td>3-4</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>monday, sept 12</td>
<td>vs. calgary stampeders</td>
<td>21-21</td>
<td>tie</td>
<td>27759</td>
<td>3-4-1</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>saturday, sept 17</td>
<td>vs. winnipeg blue bombers</td>
<td>26-14</td>
<td>loss</td>
<td>30292</td>
<td>3-5-1</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>monday, sept 19</td>
<td>at edmonton eskimos</td>
<td>18-10</td>
<td>loss</td>
<td>none</td>
<td>3-6-1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>saturday, sept 24</td>
<td>at calgary stampeders</td>
<td>28-14</td>
<td>loss</td>
<td>13000</td>
<td>3-7-1</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>thursday, oct 6</td>
<td>vs. edmonton eskimos</td>
<td>21-13</td>
<td>win</td>
<td>21707</td>
<td>4-7-1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>thursday, oct 13</td>
<td>at winnipeg blue bombers</td>
<td>49-21</td>
<td>loss</td>
<td>16773</td>
<td>4-8-1</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>saturday, oct 15</td>
<td>at saskatchewan roughriders</td>
<td>14-14</td>
<td>tie</td>
<td>7255</td>
<td>4-8-2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>saturday, oct 22</td>
<td>vs. calgary stampeders</td>
<td>22-10</td>
<td>loss</td>
<td>29599</td>
<td>4-9-2</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>saturday, oct 29</td>
<td>vs. saskatchewan roughriders</td>
<td>38-0</td>
<td>win</td>
<td>21114</td>
<td>5-9-2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>score</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>35-21</td>
</tr>
<tr>
<th>1</th>
<td>33-14</td>
</tr>
<tr>
<th>2</th>
<td>26-0</td>
</tr>
<tr>
<th>3</th>
<td>19-14</td>
</tr>
<tr>
<th>4</th>
<td>26-14</td>
</tr>
<tr>
<th>5</th>
<td>18-10</td>
</tr>
<tr>
<th>6</th>
<td>28-14</td>
</tr>
<tr>
<th>7</th>
<td>49-21</td>
</tr>
<tr>
<th>8</th>
<td>22-10</td>
</tr>
</tbody>
</table> | select score where result = 'loss' <table_name> : table | | week | date | opponent | score | result | attendance | record |
|---:|-------:|:------------------|:-----------------------------|:--------|:---------|:-------------|:---------|
| 0 | 1 | thursday, aug 11 | vs. winnipeg blue bombers | 35-21 | loss | 31837 | 0-1 |
| 1 | 2 | monday, aug 15 | at edmonton eskimos | 33-14 | loss | 17500 | 0-2 |
| 2 | 3 | saturday, aug 20 | vs. saskatchewan roughriders | 27-12 | win | 29532 | 1-2 |
| 3 | 4 | monday, aug 22 | at calgary stampeders | 26-19 | win | none | 2-2 |
| 4 | 5 | monday, aug 29 | vs. edmonton eskimos | 26-0 | loss | 28420 | 2-3 |
| 5 | 6 | thursday, sept 1 | at winnipeg blue bombers | 19-14 | loss | 18297 | 2-4 |
| 6 | 7 | monday, sept 5 | at saskatchewan roughriders | 31-21 | win | 14105 | 3-4 |
| 7 | 8 | monday, sept 12 | vs. calgary stampeders | 21-21 | tie | 27759 | 3-4-1 |
| 8 | 9 | saturday, sept 17 | vs. winnipeg blue bombers | 26-14 | loss | 30292 | 3-5-1 |
| 9 | 10 | monday, sept 19 | at edmonton eskimos | 18-10 | loss | none | 3-6-1 |
| 10 | 11 | saturday, sept 24 | at calgary stampeders | 28-14 | loss | 13000 | 3-7-1 |
| 11 | 12 | thursday, oct 6 | vs. edmonton eskimos | 21-13 | win | 21707 | 4-7-1 |
| 12 | 13 | thursday, oct 13 | at winnipeg blue bombers | 49-21 | loss | 16773 | 4-8-1 |
| 13 | 14 | saturday, oct 15 | at saskatchewan roughriders | 14-14 | tie | 7255 | 4-8-2 |
| 14 | 15 | saturday, oct 22 | vs. calgary stampeders | 22-10 | loss | 29599 | 4-9-2 |
| 15 | 16 | saturday, oct 29 | vs. saskatchewan roughriders | 38-0 | win | 21114 | 5-9-2 | | | | score |
|---:|:--------|
| 0 | 35-21 |
| 1 | 33-14 |
| 2 | 26-0 |
| 3 | 19-14 |
| 4 | 26-14 |
| 5 | 18-10 |
| 6 | 28-14 |
| 7 | 49-21 |
| 8 | 22-10 | | [
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] |
select no where driver = 'andrea de cesaris' col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 1 | alain prost | mclaren-tag | 82 | 1:54:20.388 | 4 | 9 row 2 : 2 | 6 | nelson piquet | williams-honda | 82 | + 4.205 | 2 | 6 row 3 : 3 | 28 | stefan johansson | ferrari | 81 | + 1 lap | 12 | 4 row 4 : 4 | 3 | martin brundle | tyrrell-renault | 81 | + 1 lap | 16 | 3 row 5 : 5 | 4 | philippe streiff | tyrrell-renault | 80 | out of fuel | 10 | 2 row 6 : 6 | 11 | johnny dumfries | lotus-renault | 80 | + 2 laps | 14 | 1 row 7 : 7 | 25 | rene arnoux | ligier-renault | 79 | + 3 laps | 5 | none row 8 : 8 | 26 | philippe alliot | ligier-renault | 79 | + 3 laps | 8 | none row 9 : 9 | 14 | jonathan palmer | zakspeed | 77 | + 5 laps | 21 | none row 10 : 10 | 19 | teo fabi | benetton-bmw | 77 | + 5 laps | 13 | none row 11 : nc | 16 | patrick tambay | lola-ford | 70 | not classified | 17 | none row 12 : ret | 5 | nigel mansell | williams-honda | 63 | tyre | 1 | none row 13 : ret | 7 | riccardo patrese | brabham-bmw | 63 | electrical | 19 | none row 14 : ret | 2 | keke rosberg | mclaren-tag | 62 | tyre | 7 | none row 15 : nc | 22 | allen berg | osella-alfa romeo | 61 | not classified | 26 | none row 16 : ret | 8 | derek warwick | brabham-bmw | 57 | brakes | 20 | none row 17 : ret | 17 | christian danner | arrows-bmw | 52 | engine | 24 | none row 18 : ret | 18 | thierry boutsen | arrows-bmw | 50 | engine | 22 | none row 19 : ret | 12 | ayrton senna | lotus-renault | 43 | engine | 3 | none row 20 : ret | 23 | andrea de cesaris | minardi-motori moderni | 40 | mechanical | 11 | none row 21 : ret | 20 | gerhard berger | benetton-bmw | 40 | engine | 6 | none row 22 : ret | 29 | huub rothengatter | zakspeed | 29 | suspension | 23 | none row 23 : ret | 15 | alan jones | lola-ford | 16 | engine | 15 | none row 24 : ret | 24 | alessandro nannini | minardi-motori moderni | 10 | accident | 18 | none row 25 : ret | 21 | piercarlo ghinzani | osella-alfa romeo | 2 | transmission | 25 | none row 26 : ret | 27 | michele alboreto | ferrari | 0 | collision | 9 | none | col : no row 1 : 23 | select no where driver = 'andrea de cesaris' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 1 & alain prost & mclaren-tag & 82 & 1:54:20.388 & 4 & 9 \\
1 & 2 & 6 & nelson piquet & williams-honda & 82 & + 4.205 & 2 & 6 \\
2 & 3 & 28 & stefan johansson & ferrari & 81 & + 1 lap & 12 & 4 \\
3 & 4 & 3 & martin brundle & tyrrell-renault & 81 & + 1 lap & 16 & 3 \\
4 & 5 & 4 & philippe streiff & tyrrell-renault & 80 & out of fuel & 10 & 2 \\
5 & 6 & 11 & johnny dumfries & lotus-renault & 80 & + 2 laps & 14 & 1 \\
6 & 7 & 25 & rene arnoux & ligier-renault & 79 & + 3 laps & 5 & none \\
7 & 8 & 26 & philippe alliot & ligier-renault & 79 & + 3 laps & 8 & none \\
8 & 9 & 14 & jonathan palmer & zakspeed & 77 & + 5 laps & 21 & none \\
9 & 10 & 19 & teo fabi & benetton-bmw & 77 & + 5 laps & 13 & none \\
10 & nc & 16 & patrick tambay & lola-ford & 70 & not classified & 17 & none \\
11 & ret & 5 & nigel mansell & williams-honda & 63 & tyre & 1 & none \\
12 & ret & 7 & riccardo patrese & brabham-bmw & 63 & electrical & 19 & none \\
13 & ret & 2 & keke rosberg & mclaren-tag & 62 & tyre & 7 & none \\
14 & nc & 22 & allen berg & osella-alfa romeo & 61 & not classified & 26 & none \\
15 & ret & 8 & derek warwick & brabham-bmw & 57 & brakes & 20 & none \\
16 & ret & 17 & christian danner & arrows-bmw & 52 & engine & 24 & none \\
17 & ret & 18 & thierry boutsen & arrows-bmw & 50 & engine & 22 & none \\
18 & ret & 12 & ayrton senna & lotus-renault & 43 & engine & 3 & none \\
19 & ret & 23 & andrea de cesaris & minardi-motori moderni & 40 & mechanical & 11 & none \\
20 & ret & 20 & gerhard berger & benetton-bmw & 40 & engine & 6 & none \\
21 & ret & 29 & huub rothengatter & zakspeed & 29 & suspension & 23 & none \\
22 & ret & 15 & alan jones & lola-ford & 16 & engine & 15 & none \\
23 & ret & 24 & alessandro nannini & minardi-motori moderni & 10 & accident & 18 & none \\
24 & ret & 21 & piercarlo ghinzani & osella-alfa romeo & 2 & transmission & 25 & none \\
25 & ret & 27 & michele alboreto & ferrari & 0 & collision & 9 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& no \\
\midrule
0 & 23 \\
\bottomrule
\end{tabular}
| select no where driver = 'andrea de cesaris' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>driver</th>
<th>constructor</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1</td>
<td>alain prost</td>
<td>mclaren-tag</td>
<td>82</td>
<td>1:54:20.388</td>
<td>4</td>
<td>9</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>6</td>
<td>nelson piquet</td>
<td>williams-honda</td>
<td>82</td>
<td>+ 4.205</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>28</td>
<td>stefan johansson</td>
<td>ferrari</td>
<td>81</td>
<td>+ 1 lap</td>
<td>12</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>3</td>
<td>martin brundle</td>
<td>tyrrell-renault</td>
<td>81</td>
<td>+ 1 lap</td>
<td>16</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>4</td>
<td>philippe streiff</td>
<td>tyrrell-renault</td>
<td>80</td>
<td>out of fuel</td>
<td>10</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>11</td>
<td>johnny dumfries</td>
<td>lotus-renault</td>
<td>80</td>
<td>+ 2 laps</td>
<td>14</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>25</td>
<td>rene arnoux</td>
<td>ligier-renault</td>
<td>79</td>
<td>+ 3 laps</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>26</td>
<td>philippe alliot</td>
<td>ligier-renault</td>
<td>79</td>
<td>+ 3 laps</td>
<td>8</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>14</td>
<td>jonathan palmer</td>
<td>zakspeed</td>
<td>77</td>
<td>+ 5 laps</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>19</td>
<td>teo fabi</td>
<td>benetton-bmw</td>
<td>77</td>
<td>+ 5 laps</td>
<td>13</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>nc</td>
<td>16</td>
<td>patrick tambay</td>
<td>lola-ford</td>
<td>70</td>
<td>not classified</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>ret</td>
<td>5</td>
<td>nigel mansell</td>
<td>williams-honda</td>
<td>63</td>
<td>tyre</td>
<td>1</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>ret</td>
<td>7</td>
<td>riccardo patrese</td>
<td>brabham-bmw</td>
<td>63</td>
<td>electrical</td>
<td>19</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>ret</td>
<td>2</td>
<td>keke rosberg</td>
<td>mclaren-tag</td>
<td>62</td>
<td>tyre</td>
<td>7</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>nc</td>
<td>22</td>
<td>allen berg</td>
<td>osella-alfa romeo</td>
<td>61</td>
<td>not classified</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>ret</td>
<td>8</td>
<td>derek warwick</td>
<td>brabham-bmw</td>
<td>57</td>
<td>brakes</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>ret</td>
<td>17</td>
<td>christian danner</td>
<td>arrows-bmw</td>
<td>52</td>
<td>engine</td>
<td>24</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>18</td>
<td>thierry boutsen</td>
<td>arrows-bmw</td>
<td>50</td>
<td>engine</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>12</td>
<td>ayrton senna</td>
<td>lotus-renault</td>
<td>43</td>
<td>engine</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>23</td>
<td>andrea de cesaris</td>
<td>minardi-motori moderni</td>
<td>40</td>
<td>mechanical</td>
<td>11</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>20</td>
<td>gerhard berger</td>
<td>benetton-bmw</td>
<td>40</td>
<td>engine</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>ret</td>
<td>29</td>
<td>huub rothengatter</td>
<td>zakspeed</td>
<td>29</td>
<td>suspension</td>
<td>23</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>ret</td>
<td>15</td>
<td>alan jones</td>
<td>lola-ford</td>
<td>16</td>
<td>engine</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>ret</td>
<td>24</td>
<td>alessandro nannini</td>
<td>minardi-motori moderni</td>
<td>10</td>
<td>accident</td>
<td>18</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>21</td>
<td>piercarlo ghinzani</td>
<td>osella-alfa romeo</td>
<td>2</td>
<td>transmission</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>27</td>
<td>michele alboreto</td>
<td>ferrari</td>
<td>0</td>
<td>collision</td>
<td>9</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>23</td>
</tr>
</tbody>
</table> | select no where driver = 'andrea de cesaris' <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:-------------------|:-----------------------|-------:|:---------------|-------:|:---------|
| 0 | 1 | 1 | alain prost | mclaren-tag | 82 | 1:54:20.388 | 4 | 9 |
| 1 | 2 | 6 | nelson piquet | williams-honda | 82 | + 4.205 | 2 | 6 |
| 2 | 3 | 28 | stefan johansson | ferrari | 81 | + 1 lap | 12 | 4 |
| 3 | 4 | 3 | martin brundle | tyrrell-renault | 81 | + 1 lap | 16 | 3 |
| 4 | 5 | 4 | philippe streiff | tyrrell-renault | 80 | out of fuel | 10 | 2 |
| 5 | 6 | 11 | johnny dumfries | lotus-renault | 80 | + 2 laps | 14 | 1 |
| 6 | 7 | 25 | rene arnoux | ligier-renault | 79 | + 3 laps | 5 | none |
| 7 | 8 | 26 | philippe alliot | ligier-renault | 79 | + 3 laps | 8 | none |
| 8 | 9 | 14 | jonathan palmer | zakspeed | 77 | + 5 laps | 21 | none |
| 9 | 10 | 19 | teo fabi | benetton-bmw | 77 | + 5 laps | 13 | none |
| 10 | nc | 16 | patrick tambay | lola-ford | 70 | not classified | 17 | none |
| 11 | ret | 5 | nigel mansell | williams-honda | 63 | tyre | 1 | none |
| 12 | ret | 7 | riccardo patrese | brabham-bmw | 63 | electrical | 19 | none |
| 13 | ret | 2 | keke rosberg | mclaren-tag | 62 | tyre | 7 | none |
| 14 | nc | 22 | allen berg | osella-alfa romeo | 61 | not classified | 26 | none |
| 15 | ret | 8 | derek warwick | brabham-bmw | 57 | brakes | 20 | none |
| 16 | ret | 17 | christian danner | arrows-bmw | 52 | engine | 24 | none |
| 17 | ret | 18 | thierry boutsen | arrows-bmw | 50 | engine | 22 | none |
| 18 | ret | 12 | ayrton senna | lotus-renault | 43 | engine | 3 | none |
| 19 | ret | 23 | andrea de cesaris | minardi-motori moderni | 40 | mechanical | 11 | none |
| 20 | ret | 20 | gerhard berger | benetton-bmw | 40 | engine | 6 | none |
| 21 | ret | 29 | huub rothengatter | zakspeed | 29 | suspension | 23 | none |
| 22 | ret | 15 | alan jones | lola-ford | 16 | engine | 15 | none |
| 23 | ret | 24 | alessandro nannini | minardi-motori moderni | 10 | accident | 18 | none |
| 24 | ret | 21 | piercarlo ghinzani | osella-alfa romeo | 2 | transmission | 25 | none |
| 25 | ret | 27 | michele alboreto | ferrari | 0 | collision | 9 | none | | | | no |
|---:|-----:|
| 0 | 23 | | [
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select album where single < 298 col : year | single | chart positions spa | album row 1 : 2011 | "breathe in the light" | 10 | endless road 7058 row 2 : 2011 | "last night on earth" | 6 | endless road 7058 row 3 : 2012 | "i don't think so" | 7 | endless road 7058 row 4 : 2012 | "don't give up my game" | 13 | endless road 7058 row 5 : 2012 | "1900" | none | endless road 7058 row 6 : 2012 | "i met an angel (on christmas day)" | 39 | christmas non-album release row 7 : 2013 | "cuando te volvere a ver" | 34 | from soundtrack of wreck-it ralph row 8 : 2013 | "heartbreaker" | 13 | anti-heroes | col : album row 1 : endless road 7058 row 2 : endless road 7058 row 3 : endless road 7058 row 4 : endless road 7058 row 5 : endless road 7058 row 6 : christmas non-album release row 7 : from soundtrack of wreck-it ralph row 8 : anti-heroes | select album where single < 298 <table_name> : table \begin{tabular}{lllll}
\toprule
& year & single & chart positions spa & album \\
\midrule
0 & 2011 & "breathe in the light" & 10 & endless road 7058 \\
1 & 2011 & "last night on earth" & 6 & endless road 7058 \\
2 & 2012 & "i don't think so" & 7 & endless road 7058 \\
3 & 2012 & "don't give up my game" & 13 & endless road 7058 \\
4 & 2012 & "1900" & none & endless road 7058 \\
5 & 2012 & "i met an angel (on christmas day)" & 39 & christmas non-album release \\
6 & 2013 & "cuando te volvere a ver" & 34 & from soundtrack of wreck-it ralph \\
7 & 2013 & "heartbreaker" & 13 & anti-heroes \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& album \\
\midrule
0 & endless road 7058 \\
1 & endless road 7058 \\
2 & endless road 7058 \\
3 & endless road 7058 \\
4 & endless road 7058 \\
5 & christmas non-album release \\
6 & from soundtrack of wreck-it ralph \\
7 & anti-heroes \\
\bottomrule
\end{tabular}
| select album where single < 298 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>single</th>
<th>chart positions spa</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2011</td>
<td>"breathe in the light"</td>
<td>10</td>
<td>endless road 7058</td>
</tr>
<tr>
<th>1</th>
<td>2011</td>
<td>"last night on earth"</td>
<td>6</td>
<td>endless road 7058</td>
</tr>
<tr>
<th>2</th>
<td>2012</td>
<td>"i don't think so"</td>
<td>7</td>
<td>endless road 7058</td>
</tr>
<tr>
<th>3</th>
<td>2012</td>
<td>"don't give up my game"</td>
<td>13</td>
<td>endless road 7058</td>
</tr>
<tr>
<th>4</th>
<td>2012</td>
<td>"1900"</td>
<td>none</td>
<td>endless road 7058</td>
</tr>
<tr>
<th>5</th>
<td>2012</td>
<td>"i met an angel (on christmas day)"</td>
<td>39</td>
<td>christmas non-album release</td>
</tr>
<tr>
<th>6</th>
<td>2013</td>
<td>"cuando te volvere a ver"</td>
<td>34</td>
<td>from soundtrack of wreck-it ralph</td>
</tr>
<tr>
<th>7</th>
<td>2013</td>
<td>"heartbreaker"</td>
<td>13</td>
<td>anti-heroes</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>endless road 7058</td>
</tr>
<tr>
<th>1</th>
<td>endless road 7058</td>
</tr>
<tr>
<th>2</th>
<td>endless road 7058</td>
</tr>
<tr>
<th>3</th>
<td>endless road 7058</td>
</tr>
<tr>
<th>4</th>
<td>endless road 7058</td>
</tr>
<tr>
<th>5</th>
<td>christmas non-album release</td>
</tr>
<tr>
<th>6</th>
<td>from soundtrack of wreck-it ralph</td>
</tr>
<tr>
<th>7</th>
<td>anti-heroes</td>
</tr>
</tbody>
</table> | select album where single < 298 <table_name> : table | | year | single | chart positions spa | album |
|---:|-------:|:------------------------------------|:----------------------|:----------------------------------|
| 0 | 2011 | "breathe in the light" | 10 | endless road 7058 |
| 1 | 2011 | "last night on earth" | 6 | endless road 7058 |
| 2 | 2012 | "i don't think so" | 7 | endless road 7058 |
| 3 | 2012 | "don't give up my game" | 13 | endless road 7058 |
| 4 | 2012 | "1900" | none | endless road 7058 |
| 5 | 2012 | "i met an angel (on christmas day)" | 39 | christmas non-album release |
| 6 | 2013 | "cuando te volvere a ver" | 34 | from soundtrack of wreck-it ralph |
| 7 | 2013 | "heartbreaker" | 13 | anti-heroes | | | | album |
|---:|:----------------------------------|
| 0 | endless road 7058 |
| 1 | endless road 7058 |
| 2 | endless road 7058 |
| 3 | endless road 7058 |
| 4 | endless road 7058 |
| 5 | christmas non-album release |
| 6 | from soundtrack of wreck-it ralph |
| 7 | anti-heroes | | [
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] |
select time where country = 'norway' col : rank | athlete | country | time | behind | points row 1 : 1 | sven kramer | netherlands | 01:53.98 | 0.0 | 37.993 row 2 : 2 | sverre lunde pedersen | norway | 1:54.87 | 0.89 | 38.29 row 3 : 3 | jan blokhuijsen | netherlands | 1:54.93 | 0.95 | 38.31 row 4 : 4 | denis yuskov | russia | 1:55.13 | 1.15 | 38.376 row 5 : 5 | koen verweij | netherlands | 1:55.42 | 1.44 | 38.473 row 6 : 6 | haralds silovs | latvia | 1:55.48 | 1.5 | 38.493 row 7 : 7 | zbigniew brodka | poland | 1:55.98 | 2.0 | 38.66 row 8 : 8 | bart swings | belgium | 1:56.08 | 2.1 | 38.693 row 9 : 9 | havard bøkko | norway | 1:56.35 | 2.37 | 38.783 row 10 : 10 | jan szymanski | poland | 1:56.55 | 2.57 | 38.85 row 11 : 11 | bram smallenbroek | austria | 1:57.44 | 3.46 | 39.146 row 12 : 12 | alexis contin | france | 1:57.58 | 3.6 | 39.193 row 13 : 13 | benjamin mace | france | 1:57.80 | 3.82 | 39.266 row 14 : 14 | konrad niedzwiedzki | poland | 1:57.92 | 3.94 | 39.306 row 15 : 15 | sergey gryaztsov | russia | 1:58.73 | 4.75 | 39.576 row 16 : 16 | patrick beckert | germany | 1:59.08 | 5.1 | 39.693 row 17 : 17 | kristian reistad fredriksen | norway | 1:59.19 | 5.21 | 39.73 row 18 : 18 | luca stefani | italy | 1:59.82 | 5.84 | 39.94 row 19 : 19 | marco cignini | italy | 1:59.97 | 5.99 | 39.99 row 20 : 20 | ferre spruyt | belgium | 2:00.00 | 6.02 | 40.0 row 21 : 21 | vitaly mikhailov | belarus | 2:00.75 | 6.77 | 40.52 row 22 : 22 | milan sablik | czech republic | 2:00.95 | 6.97 | 40.316 row 23 : 23 | ted jan bloemen | netherlands | 2:01.58 | 7.6 | 40.526 row 24 : 24 | moritz geisreiter | germany | 2:01.64 | 7.66 | 40.566 | col : time row 1 : 1:54.87 row 2 : 1:56.35 row 3 : 1:59.19 | select time where country = 'norway' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & athlete & country & time & behind & points \\
\midrule
0 & 1 & sven kramer & netherlands & 01:53.98 & 0.0 & 37.993 \\
1 & 2 & sverre lunde pedersen & norway & 1:54.87 & 0.89 & 38.29 \\
2 & 3 & jan blokhuijsen & netherlands & 1:54.93 & 0.95 & 38.31 \\
3 & 4 & denis yuskov & russia & 1:55.13 & 1.15 & 38.376 \\
4 & 5 & koen verweij & netherlands & 1:55.42 & 1.44 & 38.473 \\
5 & 6 & haralds silovs & latvia & 1:55.48 & 1.5 & 38.493 \\
6 & 7 & zbigniew brodka & poland & 1:55.98 & 2.0 & 38.66 \\
7 & 8 & bart swings & belgium & 1:56.08 & 2.1 & 38.693 \\
8 & 9 & havard bøkko & norway & 1:56.35 & 2.37 & 38.783 \\
9 & 10 & jan szymanski & poland & 1:56.55 & 2.57 & 38.85 \\
10 & 11 & bram smallenbroek & austria & 1:57.44 & 3.46 & 39.146 \\
11 & 12 & alexis contin & france & 1:57.58 & 3.6 & 39.193 \\
12 & 13 & benjamin mace & france & 1:57.80 & 3.82 & 39.266 \\
13 & 14 & konrad niedzwiedzki & poland & 1:57.92 & 3.94 & 39.306 \\
14 & 15 & sergey gryaztsov & russia & 1:58.73 & 4.75 & 39.576 \\
15 & 16 & patrick beckert & germany & 1:59.08 & 5.1 & 39.693 \\
16 & 17 & kristian reistad fredriksen & norway & 1:59.19 & 5.21 & 39.73 \\
17 & 18 & luca stefani & italy & 1:59.82 & 5.84 & 39.94 \\
18 & 19 & marco cignini & italy & 1:59.97 & 5.99 & 39.99 \\
19 & 20 & ferre spruyt & belgium & 2:00.00 & 6.02 & 40.0 \\
20 & 21 & vitaly mikhailov & belarus & 2:00.75 & 6.77 & 40.52 \\
21 & 22 & milan sablik & czech republic & 2:00.95 & 6.97 & 40.316 \\
22 & 23 & ted jan bloemen & netherlands & 2:01.58 & 7.6 & 40.526 \\
23 & 24 & moritz geisreiter & germany & 2:01.64 & 7.66 & 40.566 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& time \\
\midrule
0 & 1:54.87 \\
1 & 1:56.35 \\
2 & 1:59.19 \\
\bottomrule
\end{tabular}
| select time where country = 'norway' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>athlete</th>
<th>country</th>
<th>time</th>
<th>behind</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>sven kramer</td>
<td>netherlands</td>
<td>01:53.98</td>
<td>0.0</td>
<td>37.993</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>sverre lunde pedersen</td>
<td>norway</td>
<td>1:54.87</td>
<td>0.89</td>
<td>38.29</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>jan blokhuijsen</td>
<td>netherlands</td>
<td>1:54.93</td>
<td>0.95</td>
<td>38.31</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>denis yuskov</td>
<td>russia</td>
<td>1:55.13</td>
<td>1.15</td>
<td>38.376</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>koen verweij</td>
<td>netherlands</td>
<td>1:55.42</td>
<td>1.44</td>
<td>38.473</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>haralds silovs</td>
<td>latvia</td>
<td>1:55.48</td>
<td>1.5</td>
<td>38.493</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>zbigniew brodka</td>
<td>poland</td>
<td>1:55.98</td>
<td>2.0</td>
<td>38.66</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>bart swings</td>
<td>belgium</td>
<td>1:56.08</td>
<td>2.1</td>
<td>38.693</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>havard bøkko</td>
<td>norway</td>
<td>1:56.35</td>
<td>2.37</td>
<td>38.783</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>jan szymanski</td>
<td>poland</td>
<td>1:56.55</td>
<td>2.57</td>
<td>38.85</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>bram smallenbroek</td>
<td>austria</td>
<td>1:57.44</td>
<td>3.46</td>
<td>39.146</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>alexis contin</td>
<td>france</td>
<td>1:57.58</td>
<td>3.6</td>
<td>39.193</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>benjamin mace</td>
<td>france</td>
<td>1:57.80</td>
<td>3.82</td>
<td>39.266</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>konrad niedzwiedzki</td>
<td>poland</td>
<td>1:57.92</td>
<td>3.94</td>
<td>39.306</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>sergey gryaztsov</td>
<td>russia</td>
<td>1:58.73</td>
<td>4.75</td>
<td>39.576</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>patrick beckert</td>
<td>germany</td>
<td>1:59.08</td>
<td>5.1</td>
<td>39.693</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>kristian reistad fredriksen</td>
<td>norway</td>
<td>1:59.19</td>
<td>5.21</td>
<td>39.73</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>luca stefani</td>
<td>italy</td>
<td>1:59.82</td>
<td>5.84</td>
<td>39.94</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>marco cignini</td>
<td>italy</td>
<td>1:59.97</td>
<td>5.99</td>
<td>39.99</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>ferre spruyt</td>
<td>belgium</td>
<td>2:00.00</td>
<td>6.02</td>
<td>40.0</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>vitaly mikhailov</td>
<td>belarus</td>
<td>2:00.75</td>
<td>6.77</td>
<td>40.52</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>milan sablik</td>
<td>czech republic</td>
<td>2:00.95</td>
<td>6.97</td>
<td>40.316</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>ted jan bloemen</td>
<td>netherlands</td>
<td>2:01.58</td>
<td>7.6</td>
<td>40.526</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>moritz geisreiter</td>
<td>germany</td>
<td>2:01.64</td>
<td>7.66</td>
<td>40.566</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1:54.87</td>
</tr>
<tr>
<th>1</th>
<td>1:56.35</td>
</tr>
<tr>
<th>2</th>
<td>1:59.19</td>
</tr>
</tbody>
</table> | select time where country = 'norway' <table_name> : table | | rank | athlete | country | time | behind | points |
|---:|-------:|:----------------------------|:---------------|:---------|---------:|---------:|
| 0 | 1 | sven kramer | netherlands | 01:53.98 | 0 | 37.993 |
| 1 | 2 | sverre lunde pedersen | norway | 1:54.87 | 0.89 | 38.29 |
| 2 | 3 | jan blokhuijsen | netherlands | 1:54.93 | 0.95 | 38.31 |
| 3 | 4 | denis yuskov | russia | 1:55.13 | 1.15 | 38.376 |
| 4 | 5 | koen verweij | netherlands | 1:55.42 | 1.44 | 38.473 |
| 5 | 6 | haralds silovs | latvia | 1:55.48 | 1.5 | 38.493 |
| 6 | 7 | zbigniew brodka | poland | 1:55.98 | 2 | 38.66 |
| 7 | 8 | bart swings | belgium | 1:56.08 | 2.1 | 38.693 |
| 8 | 9 | havard bøkko | norway | 1:56.35 | 2.37 | 38.783 |
| 9 | 10 | jan szymanski | poland | 1:56.55 | 2.57 | 38.85 |
| 10 | 11 | bram smallenbroek | austria | 1:57.44 | 3.46 | 39.146 |
| 11 | 12 | alexis contin | france | 1:57.58 | 3.6 | 39.193 |
| 12 | 13 | benjamin mace | france | 1:57.80 | 3.82 | 39.266 |
| 13 | 14 | konrad niedzwiedzki | poland | 1:57.92 | 3.94 | 39.306 |
| 14 | 15 | sergey gryaztsov | russia | 1:58.73 | 4.75 | 39.576 |
| 15 | 16 | patrick beckert | germany | 1:59.08 | 5.1 | 39.693 |
| 16 | 17 | kristian reistad fredriksen | norway | 1:59.19 | 5.21 | 39.73 |
| 17 | 18 | luca stefani | italy | 1:59.82 | 5.84 | 39.94 |
| 18 | 19 | marco cignini | italy | 1:59.97 | 5.99 | 39.99 |
| 19 | 20 | ferre spruyt | belgium | 2:00.00 | 6.02 | 40 |
| 20 | 21 | vitaly mikhailov | belarus | 2:00.75 | 6.77 | 40.52 |
| 21 | 22 | milan sablik | czech republic | 2:00.95 | 6.97 | 40.316 |
| 22 | 23 | ted jan bloemen | netherlands | 2:01.58 | 7.6 | 40.526 |
| 23 | 24 | moritz geisreiter | germany | 2:01.64 | 7.66 | 40.566 | | | | time |
|---:|:--------|
| 0 | 1:54.87 |
| 1 | 1:56.35 |
| 2 | 1:59.19 | | [
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select count ( name ) where time = '2:39.20' col : rank | name | nationality | time | notes row 1 : none | chelsey gotell | canada | 2:28.15 | wr row 2 : none | kirby cote | canada | 2:28.65 | none row 3 : none | valerie grand maison | canada | 2:29.29 | none row 4 : 4 | kelley becherer | united states | 2:32.21 | none row 5 : 5 | prue watt | australia | 2:32.87 | none row 6 : 6 | teigan van roosmalen | australia | 2:39.20 | none row 7 : 7 | lidia marta banos | spain | 2:48.80 | none row 8 : 8 | akari kasamoto | japan | 2:55.16 | none | col : count ( "name" ) row 1 : 1 | select count ( name ) where time = '2:39.20' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & nationality & time & notes \\
\midrule
0 & none & chelsey gotell & canada & 2:28.15 & wr \\
1 & none & kirby cote & canada & 2:28.65 & none \\
2 & none & valerie grand maison & canada & 2:29.29 & none \\
3 & 4 & kelley becherer & united states & 2:32.21 & none \\
4 & 5 & prue watt & australia & 2:32.87 & none \\
5 & 6 & teigan van roosmalen & australia & 2:39.20 & none \\
6 & 7 & lidia marta banos & spain & 2:48.80 & none \\
7 & 8 & akari kasamoto & japan & 2:55.16 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "name" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( name ) where time = '2:39.20' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>time</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>chelsey gotell</td>
<td>canada</td>
<td>2:28.15</td>
<td>wr</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>kirby cote</td>
<td>canada</td>
<td>2:28.65</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>valerie grand maison</td>
<td>canada</td>
<td>2:29.29</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>kelley becherer</td>
<td>united states</td>
<td>2:32.21</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>prue watt</td>
<td>australia</td>
<td>2:32.87</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>teigan van roosmalen</td>
<td>australia</td>
<td>2:39.20</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>lidia marta banos</td>
<td>spain</td>
<td>2:48.80</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>akari kasamoto</td>
<td>japan</td>
<td>2:55.16</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "name" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( name ) where time = '2:39.20' <table_name> : table | | rank | name | nationality | time | notes |
|---:|:-------|:---------------------|:--------------|:--------|:--------|
| 0 | none | chelsey gotell | canada | 2:28.15 | wr |
| 1 | none | kirby cote | canada | 2:28.65 | none |
| 2 | none | valerie grand maison | canada | 2:29.29 | none |
| 3 | 4 | kelley becherer | united states | 2:32.21 | none |
| 4 | 5 | prue watt | australia | 2:32.87 | none |
| 5 | 6 | teigan van roosmalen | australia | 2:39.20 | none |
| 6 | 7 | lidia marta banos | spain | 2:48.80 | none |
| 7 | 8 | akari kasamoto | japan | 2:55.16 | none | | | | count ( "name" ) |
|---:|-------------------:|
| 0 | 1 | | [
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] |
select count ( * ) where player = 'tomislav kostadinov' col : player | league | cup | europa league | total row 1 : spas delev | 13 | 7 | 2 | 22 row 2 : marquinhos | 9 | 1 | 3 | 13 row 3 : michel platini | 10 | 0 | 0 | 10 row 4 : cillian sheridan | 4 | 2 | 1 | 7 row 5 : giuseppe aquaro | 3 | 0 | 2 | 5 row 6 : gregory nelson | 3 | 0 | 1 | 4 row 7 : rumen trifonov | 2 | 0 | 1 | 3 row 8 : aleksandar tonev | 2 | 0 | 0 | 2 row 9 : apostol popov | 2 | 0 | 0 | 2 row 10 : emil gargorov | 2 | 0 | 0 | 2 row 11 : todor yanchev | 0 | 1 | 1 | 2 row 12 : stanislav kostov | 1 | 0 | 0 | 1 row 13 : kostadin stoyanov | 1 | 0 | 0 | 1 row 14 : boris galchev | 1 | 0 | 0 | 1 row 15 : pavel vidanov | 0 | 0 | 1 | 1 row 16 : tomislav kostadinov | 0 | 0 | 1 | 1 row 17 : christian tiboni | 0 | 0 | 1 | 1 row 18 : total | 53 | 11 | 14 | 78 | col : count ( "*" ) row 1 : 1 | select count ( * ) where player = 'tomislav kostadinov' <table_name> : table \begin{tabular}{llllll}
\toprule
& player & league & cup & europa league & total \\
\midrule
0 & spas delev & 13 & 7 & 2 & 22 \\
1 & marquinhos & 9 & 1 & 3 & 13 \\
2 & michel platini & 10 & 0 & 0 & 10 \\
3 & cillian sheridan & 4 & 2 & 1 & 7 \\
4 & giuseppe aquaro & 3 & 0 & 2 & 5 \\
5 & gregory nelson & 3 & 0 & 1 & 4 \\
6 & rumen trifonov & 2 & 0 & 1 & 3 \\
7 & aleksandar tonev & 2 & 0 & 0 & 2 \\
8 & apostol popov & 2 & 0 & 0 & 2 \\
9 & emil gargorov & 2 & 0 & 0 & 2 \\
10 & todor yanchev & 0 & 1 & 1 & 2 \\
11 & stanislav kostov & 1 & 0 & 0 & 1 \\
12 & kostadin stoyanov & 1 & 0 & 0 & 1 \\
13 & boris galchev & 1 & 0 & 0 & 1 \\
14 & pavel vidanov & 0 & 0 & 1 & 1 \\
15 & tomislav kostadinov & 0 & 0 & 1 & 1 \\
16 & christian tiboni & 0 & 0 & 1 & 1 \\
17 & total & 53 & 11 & 14 & 78 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where player = 'tomislav kostadinov' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>player</th>
<th>league</th>
<th>cup</th>
<th>europa league</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>spas delev</td>
<td>13</td>
<td>7</td>
<td>2</td>
<td>22</td>
</tr>
<tr>
<th>1</th>
<td>marquinhos</td>
<td>9</td>
<td>1</td>
<td>3</td>
<td>13</td>
</tr>
<tr>
<th>2</th>
<td>michel platini</td>
<td>10</td>
<td>0</td>
<td>0</td>
<td>10</td>
</tr>
<tr>
<th>3</th>
<td>cillian sheridan</td>
<td>4</td>
<td>2</td>
<td>1</td>
<td>7</td>
</tr>
<tr>
<th>4</th>
<td>giuseppe aquaro</td>
<td>3</td>
<td>0</td>
<td>2</td>
<td>5</td>
</tr>
<tr>
<th>5</th>
<td>gregory nelson</td>
<td>3</td>
<td>0</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>6</th>
<td>rumen trifonov</td>
<td>2</td>
<td>0</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>7</th>
<td>aleksandar tonev</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>apostol popov</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>emil gargorov</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>10</th>
<td>todor yanchev</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>stanislav kostov</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>kostadin stoyanov</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>boris galchev</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>pavel vidanov</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>tomislav kostadinov</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>christian tiboni</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>17</th>
<td>total</td>
<td>53</td>
<td>11</td>
<td>14</td>
<td>78</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where player = 'tomislav kostadinov' <table_name> : table | | player | league | cup | europa league | total |
|---:|:--------------------|---------:|------:|----------------:|--------:|
| 0 | spas delev | 13 | 7 | 2 | 22 |
| 1 | marquinhos | 9 | 1 | 3 | 13 |
| 2 | michel platini | 10 | 0 | 0 | 10 |
| 3 | cillian sheridan | 4 | 2 | 1 | 7 |
| 4 | giuseppe aquaro | 3 | 0 | 2 | 5 |
| 5 | gregory nelson | 3 | 0 | 1 | 4 |
| 6 | rumen trifonov | 2 | 0 | 1 | 3 |
| 7 | aleksandar tonev | 2 | 0 | 0 | 2 |
| 8 | apostol popov | 2 | 0 | 0 | 2 |
| 9 | emil gargorov | 2 | 0 | 0 | 2 |
| 10 | todor yanchev | 0 | 1 | 1 | 2 |
| 11 | stanislav kostov | 1 | 0 | 0 | 1 |
| 12 | kostadin stoyanov | 1 | 0 | 0 | 1 |
| 13 | boris galchev | 1 | 0 | 0 | 1 |
| 14 | pavel vidanov | 0 | 0 | 1 | 1 |
| 15 | tomislav kostadinov | 0 | 0 | 1 | 1 |
| 16 | christian tiboni | 0 | 0 | 1 | 1 |
| 17 | total | 53 | 11 | 14 | 78 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select women's winner where women's winner = 'aselefech mergia (eth)' order by edition asc limit 1 col : edition | year | men's winner | time (m:s) -1 | women's winner | time (m:s) -2 row 1 : 1st | 1990 | marti ten kate (ned) | 47:52 | alison gooderham (gbr) | 56:09 row 2 : 2nd | 1991 | thomas naali (tan) | 47:11 | olga bondarenko (urs) | 53:16 row 3 : 3rd | 1992 | boay akonay (tan) | 47:04 | iulia negura (rom) | 53:19 row 4 : 4th | 1993 | gary staines (gbr) | 46:11 | iulia negura (rom) | 53:01 row 5 : 5th | 1994 | gary staines (gbr) | 47:00 | gitte karlshøj (den) | 54:49 row 6 : 6th | 1995 | benson masya (ken) | 45:56 | liz mccolgan (gbr) | 53:12 row 7 : 7th | 1996 | gary staines (gbr) | 46:57 | derartu tulu (eth) | 52:39 row 8 : 8th | 1997 | christopher kelong (ken) | 46:53 | liz mccolgan (gbr) | 52:00 row 9 : 9th | 1998 | stephane franke (ger) | 47:40 | marian sutton (gbr) | 54:17 row 10 : 10th | 1999 | simon kasimili (ken) | 47:42 | esther kiplagat (ken) | 54:42 row 11 : 11th | 2000 | gert thys (rsa) | 48:26 | restituta joseph (tan) | 55:10 row 12 : 12th | 2001 | khalid skah (mar) | 46:17 | restituta joseph (tan) | 52:36 row 13 : 13th | 2002 | simon kasimili (ken) | 47:27 | sonia o'sullivan (irl) | 51:00 row 14 : 14th | 2003 | john yuda (tan) | 46:35 | sonia o'sullivan (irl) | 53:26 row 15 : 15th | 2004 | hendrick ramaala (rsa) | 47:14 | benita johnson (aus) | 52:32 row 16 : 16th | 2005 | john yuda (tan) | 46:45 | derartu tulu (eth) | 51:27 row 17 : 17th | 2006 | simon arusei (ken) | 47:17 | jo pavey (gbr) | 52:46 row 18 : 18th | 2007 | luke kibet (ken) | 47:31 | rose cheruiyot (ken) | 53:44 row 19 : 19th | 2008 | bernard kipyego (ken) | 46:42 | paula radcliffe (gbr) | 51:11 row 20 : 20th | 2009 | mo farah (gbr) | 46:25 | ines monteiro (por) | 52:32 row 21 : 21st | 2010 | joseph ebuya (ken) | 45:15 | grace momanyi (ken) | 52:03 row 22 : 22nd | 2011 | leonard komon (ken) | 46:18 | aselefech mergia (eth) | 52:55 row 23 : 23rd | 2012 | stephen mokoka (rsa) | 46:40 | jo pavey (grb) | 53:01 row 24 : 24th | 2013 | emmanuel bett (ken) | 48:03 | florence kiplagat (ken) | 53:53 | col : women's winner row 1 : aselefech mergia (eth) | select women's winner where women's winner = 'aselefech mergia (eth)' order by edition asc limit 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& edition & year & men's winner & time (m:s) -1 & women's winner & time (m:s) -2 \\
\midrule
0 & 1st & 1990 & marti ten kate (ned) & 47:52 & alison gooderham (gbr) & 56:09 \\
1 & 2nd & 1991 & thomas naali (tan) & 47:11 & olga bondarenko (urs) & 53:16 \\
2 & 3rd & 1992 & boay akonay (tan) & 47:04 & iulia negura (rom) & 53:19 \\
3 & 4th & 1993 & gary staines (gbr) & 46:11 & iulia negura (rom) & 53:01 \\
4 & 5th & 1994 & gary staines (gbr) & 47:00 & gitte karlshøj (den) & 54:49 \\
5 & 6th & 1995 & benson masya (ken) & 45:56 & liz mccolgan (gbr) & 53:12 \\
6 & 7th & 1996 & gary staines (gbr) & 46:57 & derartu tulu (eth) & 52:39 \\
7 & 8th & 1997 & christopher kelong (ken) & 46:53 & liz mccolgan (gbr) & 52:00 \\
8 & 9th & 1998 & stephane franke (ger) & 47:40 & marian sutton (gbr) & 54:17 \\
9 & 10th & 1999 & simon kasimili (ken) & 47:42 & esther kiplagat (ken) & 54:42 \\
10 & 11th & 2000 & gert thys (rsa) & 48:26 & restituta joseph (tan) & 55:10 \\
11 & 12th & 2001 & khalid skah (mar) & 46:17 & restituta joseph (tan) & 52:36 \\
12 & 13th & 2002 & simon kasimili (ken) & 47:27 & sonia o'sullivan (irl) & 51:00 \\
13 & 14th & 2003 & john yuda (tan) & 46:35 & sonia o'sullivan (irl) & 53:26 \\
14 & 15th & 2004 & hendrick ramaala (rsa) & 47:14 & benita johnson (aus) & 52:32 \\
15 & 16th & 2005 & john yuda (tan) & 46:45 & derartu tulu (eth) & 51:27 \\
16 & 17th & 2006 & simon arusei (ken) & 47:17 & jo pavey (gbr) & 52:46 \\
17 & 18th & 2007 & luke kibet (ken) & 47:31 & rose cheruiyot (ken) & 53:44 \\
18 & 19th & 2008 & bernard kipyego (ken) & 46:42 & paula radcliffe (gbr) & 51:11 \\
19 & 20th & 2009 & mo farah (gbr) & 46:25 & ines monteiro (por) & 52:32 \\
20 & 21st & 2010 & joseph ebuya (ken) & 45:15 & grace momanyi (ken) & 52:03 \\
21 & 22nd & 2011 & leonard komon (ken) & 46:18 & aselefech mergia (eth) & 52:55 \\
22 & 23rd & 2012 & stephen mokoka (rsa) & 46:40 & jo pavey (grb) & 53:01 \\
23 & 24th & 2013 & emmanuel bett (ken) & 48:03 & florence kiplagat (ken) & 53:53 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& women's winner \\
\midrule
0 & aselefech mergia (eth) \\
\bottomrule
\end{tabular}
| select women's winner where women's winner = 'aselefech mergia (eth)' order by edition asc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>edition</th>
<th>year</th>
<th>men's winner</th>
<th>time (m:s) -1</th>
<th>women's winner</th>
<th>time (m:s) -2</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1st</td>
<td>1990</td>
<td>marti ten kate (ned)</td>
<td>47:52</td>
<td>alison gooderham (gbr)</td>
<td>56:09</td>
</tr>
<tr>
<th>1</th>
<td>2nd</td>
<td>1991</td>
<td>thomas naali (tan)</td>
<td>47:11</td>
<td>olga bondarenko (urs)</td>
<td>53:16</td>
</tr>
<tr>
<th>2</th>
<td>3rd</td>
<td>1992</td>
<td>boay akonay (tan)</td>
<td>47:04</td>
<td>iulia negura (rom)</td>
<td>53:19</td>
</tr>
<tr>
<th>3</th>
<td>4th</td>
<td>1993</td>
<td>gary staines (gbr)</td>
<td>46:11</td>
<td>iulia negura (rom)</td>
<td>53:01</td>
</tr>
<tr>
<th>4</th>
<td>5th</td>
<td>1994</td>
<td>gary staines (gbr)</td>
<td>47:00</td>
<td>gitte karlshøj (den)</td>
<td>54:49</td>
</tr>
<tr>
<th>5</th>
<td>6th</td>
<td>1995</td>
<td>benson masya (ken)</td>
<td>45:56</td>
<td>liz mccolgan (gbr)</td>
<td>53:12</td>
</tr>
<tr>
<th>6</th>
<td>7th</td>
<td>1996</td>
<td>gary staines (gbr)</td>
<td>46:57</td>
<td>derartu tulu (eth)</td>
<td>52:39</td>
</tr>
<tr>
<th>7</th>
<td>8th</td>
<td>1997</td>
<td>christopher kelong (ken)</td>
<td>46:53</td>
<td>liz mccolgan (gbr)</td>
<td>52:00</td>
</tr>
<tr>
<th>8</th>
<td>9th</td>
<td>1998</td>
<td>stephane franke (ger)</td>
<td>47:40</td>
<td>marian sutton (gbr)</td>
<td>54:17</td>
</tr>
<tr>
<th>9</th>
<td>10th</td>
<td>1999</td>
<td>simon kasimili (ken)</td>
<td>47:42</td>
<td>esther kiplagat (ken)</td>
<td>54:42</td>
</tr>
<tr>
<th>10</th>
<td>11th</td>
<td>2000</td>
<td>gert thys (rsa)</td>
<td>48:26</td>
<td>restituta joseph (tan)</td>
<td>55:10</td>
</tr>
<tr>
<th>11</th>
<td>12th</td>
<td>2001</td>
<td>khalid skah (mar)</td>
<td>46:17</td>
<td>restituta joseph (tan)</td>
<td>52:36</td>
</tr>
<tr>
<th>12</th>
<td>13th</td>
<td>2002</td>
<td>simon kasimili (ken)</td>
<td>47:27</td>
<td>sonia o'sullivan (irl)</td>
<td>51:00</td>
</tr>
<tr>
<th>13</th>
<td>14th</td>
<td>2003</td>
<td>john yuda (tan)</td>
<td>46:35</td>
<td>sonia o'sullivan (irl)</td>
<td>53:26</td>
</tr>
<tr>
<th>14</th>
<td>15th</td>
<td>2004</td>
<td>hendrick ramaala (rsa)</td>
<td>47:14</td>
<td>benita johnson (aus)</td>
<td>52:32</td>
</tr>
<tr>
<th>15</th>
<td>16th</td>
<td>2005</td>
<td>john yuda (tan)</td>
<td>46:45</td>
<td>derartu tulu (eth)</td>
<td>51:27</td>
</tr>
<tr>
<th>16</th>
<td>17th</td>
<td>2006</td>
<td>simon arusei (ken)</td>
<td>47:17</td>
<td>jo pavey (gbr)</td>
<td>52:46</td>
</tr>
<tr>
<th>17</th>
<td>18th</td>
<td>2007</td>
<td>luke kibet (ken)</td>
<td>47:31</td>
<td>rose cheruiyot (ken)</td>
<td>53:44</td>
</tr>
<tr>
<th>18</th>
<td>19th</td>
<td>2008</td>
<td>bernard kipyego (ken)</td>
<td>46:42</td>
<td>paula radcliffe (gbr)</td>
<td>51:11</td>
</tr>
<tr>
<th>19</th>
<td>20th</td>
<td>2009</td>
<td>mo farah (gbr)</td>
<td>46:25</td>
<td>ines monteiro (por)</td>
<td>52:32</td>
</tr>
<tr>
<th>20</th>
<td>21st</td>
<td>2010</td>
<td>joseph ebuya (ken)</td>
<td>45:15</td>
<td>grace momanyi (ken)</td>
<td>52:03</td>
</tr>
<tr>
<th>21</th>
<td>22nd</td>
<td>2011</td>
<td>leonard komon (ken)</td>
<td>46:18</td>
<td>aselefech mergia (eth)</td>
<td>52:55</td>
</tr>
<tr>
<th>22</th>
<td>23rd</td>
<td>2012</td>
<td>stephen mokoka (rsa)</td>
<td>46:40</td>
<td>jo pavey (grb)</td>
<td>53:01</td>
</tr>
<tr>
<th>23</th>
<td>24th</td>
<td>2013</td>
<td>emmanuel bett (ken)</td>
<td>48:03</td>
<td>florence kiplagat (ken)</td>
<td>53:53</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>women's winner</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>aselefech mergia (eth)</td>
</tr>
</tbody>
</table> | select women's winner where women's winner = 'aselefech mergia (eth)' order by edition asc limit 1 <table_name> : table | | edition | year | men's winner | time (m:s) -1 | women's winner | time (m:s) -2 |
|---:|:----------|-------:|:-------------------------|:----------------|:------------------------|:----------------|
| 0 | 1st | 1990 | marti ten kate (ned) | 47:52 | alison gooderham (gbr) | 56:09 |
| 1 | 2nd | 1991 | thomas naali (tan) | 47:11 | olga bondarenko (urs) | 53:16 |
| 2 | 3rd | 1992 | boay akonay (tan) | 47:04 | iulia negura (rom) | 53:19 |
| 3 | 4th | 1993 | gary staines (gbr) | 46:11 | iulia negura (rom) | 53:01 |
| 4 | 5th | 1994 | gary staines (gbr) | 47:00 | gitte karlshøj (den) | 54:49 |
| 5 | 6th | 1995 | benson masya (ken) | 45:56 | liz mccolgan (gbr) | 53:12 |
| 6 | 7th | 1996 | gary staines (gbr) | 46:57 | derartu tulu (eth) | 52:39 |
| 7 | 8th | 1997 | christopher kelong (ken) | 46:53 | liz mccolgan (gbr) | 52:00 |
| 8 | 9th | 1998 | stephane franke (ger) | 47:40 | marian sutton (gbr) | 54:17 |
| 9 | 10th | 1999 | simon kasimili (ken) | 47:42 | esther kiplagat (ken) | 54:42 |
| 10 | 11th | 2000 | gert thys (rsa) | 48:26 | restituta joseph (tan) | 55:10 |
| 11 | 12th | 2001 | khalid skah (mar) | 46:17 | restituta joseph (tan) | 52:36 |
| 12 | 13th | 2002 | simon kasimili (ken) | 47:27 | sonia o'sullivan (irl) | 51:00 |
| 13 | 14th | 2003 | john yuda (tan) | 46:35 | sonia o'sullivan (irl) | 53:26 |
| 14 | 15th | 2004 | hendrick ramaala (rsa) | 47:14 | benita johnson (aus) | 52:32 |
| 15 | 16th | 2005 | john yuda (tan) | 46:45 | derartu tulu (eth) | 51:27 |
| 16 | 17th | 2006 | simon arusei (ken) | 47:17 | jo pavey (gbr) | 52:46 |
| 17 | 18th | 2007 | luke kibet (ken) | 47:31 | rose cheruiyot (ken) | 53:44 |
| 18 | 19th | 2008 | bernard kipyego (ken) | 46:42 | paula radcliffe (gbr) | 51:11 |
| 19 | 20th | 2009 | mo farah (gbr) | 46:25 | ines monteiro (por) | 52:32 |
| 20 | 21st | 2010 | joseph ebuya (ken) | 45:15 | grace momanyi (ken) | 52:03 |
| 21 | 22nd | 2011 | leonard komon (ken) | 46:18 | aselefech mergia (eth) | 52:55 |
| 22 | 23rd | 2012 | stephen mokoka (rsa) | 46:40 | jo pavey (grb) | 53:01 |
| 23 | 24th | 2013 | emmanuel bett (ken) | 48:03 | florence kiplagat (ken) | 53:53 | | | | women's winner |
|---:|:-----------------------|
| 0 | aselefech mergia (eth) | | [
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select max ( # ) where overall record = '45-31' col : # | date | opponent | score | site/stadium | win | loss | save | attendance | overall record | ncaat record row 1 : 72 | june 15 | rice | 17-5 | rosenblatt stadium | wilson (8-5) | berry (8-5) | none | 18108 | 43-29 | 6-2 row 2 : 73 | june 17 | north carolina | 5-3 | rosenblatt stadium | breckley (3-2) | warren (9-2) | burke (13) | 23314 | 44-29 | 7-2 row 3 : 74 | june 21 | north carolina | 4-3 | rosenblatt stadium | white (13-3) | miller (6-4) | none | 18611 | 44-30 | 7-3 row 4 : 75 | june 22 | north carolina | 6-1 | rosenblatt stadium | allison (4-5) | moran (1-2) | none | 15125 | 45-30 | 8-3 row 5 : 76 | june 23 | georgia | 7-6 | rosenblatt stadium | harvil (2-1) | burke (4-6) | fields (18) | 19559 | 45-31 | 8-4 row 6 : 77 | june 24 | georgia | 19-10 | rosenblatt stadium | sprague (6-2) | dodson (5-5) | hower (1) | 17223 | 46-31 | 9-4 row 7 : 78 | june 25 | georgia | 6-1 | rosenblatt stadium | wilson (5-5) | moreau (4-4) | none | 18932 | 47-31 | 10-4 | col : max ( "#" ) row 1 : 76 | select max ( # ) where overall record = '45-31' <table_name> : table \begin{tabular}{llllllllllll}
\toprule
& # & date & opponent & score & site/stadium & win & loss & save & attendance & overall record & ncaat record \\
\midrule
0 & 72 & june 15 & rice & 17-5 & rosenblatt stadium & wilson (8-5) & berry (8-5) & none & 18108 & 43-29 & 6-2 \\
1 & 73 & june 17 & north carolina & 5-3 & rosenblatt stadium & breckley (3-2) & warren (9-2) & burke (13) & 23314 & 44-29 & 7-2 \\
2 & 74 & june 21 & north carolina & 4-3 & rosenblatt stadium & white (13-3) & miller (6-4) & none & 18611 & 44-30 & 7-3 \\
3 & 75 & june 22 & north carolina & 6-1 & rosenblatt stadium & allison (4-5) & moran (1-2) & none & 15125 & 45-30 & 8-3 \\
4 & 76 & june 23 & georgia & 7-6 & rosenblatt stadium & harvil (2-1) & burke (4-6) & fields (18) & 19559 & 45-31 & 8-4 \\
5 & 77 & june 24 & georgia & 19-10 & rosenblatt stadium & sprague (6-2) & dodson (5-5) & hower (1) & 17223 & 46-31 & 9-4 \\
6 & 78 & june 25 & georgia & 6-1 & rosenblatt stadium & wilson (5-5) & moreau (4-4) & none & 18932 & 47-31 & 10-4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& max ( "#" ) \\
\midrule
0 & 76 \\
\bottomrule
\end{tabular}
| select max ( # ) where overall record = '45-31' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>date</th>
<th>opponent</th>
<th>score</th>
<th>site/stadium</th>
<th>win</th>
<th>loss</th>
<th>save</th>
<th>attendance</th>
<th>overall record</th>
<th>ncaat record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>72</td>
<td>june 15</td>
<td>rice</td>
<td>17-5</td>
<td>rosenblatt stadium</td>
<td>wilson (8-5)</td>
<td>berry (8-5)</td>
<td>none</td>
<td>18108</td>
<td>43-29</td>
<td>6-2</td>
</tr>
<tr>
<th>1</th>
<td>73</td>
<td>june 17</td>
<td>north carolina</td>
<td>5-3</td>
<td>rosenblatt stadium</td>
<td>breckley (3-2)</td>
<td>warren (9-2)</td>
<td>burke (13)</td>
<td>23314</td>
<td>44-29</td>
<td>7-2</td>
</tr>
<tr>
<th>2</th>
<td>74</td>
<td>june 21</td>
<td>north carolina</td>
<td>4-3</td>
<td>rosenblatt stadium</td>
<td>white (13-3)</td>
<td>miller (6-4)</td>
<td>none</td>
<td>18611</td>
<td>44-30</td>
<td>7-3</td>
</tr>
<tr>
<th>3</th>
<td>75</td>
<td>june 22</td>
<td>north carolina</td>
<td>6-1</td>
<td>rosenblatt stadium</td>
<td>allison (4-5)</td>
<td>moran (1-2)</td>
<td>none</td>
<td>15125</td>
<td>45-30</td>
<td>8-3</td>
</tr>
<tr>
<th>4</th>
<td>76</td>
<td>june 23</td>
<td>georgia</td>
<td>7-6</td>
<td>rosenblatt stadium</td>
<td>harvil (2-1)</td>
<td>burke (4-6)</td>
<td>fields (18)</td>
<td>19559</td>
<td>45-31</td>
<td>8-4</td>
</tr>
<tr>
<th>5</th>
<td>77</td>
<td>june 24</td>
<td>georgia</td>
<td>19-10</td>
<td>rosenblatt stadium</td>
<td>sprague (6-2)</td>
<td>dodson (5-5)</td>
<td>hower (1)</td>
<td>17223</td>
<td>46-31</td>
<td>9-4</td>
</tr>
<tr>
<th>6</th>
<td>78</td>
<td>june 25</td>
<td>georgia</td>
<td>6-1</td>
<td>rosenblatt stadium</td>
<td>wilson (5-5)</td>
<td>moreau (4-4)</td>
<td>none</td>
<td>18932</td>
<td>47-31</td>
<td>10-4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>max ( "#" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>76</td>
</tr>
</tbody>
</table> | select max ( # ) where overall record = '45-31' <table_name> : table | | # | date | opponent | score | site/stadium | win | loss | save | attendance | overall record | ncaat record |
|---:|----:|:--------|:---------------|:--------|:-------------------|:---------------|:-------------|:------------|-------------:|:-----------------|:---------------|
| 0 | 72 | june 15 | rice | 17-5 | rosenblatt stadium | wilson (8-5) | berry (8-5) | none | 18108 | 43-29 | 6-2 |
| 1 | 73 | june 17 | north carolina | 5-3 | rosenblatt stadium | breckley (3-2) | warren (9-2) | burke (13) | 23314 | 44-29 | 7-2 |
| 2 | 74 | june 21 | north carolina | 4-3 | rosenblatt stadium | white (13-3) | miller (6-4) | none | 18611 | 44-30 | 7-3 |
| 3 | 75 | june 22 | north carolina | 6-1 | rosenblatt stadium | allison (4-5) | moran (1-2) | none | 15125 | 45-30 | 8-3 |
| 4 | 76 | june 23 | georgia | 7-6 | rosenblatt stadium | harvil (2-1) | burke (4-6) | fields (18) | 19559 | 45-31 | 8-4 |
| 5 | 77 | june 24 | georgia | 19-10 | rosenblatt stadium | sprague (6-2) | dodson (5-5) | hower (1) | 17223 | 46-31 | 9-4 |
| 6 | 78 | june 25 | georgia | 6-1 | rosenblatt stadium | wilson (5-5) | moreau (4-4) | none | 18932 | 47-31 | 10-4 | | | | max ( "#" ) |
|---:|--------------:|
| 0 | 76 | | [
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select count ( * ) where short name = 'ra' col : position | swara | short name | notation | mnemonic row 1 : 1 | shadja | sa | s | sa row 2 : 2 | shuddha rishabha | ri | r1 | ra row 3 : 3 | chatushruti rishabha | ri | r2 | ri row 4 : 3 | shuddha gandhara | ga | g1 | ga row 5 : 4 | shatshruti rishabha | ri | r3 | ru row 6 : 4 | sadharana gandhara | ga | g2 | gi row 7 : 5 | antara gandhara | ga | g3 | gu row 8 : 6 | shuddha madhyama | ma | m1 | ma row 9 : 7 | prati madhyama | ma | m2 | mi row 10 : 8 | panchama | pa | p | pa row 11 : 9 | shuddha dhaivata | dha | d1 | dha row 12 : 10 | chatushruti dhaivata | dha | d2 | dhi row 13 : 10 | shuddha nishada | ni | n1 | na row 14 : 11 | shatshruti dhaivata | dha | d3 | dhu row 15 : 11 | kaisiki nishada | ni | n2 | ni row 16 : 12 | kakali nishada | ni | n3 | nu | col : count ( "*" ) row 1 : 0 | select count ( * ) where short name = 'ra' <table_name> : table \begin{tabular}{llllll}
\toprule
& position & swara & short name & notation & mnemonic \\
\midrule
0 & 1 & shadja & sa & s & sa \\
1 & 2 & shuddha rishabha & ri & r1 & ra \\
2 & 3 & chatushruti rishabha & ri & r2 & ri \\
3 & 3 & shuddha gandhara & ga & g1 & ga \\
4 & 4 & shatshruti rishabha & ri & r3 & ru \\
5 & 4 & sadharana gandhara & ga & g2 & gi \\
6 & 5 & antara gandhara & ga & g3 & gu \\
7 & 6 & shuddha madhyama & ma & m1 & ma \\
8 & 7 & prati madhyama & ma & m2 & mi \\
9 & 8 & panchama & pa & p & pa \\
10 & 9 & shuddha dhaivata & dha & d1 & dha \\
11 & 10 & chatushruti dhaivata & dha & d2 & dhi \\
12 & 10 & shuddha nishada & ni & n1 & na \\
13 & 11 & shatshruti dhaivata & dha & d3 & dhu \\
14 & 11 & kaisiki nishada & ni & n2 & ni \\
15 & 12 & kakali nishada & ni & n3 & nu \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where short name = 'ra' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
<th>swara</th>
<th>short name</th>
<th>notation</th>
<th>mnemonic</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>shadja</td>
<td>sa</td>
<td>s</td>
<td>sa</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>shuddha rishabha</td>
<td>ri</td>
<td>r1</td>
<td>ra</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>chatushruti rishabha</td>
<td>ri</td>
<td>r2</td>
<td>ri</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>shuddha gandhara</td>
<td>ga</td>
<td>g1</td>
<td>ga</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>shatshruti rishabha</td>
<td>ri</td>
<td>r3</td>
<td>ru</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>sadharana gandhara</td>
<td>ga</td>
<td>g2</td>
<td>gi</td>
</tr>
<tr>
<th>6</th>
<td>5</td>
<td>antara gandhara</td>
<td>ga</td>
<td>g3</td>
<td>gu</td>
</tr>
<tr>
<th>7</th>
<td>6</td>
<td>shuddha madhyama</td>
<td>ma</td>
<td>m1</td>
<td>ma</td>
</tr>
<tr>
<th>8</th>
<td>7</td>
<td>prati madhyama</td>
<td>ma</td>
<td>m2</td>
<td>mi</td>
</tr>
<tr>
<th>9</th>
<td>8</td>
<td>panchama</td>
<td>pa</td>
<td>p</td>
<td>pa</td>
</tr>
<tr>
<th>10</th>
<td>9</td>
<td>shuddha dhaivata</td>
<td>dha</td>
<td>d1</td>
<td>dha</td>
</tr>
<tr>
<th>11</th>
<td>10</td>
<td>chatushruti dhaivata</td>
<td>dha</td>
<td>d2</td>
<td>dhi</td>
</tr>
<tr>
<th>12</th>
<td>10</td>
<td>shuddha nishada</td>
<td>ni</td>
<td>n1</td>
<td>na</td>
</tr>
<tr>
<th>13</th>
<td>11</td>
<td>shatshruti dhaivata</td>
<td>dha</td>
<td>d3</td>
<td>dhu</td>
</tr>
<tr>
<th>14</th>
<td>11</td>
<td>kaisiki nishada</td>
<td>ni</td>
<td>n2</td>
<td>ni</td>
</tr>
<tr>
<th>15</th>
<td>12</td>
<td>kakali nishada</td>
<td>ni</td>
<td>n3</td>
<td>nu</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where short name = 'ra' <table_name> : table | | position | swara | short name | notation | mnemonic |
|---:|-----------:|:---------------------|:-------------|:-----------|:-----------|
| 0 | 1 | shadja | sa | s | sa |
| 1 | 2 | shuddha rishabha | ri | r1 | ra |
| 2 | 3 | chatushruti rishabha | ri | r2 | ri |
| 3 | 3 | shuddha gandhara | ga | g1 | ga |
| 4 | 4 | shatshruti rishabha | ri | r3 | ru |
| 5 | 4 | sadharana gandhara | ga | g2 | gi |
| 6 | 5 | antara gandhara | ga | g3 | gu |
| 7 | 6 | shuddha madhyama | ma | m1 | ma |
| 8 | 7 | prati madhyama | ma | m2 | mi |
| 9 | 8 | panchama | pa | p | pa |
| 10 | 9 | shuddha dhaivata | dha | d1 | dha |
| 11 | 10 | chatushruti dhaivata | dha | d2 | dhi |
| 12 | 10 | shuddha nishada | ni | n1 | na |
| 13 | 11 | shatshruti dhaivata | dha | d3 | dhu |
| 14 | 11 | kaisiki nishada | ni | n2 | ni |
| 15 | 12 | kakali nishada | ni | n3 | nu | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select category where year > 1311 col : year | award | result | category | series row 1 : 2004 | bet comedy awards | won | outstanding supporting actor in a comedy series | scrubs row 2 : 2002 | bet comedy awards | won | outstanding supporting actor in a comedy series | scrubs row 3 : 2004 | teen choice awards | nominated | choice tv sidekick | scrubs row 4 : 2005 | teen choice awards | nominated | choice tv sidekick | scrubs row 5 : 2006 | teen choice awards | nominated | choice tv sidekick | scrubs row 6 : 2007 | teen choice awards | nominated | choice tv sidekick | scrubs row 7 : 2005 | naacp image awards | nominated | outstanding supporting actor in a comedy series | scrubs row 8 : 2006 | naacp image awards | nominated | outstanding actor in a comedy series | scrubs row 9 : 2007 | naacp image awards | nominated | outstanding actor in a comedy series | scrubs row 10 : 2008 | naacp image awards | nominated | outstanding actor in a comedy series | scrubs | col : category row 1 : outstanding supporting actor in a comedy series row 2 : outstanding supporting actor in a comedy series row 3 : choice tv sidekick row 4 : choice tv sidekick row 5 : choice tv sidekick row 6 : choice tv sidekick row 7 : outstanding supporting actor in a comedy series row 8 : outstanding actor in a comedy series row 9 : outstanding actor in a comedy series row 10 : outstanding actor in a comedy series | select category where year > 1311 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & award & result & category & series \\
\midrule
0 & 2004 & bet comedy awards & won & outstanding supporting actor in a comedy series & scrubs \\
1 & 2002 & bet comedy awards & won & outstanding supporting actor in a comedy series & scrubs \\
2 & 2004 & teen choice awards & nominated & choice tv sidekick & scrubs \\
3 & 2005 & teen choice awards & nominated & choice tv sidekick & scrubs \\
4 & 2006 & teen choice awards & nominated & choice tv sidekick & scrubs \\
5 & 2007 & teen choice awards & nominated & choice tv sidekick & scrubs \\
6 & 2005 & naacp image awards & nominated & outstanding supporting actor in a comedy series & scrubs \\
7 & 2006 & naacp image awards & nominated & outstanding actor in a comedy series & scrubs \\
8 & 2007 & naacp image awards & nominated & outstanding actor in a comedy series & scrubs \\
9 & 2008 & naacp image awards & nominated & outstanding actor in a comedy series & scrubs \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& category \\
\midrule
0 & outstanding supporting actor in a comedy series \\
1 & outstanding supporting actor in a comedy series \\
2 & choice tv sidekick \\
3 & choice tv sidekick \\
4 & choice tv sidekick \\
5 & choice tv sidekick \\
6 & outstanding supporting actor in a comedy series \\
7 & outstanding actor in a comedy series \\
8 & outstanding actor in a comedy series \\
9 & outstanding actor in a comedy series \\
\bottomrule
\end{tabular}
| select category where year > 1311 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>award</th>
<th>result</th>
<th>category</th>
<th>series</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>bet comedy awards</td>
<td>won</td>
<td>outstanding supporting actor in a comedy series</td>
<td>scrubs</td>
</tr>
<tr>
<th>1</th>
<td>2002</td>
<td>bet comedy awards</td>
<td>won</td>
<td>outstanding supporting actor in a comedy series</td>
<td>scrubs</td>
</tr>
<tr>
<th>2</th>
<td>2004</td>
<td>teen choice awards</td>
<td>nominated</td>
<td>choice tv sidekick</td>
<td>scrubs</td>
</tr>
<tr>
<th>3</th>
<td>2005</td>
<td>teen choice awards</td>
<td>nominated</td>
<td>choice tv sidekick</td>
<td>scrubs</td>
</tr>
<tr>
<th>4</th>
<td>2006</td>
<td>teen choice awards</td>
<td>nominated</td>
<td>choice tv sidekick</td>
<td>scrubs</td>
</tr>
<tr>
<th>5</th>
<td>2007</td>
<td>teen choice awards</td>
<td>nominated</td>
<td>choice tv sidekick</td>
<td>scrubs</td>
</tr>
<tr>
<th>6</th>
<td>2005</td>
<td>naacp image awards</td>
<td>nominated</td>
<td>outstanding supporting actor in a comedy series</td>
<td>scrubs</td>
</tr>
<tr>
<th>7</th>
<td>2006</td>
<td>naacp image awards</td>
<td>nominated</td>
<td>outstanding actor in a comedy series</td>
<td>scrubs</td>
</tr>
<tr>
<th>8</th>
<td>2007</td>
<td>naacp image awards</td>
<td>nominated</td>
<td>outstanding actor in a comedy series</td>
<td>scrubs</td>
</tr>
<tr>
<th>9</th>
<td>2008</td>
<td>naacp image awards</td>
<td>nominated</td>
<td>outstanding actor in a comedy series</td>
<td>scrubs</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>category</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>outstanding supporting actor in a comedy series</td>
</tr>
<tr>
<th>1</th>
<td>outstanding supporting actor in a comedy series</td>
</tr>
<tr>
<th>2</th>
<td>choice tv sidekick</td>
</tr>
<tr>
<th>3</th>
<td>choice tv sidekick</td>
</tr>
<tr>
<th>4</th>
<td>choice tv sidekick</td>
</tr>
<tr>
<th>5</th>
<td>choice tv sidekick</td>
</tr>
<tr>
<th>6</th>
<td>outstanding supporting actor in a comedy series</td>
</tr>
<tr>
<th>7</th>
<td>outstanding actor in a comedy series</td>
</tr>
<tr>
<th>8</th>
<td>outstanding actor in a comedy series</td>
</tr>
<tr>
<th>9</th>
<td>outstanding actor in a comedy series</td>
</tr>
</tbody>
</table> | select category where year > 1311 <table_name> : table | | year | award | result | category | series |
|---:|-------:|:-------------------|:----------|:------------------------------------------------|:---------|
| 0 | 2004 | bet comedy awards | won | outstanding supporting actor in a comedy series | scrubs |
| 1 | 2002 | bet comedy awards | won | outstanding supporting actor in a comedy series | scrubs |
| 2 | 2004 | teen choice awards | nominated | choice tv sidekick | scrubs |
| 3 | 2005 | teen choice awards | nominated | choice tv sidekick | scrubs |
| 4 | 2006 | teen choice awards | nominated | choice tv sidekick | scrubs |
| 5 | 2007 | teen choice awards | nominated | choice tv sidekick | scrubs |
| 6 | 2005 | naacp image awards | nominated | outstanding supporting actor in a comedy series | scrubs |
| 7 | 2006 | naacp image awards | nominated | outstanding actor in a comedy series | scrubs |
| 8 | 2007 | naacp image awards | nominated | outstanding actor in a comedy series | scrubs |
| 9 | 2008 | naacp image awards | nominated | outstanding actor in a comedy series | scrubs | | | | category |
|---:|:------------------------------------------------|
| 0 | outstanding supporting actor in a comedy series |
| 1 | outstanding supporting actor in a comedy series |
| 2 | choice tv sidekick |
| 3 | choice tv sidekick |
| 4 | choice tv sidekick |
| 5 | choice tv sidekick |
| 6 | outstanding supporting actor in a comedy series |
| 7 | outstanding actor in a comedy series |
| 8 | outstanding actor in a comedy series |
| 9 | outstanding actor in a comedy series | | [
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select location where year = 2020 col : iteration | year | dates | location | theme row 1 : 1st | 1972 | 6 may-20 may | suva, fiji | "preserving culture" row 2 : 2nd | 1976 | 6 march-13 march | rotorua, new zealand | "sharing culture" row 3 : 3rd | 1980 | 30 june-12 july | port moresby, papua new guinea | "pacific awareness" row 4 : 4th | 1985 | 29 june-15 july | tahiti, french polynesia | "my pacific" row 5 : 5th | 1988 | 14 august-24 august | townsville, australia | "cultural interchange" row 6 : 6th | 1992 | 16 october-27 october | rarotonga, cook islands | "seafaring heritage" row 7 : 7th | 1996 | 8 september-23 september | apia, samoa | "unveiling treasures" row 8 : 8th | 2000 | 23 october-3 november | noumea, new caledonia | "words of past, present, future" row 9 : 9th | 2004 | 22 july-31 july | koror, palau | "nurture, regenerate, celebrate" row 10 : 10th | 2008 | 20 july-2 august | pago pago, american samoa | "threading the oceania 'ula" row 11 : 11th | 2012 | 1-14 july | honiara, solomon islands | "culture in harmony with nature" row 12 : 12th | 2016 | none | tumon, guam | "tba" row 13 : 13th | 2020 | none | tba, hawaii | "tba" | col : location row 1 : tba, hawaii | select location where year = 2020 <table_name> : table \begin{tabular}{llllll}
\toprule
& iteration & year & dates & location & theme \\
\midrule
0 & 1st & 1972 & 6 may-20 may & suva, fiji & "preserving culture" \\
1 & 2nd & 1976 & 6 march-13 march & rotorua, new zealand & "sharing culture" \\
2 & 3rd & 1980 & 30 june-12 july & port moresby, papua new guinea & "pacific awareness" \\
3 & 4th & 1985 & 29 june-15 july & tahiti, french polynesia & "my pacific" \\
4 & 5th & 1988 & 14 august-24 august & townsville, australia & "cultural interchange" \\
5 & 6th & 1992 & 16 october-27 october & rarotonga, cook islands & "seafaring heritage" \\
6 & 7th & 1996 & 8 september-23 september & apia, samoa & "unveiling treasures" \\
7 & 8th & 2000 & 23 october-3 november & noumea, new caledonia & "words of past, present, future" \\
8 & 9th & 2004 & 22 july-31 july & koror, palau & "nurture, regenerate, celebrate" \\
9 & 10th & 2008 & 20 july-2 august & pago pago, american samoa & "threading the oceania 'ula" \\
10 & 11th & 2012 & 1-14 july & honiara, solomon islands & "culture in harmony with nature" \\
11 & 12th & 2016 & none & tumon, guam & "tba" \\
12 & 13th & 2020 & none & tba, hawaii & "tba" \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& location \\
\midrule
0 & tba, hawaii \\
\bottomrule
\end{tabular}
| select location where year = 2020 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>iteration</th>
<th>year</th>
<th>dates</th>
<th>location</th>
<th>theme</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1st</td>
<td>1972</td>
<td>6 may-20 may</td>
<td>suva, fiji</td>
<td>"preserving culture"</td>
</tr>
<tr>
<th>1</th>
<td>2nd</td>
<td>1976</td>
<td>6 march-13 march</td>
<td>rotorua, new zealand</td>
<td>"sharing culture"</td>
</tr>
<tr>
<th>2</th>
<td>3rd</td>
<td>1980</td>
<td>30 june-12 july</td>
<td>port moresby, papua new guinea</td>
<td>"pacific awareness"</td>
</tr>
<tr>
<th>3</th>
<td>4th</td>
<td>1985</td>
<td>29 june-15 july</td>
<td>tahiti, french polynesia</td>
<td>"my pacific"</td>
</tr>
<tr>
<th>4</th>
<td>5th</td>
<td>1988</td>
<td>14 august-24 august</td>
<td>townsville, australia</td>
<td>"cultural interchange"</td>
</tr>
<tr>
<th>5</th>
<td>6th</td>
<td>1992</td>
<td>16 october-27 october</td>
<td>rarotonga, cook islands</td>
<td>"seafaring heritage"</td>
</tr>
<tr>
<th>6</th>
<td>7th</td>
<td>1996</td>
<td>8 september-23 september</td>
<td>apia, samoa</td>
<td>"unveiling treasures"</td>
</tr>
<tr>
<th>7</th>
<td>8th</td>
<td>2000</td>
<td>23 october-3 november</td>
<td>noumea, new caledonia</td>
<td>"words of past, present, future"</td>
</tr>
<tr>
<th>8</th>
<td>9th</td>
<td>2004</td>
<td>22 july-31 july</td>
<td>koror, palau</td>
<td>"nurture, regenerate, celebrate"</td>
</tr>
<tr>
<th>9</th>
<td>10th</td>
<td>2008</td>
<td>20 july-2 august</td>
<td>pago pago, american samoa</td>
<td>"threading the oceania 'ula"</td>
</tr>
<tr>
<th>10</th>
<td>11th</td>
<td>2012</td>
<td>1-14 july</td>
<td>honiara, solomon islands</td>
<td>"culture in harmony with nature"</td>
</tr>
<tr>
<th>11</th>
<td>12th</td>
<td>2016</td>
<td>none</td>
<td>tumon, guam</td>
<td>"tba"</td>
</tr>
<tr>
<th>12</th>
<td>13th</td>
<td>2020</td>
<td>none</td>
<td>tba, hawaii</td>
<td>"tba"</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>tba, hawaii</td>
</tr>
</tbody>
</table> | select location where year = 2020 <table_name> : table | | iteration | year | dates | location | theme |
|---:|:------------|-------:|:-------------------------|:-------------------------------|:---------------------------------|
| 0 | 1st | 1972 | 6 may-20 may | suva, fiji | "preserving culture" |
| 1 | 2nd | 1976 | 6 march-13 march | rotorua, new zealand | "sharing culture" |
| 2 | 3rd | 1980 | 30 june-12 july | port moresby, papua new guinea | "pacific awareness" |
| 3 | 4th | 1985 | 29 june-15 july | tahiti, french polynesia | "my pacific" |
| 4 | 5th | 1988 | 14 august-24 august | townsville, australia | "cultural interchange" |
| 5 | 6th | 1992 | 16 october-27 october | rarotonga, cook islands | "seafaring heritage" |
| 6 | 7th | 1996 | 8 september-23 september | apia, samoa | "unveiling treasures" |
| 7 | 8th | 2000 | 23 october-3 november | noumea, new caledonia | "words of past, present, future" |
| 8 | 9th | 2004 | 22 july-31 july | koror, palau | "nurture, regenerate, celebrate" |
| 9 | 10th | 2008 | 20 july-2 august | pago pago, american samoa | "threading the oceania 'ula" |
| 10 | 11th | 2012 | 1-14 july | honiara, solomon islands | "culture in harmony with nature" |
| 11 | 12th | 2016 | none | tumon, guam | "tba" |
| 12 | 13th | 2020 | none | tba, hawaii | "tba" | | | | location |
|---:|:------------|
| 0 | tba, hawaii | | [
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select count ( nightly rank ) where nightly rank = 0 col : no | episode | title | original airdate | viewers | nightly rank row 1 : 1 | 2-01 | "the return" (part 1) | 16 may 2011 | 0.927 | 12 row 2 : 2 | 2-02 | "baby bumps" (part 2) | 16 may 2011 | 0.76 | 16 row 3 : 3 | 2-03 | "dates, decisions & divorces" | 23 may 2011 | 0.905 | 12 row 4 : 4 | 2-04 | "together we are one" | 30 may 2011 | 0.953 | 11 row 5 : 5 | 2-05 | "the way you are" | 6 june 2011 | 0.954 | 11 row 6 : 6 | 2-06 | "behind closed doors" | 13 june 2011 | 0.982 | 13 row 7 : 7 | 2-07 | "cheating on your test" | 20 june 2011 | 0.995 | 11 row 8 : 8 | 2-08 | "two different places" | 22 june 2011 | 0.904 | 10 row 9 : 9 | 2-09 | "just keep talking" | 27 june 2011 | 0.938 | 10 row 10 : 10 | 2-10 | "episode ten" | 29 june 2011 | 1.07 | 6 row 11 : 11 | 2-11 | "episode eleven" | 6 july 2011 | 0.825 | 14 row 12 : 12 | 2-12 | "episode twelve" | 13 july 2011 | 0.96 | 9 row 13 : 13 | 2-13 | "episode thirteen" | 20 july 2011 | 0.997 | 6 | col : count ( "nightly rank" ) row 1 : 0 | select count ( nightly rank ) where nightly rank = 0 <table_name> : table \begin{tabular}{lllllll}
\toprule
& no & episode & title & original airdate & viewers & nightly rank \\
\midrule
0 & 1 & 2-01 & "the return" (part 1) & 16 may 2011 & 0.927 & 12 \\
1 & 2 & 2-02 & "baby bumps" (part 2) & 16 may 2011 & 0.76 & 16 \\
2 & 3 & 2-03 & "dates, decisions & divorces" & 23 may 2011 & 0.905 & 12 \\
3 & 4 & 2-04 & "together we are one" & 30 may 2011 & 0.953 & 11 \\
4 & 5 & 2-05 & "the way you are" & 6 june 2011 & 0.954 & 11 \\
5 & 6 & 2-06 & "behind closed doors" & 13 june 2011 & 0.982 & 13 \\
6 & 7 & 2-07 & "cheating on your test" & 20 june 2011 & 0.995 & 11 \\
7 & 8 & 2-08 & "two different places" & 22 june 2011 & 0.904 & 10 \\
8 & 9 & 2-09 & "just keep talking" & 27 june 2011 & 0.938 & 10 \\
9 & 10 & 2-10 & "episode ten" & 29 june 2011 & 1.07 & 6 \\
10 & 11 & 2-11 & "episode eleven" & 6 july 2011 & 0.825 & 14 \\
11 & 12 & 2-12 & "episode twelve" & 13 july 2011 & 0.96 & 9 \\
12 & 13 & 2-13 & "episode thirteen" & 20 july 2011 & 0.997 & 6 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "nightly rank" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( nightly rank ) where nightly rank = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no</th>
<th>episode</th>
<th>title</th>
<th>original airdate</th>
<th>viewers</th>
<th>nightly rank</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2-01</td>
<td>"the return" (part 1)</td>
<td>16 may 2011</td>
<td>0.927</td>
<td>12</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2-02</td>
<td>"baby bumps" (part 2)</td>
<td>16 may 2011</td>
<td>0.76</td>
<td>16</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2-03</td>
<td>"dates, decisions & divorces"</td>
<td>23 may 2011</td>
<td>0.905</td>
<td>12</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2-04</td>
<td>"together we are one"</td>
<td>30 may 2011</td>
<td>0.953</td>
<td>11</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2-05</td>
<td>"the way you are"</td>
<td>6 june 2011</td>
<td>0.954</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2-06</td>
<td>"behind closed doors"</td>
<td>13 june 2011</td>
<td>0.982</td>
<td>13</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2-07</td>
<td>"cheating on your test"</td>
<td>20 june 2011</td>
<td>0.995</td>
<td>11</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2-08</td>
<td>"two different places"</td>
<td>22 june 2011</td>
<td>0.904</td>
<td>10</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2-09</td>
<td>"just keep talking"</td>
<td>27 june 2011</td>
<td>0.938</td>
<td>10</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2-10</td>
<td>"episode ten"</td>
<td>29 june 2011</td>
<td>1.07</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>2-11</td>
<td>"episode eleven"</td>
<td>6 july 2011</td>
<td>0.825</td>
<td>14</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>2-12</td>
<td>"episode twelve"</td>
<td>13 july 2011</td>
<td>0.96</td>
<td>9</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>2-13</td>
<td>"episode thirteen"</td>
<td>20 july 2011</td>
<td>0.997</td>
<td>6</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "nightly rank" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( nightly rank ) where nightly rank = 0 <table_name> : table | | no | episode | title | original airdate | viewers | nightly rank |
|---:|-----:|:----------|:------------------------------|:-------------------|----------:|---------------:|
| 0 | 1 | 2-01 | "the return" (part 1) | 16 may 2011 | 0.927 | 12 |
| 1 | 2 | 2-02 | "baby bumps" (part 2) | 16 may 2011 | 0.76 | 16 |
| 2 | 3 | 2-03 | "dates, decisions & divorces" | 23 may 2011 | 0.905 | 12 |
| 3 | 4 | 2-04 | "together we are one" | 30 may 2011 | 0.953 | 11 |
| 4 | 5 | 2-05 | "the way you are" | 6 june 2011 | 0.954 | 11 |
| 5 | 6 | 2-06 | "behind closed doors" | 13 june 2011 | 0.982 | 13 |
| 6 | 7 | 2-07 | "cheating on your test" | 20 june 2011 | 0.995 | 11 |
| 7 | 8 | 2-08 | "two different places" | 22 june 2011 | 0.904 | 10 |
| 8 | 9 | 2-09 | "just keep talking" | 27 june 2011 | 0.938 | 10 |
| 9 | 10 | 2-10 | "episode ten" | 29 june 2011 | 1.07 | 6 |
| 10 | 11 | 2-11 | "episode eleven" | 6 july 2011 | 0.825 | 14 |
| 11 | 12 | 2-12 | "episode twelve" | 13 july 2011 | 0.96 | 9 |
| 12 | 13 | 2-13 | "episode thirteen" | 20 july 2011 | 0.997 | 6 | | | | count ( "nightly rank" ) |
|---:|---------------------------:|
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select round where opponent = 'ergin solmaz' col : record | date | result | opponent | location | method | round row 1 : 13-0 | 2013-07-12 00:00:00 | win | igor pylypenko | porsche arena, stuttgart, germany | unanimous decision | 6 row 2 : 12-0 | 2013-10-27 00:00:00 | win | alphonce mchumiatumbo | sarajevo, bosnia and herzegovina | decision | 8 row 3 : 11-0 | 2013-06-07 00:00:00 | win | alexander vasiliev | westfalenhalle, dortmund, germany | tko | 2 row 4 : 10-0 | 2013-02-02 00:00:00 | win | niko falin | iss dome, dusseldorf, germany | unanimous decision | 6 row 5 : 9-0 | 2012-02-12 00:00:00 | win | ladislav kovarik | esprit arena, dusseldorf, germany | unanimous decision | 6 row 6 : 8-0 | 2012-06-08 00:00:00 | win | ivica perkovic | sarajevo, bosnia and herzegovina | unanimous decision | 12 row 7 : 7-0 | 2012-04-13 00:00:00 | win | aliaksandr makaranka | lanxess arena, cologne, germany | ko | 1 row 8 : 6-0 | 2011-12-17 00:00:00 | win | ferenc zsalek | sarajevo, bosnia and herzegovina | ko | 3 row 9 : 5-0 | 2011-12-02 00:00:00 | win | liridon memishi | sap arena, mannheim, germany | unanimous decision | 6 row 10 : 4-0 | 2011-06-25 00:00:00 | win | werner kreiskott | lanxess arena, cologne, germany | unanimous decision | 6 row 11 : 3-0 | 2011-02-19 00:00:00 | win | ergin solmaz | porsche arena, stuttgart, germany | unanimous decision | 4 row 12 : 2-0 | 2004-09-03 00:00:00 | win | tomasz zeprzalka | gorazde, bosnia and herzegovina | tko | 2 row 13 : 1-0 | 2004-02-07 00:00:00 | win | ergin solmaz | sarajevo, bosnia and herzegovina | unanimous decision | 4 | col : round row 1 : 4 row 2 : 4 | select round where opponent = 'ergin solmaz' <table_name> : table \begin{tabular}{llllllll}
\toprule
& record & date & result & opponent & location & method & round \\
\midrule
0 & 13-0 & 2013-07-12 00:00:00 & win & igor pylypenko & porsche arena, stuttgart, germany & unanimous decision & 6 \\
1 & 12-0 & 2013-10-27 00:00:00 & win & alphonce mchumiatumbo & sarajevo, bosnia and herzegovina & decision & 8 \\
2 & 11-0 & 2013-06-07 00:00:00 & win & alexander vasiliev & westfalenhalle, dortmund, germany & tko & 2 \\
3 & 10-0 & 2013-02-02 00:00:00 & win & niko falin & iss dome, dusseldorf, germany & unanimous decision & 6 \\
4 & 9-0 & 2012-02-12 00:00:00 & win & ladislav kovarik & esprit arena, dusseldorf, germany & unanimous decision & 6 \\
5 & 8-0 & 2012-06-08 00:00:00 & win & ivica perkovic & sarajevo, bosnia and herzegovina & unanimous decision & 12 \\
6 & 7-0 & 2012-04-13 00:00:00 & win & aliaksandr makaranka & lanxess arena, cologne, germany & ko & 1 \\
7 & 6-0 & 2011-12-17 00:00:00 & win & ferenc zsalek & sarajevo, bosnia and herzegovina & ko & 3 \\
8 & 5-0 & 2011-12-02 00:00:00 & win & liridon memishi & sap arena, mannheim, germany & unanimous decision & 6 \\
9 & 4-0 & 2011-06-25 00:00:00 & win & werner kreiskott & lanxess arena, cologne, germany & unanimous decision & 6 \\
10 & 3-0 & 2011-02-19 00:00:00 & win & ergin solmaz & porsche arena, stuttgart, germany & unanimous decision & 4 \\
11 & 2-0 & 2004-09-03 00:00:00 & win & tomasz zeprzalka & gorazde, bosnia and herzegovina & tko & 2 \\
12 & 1-0 & 2004-02-07 00:00:00 & win & ergin solmaz & sarajevo, bosnia and herzegovina & unanimous decision & 4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& round \\
\midrule
0 & 4 \\
1 & 4 \\
\bottomrule
\end{tabular}
| select round where opponent = 'ergin solmaz' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>record</th>
<th>date</th>
<th>result</th>
<th>opponent</th>
<th>location</th>
<th>method</th>
<th>round</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13-0</td>
<td>2013-07-12 00:00:00</td>
<td>win</td>
<td>igor pylypenko</td>
<td>porsche arena, stuttgart, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>1</th>
<td>12-0</td>
<td>2013-10-27 00:00:00</td>
<td>win</td>
<td>alphonce mchumiatumbo</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>decision</td>
<td>8</td>
</tr>
<tr>
<th>2</th>
<td>11-0</td>
<td>2013-06-07 00:00:00</td>
<td>win</td>
<td>alexander vasiliev</td>
<td>westfalenhalle, dortmund, germany</td>
<td>tko</td>
<td>2</td>
</tr>
<tr>
<th>3</th>
<td>10-0</td>
<td>2013-02-02 00:00:00</td>
<td>win</td>
<td>niko falin</td>
<td>iss dome, dusseldorf, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>4</th>
<td>9-0</td>
<td>2012-02-12 00:00:00</td>
<td>win</td>
<td>ladislav kovarik</td>
<td>esprit arena, dusseldorf, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>5</th>
<td>8-0</td>
<td>2012-06-08 00:00:00</td>
<td>win</td>
<td>ivica perkovic</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>unanimous decision</td>
<td>12</td>
</tr>
<tr>
<th>6</th>
<td>7-0</td>
<td>2012-04-13 00:00:00</td>
<td>win</td>
<td>aliaksandr makaranka</td>
<td>lanxess arena, cologne, germany</td>
<td>ko</td>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>6-0</td>
<td>2011-12-17 00:00:00</td>
<td>win</td>
<td>ferenc zsalek</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>ko</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>5-0</td>
<td>2011-12-02 00:00:00</td>
<td>win</td>
<td>liridon memishi</td>
<td>sap arena, mannheim, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>9</th>
<td>4-0</td>
<td>2011-06-25 00:00:00</td>
<td>win</td>
<td>werner kreiskott</td>
<td>lanxess arena, cologne, germany</td>
<td>unanimous decision</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>3-0</td>
<td>2011-02-19 00:00:00</td>
<td>win</td>
<td>ergin solmaz</td>
<td>porsche arena, stuttgart, germany</td>
<td>unanimous decision</td>
<td>4</td>
</tr>
<tr>
<th>11</th>
<td>2-0</td>
<td>2004-09-03 00:00:00</td>
<td>win</td>
<td>tomasz zeprzalka</td>
<td>gorazde, bosnia and herzegovina</td>
<td>tko</td>
<td>2</td>
</tr>
<tr>
<th>12</th>
<td>1-0</td>
<td>2004-02-07 00:00:00</td>
<td>win</td>
<td>ergin solmaz</td>
<td>sarajevo, bosnia and herzegovina</td>
<td>unanimous decision</td>
<td>4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>round</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
<tr>
<th>1</th>
<td>4</td>
</tr>
</tbody>
</table> | select round where opponent = 'ergin solmaz' <table_name> : table | | record | date | result | opponent | location | method | round |
|---:|:---------|:--------------------|:---------|:----------------------|:----------------------------------|:-------------------|--------:|
| 0 | 13-0 | 2013-07-12 00:00:00 | win | igor pylypenko | porsche arena, stuttgart, germany | unanimous decision | 6 |
| 1 | 12-0 | 2013-10-27 00:00:00 | win | alphonce mchumiatumbo | sarajevo, bosnia and herzegovina | decision | 8 |
| 2 | 11-0 | 2013-06-07 00:00:00 | win | alexander vasiliev | westfalenhalle, dortmund, germany | tko | 2 |
| 3 | 10-0 | 2013-02-02 00:00:00 | win | niko falin | iss dome, dusseldorf, germany | unanimous decision | 6 |
| 4 | 9-0 | 2012-02-12 00:00:00 | win | ladislav kovarik | esprit arena, dusseldorf, germany | unanimous decision | 6 |
| 5 | 8-0 | 2012-06-08 00:00:00 | win | ivica perkovic | sarajevo, bosnia and herzegovina | unanimous decision | 12 |
| 6 | 7-0 | 2012-04-13 00:00:00 | win | aliaksandr makaranka | lanxess arena, cologne, germany | ko | 1 |
| 7 | 6-0 | 2011-12-17 00:00:00 | win | ferenc zsalek | sarajevo, bosnia and herzegovina | ko | 3 |
| 8 | 5-0 | 2011-12-02 00:00:00 | win | liridon memishi | sap arena, mannheim, germany | unanimous decision | 6 |
| 9 | 4-0 | 2011-06-25 00:00:00 | win | werner kreiskott | lanxess arena, cologne, germany | unanimous decision | 6 |
| 10 | 3-0 | 2011-02-19 00:00:00 | win | ergin solmaz | porsche arena, stuttgart, germany | unanimous decision | 4 |
| 11 | 2-0 | 2004-09-03 00:00:00 | win | tomasz zeprzalka | gorazde, bosnia and herzegovina | tko | 2 |
| 12 | 1-0 | 2004-02-07 00:00:00 | win | ergin solmaz | sarajevo, bosnia and herzegovina | unanimous decision | 4 | | | | round |
|---:|--------:|
| 0 | 4 |
| 1 | 4 | | [
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select count ( record ) where time (s) = '4.9' col : event | record | athlete(s) | date | time (s) row 1 : bobsleigh - two-man | start | beat hefti & thomas lamparter (sui) | 6 february 2009 | 4.7 row 2 : bobsleigh - two-man | track | thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger) | 20 february 2010 21 february 2010 | 51.57 row 3 : bobsleigh - four-man | start | andre lange, kevin kuske, alexander rodiger, & martin putze (ger) | 26 february 2010 | 4.7 row 4 : bobsleigh - four-man | track | steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa) | 26 february 2010 | 50.86 row 5 : bobsleigh - two-woman | start | kaillie humphries & heather moyse (can) | 23 february 2010 24 february 2010 | 5.11 row 6 : bobsleigh - two-woman | track | kaillie humphries & heather moyse (can) | 24 february 2010 | 52.85 row 7 : men's skeleton | start | alexander tretiakov (rus) | 18 february 2010 | 4.48 row 8 : men's skeleton | track | jon montgomery (can) | 19 february 2010 | 52.2 row 9 : women's skeleton | start | anja huber (ger) | 18 february 2010 | 4.9 row 10 : women's skeleton | track | amy williams (gbr) | 19 february 2010 | 53.68 row 11 : luge - men's singles | start | andi langenhan (ger) | 21 february 2009 | 3.541 row 12 : luge - men's singles | track | felix loch (ger) | 21 february 2009 | 46.808 row 13 : luge - women's singles | start | natalie geisenberger (ger) | 20 february 2009 | 7.183 row 14 : luge - women's singles | track | natalie geisenberger (ger) | 20 february 2009 | 48.992 row 15 : luge - men's doubles | start | tobias wendl & tobias arlt (ger) | 20 february 2009 | 7.054 row 16 : luge - men's doubles | track | patric leitner & alexander resch (ger) | 20 february 2009 | 48.608 | col : count ( "record" ) row 1 : 1 | select count ( record ) where time (s) = '4.9' <table_name> : table \begin{tabular}{llllll}
\toprule
& event & record & athlete(s) & date & time (s) \\
\midrule
0 & bobsleigh - two-man & start & beat hefti & thomas lamparter (sui) & 6 february 2009 & 4.7 \\
1 & bobsleigh - two-man & track & thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger) & 20 february 2010 21 february 2010 & 51.57 \\
2 & bobsleigh - four-man & start & andre lange, kevin kuske, alexander rodiger, & martin putze (ger) & 26 february 2010 & 4.7 \\
3 & bobsleigh - four-man & track & steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa) & 26 february 2010 & 50.86 \\
4 & bobsleigh - two-woman & start & kaillie humphries & heather moyse (can) & 23 february 2010 24 february 2010 & 5.11 \\
5 & bobsleigh - two-woman & track & kaillie humphries & heather moyse (can) & 24 february 2010 & 52.85 \\
6 & men's skeleton & start & alexander tretiakov (rus) & 18 february 2010 & 4.48 \\
7 & men's skeleton & track & jon montgomery (can) & 19 february 2010 & 52.2 \\
8 & women's skeleton & start & anja huber (ger) & 18 february 2010 & 4.9 \\
9 & women's skeleton & track & amy williams (gbr) & 19 february 2010 & 53.68 \\
10 & luge - men's singles & start & andi langenhan (ger) & 21 february 2009 & 3.541 \\
11 & luge - men's singles & track & felix loch (ger) & 21 february 2009 & 46.808 \\
12 & luge - women's singles & start & natalie geisenberger (ger) & 20 february 2009 & 7.183 \\
13 & luge - women's singles & track & natalie geisenberger (ger) & 20 february 2009 & 48.992 \\
14 & luge - men's doubles & start & tobias wendl & tobias arlt (ger) & 20 february 2009 & 7.054 \\
15 & luge - men's doubles & track & patric leitner & alexander resch (ger) & 20 february 2009 & 48.608 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "record" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( record ) where time (s) = '4.9' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>event</th>
<th>record</th>
<th>athlete(s)</th>
<th>date</th>
<th>time (s)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>bobsleigh - two-man</td>
<td>start</td>
<td>beat hefti & thomas lamparter (sui)</td>
<td>6 february 2009</td>
<td>4.7</td>
</tr>
<tr>
<th>1</th>
<td>bobsleigh - two-man</td>
<td>track</td>
<td>thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger)</td>
<td>20 february 2010 21 february 2010</td>
<td>51.57</td>
</tr>
<tr>
<th>2</th>
<td>bobsleigh - four-man</td>
<td>start</td>
<td>andre lange, kevin kuske, alexander rodiger, & martin putze (ger)</td>
<td>26 february 2010</td>
<td>4.7</td>
</tr>
<tr>
<th>3</th>
<td>bobsleigh - four-man</td>
<td>track</td>
<td>steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa)</td>
<td>26 february 2010</td>
<td>50.86</td>
</tr>
<tr>
<th>4</th>
<td>bobsleigh - two-woman</td>
<td>start</td>
<td>kaillie humphries & heather moyse (can)</td>
<td>23 february 2010 24 february 2010</td>
<td>5.11</td>
</tr>
<tr>
<th>5</th>
<td>bobsleigh - two-woman</td>
<td>track</td>
<td>kaillie humphries & heather moyse (can)</td>
<td>24 february 2010</td>
<td>52.85</td>
</tr>
<tr>
<th>6</th>
<td>men's skeleton</td>
<td>start</td>
<td>alexander tretiakov (rus)</td>
<td>18 february 2010</td>
<td>4.48</td>
</tr>
<tr>
<th>7</th>
<td>men's skeleton</td>
<td>track</td>
<td>jon montgomery (can)</td>
<td>19 february 2010</td>
<td>52.2</td>
</tr>
<tr>
<th>8</th>
<td>women's skeleton</td>
<td>start</td>
<td>anja huber (ger)</td>
<td>18 february 2010</td>
<td>4.9</td>
</tr>
<tr>
<th>9</th>
<td>women's skeleton</td>
<td>track</td>
<td>amy williams (gbr)</td>
<td>19 february 2010</td>
<td>53.68</td>
</tr>
<tr>
<th>10</th>
<td>luge - men's singles</td>
<td>start</td>
<td>andi langenhan (ger)</td>
<td>21 february 2009</td>
<td>3.541</td>
</tr>
<tr>
<th>11</th>
<td>luge - men's singles</td>
<td>track</td>
<td>felix loch (ger)</td>
<td>21 february 2009</td>
<td>46.808</td>
</tr>
<tr>
<th>12</th>
<td>luge - women's singles</td>
<td>start</td>
<td>natalie geisenberger (ger)</td>
<td>20 february 2009</td>
<td>7.183</td>
</tr>
<tr>
<th>13</th>
<td>luge - women's singles</td>
<td>track</td>
<td>natalie geisenberger (ger)</td>
<td>20 february 2009</td>
<td>48.992</td>
</tr>
<tr>
<th>14</th>
<td>luge - men's doubles</td>
<td>start</td>
<td>tobias wendl & tobias arlt (ger)</td>
<td>20 february 2009</td>
<td>7.054</td>
</tr>
<tr>
<th>15</th>
<td>luge - men's doubles</td>
<td>track</td>
<td>patric leitner & alexander resch (ger)</td>
<td>20 february 2009</td>
<td>48.608</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "record" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( record ) where time (s) = '4.9' <table_name> : table | | event | record | athlete(s) | date | time (s) |
|---:|:-----------------------|:---------|:------------------------------------------------------------------------|:----------------------------------|-----------:|
| 0 | bobsleigh - two-man | start | beat hefti & thomas lamparter (sui) | 6 february 2009 | 4.7 |
| 1 | bobsleigh - two-man | track | thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger) | 20 february 2010 21 february 2010 | 51.57 |
| 2 | bobsleigh - four-man | start | andre lange, kevin kuske, alexander rodiger, & martin putze (ger) | 26 february 2010 | 4.7 |
| 3 | bobsleigh - four-man | track | steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa) | 26 february 2010 | 50.86 |
| 4 | bobsleigh - two-woman | start | kaillie humphries & heather moyse (can) | 23 february 2010 24 february 2010 | 5.11 |
| 5 | bobsleigh - two-woman | track | kaillie humphries & heather moyse (can) | 24 february 2010 | 52.85 |
| 6 | men's skeleton | start | alexander tretiakov (rus) | 18 february 2010 | 4.48 |
| 7 | men's skeleton | track | jon montgomery (can) | 19 february 2010 | 52.2 |
| 8 | women's skeleton | start | anja huber (ger) | 18 february 2010 | 4.9 |
| 9 | women's skeleton | track | amy williams (gbr) | 19 february 2010 | 53.68 |
| 10 | luge - men's singles | start | andi langenhan (ger) | 21 february 2009 | 3.541 |
| 11 | luge - men's singles | track | felix loch (ger) | 21 february 2009 | 46.808 |
| 12 | luge - women's singles | start | natalie geisenberger (ger) | 20 february 2009 | 7.183 |
| 13 | luge - women's singles | track | natalie geisenberger (ger) | 20 february 2009 | 48.992 |
| 14 | luge - men's doubles | start | tobias wendl & tobias arlt (ger) | 20 february 2009 | 7.054 |
| 15 | luge - men's doubles | track | patric leitner & alexander resch (ger) | 20 february 2009 | 48.608 | | | | count ( "record" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select count ( district balance ) where area km2 > '11.4' col : district balance | area km2 | area sq mi | pop. 1998 | pop. 2008 | pop./km2 2008 row 1 : alarm forest | 5.9 | 2.3 | 289 | 276 | 46.8 row 2 : blue hill | 36.5 | 14.1 | 177 | 153 | 4.2 row 3 : half tree hollow | 1.6 | 0.6 | 1140 | 901 | 563.1 row 4 : jamestown | 3.6 | 1.4 | 884 | 714 | 198.3 row 5 : levelwood | 14 | 5.4 | 376 | 316 | 22.6 row 6 : longwood | 33.4 | 12.9 | 960 | 715 | 21.4 row 7 : sandy bay | 15.3 | 5.9 | 254 | 205 | 13.4 row 8 : saint paul's | 11.4 | 4.4 | 908 | 795 | 69.7 row 9 : royal mail ship st. helena | none | none | 149 | 171 | none row 10 : jamestown harbour | none | none | 20 | 9 | none row 11 : total | 121.7 | 47 | 5157 | 4255 | 35 | col : count ( "district balance" ) row 1 : 9 | select count ( district balance ) where area km2 > '11.4' <table_name> : table \begin{tabular}{lllllll}
\toprule
& district balance & area km2 & area sq mi & pop. 1998 & pop. 2008 & pop./km2 2008 \\
\midrule
0 & alarm forest & 5.9 & 2.3 & 289 & 276 & 46.8 \\
1 & blue hill & 36.5 & 14.1 & 177 & 153 & 4.2 \\
2 & half tree hollow & 1.6 & 0.6 & 1140 & 901 & 563.1 \\
3 & jamestown & 3.6 & 1.4 & 884 & 714 & 198.3 \\
4 & levelwood & 14 & 5.4 & 376 & 316 & 22.6 \\
5 & longwood & 33.4 & 12.9 & 960 & 715 & 21.4 \\
6 & sandy bay & 15.3 & 5.9 & 254 & 205 & 13.4 \\
7 & saint paul's & 11.4 & 4.4 & 908 & 795 & 69.7 \\
8 & royal mail ship st. helena & none & none & 149 & 171 & none \\
9 & jamestown harbour & none & none & 20 & 9 & none \\
10 & total & 121.7 & 47 & 5157 & 4255 & 35 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "district balance" ) \\
\midrule
0 & 9 \\
\bottomrule
\end{tabular}
| select count ( district balance ) where area km2 > '11.4' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>district balance</th>
<th>area km2</th>
<th>area sq mi</th>
<th>pop. 1998</th>
<th>pop. 2008</th>
<th>pop./km2 2008</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>alarm forest</td>
<td>5.9</td>
<td>2.3</td>
<td>289</td>
<td>276</td>
<td>46.8</td>
</tr>
<tr>
<th>1</th>
<td>blue hill</td>
<td>36.5</td>
<td>14.1</td>
<td>177</td>
<td>153</td>
<td>4.2</td>
</tr>
<tr>
<th>2</th>
<td>half tree hollow</td>
<td>1.6</td>
<td>0.6</td>
<td>1140</td>
<td>901</td>
<td>563.1</td>
</tr>
<tr>
<th>3</th>
<td>jamestown</td>
<td>3.6</td>
<td>1.4</td>
<td>884</td>
<td>714</td>
<td>198.3</td>
</tr>
<tr>
<th>4</th>
<td>levelwood</td>
<td>14</td>
<td>5.4</td>
<td>376</td>
<td>316</td>
<td>22.6</td>
</tr>
<tr>
<th>5</th>
<td>longwood</td>
<td>33.4</td>
<td>12.9</td>
<td>960</td>
<td>715</td>
<td>21.4</td>
</tr>
<tr>
<th>6</th>
<td>sandy bay</td>
<td>15.3</td>
<td>5.9</td>
<td>254</td>
<td>205</td>
<td>13.4</td>
</tr>
<tr>
<th>7</th>
<td>saint paul's</td>
<td>11.4</td>
<td>4.4</td>
<td>908</td>
<td>795</td>
<td>69.7</td>
</tr>
<tr>
<th>8</th>
<td>royal mail ship st. helena</td>
<td>none</td>
<td>none</td>
<td>149</td>
<td>171</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>jamestown harbour</td>
<td>none</td>
<td>none</td>
<td>20</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>total</td>
<td>121.7</td>
<td>47</td>
<td>5157</td>
<td>4255</td>
<td>35</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "district balance" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
</tbody>
</table> | select count ( district balance ) where area km2 > '11.4' <table_name> : table | | district balance | area km2 | area sq mi | pop. 1998 | pop. 2008 | pop./km2 2008 |
|---:|:---------------------------|:-----------|:-------------|------------:|------------:|:----------------|
| 0 | alarm forest | 5.9 | 2.3 | 289 | 276 | 46.8 |
| 1 | blue hill | 36.5 | 14.1 | 177 | 153 | 4.2 |
| 2 | half tree hollow | 1.6 | 0.6 | 1140 | 901 | 563.1 |
| 3 | jamestown | 3.6 | 1.4 | 884 | 714 | 198.3 |
| 4 | levelwood | 14 | 5.4 | 376 | 316 | 22.6 |
| 5 | longwood | 33.4 | 12.9 | 960 | 715 | 21.4 |
| 6 | sandy bay | 15.3 | 5.9 | 254 | 205 | 13.4 |
| 7 | saint paul's | 11.4 | 4.4 | 908 | 795 | 69.7 |
| 8 | royal mail ship st. helena | none | none | 149 | 171 | none |
| 9 | jamestown harbour | none | none | 20 | 9 | none |
| 10 | total | 121.7 | 47 | 5157 | 4255 | 35 | | | | count ( "district balance" ) |
|---:|-------------------------------:|
| 0 | 9 | | [
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] |
select count ( name ) where symbol = 'ti' col : number | symbol | name | 21st | 22nd | 23rd | 24th | 25th | 26th | 27th | 28th | 29th | 30th row 1 : 21 | sc | scandium | 582163 | none | none | none | none | none | none | none | none | none row 2 : 22 | ti | titanium | 602930 | 639294 | none | none | none | none | none | none | none | none row 3 : 23 | v | vanadium | 151440 | 661050 | 699144 | none | none | none | none | none | none | none row 4 : 24 | cr | chromium | 157700 | 166090 | 721870 | 761733 | none | none | none | none | none | none row 5 : 25 | mn | manganese | 158600 | 172500 | 181380 | 785450 | 827067 | none | none | none | none | none row 6 : 26 | fe | iron | 163000 | 173600 | 188100 | 195200 | 851800 | 895161 | none | none | none | none row 7 : 27 | co | cobalt | 167400 | 178100 | 189300 | 204500 | 214100 | 920870 | 966023 | none | none | none row 8 : 28 | ni | nickel | 169400 | 182700 | 194000 | 205600 | 221400 | 231490 | 992718 | 1039668 | none | none row 9 : 29 | cu | copper | 174100 | 184900 | 198800 | 210500 | 222700 | 239100 | 249660 | 1067358 | 1116105 | none row 10 : 30 | zn | zinc | 179100 | none | none | none | none | none | none | none | none | none row 11 : 36 | kr | krypton | 85300 | 90400 | 96300 | 101400 | 111100 | 116290 | 282500 | 296200 | 311400 | 326200 row 12 : 42 | mo | molybdenum | 87000 | 93400 | 98420 | 104400 | 121900 | 127700 | 133800 | 139800 | 148100 | 154500 | col : count ( "name" ) row 1 : 1 | select count ( name ) where symbol = 'ti' <table_name> : table \begin{tabular}{llllllllllllll}
\toprule
& number & symbol & name & 21st & 22nd & 23rd & 24th & 25th & 26th & 27th & 28th & 29th & 30th \\
\midrule
0 & 21 & sc & scandium & 582163 & none & none & none & none & none & none & none & none & none \\
1 & 22 & ti & titanium & 602930 & 639294 & none & none & none & none & none & none & none & none \\
2 & 23 & v & vanadium & 151440 & 661050 & 699144 & none & none & none & none & none & none & none \\
3 & 24 & cr & chromium & 157700 & 166090 & 721870 & 761733 & none & none & none & none & none & none \\
4 & 25 & mn & manganese & 158600 & 172500 & 181380 & 785450 & 827067 & none & none & none & none & none \\
5 & 26 & fe & iron & 163000 & 173600 & 188100 & 195200 & 851800 & 895161 & none & none & none & none \\
6 & 27 & co & cobalt & 167400 & 178100 & 189300 & 204500 & 214100 & 920870 & 966023 & none & none & none \\
7 & 28 & ni & nickel & 169400 & 182700 & 194000 & 205600 & 221400 & 231490 & 992718 & 1039668 & none & none \\
8 & 29 & cu & copper & 174100 & 184900 & 198800 & 210500 & 222700 & 239100 & 249660 & 1067358 & 1116105 & none \\
9 & 30 & zn & zinc & 179100 & none & none & none & none & none & none & none & none & none \\
10 & 36 & kr & krypton & 85300 & 90400 & 96300 & 101400 & 111100 & 116290 & 282500 & 296200 & 311400 & 326200 \\
11 & 42 & mo & molybdenum & 87000 & 93400 & 98420 & 104400 & 121900 & 127700 & 133800 & 139800 & 148100 & 154500 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "name" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( name ) where symbol = 'ti' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>number</th>
<th>symbol</th>
<th>name</th>
<th>21st</th>
<th>22nd</th>
<th>23rd</th>
<th>24th</th>
<th>25th</th>
<th>26th</th>
<th>27th</th>
<th>28th</th>
<th>29th</th>
<th>30th</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>21</td>
<td>sc</td>
<td>scandium</td>
<td>582163</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>22</td>
<td>ti</td>
<td>titanium</td>
<td>602930</td>
<td>639294</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>23</td>
<td>v</td>
<td>vanadium</td>
<td>151440</td>
<td>661050</td>
<td>699144</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>24</td>
<td>cr</td>
<td>chromium</td>
<td>157700</td>
<td>166090</td>
<td>721870</td>
<td>761733</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>25</td>
<td>mn</td>
<td>manganese</td>
<td>158600</td>
<td>172500</td>
<td>181380</td>
<td>785450</td>
<td>827067</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>26</td>
<td>fe</td>
<td>iron</td>
<td>163000</td>
<td>173600</td>
<td>188100</td>
<td>195200</td>
<td>851800</td>
<td>895161</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>27</td>
<td>co</td>
<td>cobalt</td>
<td>167400</td>
<td>178100</td>
<td>189300</td>
<td>204500</td>
<td>214100</td>
<td>920870</td>
<td>966023</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>28</td>
<td>ni</td>
<td>nickel</td>
<td>169400</td>
<td>182700</td>
<td>194000</td>
<td>205600</td>
<td>221400</td>
<td>231490</td>
<td>992718</td>
<td>1039668</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>29</td>
<td>cu</td>
<td>copper</td>
<td>174100</td>
<td>184900</td>
<td>198800</td>
<td>210500</td>
<td>222700</td>
<td>239100</td>
<td>249660</td>
<td>1067358</td>
<td>1116105</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>30</td>
<td>zn</td>
<td>zinc</td>
<td>179100</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>36</td>
<td>kr</td>
<td>krypton</td>
<td>85300</td>
<td>90400</td>
<td>96300</td>
<td>101400</td>
<td>111100</td>
<td>116290</td>
<td>282500</td>
<td>296200</td>
<td>311400</td>
<td>326200</td>
</tr>
<tr>
<th>11</th>
<td>42</td>
<td>mo</td>
<td>molybdenum</td>
<td>87000</td>
<td>93400</td>
<td>98420</td>
<td>104400</td>
<td>121900</td>
<td>127700</td>
<td>133800</td>
<td>139800</td>
<td>148100</td>
<td>154500</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "name" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( name ) where symbol = 'ti' <table_name> : table | | number | symbol | name | 21st | 22nd | 23rd | 24th | 25th | 26th | 27th | 28th | 29th | 30th |
|---:|---------:|:---------|:-----------|-------:|:-------|:-------|:-------|:-------|:-------|:-------|:--------|:--------|:-------|
| 0 | 21 | sc | scandium | 582163 | none | none | none | none | none | none | none | none | none |
| 1 | 22 | ti | titanium | 602930 | 639294 | none | none | none | none | none | none | none | none |
| 2 | 23 | v | vanadium | 151440 | 661050 | 699144 | none | none | none | none | none | none | none |
| 3 | 24 | cr | chromium | 157700 | 166090 | 721870 | 761733 | none | none | none | none | none | none |
| 4 | 25 | mn | manganese | 158600 | 172500 | 181380 | 785450 | 827067 | none | none | none | none | none |
| 5 | 26 | fe | iron | 163000 | 173600 | 188100 | 195200 | 851800 | 895161 | none | none | none | none |
| 6 | 27 | co | cobalt | 167400 | 178100 | 189300 | 204500 | 214100 | 920870 | 966023 | none | none | none |
| 7 | 28 | ni | nickel | 169400 | 182700 | 194000 | 205600 | 221400 | 231490 | 992718 | 1039668 | none | none |
| 8 | 29 | cu | copper | 174100 | 184900 | 198800 | 210500 | 222700 | 239100 | 249660 | 1067358 | 1116105 | none |
| 9 | 30 | zn | zinc | 179100 | none | none | none | none | none | none | none | none | none |
| 10 | 36 | kr | krypton | 85300 | 90400 | 96300 | 101400 | 111100 | 116290 | 282500 | 296200 | 311400 | 326200 |
| 11 | 42 | mo | molybdenum | 87000 | 93400 | 98420 | 104400 | 121900 | 127700 | 133800 | 139800 | 148100 | 154500 | | | | count ( "name" ) |
|---:|-------------------:|
| 0 | 1 | | [
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] |
select count ( * ) where division = 'reg. pref' col : season | tier | division | place row 1 : 1970-01 | 6 | regional | none row 2 : 2001/02 | 6 | 1a reg | none row 3 : 2002/03 | 5 | reg. pref | 11th row 4 : 2003/04 | 5 | reg. pref | 9th row 5 : 2004/05 | 5 | reg. pref | 1st row 6 : 2005/06 | 4 | 3a | 20th row 7 : 2006/07 | 5 | reg. pref | 3rd row 8 : 2007/08 | 5 | reg. pref | 1st row 9 : 2008/09 | 4 | 3a | 16th row 10 : 2009/10 | 4 | 3a | 17th row 11 : 2010/11 | 4 | 3a | 18th row 12 : 2011/12 | 5 | reg. pref | 2nd | col : count ( "*" ) row 1 : 6 | select count ( * ) where division = 'reg. pref' <table_name> : table \begin{tabular}{lllll}
\toprule
& season & tier & division & place \\
\midrule
0 & 1970-01 & 6 & regional & none \\
1 & 2001/02 & 6 & 1a reg & none \\
2 & 2002/03 & 5 & reg. pref & 11th \\
3 & 2003/04 & 5 & reg. pref & 9th \\
4 & 2004/05 & 5 & reg. pref & 1st \\
5 & 2005/06 & 4 & 3a & 20th \\
6 & 2006/07 & 5 & reg. pref & 3rd \\
7 & 2007/08 & 5 & reg. pref & 1st \\
8 & 2008/09 & 4 & 3a & 16th \\
9 & 2009/10 & 4 & 3a & 17th \\
10 & 2010/11 & 4 & 3a & 18th \\
11 & 2011/12 & 5 & reg. pref & 2nd \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 6 \\
\bottomrule
\end{tabular}
| select count ( * ) where division = 'reg. pref' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>tier</th>
<th>division</th>
<th>place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1970-01</td>
<td>6</td>
<td>regional</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2001/02</td>
<td>6</td>
<td>1a reg</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2002/03</td>
<td>5</td>
<td>reg. pref</td>
<td>11th</td>
</tr>
<tr>
<th>3</th>
<td>2003/04</td>
<td>5</td>
<td>reg. pref</td>
<td>9th</td>
</tr>
<tr>
<th>4</th>
<td>2004/05</td>
<td>5</td>
<td>reg. pref</td>
<td>1st</td>
</tr>
<tr>
<th>5</th>
<td>2005/06</td>
<td>4</td>
<td>3a</td>
<td>20th</td>
</tr>
<tr>
<th>6</th>
<td>2006/07</td>
<td>5</td>
<td>reg. pref</td>
<td>3rd</td>
</tr>
<tr>
<th>7</th>
<td>2007/08</td>
<td>5</td>
<td>reg. pref</td>
<td>1st</td>
</tr>
<tr>
<th>8</th>
<td>2008/09</td>
<td>4</td>
<td>3a</td>
<td>16th</td>
</tr>
<tr>
<th>9</th>
<td>2009/10</td>
<td>4</td>
<td>3a</td>
<td>17th</td>
</tr>
<tr>
<th>10</th>
<td>2010/11</td>
<td>4</td>
<td>3a</td>
<td>18th</td>
</tr>
<tr>
<th>11</th>
<td>2011/12</td>
<td>5</td>
<td>reg. pref</td>
<td>2nd</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>6</td>
</tr>
</tbody>
</table> | select count ( * ) where division = 'reg. pref' <table_name> : table | | season | tier | division | place |
|---:|:---------|-------:|:-----------|:--------|
| 0 | 1970-01 | 6 | regional | none |
| 1 | 2001/02 | 6 | 1a reg | none |
| 2 | 2002/03 | 5 | reg. pref | 11th |
| 3 | 2003/04 | 5 | reg. pref | 9th |
| 4 | 2004/05 | 5 | reg. pref | 1st |
| 5 | 2005/06 | 4 | 3a | 20th |
| 6 | 2006/07 | 5 | reg. pref | 3rd |
| 7 | 2007/08 | 5 | reg. pref | 1st |
| 8 | 2008/09 | 4 | 3a | 16th |
| 9 | 2009/10 | 4 | 3a | 17th |
| 10 | 2010/11 | 4 | 3a | 18th |
| 11 | 2011/12 | 5 | reg. pref | 2nd | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 6 | | [
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select political lieutenant where took office = 1988 col : political lieutenant | district (area) | took office | left office | party leader row 1 : georges-henri heon | argenteuil (laurentides) | 1949 | 1949 | george a. drew row 2 : leon balcer | trois-rivieres (mauricie) | 1957 | 1965 | john george diefenbaker row 3 : marcel faribault | none | 1967 | 1968 | robert stanfield row 4 : claude wagner | saint-hyacinthe (monteregie) | 1972 | 1978 | robert stanfield joe clark row 5 : lucien bouchard | lac-saint-jean (saguenay-lac-saint-jean) | 1988 | 1990 | brian mulroney row 6 : benoit bouchard | roberval (saguenay-lac-saint-jean) | 1990 | 1993 | brian mulroney row 7 : monique landry | blainville-deux-montagnes (laurentides) | 1993 | 1993 | kim campbell row 8 : andre bachand | richmond-arthabaska (centre-du-quebec & eastern townships) | 1998 | 2004 | joe clark peter mackay | col : political lieutenant row 1 : lucien bouchard | select political lieutenant where took office = 1988 <table_name> : table \begin{tabular}{llllll}
\toprule
& political lieutenant & district (area) & took office & left office & party leader \\
\midrule
0 & georges-henri heon & argenteuil (laurentides) & 1949 & 1949 & george a. drew \\
1 & leon balcer & trois-rivieres (mauricie) & 1957 & 1965 & john george diefenbaker \\
2 & marcel faribault & none & 1967 & 1968 & robert stanfield \\
3 & claude wagner & saint-hyacinthe (monteregie) & 1972 & 1978 & robert stanfield joe clark \\
4 & lucien bouchard & lac-saint-jean (saguenay-lac-saint-jean) & 1988 & 1990 & brian mulroney \\
5 & benoit bouchard & roberval (saguenay-lac-saint-jean) & 1990 & 1993 & brian mulroney \\
6 & monique landry & blainville-deux-montagnes (laurentides) & 1993 & 1993 & kim campbell \\
7 & andre bachand & richmond-arthabaska (centre-du-quebec & eastern townships) & 1998 & 2004 & joe clark peter mackay \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& political lieutenant \\
\midrule
0 & lucien bouchard \\
\bottomrule
\end{tabular}
| select political lieutenant where took office = 1988 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>political lieutenant</th>
<th>district (area)</th>
<th>took office</th>
<th>left office</th>
<th>party leader</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>georges-henri heon</td>
<td>argenteuil (laurentides)</td>
<td>1949</td>
<td>1949</td>
<td>george a. drew</td>
</tr>
<tr>
<th>1</th>
<td>leon balcer</td>
<td>trois-rivieres (mauricie)</td>
<td>1957</td>
<td>1965</td>
<td>john george diefenbaker</td>
</tr>
<tr>
<th>2</th>
<td>marcel faribault</td>
<td>none</td>
<td>1967</td>
<td>1968</td>
<td>robert stanfield</td>
</tr>
<tr>
<th>3</th>
<td>claude wagner</td>
<td>saint-hyacinthe (monteregie)</td>
<td>1972</td>
<td>1978</td>
<td>robert stanfield joe clark</td>
</tr>
<tr>
<th>4</th>
<td>lucien bouchard</td>
<td>lac-saint-jean (saguenay-lac-saint-jean)</td>
<td>1988</td>
<td>1990</td>
<td>brian mulroney</td>
</tr>
<tr>
<th>5</th>
<td>benoit bouchard</td>
<td>roberval (saguenay-lac-saint-jean)</td>
<td>1990</td>
<td>1993</td>
<td>brian mulroney</td>
</tr>
<tr>
<th>6</th>
<td>monique landry</td>
<td>blainville-deux-montagnes (laurentides)</td>
<td>1993</td>
<td>1993</td>
<td>kim campbell</td>
</tr>
<tr>
<th>7</th>
<td>andre bachand</td>
<td>richmond-arthabaska (centre-du-quebec & eastern townships)</td>
<td>1998</td>
<td>2004</td>
<td>joe clark peter mackay</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>political lieutenant</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>lucien bouchard</td>
</tr>
</tbody>
</table> | select political lieutenant where took office = 1988 <table_name> : table | | political lieutenant | district (area) | took office | left office | party leader |
|---:|:-----------------------|:-----------------------------------------------------------|--------------:|--------------:|:---------------------------|
| 0 | georges-henri heon | argenteuil (laurentides) | 1949 | 1949 | george a. drew |
| 1 | leon balcer | trois-rivieres (mauricie) | 1957 | 1965 | john george diefenbaker |
| 2 | marcel faribault | none | 1967 | 1968 | robert stanfield |
| 3 | claude wagner | saint-hyacinthe (monteregie) | 1972 | 1978 | robert stanfield joe clark |
| 4 | lucien bouchard | lac-saint-jean (saguenay-lac-saint-jean) | 1988 | 1990 | brian mulroney |
| 5 | benoit bouchard | roberval (saguenay-lac-saint-jean) | 1990 | 1993 | brian mulroney |
| 6 | monique landry | blainville-deux-montagnes (laurentides) | 1993 | 1993 | kim campbell |
| 7 | andre bachand | richmond-arthabaska (centre-du-quebec & eastern townships) | 1998 | 2004 | joe clark peter mackay | | | | political lieutenant |
|---:|:-----------------------|
| 0 | lucien bouchard | | [
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select count ( work ) where year > 2008 col : year | organization | award | work | result row 1 : 2005 | 47th the television drama academy awards | best actress | hana yori dango | won row 2 : 2007 | 10th nikkan sports drama grand prix | best actress | hana yori dango 2 | won row 3 : 2007 | 16th hashida awards | newcomer award | hana yori dango 2 | won row 4 : 2007 | 2007 mtv student voice awards | best actress | hana yori dango 2 | won row 5 : 2007 | 54th the television academy drama awards | best actress | first kiss | nominated row 6 : 2008 | nickelodeon kids' choice awards | best actress | hana yori dango 2 | won row 7 : 2010 | nikkan sports grand prix (fall) | best supporting actress | veterinarian dolittle | nominated row 8 : 2011 | 3rd tama film award | best emerging actress | miracle in the pacific | won row 9 : 2011 | 35th fumiko yamaji award film awards | newcomer actress | youkame no semi | won row 10 : 2011 | 26th nikkan sport film awards | best newcomer | youkame no semi, miracle in the pacific | won row 11 : 2011 | tv navi | best actress | ohisama | won row 12 : 2011 | 70th the television drama academy awards | best actress | ohisama | won row 13 : 2012 | 35th japan academy awards | best starring actress | youkame no semi | won row 14 : 2012 | japan film festival theater staff | best actress | youkame no semi | won row 15 : 2012 | 16th nikkan sport grand prix | best actress | tokkan | nominated | col : count ( "work" ) row 1 : 9 | select count ( work ) where year > 2008 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & organization & award & work & result \\
\midrule
0 & 2005 & 47th the television drama academy awards & best actress & hana yori dango & won \\
1 & 2007 & 10th nikkan sports drama grand prix & best actress & hana yori dango 2 & won \\
2 & 2007 & 16th hashida awards & newcomer award & hana yori dango 2 & won \\
3 & 2007 & 2007 mtv student voice awards & best actress & hana yori dango 2 & won \\
4 & 2007 & 54th the television academy drama awards & best actress & first kiss & nominated \\
5 & 2008 & nickelodeon kids' choice awards & best actress & hana yori dango 2 & won \\
6 & 2010 & nikkan sports grand prix (fall) & best supporting actress & veterinarian dolittle & nominated \\
7 & 2011 & 3rd tama film award & best emerging actress & miracle in the pacific & won \\
8 & 2011 & 35th fumiko yamaji award film awards & newcomer actress & youkame no semi & won \\
9 & 2011 & 26th nikkan sport film awards & best newcomer & youkame no semi, miracle in the pacific & won \\
10 & 2011 & tv navi & best actress & ohisama & won \\
11 & 2011 & 70th the television drama academy awards & best actress & ohisama & won \\
12 & 2012 & 35th japan academy awards & best starring actress & youkame no semi & won \\
13 & 2012 & japan film festival theater staff & best actress & youkame no semi & won \\
14 & 2012 & 16th nikkan sport grand prix & best actress & tokkan & nominated \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "work" ) \\
\midrule
0 & 9 \\
\bottomrule
\end{tabular}
| select count ( work ) where year > 2008 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>organization</th>
<th>award</th>
<th>work</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2005</td>
<td>47th the television drama academy awards</td>
<td>best actress</td>
<td>hana yori dango</td>
<td>won</td>
</tr>
<tr>
<th>1</th>
<td>2007</td>
<td>10th nikkan sports drama grand prix</td>
<td>best actress</td>
<td>hana yori dango 2</td>
<td>won</td>
</tr>
<tr>
<th>2</th>
<td>2007</td>
<td>16th hashida awards</td>
<td>newcomer award</td>
<td>hana yori dango 2</td>
<td>won</td>
</tr>
<tr>
<th>3</th>
<td>2007</td>
<td>2007 mtv student voice awards</td>
<td>best actress</td>
<td>hana yori dango 2</td>
<td>won</td>
</tr>
<tr>
<th>4</th>
<td>2007</td>
<td>54th the television academy drama awards</td>
<td>best actress</td>
<td>first kiss</td>
<td>nominated</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>nickelodeon kids' choice awards</td>
<td>best actress</td>
<td>hana yori dango 2</td>
<td>won</td>
</tr>
<tr>
<th>6</th>
<td>2010</td>
<td>nikkan sports grand prix (fall)</td>
<td>best supporting actress</td>
<td>veterinarian dolittle</td>
<td>nominated</td>
</tr>
<tr>
<th>7</th>
<td>2011</td>
<td>3rd tama film award</td>
<td>best emerging actress</td>
<td>miracle in the pacific</td>
<td>won</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>35th fumiko yamaji award film awards</td>
<td>newcomer actress</td>
<td>youkame no semi</td>
<td>won</td>
</tr>
<tr>
<th>9</th>
<td>2011</td>
<td>26th nikkan sport film awards</td>
<td>best newcomer</td>
<td>youkame no semi, miracle in the pacific</td>
<td>won</td>
</tr>
<tr>
<th>10</th>
<td>2011</td>
<td>tv navi</td>
<td>best actress</td>
<td>ohisama</td>
<td>won</td>
</tr>
<tr>
<th>11</th>
<td>2011</td>
<td>70th the television drama academy awards</td>
<td>best actress</td>
<td>ohisama</td>
<td>won</td>
</tr>
<tr>
<th>12</th>
<td>2012</td>
<td>35th japan academy awards</td>
<td>best starring actress</td>
<td>youkame no semi</td>
<td>won</td>
</tr>
<tr>
<th>13</th>
<td>2012</td>
<td>japan film festival theater staff</td>
<td>best actress</td>
<td>youkame no semi</td>
<td>won</td>
</tr>
<tr>
<th>14</th>
<td>2012</td>
<td>16th nikkan sport grand prix</td>
<td>best actress</td>
<td>tokkan</td>
<td>nominated</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "work" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
</tbody>
</table> | select count ( work ) where year > 2008 <table_name> : table | | year | organization | award | work | result |
|---:|-------:|:-----------------------------------------|:------------------------|:----------------------------------------|:----------|
| 0 | 2005 | 47th the television drama academy awards | best actress | hana yori dango | won |
| 1 | 2007 | 10th nikkan sports drama grand prix | best actress | hana yori dango 2 | won |
| 2 | 2007 | 16th hashida awards | newcomer award | hana yori dango 2 | won |
| 3 | 2007 | 2007 mtv student voice awards | best actress | hana yori dango 2 | won |
| 4 | 2007 | 54th the television academy drama awards | best actress | first kiss | nominated |
| 5 | 2008 | nickelodeon kids' choice awards | best actress | hana yori dango 2 | won |
| 6 | 2010 | nikkan sports grand prix (fall) | best supporting actress | veterinarian dolittle | nominated |
| 7 | 2011 | 3rd tama film award | best emerging actress | miracle in the pacific | won |
| 8 | 2011 | 35th fumiko yamaji award film awards | newcomer actress | youkame no semi | won |
| 9 | 2011 | 26th nikkan sport film awards | best newcomer | youkame no semi, miracle in the pacific | won |
| 10 | 2011 | tv navi | best actress | ohisama | won |
| 11 | 2011 | 70th the television drama academy awards | best actress | ohisama | won |
| 12 | 2012 | 35th japan academy awards | best starring actress | youkame no semi | won |
| 13 | 2012 | japan film festival theater staff | best actress | youkame no semi | won |
| 14 | 2012 | 16th nikkan sport grand prix | best actress | tokkan | nominated | | | | count ( "work" ) |
|---:|-------------------:|
| 0 | 9 | | [
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select count ( * ) where percentage = '31.03%' col : candidate | votes | percentage | counties | delegates row 1 : john mccain | 701761 | 36% | 45 | 57 row 2 : mitt romney | 604932 | 31.03% | 18 | 0 row 3 : rudy giuliani | 286089 | 14.68% | 0 | 0 row 4 : mike huckabee | 262681 | 13.47% | 4 | 0 row 5 : ron paul | 62887 | 3.23% | 0 | 0 row 6 : fred thompson | 22668 | 1.16% | 0 | 0 row 7 : alan keyes | 4060 | 0.21% | 0 | 0 row 8 : duncan hunter | 2847 | 0.15% | 0 | 0 row 9 : tom tancredo | 1573 | 0.08% | 0 | 0 row 10 : totals | 1949498 | 100% | 67 | 57 | col : count ( "*" ) row 1 : 1 | select count ( * ) where percentage = '31.03%' <table_name> : table \begin{tabular}{llllll}
\toprule
& candidate & votes & percentage & counties & delegates \\
\midrule
0 & john mccain & 701761 & 36% & 45 & 57 \\
1 & mitt romney & 604932 & 31.03% & 18 & 0 \\
2 & rudy giuliani & 286089 & 14.68% & 0 & 0 \\
3 & mike huckabee & 262681 & 13.47% & 4 & 0 \\
4 & ron paul & 62887 & 3.23% & 0 & 0 \\
5 & fred thompson & 22668 & 1.16% & 0 & 0 \\
6 & alan keyes & 4060 & 0.21% & 0 & 0 \\
7 & duncan hunter & 2847 & 0.15% & 0 & 0 \\
8 & tom tancredo & 1573 & 0.08% & 0 & 0 \\
9 & totals & 1949498 & 100% & 67 & 57 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where percentage = '31.03%' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>candidate</th>
<th>votes</th>
<th>percentage</th>
<th>counties</th>
<th>delegates</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>john mccain</td>
<td>701761</td>
<td>36%</td>
<td>45</td>
<td>57</td>
</tr>
<tr>
<th>1</th>
<td>mitt romney</td>
<td>604932</td>
<td>31.03%</td>
<td>18</td>
<td>0</td>
</tr>
<tr>
<th>2</th>
<td>rudy giuliani</td>
<td>286089</td>
<td>14.68%</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>mike huckabee</td>
<td>262681</td>
<td>13.47%</td>
<td>4</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>ron paul</td>
<td>62887</td>
<td>3.23%</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>fred thompson</td>
<td>22668</td>
<td>1.16%</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>alan keyes</td>
<td>4060</td>
<td>0.21%</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>duncan hunter</td>
<td>2847</td>
<td>0.15%</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>8</th>
<td>tom tancredo</td>
<td>1573</td>
<td>0.08%</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>totals</td>
<td>1949498</td>
<td>100%</td>
<td>67</td>
<td>57</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where percentage = '31.03%' <table_name> : table | | candidate | votes | percentage | counties | delegates |
|---:|:--------------|--------:|:-------------|-----------:|------------:|
| 0 | john mccain | 701761 | 36% | 45 | 57 |
| 1 | mitt romney | 604932 | 31.03% | 18 | 0 |
| 2 | rudy giuliani | 286089 | 14.68% | 0 | 0 |
| 3 | mike huckabee | 262681 | 13.47% | 4 | 0 |
| 4 | ron paul | 62887 | 3.23% | 0 | 0 |
| 5 | fred thompson | 22668 | 1.16% | 0 | 0 |
| 6 | alan keyes | 4060 | 0.21% | 0 | 0 |
| 7 | duncan hunter | 2847 | 0.15% | 0 | 0 |
| 8 | tom tancredo | 1573 | 0.08% | 0 | 0 |
| 9 | totals | 1949498 | 100% | 67 | 57 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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] |
select count ( * ) where year = '-24 (-31)' col : month | jan | feb | mar | apr | may | jun | jul | aug | sep | oct | nov | dec | year row 1 : record high °f (°c) | 76 (24) | 86 (30) | 96 (36) | 96 (36) | 95 (35) | 104 (40) | 111 (44) | 109 (43) | 105 (41) | 96 (36) | 90 (32) | 78 (26) | 111 (44) row 2 : average high °f (°c) | 46.2 (7.9) | 50.4 (10.2) | 59.1 (15.1) | 68.7 (20.4) | 75.5 (24.2) | 83.5 (28.6) | 88.7 (31.5) | 89.4 (31.9) | 80.8 (27.1) | 70.3 (21.3) | 59.2 (15.1) | 48.0 (8.9) | 68.3 (20.2) row 3 : average low °f (°c) | 26.1 (-3.3) | 29.0 (-1.7) | 37.8 (3.2) | 46.9 (8.3) | 55.7 (13.2) | 64.1 (17.8) | 68.7 (20.4) | 67.7 (19.8) | 58.9 (14.9) | 47.6 (8.7) | 39.2 (4) | 28.1 (-2.2) | 47.5 (8.6) row 4 : record low °f (°c) | -23 (-31) | -24 (-31) | -11 (-24) | 18 (-8) | 28 (-2) | 41 (5) | 48 (9) | 44 (7) | 29 (-2) | 17 (-8) | 5 (-15) | -12 (-24) | -24 (-31) row 5 : precipitation inches (mm) | 1.99 (50.5) | 2.43 (61.7) | 3.54 (89.9) | 4.05 (102.9) | 4.99 (126.7) | 4.59 (116.6) | 3.18 (80.8) | 2.75 (69.9) | 4.43 (112.5) | 3.83 (97.3) | 4.19 (106.4) | 2.73 (69.3) | 42.7 (1,084.6) row 6 : snowfall inches (cm) | 1.6 (4.1) | 2.0 (5.1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | .7 (1.8) | 4.4 (11.2) row 7 : avg. precipitation days (≥ 0.01 in) | 5.4 | 6.6 | 8.2 | 9.0 | 11.2 | 8.9 | 7.0 | 6.4 | 7.6 | 7.9 | 7.0 | 6.3 | 91.4 row 8 : avg. snowy days (≥ 0.1 in) | .7 | .9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .5 | 2.3 | col : count ( "*" ) row 1 : 1 | select count ( * ) where year = '-24 (-31)' <table_name> : table \begin{tabular}{lllllllllllllll}
\toprule
& month & jan & feb & mar & apr & may & jun & jul & aug & sep & oct & nov & dec & year \\
\midrule
0 & record high °f (°c) & 76 (24) & 86 (30) & 96 (36) & 96 (36) & 95 (35) & 104 (40) & 111 (44) & 109 (43) & 105 (41) & 96 (36) & 90 (32) & 78 (26) & 111 (44) \\
1 & average high °f (°c) & 46.2 (7.9) & 50.4 (10.2) & 59.1 (15.1) & 68.7 (20.4) & 75.5 (24.2) & 83.5 (28.6) & 88.7 (31.5) & 89.4 (31.9) & 80.8 (27.1) & 70.3 (21.3) & 59.2 (15.1) & 48.0 (8.9) & 68.3 (20.2) \\
2 & average low °f (°c) & 26.1 (-3.3) & 29.0 (-1.7) & 37.8 (3.2) & 46.9 (8.3) & 55.7 (13.2) & 64.1 (17.8) & 68.7 (20.4) & 67.7 (19.8) & 58.9 (14.9) & 47.6 (8.7) & 39.2 (4) & 28.1 (-2.2) & 47.5 (8.6) \\
3 & record low °f (°c) & -23 (-31) & -24 (-31) & -11 (-24) & 18 (-8) & 28 (-2) & 41 (5) & 48 (9) & 44 (7) & 29 (-2) & 17 (-8) & 5 (-15) & -12 (-24) & -24 (-31) \\
4 & precipitation inches (mm) & 1.99 (50.5) & 2.43 (61.7) & 3.54 (89.9) & 4.05 (102.9) & 4.99 (126.7) & 4.59 (116.6) & 3.18 (80.8) & 2.75 (69.9) & 4.43 (112.5) & 3.83 (97.3) & 4.19 (106.4) & 2.73 (69.3) & 42.7 (1,084.6) \\
5 & snowfall inches (cm) & 1.6 (4.1) & 2.0 (5.1) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & .7 (1.8) & 4.4 (11.2) \\
6 & avg. precipitation days (≥ 0.01 in) & 5.4 & 6.6 & 8.2 & 9.0 & 11.2 & 8.9 & 7.0 & 6.4 & 7.6 & 7.9 & 7.0 & 6.3 & 91.4 \\
7 & avg. snowy days (≥ 0.1 in) & .7 & .9 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & .5 & 2.3 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where year = '-24 (-31)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>month</th>
<th>jan</th>
<th>feb</th>
<th>mar</th>
<th>apr</th>
<th>may</th>
<th>jun</th>
<th>jul</th>
<th>aug</th>
<th>sep</th>
<th>oct</th>
<th>nov</th>
<th>dec</th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>record high °f (°c)</td>
<td>76 (24)</td>
<td>86 (30)</td>
<td>96 (36)</td>
<td>96 (36)</td>
<td>95 (35)</td>
<td>104 (40)</td>
<td>111 (44)</td>
<td>109 (43)</td>
<td>105 (41)</td>
<td>96 (36)</td>
<td>90 (32)</td>
<td>78 (26)</td>
<td>111 (44)</td>
</tr>
<tr>
<th>1</th>
<td>average high °f (°c)</td>
<td>46.2 (7.9)</td>
<td>50.4 (10.2)</td>
<td>59.1 (15.1)</td>
<td>68.7 (20.4)</td>
<td>75.5 (24.2)</td>
<td>83.5 (28.6)</td>
<td>88.7 (31.5)</td>
<td>89.4 (31.9)</td>
<td>80.8 (27.1)</td>
<td>70.3 (21.3)</td>
<td>59.2 (15.1)</td>
<td>48.0 (8.9)</td>
<td>68.3 (20.2)</td>
</tr>
<tr>
<th>2</th>
<td>average low °f (°c)</td>
<td>26.1 (-3.3)</td>
<td>29.0 (-1.7)</td>
<td>37.8 (3.2)</td>
<td>46.9 (8.3)</td>
<td>55.7 (13.2)</td>
<td>64.1 (17.8)</td>
<td>68.7 (20.4)</td>
<td>67.7 (19.8)</td>
<td>58.9 (14.9)</td>
<td>47.6 (8.7)</td>
<td>39.2 (4)</td>
<td>28.1 (-2.2)</td>
<td>47.5 (8.6)</td>
</tr>
<tr>
<th>3</th>
<td>record low °f (°c)</td>
<td>-23 (-31)</td>
<td>-24 (-31)</td>
<td>-11 (-24)</td>
<td>18 (-8)</td>
<td>28 (-2)</td>
<td>41 (5)</td>
<td>48 (9)</td>
<td>44 (7)</td>
<td>29 (-2)</td>
<td>17 (-8)</td>
<td>5 (-15)</td>
<td>-12 (-24)</td>
<td>-24 (-31)</td>
</tr>
<tr>
<th>4</th>
<td>precipitation inches (mm)</td>
<td>1.99 (50.5)</td>
<td>2.43 (61.7)</td>
<td>3.54 (89.9)</td>
<td>4.05 (102.9)</td>
<td>4.99 (126.7)</td>
<td>4.59 (116.6)</td>
<td>3.18 (80.8)</td>
<td>2.75 (69.9)</td>
<td>4.43 (112.5)</td>
<td>3.83 (97.3)</td>
<td>4.19 (106.4)</td>
<td>2.73 (69.3)</td>
<td>42.7 (1,084.6)</td>
</tr>
<tr>
<th>5</th>
<td>snowfall inches (cm)</td>
<td>1.6 (4.1)</td>
<td>2.0 (5.1)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>0 (0)</td>
<td>.7 (1.8)</td>
<td>4.4 (11.2)</td>
</tr>
<tr>
<th>6</th>
<td>avg. precipitation days (≥ 0.01 in)</td>
<td>5.4</td>
<td>6.6</td>
<td>8.2</td>
<td>9.0</td>
<td>11.2</td>
<td>8.9</td>
<td>7.0</td>
<td>6.4</td>
<td>7.6</td>
<td>7.9</td>
<td>7.0</td>
<td>6.3</td>
<td>91.4</td>
</tr>
<tr>
<th>7</th>
<td>avg. snowy days (≥ 0.1 in)</td>
<td>.7</td>
<td>.9</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>.5</td>
<td>2.3</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where year = '-24 (-31)' <table_name> : table | | month | jan | feb | mar | apr | may | jun | jul | aug | sep | oct | nov | dec | year |
|---:|:------------------------------------|:------------|:------------|:------------|:-------------|:-------------|:-------------|:------------|:------------|:-------------|:------------|:-------------|:------------|:---------------|
| 0 | record high °f (°c) | 76 (24) | 86 (30) | 96 (36) | 96 (36) | 95 (35) | 104 (40) | 111 (44) | 109 (43) | 105 (41) | 96 (36) | 90 (32) | 78 (26) | 111 (44) |
| 1 | average high °f (°c) | 46.2 (7.9) | 50.4 (10.2) | 59.1 (15.1) | 68.7 (20.4) | 75.5 (24.2) | 83.5 (28.6) | 88.7 (31.5) | 89.4 (31.9) | 80.8 (27.1) | 70.3 (21.3) | 59.2 (15.1) | 48.0 (8.9) | 68.3 (20.2) |
| 2 | average low °f (°c) | 26.1 (-3.3) | 29.0 (-1.7) | 37.8 (3.2) | 46.9 (8.3) | 55.7 (13.2) | 64.1 (17.8) | 68.7 (20.4) | 67.7 (19.8) | 58.9 (14.9) | 47.6 (8.7) | 39.2 (4) | 28.1 (-2.2) | 47.5 (8.6) |
| 3 | record low °f (°c) | -23 (-31) | -24 (-31) | -11 (-24) | 18 (-8) | 28 (-2) | 41 (5) | 48 (9) | 44 (7) | 29 (-2) | 17 (-8) | 5 (-15) | -12 (-24) | -24 (-31) |
| 4 | precipitation inches (mm) | 1.99 (50.5) | 2.43 (61.7) | 3.54 (89.9) | 4.05 (102.9) | 4.99 (126.7) | 4.59 (116.6) | 3.18 (80.8) | 2.75 (69.9) | 4.43 (112.5) | 3.83 (97.3) | 4.19 (106.4) | 2.73 (69.3) | 42.7 (1,084.6) |
| 5 | snowfall inches (cm) | 1.6 (4.1) | 2.0 (5.1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | .7 (1.8) | 4.4 (11.2) |
| 6 | avg. precipitation days (≥ 0.01 in) | 5.4 | 6.6 | 8.2 | 9.0 | 11.2 | 8.9 | 7.0 | 6.4 | 7.6 | 7.9 | 7.0 | 6.3 | 91.4 |
| 7 | avg. snowy days (≥ 0.1 in) | .7 | .9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .5 | 2.3 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where position = 'l' col : n° | name | position | date of birth | nationality row 1 : 1 | marcus popp | s | 23 settembre 1981 | germany row 2 : 2 | stanislav simin | c | 4 ottobre 1986 | serbia row 3 : 3 | gerald hardy-dessources | c | 9 febbraio 1983 | france row 4 : 4 | soane falafala | s | 16 aprile 1993 | france row 5 : 5 | cyril guittet | l | 13 agosto 1992 | france row 6 : 6 | david konecny | s/o | 10 ottobre 1982 | czech republic row 7 : 7 | jean-francois exiga | l | 9 marzo 1982 | france row 8 : 8 | nuno pinheiro | p | 31 dicembre 1984 | portugal row 9 : 10 | guillaume di betta | s | 8 settembre 1994 | france row 10 : 12 | maxime dillies | p | 11 aprile 1984 | france row 11 : 13 | kamil baranek | s | 2 maggio 1983 | czech republic row 12 : 14 | renaud lachaise | p | 12 maggio 1991 | france row 13 : 15 | david smith | c | 15 maggio 1985 | united states row 14 : 16 | emmanuel ragondet | s | 6 agosto 1987 | france row 15 : 17 | victor le guennec | s | 19 giugno 1994 | france row 16 : 18 | thibault szymkowiak | c | 19 settembre 1991 | france | col : count ( "*" ) row 1 : 2 | select count ( * ) where position = 'l' <table_name> : table \begin{tabular}{llllll}
\toprule
& n° & name & position & date of birth & nationality \\
\midrule
0 & 1 & marcus popp & s & 23 settembre 1981 & germany \\
1 & 2 & stanislav simin & c & 4 ottobre 1986 & serbia \\
2 & 3 & gerald hardy-dessources & c & 9 febbraio 1983 & france \\
3 & 4 & soane falafala & s & 16 aprile 1993 & france \\
4 & 5 & cyril guittet & l & 13 agosto 1992 & france \\
5 & 6 & david konecny & s/o & 10 ottobre 1982 & czech republic \\
6 & 7 & jean-francois exiga & l & 9 marzo 1982 & france \\
7 & 8 & nuno pinheiro & p & 31 dicembre 1984 & portugal \\
8 & 10 & guillaume di betta & s & 8 settembre 1994 & france \\
9 & 12 & maxime dillies & p & 11 aprile 1984 & france \\
10 & 13 & kamil baranek & s & 2 maggio 1983 & czech republic \\
11 & 14 & renaud lachaise & p & 12 maggio 1991 & france \\
12 & 15 & david smith & c & 15 maggio 1985 & united states \\
13 & 16 & emmanuel ragondet & s & 6 agosto 1987 & france \\
14 & 17 & victor le guennec & s & 19 giugno 1994 & france \\
15 & 18 & thibault szymkowiak & c & 19 settembre 1991 & france \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( * ) where position = 'l' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>n°</th>
<th>name</th>
<th>position</th>
<th>date of birth</th>
<th>nationality</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>marcus popp</td>
<td>s</td>
<td>23 settembre 1981</td>
<td>germany</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>stanislav simin</td>
<td>c</td>
<td>4 ottobre 1986</td>
<td>serbia</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>gerald hardy-dessources</td>
<td>c</td>
<td>9 febbraio 1983</td>
<td>france</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>soane falafala</td>
<td>s</td>
<td>16 aprile 1993</td>
<td>france</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>cyril guittet</td>
<td>l</td>
<td>13 agosto 1992</td>
<td>france</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>david konecny</td>
<td>s/o</td>
<td>10 ottobre 1982</td>
<td>czech republic</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>jean-francois exiga</td>
<td>l</td>
<td>9 marzo 1982</td>
<td>france</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>nuno pinheiro</td>
<td>p</td>
<td>31 dicembre 1984</td>
<td>portugal</td>
</tr>
<tr>
<th>8</th>
<td>10</td>
<td>guillaume di betta</td>
<td>s</td>
<td>8 settembre 1994</td>
<td>france</td>
</tr>
<tr>
<th>9</th>
<td>12</td>
<td>maxime dillies</td>
<td>p</td>
<td>11 aprile 1984</td>
<td>france</td>
</tr>
<tr>
<th>10</th>
<td>13</td>
<td>kamil baranek</td>
<td>s</td>
<td>2 maggio 1983</td>
<td>czech republic</td>
</tr>
<tr>
<th>11</th>
<td>14</td>
<td>renaud lachaise</td>
<td>p</td>
<td>12 maggio 1991</td>
<td>france</td>
</tr>
<tr>
<th>12</th>
<td>15</td>
<td>david smith</td>
<td>c</td>
<td>15 maggio 1985</td>
<td>united states</td>
</tr>
<tr>
<th>13</th>
<td>16</td>
<td>emmanuel ragondet</td>
<td>s</td>
<td>6 agosto 1987</td>
<td>france</td>
</tr>
<tr>
<th>14</th>
<td>17</td>
<td>victor le guennec</td>
<td>s</td>
<td>19 giugno 1994</td>
<td>france</td>
</tr>
<tr>
<th>15</th>
<td>18</td>
<td>thibault szymkowiak</td>
<td>c</td>
<td>19 settembre 1991</td>
<td>france</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( * ) where position = 'l' <table_name> : table | | n° | name | position | date of birth | nationality |
|---:|-----:|:------------------------|:-----------|:------------------|:---------------|
| 0 | 1 | marcus popp | s | 23 settembre 1981 | germany |
| 1 | 2 | stanislav simin | c | 4 ottobre 1986 | serbia |
| 2 | 3 | gerald hardy-dessources | c | 9 febbraio 1983 | france |
| 3 | 4 | soane falafala | s | 16 aprile 1993 | france |
| 4 | 5 | cyril guittet | l | 13 agosto 1992 | france |
| 5 | 6 | david konecny | s/o | 10 ottobre 1982 | czech republic |
| 6 | 7 | jean-francois exiga | l | 9 marzo 1982 | france |
| 7 | 8 | nuno pinheiro | p | 31 dicembre 1984 | portugal |
| 8 | 10 | guillaume di betta | s | 8 settembre 1994 | france |
| 9 | 12 | maxime dillies | p | 11 aprile 1984 | france |
| 10 | 13 | kamil baranek | s | 2 maggio 1983 | czech republic |
| 11 | 14 | renaud lachaise | p | 12 maggio 1991 | france |
| 12 | 15 | david smith | c | 15 maggio 1985 | united states |
| 13 | 16 | emmanuel ragondet | s | 6 agosto 1987 | france |
| 14 | 17 | victor le guennec | s | 19 giugno 1994 | france |
| 15 | 18 | thibault szymkowiak | c | 19 settembre 1991 | france | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 2 | | [
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