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|---|---|---|---|---|---|---|---|---|---|---|
select song where artist = 'wind' col : draw | country | language | artist | song | english translation | place | points row 1 : 1 | spain | spanish | serafin zubiri | "todo esto es la musica" | all this is music | 14.0 | 37.0 row 2 : 2 | belgium | french | morgane | "nous, on veut des violons" | we want violins | 20.0 | 11.0 row 3 : 3 | israel | hebrew | dafna dekel | "ze rak sport" (זה רק ספורט) | it's just sport | 6.0 | 85.0 row 4 : 4 | turkey | turkish | aylin vatankos | "yaz bitti" | summer is over | 19.0 | 17.0 row 5 : 5 | greece | greek | cleopatra | "olou tou kosmou i elpida" (ολου του κοσμου η ελπιδα) | the whole world's hope | 5.0 | 94.0 row 6 : 6 | france | french, antillean creole | kali | "monte la rivie" | go up the river | 8.0 | 73.0 row 7 : 7 | sweden | swedish | christer bjorkman | "i morgon ar en annan dag" | tomor | | row 8 : is another day | 22 | 9 | | | | | row 9 : 8 | portugal | portuguese | dina | "amor d'agua fresca" | fresh water love | 17.0 | 26.0 row 10 : 9 | cyprus | greek | evridiki | "teriazoume" (ταιριαζουμε) | we hit it off | 11.0 | 57.0 row 11 : 10 | malta | english | mary spiteri | "little child" | none | 3.0 | 123.0 row 12 : 11 | iceland | icelandic | heart 2 heart | "nei eða ja" | no or yes? | 7.0 | 80.0 row 13 : 12 | finland | finnish | pave maijanen | "yamma, yamma" | none | 23.0 | 4.0 row 14 : 13 | switzerland | french | daisy auvray | "mister music man" | none | 15.0 | 32.0 row 15 : 14 | luxembourg | luxembourgish | marion welter & kontinent | "sou frai" | so free | 21.0 | 10.0 row 16 : 15 | austria | german | tony wegas | "zusammen geh'n" | go together | 10.0 | 63.0 row 17 : 16 | united kingdom | english | michael ball | "one step out of time" | none | 2.0 | 139.0 row 18 : 17 | ireland | english | linda martin | "why me?" | none | 1.0 | 155.0 row 19 : 18 | denmark | danish | kenny lubcke & lotte nilsson | "alt det som ingen ser" | all the things that nobody sees | 12.0 | 47.0 row 20 : 19 | italy | italian | mia martini | "rapsodia" | rhapsody | 4.0 | 111.0 row 21 : 20 | fr yugoslavia | serbian | extra nena | "ljubim te pesmama" (љубим те песмама) | i'm kissing you with songs | 13.0 | 44.0 row 22 : 21 | norway | norwegian | merethe trøan | "visjoner" | visions | 18.0 | 23.0 row 23 : 22 | germany | german | wind | "traume sind fur alle da" | dreams are there for everyone | 16.0 | 27.0 row 24 : 23 | netherlands | dutch | humphrey campbell | "wijs me de weg" | show me the way | 9.0 | 67.0 | col : song row 1 : "traume sind fur alle da" | select song where artist = 'wind' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& draw & country & language & artist & song & english translation & place & points \\
\midrule
0 & 1 & spain & spanish & serafin zubiri & "todo esto es la musica" & all this is music & 14.0 & 37.0 \\
1 & 2 & belgium & french & morgane & "nous, on veut des violons" & we want violins & 20.0 & 11.0 \\
2 & 3 & israel & hebrew & dafna dekel & "ze rak sport" (זה רק ספורט) & it's just sport & 6.0 & 85.0 \\
3 & 4 & turkey & turkish & aylin vatankos & "yaz bitti" & summer is over & 19.0 & 17.0 \\
4 & 5 & greece & greek & cleopatra & "olou tou kosmou i elpida" (ολου του κοσμου η ελπιδα) & the whole world's hope & 5.0 & 94.0 \\
5 & 6 & france & french, antillean creole & kali & "monte la rivie" & go up the river & 8.0 & 73.0 \\
6 & 7 & sweden & swedish & christer bjorkman & "i morgon ar en annan dag" & tomor & & \\
7 & is another day & 22 & 9 & & & & & \\
8 & 8 & portugal & portuguese & dina & "amor d'agua fresca" & fresh water love & 17.0 & 26.0 \\
9 & 9 & cyprus & greek & evridiki & "teriazoume" (ταιριαζουμε) & we hit it off & 11.0 & 57.0 \\
10 & 10 & malta & english & mary spiteri & "little child" & none & 3.0 & 123.0 \\
11 & 11 & iceland & icelandic & heart 2 heart & "nei eða ja" & no or yes? & 7.0 & 80.0 \\
12 & 12 & finland & finnish & pave maijanen & "yamma, yamma" & none & 23.0 & 4.0 \\
13 & 13 & switzerland & french & daisy auvray & "mister music man" & none & 15.0 & 32.0 \\
14 & 14 & luxembourg & luxembourgish & marion welter & kontinent & "sou frai" & so free & 21.0 & 10.0 \\
15 & 15 & austria & german & tony wegas & "zusammen geh'n" & go together & 10.0 & 63.0 \\
16 & 16 & united kingdom & english & michael ball & "one step out of time" & none & 2.0 & 139.0 \\
17 & 17 & ireland & english & linda martin & "why me?" & none & 1.0 & 155.0 \\
18 & 18 & denmark & danish & kenny lubcke & lotte nilsson & "alt det som ingen ser" & all the things that nobody sees & 12.0 & 47.0 \\
19 & 19 & italy & italian & mia martini & "rapsodia" & rhapsody & 4.0 & 111.0 \\
20 & 20 & fr yugoslavia & serbian & extra nena & "ljubim te pesmama" (љубим те песмама) & i'm kissing you with songs & 13.0 & 44.0 \\
21 & 21 & norway & norwegian & merethe trøan & "visjoner" & visions & 18.0 & 23.0 \\
22 & 22 & germany & german & wind & "traume sind fur alle da" & dreams are there for everyone & 16.0 & 27.0 \\
23 & 23 & netherlands & dutch & humphrey campbell & "wijs me de weg" & show me the way & 9.0 & 67.0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& song \\
\midrule
0 & "traume sind fur alle da" \\
\bottomrule
\end{tabular}
| select song where artist = 'wind' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>draw</th>
<th>country</th>
<th>language</th>
<th>artist</th>
<th>song</th>
<th>english translation</th>
<th>place</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>spain</td>
<td>spanish</td>
<td>serafin zubiri</td>
<td>"todo esto es la musica"</td>
<td>all this is music</td>
<td>14.0</td>
<td>37.0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>belgium</td>
<td>french</td>
<td>morgane</td>
<td>"nous, on veut des violons"</td>
<td>we want violins</td>
<td>20.0</td>
<td>11.0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>israel</td>
<td>hebrew</td>
<td>dafna dekel</td>
<td>"ze rak sport" (זה רק ספורט)</td>
<td>it's just sport</td>
<td>6.0</td>
<td>85.0</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>turkey</td>
<td>turkish</td>
<td>aylin vatankos</td>
<td>"yaz bitti"</td>
<td>summer is over</td>
<td>19.0</td>
<td>17.0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>greece</td>
<td>greek</td>
<td>cleopatra</td>
<td>"olou tou kosmou i elpida" (ολου του κοσμου η ελπιδα)</td>
<td>the whole world's hope</td>
<td>5.0</td>
<td>94.0</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>france</td>
<td>french, antillean creole</td>
<td>kali</td>
<td>"monte la rivie"</td>
<td>go up the river</td>
<td>8.0</td>
<td>73.0</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>sweden</td>
<td>swedish</td>
<td>christer bjorkman</td>
<td>"i morgon ar en annan dag"</td>
<td>tomor</td>
<td></td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>is another day</td>
<td>22</td>
<td>9</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>portugal</td>
<td>portuguese</td>
<td>dina</td>
<td>"amor d'agua fresca"</td>
<td>fresh water love</td>
<td>17.0</td>
<td>26.0</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>cyprus</td>
<td>greek</td>
<td>evridiki</td>
<td>"teriazoume" (ταιριαζουμε)</td>
<td>we hit it off</td>
<td>11.0</td>
<td>57.0</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>malta</td>
<td>english</td>
<td>mary spiteri</td>
<td>"little child"</td>
<td>none</td>
<td>3.0</td>
<td>123.0</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>iceland</td>
<td>icelandic</td>
<td>heart 2 heart</td>
<td>"nei eða ja"</td>
<td>no or yes?</td>
<td>7.0</td>
<td>80.0</td>
</tr>
<tr>
<th>12</th>
<td>12</td>
<td>finland</td>
<td>finnish</td>
<td>pave maijanen</td>
<td>"yamma, yamma"</td>
<td>none</td>
<td>23.0</td>
<td>4.0</td>
</tr>
<tr>
<th>13</th>
<td>13</td>
<td>switzerland</td>
<td>french</td>
<td>daisy auvray</td>
<td>"mister music man"</td>
<td>none</td>
<td>15.0</td>
<td>32.0</td>
</tr>
<tr>
<th>14</th>
<td>14</td>
<td>luxembourg</td>
<td>luxembourgish</td>
<td>marion welter & kontinent</td>
<td>"sou frai"</td>
<td>so free</td>
<td>21.0</td>
<td>10.0</td>
</tr>
<tr>
<th>15</th>
<td>15</td>
<td>austria</td>
<td>german</td>
<td>tony wegas</td>
<td>"zusammen geh'n"</td>
<td>go together</td>
<td>10.0</td>
<td>63.0</td>
</tr>
<tr>
<th>16</th>
<td>16</td>
<td>united kingdom</td>
<td>english</td>
<td>michael ball</td>
<td>"one step out of time"</td>
<td>none</td>
<td>2.0</td>
<td>139.0</td>
</tr>
<tr>
<th>17</th>
<td>17</td>
<td>ireland</td>
<td>english</td>
<td>linda martin</td>
<td>"why me?"</td>
<td>none</td>
<td>1.0</td>
<td>155.0</td>
</tr>
<tr>
<th>18</th>
<td>18</td>
<td>denmark</td>
<td>danish</td>
<td>kenny lubcke & lotte nilsson</td>
<td>"alt det som ingen ser"</td>
<td>all the things that nobody sees</td>
<td>12.0</td>
<td>47.0</td>
</tr>
<tr>
<th>19</th>
<td>19</td>
<td>italy</td>
<td>italian</td>
<td>mia martini</td>
<td>"rapsodia"</td>
<td>rhapsody</td>
<td>4.0</td>
<td>111.0</td>
</tr>
<tr>
<th>20</th>
<td>20</td>
<td>fr yugoslavia</td>
<td>serbian</td>
<td>extra nena</td>
<td>"ljubim te pesmama" (љубим те песмама)</td>
<td>i'm kissing you with songs</td>
<td>13.0</td>
<td>44.0</td>
</tr>
<tr>
<th>21</th>
<td>21</td>
<td>norway</td>
<td>norwegian</td>
<td>merethe trøan</td>
<td>"visjoner"</td>
<td>visions</td>
<td>18.0</td>
<td>23.0</td>
</tr>
<tr>
<th>22</th>
<td>22</td>
<td>germany</td>
<td>german</td>
<td>wind</td>
<td>"traume sind fur alle da"</td>
<td>dreams are there for everyone</td>
<td>16.0</td>
<td>27.0</td>
</tr>
<tr>
<th>23</th>
<td>23</td>
<td>netherlands</td>
<td>dutch</td>
<td>humphrey campbell</td>
<td>"wijs me de weg"</td>
<td>show me the way</td>
<td>9.0</td>
<td>67.0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>song</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>"traume sind fur alle da"</td>
</tr>
</tbody>
</table> | select song where artist = 'wind' <table_name> : table | | draw | country | language | artist | song | english translation | place | points |
|---:|:---------------|:---------------|:-------------------------|:-----------------------------|:------------------------------------------------------|:--------------------------------|:--------|:---------|
| 0 | 1 | spain | spanish | serafin zubiri | "todo esto es la musica" | all this is music | 14.0 | 37.0 |
| 1 | 2 | belgium | french | morgane | "nous, on veut des violons" | we want violins | 20.0 | 11.0 |
| 2 | 3 | israel | hebrew | dafna dekel | "ze rak sport" (זה רק ספורט) | it's just sport | 6.0 | 85.0 |
| 3 | 4 | turkey | turkish | aylin vatankos | "yaz bitti" | summer is over | 19.0 | 17.0 |
| 4 | 5 | greece | greek | cleopatra | "olou tou kosmou i elpida" (ολου του κοσμου η ελπιδα) | the whole world's hope | 5.0 | 94.0 |
| 5 | 6 | france | french, antillean creole | kali | "monte la rivie" | go up the river | 8.0 | 73.0 |
| 6 | 7 | sweden | swedish | christer bjorkman | "i morgon ar en annan dag" | tomor | | |
| 7 | is another day | 22 | 9 | | | | | |
| 8 | 8 | portugal | portuguese | dina | "amor d'agua fresca" | fresh water love | 17.0 | 26.0 |
| 9 | 9 | cyprus | greek | evridiki | "teriazoume" (ταιριαζουμε) | we hit it off | 11.0 | 57.0 |
| 10 | 10 | malta | english | mary spiteri | "little child" | none | 3.0 | 123.0 |
| 11 | 11 | iceland | icelandic | heart 2 heart | "nei eða ja" | no or yes? | 7.0 | 80.0 |
| 12 | 12 | finland | finnish | pave maijanen | "yamma, yamma" | none | 23.0 | 4.0 |
| 13 | 13 | switzerland | french | daisy auvray | "mister music man" | none | 15.0 | 32.0 |
| 14 | 14 | luxembourg | luxembourgish | marion welter & kontinent | "sou frai" | so free | 21.0 | 10.0 |
| 15 | 15 | austria | german | tony wegas | "zusammen geh'n" | go together | 10.0 | 63.0 |
| 16 | 16 | united kingdom | english | michael ball | "one step out of time" | none | 2.0 | 139.0 |
| 17 | 17 | ireland | english | linda martin | "why me?" | none | 1.0 | 155.0 |
| 18 | 18 | denmark | danish | kenny lubcke & lotte nilsson | "alt det som ingen ser" | all the things that nobody sees | 12.0 | 47.0 |
| 19 | 19 | italy | italian | mia martini | "rapsodia" | rhapsody | 4.0 | 111.0 |
| 20 | 20 | fr yugoslavia | serbian | extra nena | "ljubim te pesmama" (љубим те песмама) | i'm kissing you with songs | 13.0 | 44.0 |
| 21 | 21 | norway | norwegian | merethe trøan | "visjoner" | visions | 18.0 | 23.0 |
| 22 | 22 | germany | german | wind | "traume sind fur alle da" | dreams are there for everyone | 16.0 | 27.0 |
| 23 | 23 | netherlands | dutch | humphrey campbell | "wijs me de weg" | show me the way | 9.0 | 67.0 | | | | song |
|---:|:--------------------------|
| 0 | "traume sind fur alle da" | | [
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select membership where members = '16' col : state | membership | parliament | membership status | represented since | members row 1 : denmark | full | the folketing | sovereign state | 1952 | 16 row 2 : iceland | full | alþingi | sovereign state | 1952 | 7 row 3 : norway | full | the storting | sovereign state | 1952 | 20 row 4 : sweden | full | the riksdag | sovereign state | 1952 | 20 row 5 : finland | full | eduskunta | sovereign state | 1955 | 18 row 6 : greenland | associate | landsting | self-governing region of the danish realm | 1984 | 2 row 7 : faroe islands | associate | løgting | self-governing region of the danish realm | 1970 | 2 row 8 : aland islands | associate | lagting | self-governing region of finland | 1970 | 2 row 9 : estonia | observers | none | none | none | none row 10 : latvia | observers | none | none | none | none row 11 : lithuania | observers | none | none | none | none | col : membership row 1 : full | select membership where members = '16' <table_name> : table \begin{tabular}{lllllll}
\toprule
& state & membership & parliament & membership status & represented since & members \\
\midrule
0 & denmark & full & the folketing & sovereign state & 1952 & 16 \\
1 & iceland & full & alþingi & sovereign state & 1952 & 7 \\
2 & norway & full & the storting & sovereign state & 1952 & 20 \\
3 & sweden & full & the riksdag & sovereign state & 1952 & 20 \\
4 & finland & full & eduskunta & sovereign state & 1955 & 18 \\
5 & greenland & associate & landsting & self-governing region of the danish realm & 1984 & 2 \\
6 & faroe islands & associate & løgting & self-governing region of the danish realm & 1970 & 2 \\
7 & aland islands & associate & lagting & self-governing region of finland & 1970 & 2 \\
8 & estonia & observers & none & none & none & none \\
9 & latvia & observers & none & none & none & none \\
10 & lithuania & observers & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& membership \\
\midrule
0 & full \\
\bottomrule
\end{tabular}
| select membership where members = '16' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>state</th>
<th>membership</th>
<th>parliament</th>
<th>membership status</th>
<th>represented since</th>
<th>members</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>denmark</td>
<td>full</td>
<td>the folketing</td>
<td>sovereign state</td>
<td>1952</td>
<td>16</td>
</tr>
<tr>
<th>1</th>
<td>iceland</td>
<td>full</td>
<td>alþingi</td>
<td>sovereign state</td>
<td>1952</td>
<td>7</td>
</tr>
<tr>
<th>2</th>
<td>norway</td>
<td>full</td>
<td>the storting</td>
<td>sovereign state</td>
<td>1952</td>
<td>20</td>
</tr>
<tr>
<th>3</th>
<td>sweden</td>
<td>full</td>
<td>the riksdag</td>
<td>sovereign state</td>
<td>1952</td>
<td>20</td>
</tr>
<tr>
<th>4</th>
<td>finland</td>
<td>full</td>
<td>eduskunta</td>
<td>sovereign state</td>
<td>1955</td>
<td>18</td>
</tr>
<tr>
<th>5</th>
<td>greenland</td>
<td>associate</td>
<td>landsting</td>
<td>self-governing region of the danish realm</td>
<td>1984</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>faroe islands</td>
<td>associate</td>
<td>løgting</td>
<td>self-governing region of the danish realm</td>
<td>1970</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>aland islands</td>
<td>associate</td>
<td>lagting</td>
<td>self-governing region of finland</td>
<td>1970</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>estonia</td>
<td>observers</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>latvia</td>
<td>observers</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>lithuania</td>
<td>observers</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>membership</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>full</td>
</tr>
</tbody>
</table> | select membership where members = '16' <table_name> : table | | state | membership | parliament | membership status | represented since | members |
|---:|:--------------|:-------------|:--------------|:------------------------------------------|:--------------------|:----------|
| 0 | denmark | full | the folketing | sovereign state | 1952 | 16 |
| 1 | iceland | full | alþingi | sovereign state | 1952 | 7 |
| 2 | norway | full | the storting | sovereign state | 1952 | 20 |
| 3 | sweden | full | the riksdag | sovereign state | 1952 | 20 |
| 4 | finland | full | eduskunta | sovereign state | 1955 | 18 |
| 5 | greenland | associate | landsting | self-governing region of the danish realm | 1984 | 2 |
| 6 | faroe islands | associate | løgting | self-governing region of the danish realm | 1970 | 2 |
| 7 | aland islands | associate | lagting | self-governing region of finland | 1970 | 2 |
| 8 | estonia | observers | none | none | none | none |
| 9 | latvia | observers | none | none | none | none |
| 10 | lithuania | observers | none | none | none | none | | | | membership |
|---:|:-------------|
| 0 | full | | [
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select min ( birds ) where amphibians > 10 col : country | amphibians | birds | mammals | reptile | total terrestrial vertebrates | vascular plants | biodiversity row 1 : belize | 46 | 544 | 147 | 140 | 877 | 2894 | 3771 row 2 : costa rica | 183 | 838 | 232 | 258 | 1511 | 12119 | 13630 row 3 : el salvador | 30 | 434 | 137 | 106 | 707 | 2911 | 3618 row 4 : guatemala | 133 | 684 | 193 | 236 | 1246 | 8681 | 9927 row 5 : honduras | 101 | 699 | 201 | 213 | 1214 | 5680 | 6894 row 6 : nicaragua | 61 | 632 | 181 | 178 | 1052 | 7590 | 8642 row 7 : panama | 182 | 904 | 241 | 242 | 1569 | 9915 | 11484 | col : min ( "birds" ) row 1 : 434 | select min ( birds ) where amphibians > 10 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& country & amphibians & birds & mammals & reptile & total terrestrial vertebrates & vascular plants & biodiversity \\
\midrule
0 & belize & 46 & 544 & 147 & 140 & 877 & 2894 & 3771 \\
1 & costa rica & 183 & 838 & 232 & 258 & 1511 & 12119 & 13630 \\
2 & el salvador & 30 & 434 & 137 & 106 & 707 & 2911 & 3618 \\
3 & guatemala & 133 & 684 & 193 & 236 & 1246 & 8681 & 9927 \\
4 & honduras & 101 & 699 & 201 & 213 & 1214 & 5680 & 6894 \\
5 & nicaragua & 61 & 632 & 181 & 178 & 1052 & 7590 & 8642 \\
6 & panama & 182 & 904 & 241 & 242 & 1569 & 9915 & 11484 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& min ( "birds" ) \\
\midrule
0 & 434 \\
\bottomrule
\end{tabular}
| select min ( birds ) where amphibians > 10 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>country</th>
<th>amphibians</th>
<th>birds</th>
<th>mammals</th>
<th>reptile</th>
<th>total terrestrial vertebrates</th>
<th>vascular plants</th>
<th>biodiversity</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>belize</td>
<td>46</td>
<td>544</td>
<td>147</td>
<td>140</td>
<td>877</td>
<td>2894</td>
<td>3771</td>
</tr>
<tr>
<th>1</th>
<td>costa rica</td>
<td>183</td>
<td>838</td>
<td>232</td>
<td>258</td>
<td>1511</td>
<td>12119</td>
<td>13630</td>
</tr>
<tr>
<th>2</th>
<td>el salvador</td>
<td>30</td>
<td>434</td>
<td>137</td>
<td>106</td>
<td>707</td>
<td>2911</td>
<td>3618</td>
</tr>
<tr>
<th>3</th>
<td>guatemala</td>
<td>133</td>
<td>684</td>
<td>193</td>
<td>236</td>
<td>1246</td>
<td>8681</td>
<td>9927</td>
</tr>
<tr>
<th>4</th>
<td>honduras</td>
<td>101</td>
<td>699</td>
<td>201</td>
<td>213</td>
<td>1214</td>
<td>5680</td>
<td>6894</td>
</tr>
<tr>
<th>5</th>
<td>nicaragua</td>
<td>61</td>
<td>632</td>
<td>181</td>
<td>178</td>
<td>1052</td>
<td>7590</td>
<td>8642</td>
</tr>
<tr>
<th>6</th>
<td>panama</td>
<td>182</td>
<td>904</td>
<td>241</td>
<td>242</td>
<td>1569</td>
<td>9915</td>
<td>11484</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>min ( "birds" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>434</td>
</tr>
</tbody>
</table> | select min ( birds ) where amphibians > 10 <table_name> : table | | country | amphibians | birds | mammals | reptile | total terrestrial vertebrates | vascular plants | biodiversity |
|---:|:------------|-------------:|--------:|----------:|----------:|--------------------------------:|------------------:|---------------:|
| 0 | belize | 46 | 544 | 147 | 140 | 877 | 2894 | 3771 |
| 1 | costa rica | 183 | 838 | 232 | 258 | 1511 | 12119 | 13630 |
| 2 | el salvador | 30 | 434 | 137 | 106 | 707 | 2911 | 3618 |
| 3 | guatemala | 133 | 684 | 193 | 236 | 1246 | 8681 | 9927 |
| 4 | honduras | 101 | 699 | 201 | 213 | 1214 | 5680 | 6894 |
| 5 | nicaragua | 61 | 632 | 181 | 178 | 1052 | 7590 | 8642 |
| 6 | panama | 182 | 904 | 241 | 242 | 1569 | 9915 | 11484 | | | | min ( "birds" ) |
|---:|------------------:|
| 0 | 434 | | [
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select year where year = 1976 col : year | film title | duration | film type | shoot location row 1 : 1972 | kwadrat (square) | 4:40 | 35 mm short film | pwsftvit łodz, poland row 2 : 1972 | take five | 3:36 | 35 mm short film | pwsftvit łodz, poland row 3 : 1973 | plamuz (music art) | 9:38 | 35 mm short film | smff se-ma-for łodz, poland row 4 : 1974 | zupa (soup) | 8:22 | 35 mm short film | smff se-ma-for łodz, poland row 5 : 1975 | nowa ksiazka (new book) | 10:26 | 35 mm short film | smff se-ma-for łodz, poland row 6 : 1975 | lokomotywa (locomotive) | 9:38 | 35 mm short film | smff se-ma-for łodz, poland row 7 : 1975 | swieto (holiday) | 9:38 | 35 mm short film | smff se-ma-for łodz, poland row 8 : 1976 | oj! nie moge sie zatrzymac! (oh, i can't stop!) | 10:07 | 35 mm short film | smff se-ma-for łodz, poland row 9 : 1976 | weg zum nachbarn (way to your neighbor) | 2:30 | 35 mm short film | smff se-ma-for łodz, poland row 10 : 1977 | piatek - sobota (friday - saturday) | 3:00 | 35 mm short film | smff se-ma-for łodz, poland row 11 : 1979 | mein fenster (my window) | 2:26 | 35 mm short film | vienna row 12 : 1980 | tango | 8:14 | 35 mm short film | smff se-ma-for łodz, poland row 13 : 1980 | media | 1:36 | 35 mm short film | smff se-ma-for łodz, poland row 14 : 1980 | sceny narciarskie z franzem klammeren (ski scenes with franz klammer) | 9:38 | 35 mm documentary film | in collaboration with b. dziworski, wfo łodz, poland and signal film, vienna row 15 : 1981 | wdech-wydech (inhale-exhale) | 2:26 | 35 mm short film | in collaboration with b. dziworski, smff se-ma-for łodz, for tvp, poland | col : year row 1 : 1976 row 2 : 1976 | select year where year = 1976 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & film title & duration & film type & shoot location \\
\midrule
0 & 1972 & kwadrat (square) & 4:40 & 35 mm short film & pwsftvit łodz, poland \\
1 & 1972 & take five & 3:36 & 35 mm short film & pwsftvit łodz, poland \\
2 & 1973 & plamuz (music art) & 9:38 & 35 mm short film & smff se-ma-for łodz, poland \\
3 & 1974 & zupa (soup) & 8:22 & 35 mm short film & smff se-ma-for łodz, poland \\
4 & 1975 & nowa ksiazka (new book) & 10:26 & 35 mm short film & smff se-ma-for łodz, poland \\
5 & 1975 & lokomotywa (locomotive) & 9:38 & 35 mm short film & smff se-ma-for łodz, poland \\
6 & 1975 & swieto (holiday) & 9:38 & 35 mm short film & smff se-ma-for łodz, poland \\
7 & 1976 & oj! nie moge sie zatrzymac! (oh, i can't stop!) & 10:07 & 35 mm short film & smff se-ma-for łodz, poland \\
8 & 1976 & weg zum nachbarn (way to your neighbor) & 2:30 & 35 mm short film & smff se-ma-for łodz, poland \\
9 & 1977 & piatek - sobota (friday - saturday) & 3:00 & 35 mm short film & smff se-ma-for łodz, poland \\
10 & 1979 & mein fenster (my window) & 2:26 & 35 mm short film & vienna \\
11 & 1980 & tango & 8:14 & 35 mm short film & smff se-ma-for łodz, poland \\
12 & 1980 & media & 1:36 & 35 mm short film & smff se-ma-for łodz, poland \\
13 & 1980 & sceny narciarskie z franzem klammeren (ski scenes with franz klammer) & 9:38 & 35 mm documentary film & in collaboration with b. dziworski, wfo łodz, poland and signal film, vienna \\
14 & 1981 & wdech-wydech (inhale-exhale) & 2:26 & 35 mm short film & in collaboration with b. dziworski, smff se-ma-for łodz, for tvp, poland \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1976 \\
1 & 1976 \\
\bottomrule
\end{tabular}
| select year where year = 1976 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>film title</th>
<th>duration</th>
<th>film type</th>
<th>shoot location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1972</td>
<td>kwadrat (square)</td>
<td>4:40</td>
<td>35 mm short film</td>
<td>pwsftvit łodz, poland</td>
</tr>
<tr>
<th>1</th>
<td>1972</td>
<td>take five</td>
<td>3:36</td>
<td>35 mm short film</td>
<td>pwsftvit łodz, poland</td>
</tr>
<tr>
<th>2</th>
<td>1973</td>
<td>plamuz (music art)</td>
<td>9:38</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>3</th>
<td>1974</td>
<td>zupa (soup)</td>
<td>8:22</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>4</th>
<td>1975</td>
<td>nowa ksiazka (new book)</td>
<td>10:26</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>5</th>
<td>1975</td>
<td>lokomotywa (locomotive)</td>
<td>9:38</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>6</th>
<td>1975</td>
<td>swieto (holiday)</td>
<td>9:38</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>7</th>
<td>1976</td>
<td>oj! nie moge sie zatrzymac! (oh, i can't stop!)</td>
<td>10:07</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>8</th>
<td>1976</td>
<td>weg zum nachbarn (way to your neighbor)</td>
<td>2:30</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>9</th>
<td>1977</td>
<td>piatek - sobota (friday - saturday)</td>
<td>3:00</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>10</th>
<td>1979</td>
<td>mein fenster (my window)</td>
<td>2:26</td>
<td>35 mm short film</td>
<td>vienna</td>
</tr>
<tr>
<th>11</th>
<td>1980</td>
<td>tango</td>
<td>8:14</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>12</th>
<td>1980</td>
<td>media</td>
<td>1:36</td>
<td>35 mm short film</td>
<td>smff se-ma-for łodz, poland</td>
</tr>
<tr>
<th>13</th>
<td>1980</td>
<td>sceny narciarskie z franzem klammeren (ski scenes with franz klammer)</td>
<td>9:38</td>
<td>35 mm documentary film</td>
<td>in collaboration with b. dziworski, wfo łodz, poland and signal film, vienna</td>
</tr>
<tr>
<th>14</th>
<td>1981</td>
<td>wdech-wydech (inhale-exhale)</td>
<td>2:26</td>
<td>35 mm short film</td>
<td>in collaboration with b. dziworski, smff se-ma-for łodz, for tvp, poland</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1976</td>
</tr>
<tr>
<th>1</th>
<td>1976</td>
</tr>
</tbody>
</table> | select year where year = 1976 <table_name> : table | | year | film title | duration | film type | shoot location |
|---:|-------:|:----------------------------------------------------------------------|:-----------|:-----------------------|:-----------------------------------------------------------------------------|
| 0 | 1972 | kwadrat (square) | 4:40 | 35 mm short film | pwsftvit łodz, poland |
| 1 | 1972 | take five | 3:36 | 35 mm short film | pwsftvit łodz, poland |
| 2 | 1973 | plamuz (music art) | 9:38 | 35 mm short film | smff se-ma-for łodz, poland |
| 3 | 1974 | zupa (soup) | 8:22 | 35 mm short film | smff se-ma-for łodz, poland |
| 4 | 1975 | nowa ksiazka (new book) | 10:26 | 35 mm short film | smff se-ma-for łodz, poland |
| 5 | 1975 | lokomotywa (locomotive) | 9:38 | 35 mm short film | smff se-ma-for łodz, poland |
| 6 | 1975 | swieto (holiday) | 9:38 | 35 mm short film | smff se-ma-for łodz, poland |
| 7 | 1976 | oj! nie moge sie zatrzymac! (oh, i can't stop!) | 10:07 | 35 mm short film | smff se-ma-for łodz, poland |
| 8 | 1976 | weg zum nachbarn (way to your neighbor) | 2:30 | 35 mm short film | smff se-ma-for łodz, poland |
| 9 | 1977 | piatek - sobota (friday - saturday) | 3:00 | 35 mm short film | smff se-ma-for łodz, poland |
| 10 | 1979 | mein fenster (my window) | 2:26 | 35 mm short film | vienna |
| 11 | 1980 | tango | 8:14 | 35 mm short film | smff se-ma-for łodz, poland |
| 12 | 1980 | media | 1:36 | 35 mm short film | smff se-ma-for łodz, poland |
| 13 | 1980 | sceny narciarskie z franzem klammeren (ski scenes with franz klammer) | 9:38 | 35 mm documentary film | in collaboration with b. dziworski, wfo łodz, poland and signal film, vienna |
| 14 | 1981 | wdech-wydech (inhale-exhale) | 2:26 | 35 mm short film | in collaboration with b. dziworski, smff se-ma-for łodz, for tvp, poland | | | | year |
|---:|-------:|
| 0 | 1976 |
| 1 | 1976 | | [
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select count ( title ) where title = 11 col : year | title | role | notes row 1 : 1989-1993 | short attention span theater | host | co-presented four seasons row 2 : 1993-1995 | the jon stewart show | host | creator, executive producer, writer row 3 : 1996 | the larry sanders show | himself | 6 episodes from 1996-1998 row 4 : 1997 | the nanny | bobby | episode: "kissing cousins" row 5 : 1997 | newsradio | andrew | episode: "twins" row 6 : 1997 | dr katz, professional therapist | jon | voice, episode "guess who" row 7 : 1997 | space ghost coast to coast | himself | episode: "mayonnaise" row 8 : 1997 | mr. show | himself | episode: "a white man set them free" row 9 : 1998 | elmopalooza | himself | tv special row 10 : 1999 | spin city | parker | episode: "wall street" row 11 : 1999-present | the daily show | host | executive producer, writer row 12 : 2001 | 43rd annual grammy awards | host | tv special row 13 : 2002 | 44th annual grammy awards | host | tv special row 14 : 2002 | saturday night live | host | episode: "jon stewart/india.arie" row 15 : 2006 | 78th academy awards | host | tv special row 16 : 2006 | american dad | himself | voice, episode: "irregarding steve" row 17 : 2007 | jack's big music show | brunk stinegrouber | episode: "groundhog day" row 18 : 2008 | the simpsons | himself | voice, episode: "e pluribus wiggum" row 19 : 2008 | 80th academy awards | host | tv special row 20 : 2012 | robot chicken | matt trakker, serpentor | voice, episode: "executed by the state" row 21 : 2013 | big time rush | himself | episode: "big time invasion" | col : count ( "title" ) row 1 : 0 | select count ( title ) where title = 11 <table_name> : table \begin{tabular}{lllll}
\toprule
& year & title & role & notes \\
\midrule
0 & 1989-1993 & short attention span theater & host & co-presented four seasons \\
1 & 1993-1995 & the jon stewart show & host & creator, executive producer, writer \\
2 & 1996 & the larry sanders show & himself & 6 episodes from 1996-1998 \\
3 & 1997 & the nanny & bobby & episode: "kissing cousins" \\
4 & 1997 & newsradio & andrew & episode: "twins" \\
5 & 1997 & dr katz, professional therapist & jon & voice, episode "guess who" \\
6 & 1997 & space ghost coast to coast & himself & episode: "mayonnaise" \\
7 & 1997 & mr. show & himself & episode: "a white man set them free" \\
8 & 1998 & elmopalooza & himself & tv special \\
9 & 1999 & spin city & parker & episode: "wall street" \\
10 & 1999-present & the daily show & host & executive producer, writer \\
11 & 2001 & 43rd annual grammy awards & host & tv special \\
12 & 2002 & 44th annual grammy awards & host & tv special \\
13 & 2002 & saturday night live & host & episode: "jon stewart/india.arie" \\
14 & 2006 & 78th academy awards & host & tv special \\
15 & 2006 & american dad & himself & voice, episode: "irregarding steve" \\
16 & 2007 & jack's big music show & brunk stinegrouber & episode: "groundhog day" \\
17 & 2008 & the simpsons & himself & voice, episode: "e pluribus wiggum" \\
18 & 2008 & 80th academy awards & host & tv special \\
19 & 2012 & robot chicken & matt trakker, serpentor & voice, episode: "executed by the state" \\
20 & 2013 & big time rush & himself & episode: "big time invasion" \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "title" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( title ) where title = 11 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>role</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1989-1993</td>
<td>short attention span theater</td>
<td>host</td>
<td>co-presented four seasons</td>
</tr>
<tr>
<th>1</th>
<td>1993-1995</td>
<td>the jon stewart show</td>
<td>host</td>
<td>creator, executive producer, writer</td>
</tr>
<tr>
<th>2</th>
<td>1996</td>
<td>the larry sanders show</td>
<td>himself</td>
<td>6 episodes from 1996-1998</td>
</tr>
<tr>
<th>3</th>
<td>1997</td>
<td>the nanny</td>
<td>bobby</td>
<td>episode: "kissing cousins"</td>
</tr>
<tr>
<th>4</th>
<td>1997</td>
<td>newsradio</td>
<td>andrew</td>
<td>episode: "twins"</td>
</tr>
<tr>
<th>5</th>
<td>1997</td>
<td>dr katz, professional therapist</td>
<td>jon</td>
<td>voice, episode "guess who"</td>
</tr>
<tr>
<th>6</th>
<td>1997</td>
<td>space ghost coast to coast</td>
<td>himself</td>
<td>episode: "mayonnaise"</td>
</tr>
<tr>
<th>7</th>
<td>1997</td>
<td>mr. show</td>
<td>himself</td>
<td>episode: "a white man set them free"</td>
</tr>
<tr>
<th>8</th>
<td>1998</td>
<td>elmopalooza</td>
<td>himself</td>
<td>tv special</td>
</tr>
<tr>
<th>9</th>
<td>1999</td>
<td>spin city</td>
<td>parker</td>
<td>episode: "wall street"</td>
</tr>
<tr>
<th>10</th>
<td>1999-present</td>
<td>the daily show</td>
<td>host</td>
<td>executive producer, writer</td>
</tr>
<tr>
<th>11</th>
<td>2001</td>
<td>43rd annual grammy awards</td>
<td>host</td>
<td>tv special</td>
</tr>
<tr>
<th>12</th>
<td>2002</td>
<td>44th annual grammy awards</td>
<td>host</td>
<td>tv special</td>
</tr>
<tr>
<th>13</th>
<td>2002</td>
<td>saturday night live</td>
<td>host</td>
<td>episode: "jon stewart/india.arie"</td>
</tr>
<tr>
<th>14</th>
<td>2006</td>
<td>78th academy awards</td>
<td>host</td>
<td>tv special</td>
</tr>
<tr>
<th>15</th>
<td>2006</td>
<td>american dad</td>
<td>himself</td>
<td>voice, episode: "irregarding steve"</td>
</tr>
<tr>
<th>16</th>
<td>2007</td>
<td>jack's big music show</td>
<td>brunk stinegrouber</td>
<td>episode: "groundhog day"</td>
</tr>
<tr>
<th>17</th>
<td>2008</td>
<td>the simpsons</td>
<td>himself</td>
<td>voice, episode: "e pluribus wiggum"</td>
</tr>
<tr>
<th>18</th>
<td>2008</td>
<td>80th academy awards</td>
<td>host</td>
<td>tv special</td>
</tr>
<tr>
<th>19</th>
<td>2012</td>
<td>robot chicken</td>
<td>matt trakker, serpentor</td>
<td>voice, episode: "executed by the state"</td>
</tr>
<tr>
<th>20</th>
<td>2013</td>
<td>big time rush</td>
<td>himself</td>
<td>episode: "big time invasion"</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>0</td>
</tr>
</tbody>
</table> | select count ( title ) where title = 11 <table_name> : table | | year | title | role | notes |
|---:|:-------------|:--------------------------------|:------------------------|:----------------------------------------|
| 0 | 1989-1993 | short attention span theater | host | co-presented four seasons |
| 1 | 1993-1995 | the jon stewart show | host | creator, executive producer, writer |
| 2 | 1996 | the larry sanders show | himself | 6 episodes from 1996-1998 |
| 3 | 1997 | the nanny | bobby | episode: "kissing cousins" |
| 4 | 1997 | newsradio | andrew | episode: "twins" |
| 5 | 1997 | dr katz, professional therapist | jon | voice, episode "guess who" |
| 6 | 1997 | space ghost coast to coast | himself | episode: "mayonnaise" |
| 7 | 1997 | mr. show | himself | episode: "a white man set them free" |
| 8 | 1998 | elmopalooza | himself | tv special |
| 9 | 1999 | spin city | parker | episode: "wall street" |
| 10 | 1999-present | the daily show | host | executive producer, writer |
| 11 | 2001 | 43rd annual grammy awards | host | tv special |
| 12 | 2002 | 44th annual grammy awards | host | tv special |
| 13 | 2002 | saturday night live | host | episode: "jon stewart/india.arie" |
| 14 | 2006 | 78th academy awards | host | tv special |
| 15 | 2006 | american dad | himself | voice, episode: "irregarding steve" |
| 16 | 2007 | jack's big music show | brunk stinegrouber | episode: "groundhog day" |
| 17 | 2008 | the simpsons | himself | voice, episode: "e pluribus wiggum" |
| 18 | 2008 | 80th academy awards | host | tv special |
| 19 | 2012 | robot chicken | matt trakker, serpentor | voice, episode: "executed by the state" |
| 20 | 2013 | big time rush | himself | episode: "big time invasion" | | | | count ( "title" ) |
|---:|--------------------:|
| 0 | 0 | | [
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select name where grammy = 1977 col : name | egot completed | emmy | grammy | oscar | tony row 1 : richard rodgers | 1962 (17 years) | 1962 | 1960 | 1945 | 1950 row 2 : helen hayes | 1977 (45 years) | 1953 | 1977 | 1932 | 1947 row 3 : rita moreno | 1977 (16 years) | 1977 | 1972 | 1961 | 1975 row 4 : john gielgud | 1991 (30 years) | 1991 | 1979 | 1981 | 1961 row 5 : audrey hepburn | 1994 (41 years) | 1993 | 1994 | 1953 | 1954 row 6 : marvin hamlisch | 1995 (23 years) | 1995 | 1974 | 1973 | 1976 row 7 : jonathan tunick | 1997 (20 years) | 1982 | 1988 | 1977 | 1997 row 8 : mel brooks | 2001 (34 years) | 1967 | 1998 | 1968 | 2001 row 9 : mike nichols | 2001 (40 years) | 2001 | 1961 | 1967 | 1964 row 10 : whoopi goldberg | 2002 (17 years) | 2002 | 1985 | 1990 | 2002 row 11 : scott rudin | 2012 (28 years) | 1984 | 2012 | 2007 | 1994 row 12 : robert lopez | 2014 (10 years) | 2008 | 2012 | 2014 | 2004 | col : name row 1 : helen hayes | select name where grammy = 1977 <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & egot completed & emmy & grammy & oscar & tony \\
\midrule
0 & richard rodgers & 1962 (17 years) & 1962 & 1960 & 1945 & 1950 \\
1 & helen hayes & 1977 (45 years) & 1953 & 1977 & 1932 & 1947 \\
2 & rita moreno & 1977 (16 years) & 1977 & 1972 & 1961 & 1975 \\
3 & john gielgud & 1991 (30 years) & 1991 & 1979 & 1981 & 1961 \\
4 & audrey hepburn & 1994 (41 years) & 1993 & 1994 & 1953 & 1954 \\
5 & marvin hamlisch & 1995 (23 years) & 1995 & 1974 & 1973 & 1976 \\
6 & jonathan tunick & 1997 (20 years) & 1982 & 1988 & 1977 & 1997 \\
7 & mel brooks & 2001 (34 years) & 1967 & 1998 & 1968 & 2001 \\
8 & mike nichols & 2001 (40 years) & 2001 & 1961 & 1967 & 1964 \\
9 & whoopi goldberg & 2002 (17 years) & 2002 & 1985 & 1990 & 2002 \\
10 & scott rudin & 2012 (28 years) & 1984 & 2012 & 2007 & 1994 \\
11 & robert lopez & 2014 (10 years) & 2008 & 2012 & 2014 & 2004 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & helen hayes \\
\bottomrule
\end{tabular}
| select name where grammy = 1977 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>egot completed</th>
<th>emmy</th>
<th>grammy</th>
<th>oscar</th>
<th>tony</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>richard rodgers</td>
<td>1962 (17 years)</td>
<td>1962</td>
<td>1960</td>
<td>1945</td>
<td>1950</td>
</tr>
<tr>
<th>1</th>
<td>helen hayes</td>
<td>1977 (45 years)</td>
<td>1953</td>
<td>1977</td>
<td>1932</td>
<td>1947</td>
</tr>
<tr>
<th>2</th>
<td>rita moreno</td>
<td>1977 (16 years)</td>
<td>1977</td>
<td>1972</td>
<td>1961</td>
<td>1975</td>
</tr>
<tr>
<th>3</th>
<td>john gielgud</td>
<td>1991 (30 years)</td>
<td>1991</td>
<td>1979</td>
<td>1981</td>
<td>1961</td>
</tr>
<tr>
<th>4</th>
<td>audrey hepburn</td>
<td>1994 (41 years)</td>
<td>1993</td>
<td>1994</td>
<td>1953</td>
<td>1954</td>
</tr>
<tr>
<th>5</th>
<td>marvin hamlisch</td>
<td>1995 (23 years)</td>
<td>1995</td>
<td>1974</td>
<td>1973</td>
<td>1976</td>
</tr>
<tr>
<th>6</th>
<td>jonathan tunick</td>
<td>1997 (20 years)</td>
<td>1982</td>
<td>1988</td>
<td>1977</td>
<td>1997</td>
</tr>
<tr>
<th>7</th>
<td>mel brooks</td>
<td>2001 (34 years)</td>
<td>1967</td>
<td>1998</td>
<td>1968</td>
<td>2001</td>
</tr>
<tr>
<th>8</th>
<td>mike nichols</td>
<td>2001 (40 years)</td>
<td>2001</td>
<td>1961</td>
<td>1967</td>
<td>1964</td>
</tr>
<tr>
<th>9</th>
<td>whoopi goldberg</td>
<td>2002 (17 years)</td>
<td>2002</td>
<td>1985</td>
<td>1990</td>
<td>2002</td>
</tr>
<tr>
<th>10</th>
<td>scott rudin</td>
<td>2012 (28 years)</td>
<td>1984</td>
<td>2012</td>
<td>2007</td>
<td>1994</td>
</tr>
<tr>
<th>11</th>
<td>robert lopez</td>
<td>2014 (10 years)</td>
<td>2008</td>
<td>2012</td>
<td>2014</td>
<td>2004</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>helen hayes</td>
</tr>
</tbody>
</table> | select name where grammy = 1977 <table_name> : table | | name | egot completed | emmy | grammy | oscar | tony |
|---:|:----------------|:-----------------|-------:|---------:|--------:|-------:|
| 0 | richard rodgers | 1962 (17 years) | 1962 | 1960 | 1945 | 1950 |
| 1 | helen hayes | 1977 (45 years) | 1953 | 1977 | 1932 | 1947 |
| 2 | rita moreno | 1977 (16 years) | 1977 | 1972 | 1961 | 1975 |
| 3 | john gielgud | 1991 (30 years) | 1991 | 1979 | 1981 | 1961 |
| 4 | audrey hepburn | 1994 (41 years) | 1993 | 1994 | 1953 | 1954 |
| 5 | marvin hamlisch | 1995 (23 years) | 1995 | 1974 | 1973 | 1976 |
| 6 | jonathan tunick | 1997 (20 years) | 1982 | 1988 | 1977 | 1997 |
| 7 | mel brooks | 2001 (34 years) | 1967 | 1998 | 1968 | 2001 |
| 8 | mike nichols | 2001 (40 years) | 2001 | 1961 | 1967 | 1964 |
| 9 | whoopi goldberg | 2002 (17 years) | 2002 | 1985 | 1990 | 2002 |
| 10 | scott rudin | 2012 (28 years) | 1984 | 2012 | 2007 | 1994 |
| 11 | robert lopez | 2014 (10 years) | 2008 | 2012 | 2014 | 2004 | | | | name |
|---:|:------------|
| 0 | helen hayes | | [
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select count ( opponent ) where week = 3 col : week | date | opponent | result | game site | attendance row 1 : 1 | 1960-09-11 00:00:00 | at new york titans | l 27-3 | polo grounds | 10,200 row 2 : 2 | 1960-09-18 00:00:00 | denver broncos | l 27-21 | war memorial stadium | 15,229 row 3 : 3 | 1960-09-23 00:00:00 | at boston patriots | w 13-0 | nickerson field | 20,732 row 4 : 4 | 1960-10-02 00:00:00 | los angeles chargers | l 24-10 | war memorial stadium | 15,821 row 5 : 6 | 1960-10-16 00:00:00 | new york titans | l 17-13 | war memorial stadium | 14,988 row 6 : 7 | 1960-10-23 00:00:00 | oakland raiders | w 38-9 | war memorial stadium | 8,876 row 7 : 8 | 1960-10-30 00:00:00 | houston oilers | w 25-24 | war memorial stadium | 23,001 row 8 : 9 | 1960-11-06 00:00:00 | dallas texans | l 45-28 | war memorial stadium | 19,610 row 9 : 10 | 1960-11-13 00:00:00 | at oakland raiders | l 20-7 | kezar stadium | 8,800 row 10 : 11 | 1960-11-20 00:00:00 | at los angeles chargers | w 32-3 | los angeles memorial coliseum | 16,161 row 11 : 12 | 1960-11-27 00:00:00 | at denver broncos | t 38-38 | bears stadium | 7,785 row 12 : 13 | 1960-12-04 00:00:00 | boston patriots | w 38-14 | war memorial stadium | 14,335 row 13 : 14 | 1960-12-11 00:00:00 | at houston oilers | l 31-23 | jeppesen stadium | 25,243 row 14 : 15 | 1960-12-18 00:00:00 | at dallas texans | l 24-7 | cotton bowl | 18,000 | col : count ( "opponent" ) row 1 : 1 | select count ( opponent ) where week = 3 <table_name> : table \begin{tabular}{lllllll}
\toprule
& week & date & opponent & result & game site & attendance \\
\midrule
0 & 1 & 1960-09-11 00:00:00 & at new york titans & l 27-3 & polo grounds & 10,200 \\
1 & 2 & 1960-09-18 00:00:00 & denver broncos & l 27-21 & war memorial stadium & 15,229 \\
2 & 3 & 1960-09-23 00:00:00 & at boston patriots & w 13-0 & nickerson field & 20,732 \\
3 & 4 & 1960-10-02 00:00:00 & los angeles chargers & l 24-10 & war memorial stadium & 15,821 \\
4 & 6 & 1960-10-16 00:00:00 & new york titans & l 17-13 & war memorial stadium & 14,988 \\
5 & 7 & 1960-10-23 00:00:00 & oakland raiders & w 38-9 & war memorial stadium & 8,876 \\
6 & 8 & 1960-10-30 00:00:00 & houston oilers & w 25-24 & war memorial stadium & 23,001 \\
7 & 9 & 1960-11-06 00:00:00 & dallas texans & l 45-28 & war memorial stadium & 19,610 \\
8 & 10 & 1960-11-13 00:00:00 & at oakland raiders & l 20-7 & kezar stadium & 8,800 \\
9 & 11 & 1960-11-20 00:00:00 & at los angeles chargers & w 32-3 & los angeles memorial coliseum & 16,161 \\
10 & 12 & 1960-11-27 00:00:00 & at denver broncos & t 38-38 & bears stadium & 7,785 \\
11 & 13 & 1960-12-04 00:00:00 & boston patriots & w 38-14 & war memorial stadium & 14,335 \\
12 & 14 & 1960-12-11 00:00:00 & at houston oilers & l 31-23 & jeppesen stadium & 25,243 \\
13 & 15 & 1960-12-18 00:00:00 & at dallas texans & l 24-7 & cotton bowl & 18,000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "opponent" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( opponent ) where week = 3 <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>result</th>
<th>game site</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1960-09-11 00:00:00</td>
<td>at new york titans</td>
<td>l 27-3</td>
<td>polo grounds</td>
<td>10,200</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1960-09-18 00:00:00</td>
<td>denver broncos</td>
<td>l 27-21</td>
<td>war memorial stadium</td>
<td>15,229</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1960-09-23 00:00:00</td>
<td>at boston patriots</td>
<td>w 13-0</td>
<td>nickerson field</td>
<td>20,732</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1960-10-02 00:00:00</td>
<td>los angeles chargers</td>
<td>l 24-10</td>
<td>war memorial stadium</td>
<td>15,821</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>1960-10-16 00:00:00</td>
<td>new york titans</td>
<td>l 17-13</td>
<td>war memorial stadium</td>
<td>14,988</td>
</tr>
<tr>
<th>5</th>
<td>7</td>
<td>1960-10-23 00:00:00</td>
<td>oakland raiders</td>
<td>w 38-9</td>
<td>war memorial stadium</td>
<td>8,876</td>
</tr>
<tr>
<th>6</th>
<td>8</td>
<td>1960-10-30 00:00:00</td>
<td>houston oilers</td>
<td>w 25-24</td>
<td>war memorial stadium</td>
<td>23,001</td>
</tr>
<tr>
<th>7</th>
<td>9</td>
<td>1960-11-06 00:00:00</td>
<td>dallas texans</td>
<td>l 45-28</td>
<td>war memorial stadium</td>
<td>19,610</td>
</tr>
<tr>
<th>8</th>
<td>10</td>
<td>1960-11-13 00:00:00</td>
<td>at oakland raiders</td>
<td>l 20-7</td>
<td>kezar stadium</td>
<td>8,800</td>
</tr>
<tr>
<th>9</th>
<td>11</td>
<td>1960-11-20 00:00:00</td>
<td>at los angeles chargers</td>
<td>w 32-3</td>
<td>los angeles memorial coliseum</td>
<td>16,161</td>
</tr>
<tr>
<th>10</th>
<td>12</td>
<td>1960-11-27 00:00:00</td>
<td>at denver broncos</td>
<td>t 38-38</td>
<td>bears stadium</td>
<td>7,785</td>
</tr>
<tr>
<th>11</th>
<td>13</td>
<td>1960-12-04 00:00:00</td>
<td>boston patriots</td>
<td>w 38-14</td>
<td>war memorial stadium</td>
<td>14,335</td>
</tr>
<tr>
<th>12</th>
<td>14</td>
<td>1960-12-11 00:00:00</td>
<td>at houston oilers</td>
<td>l 31-23</td>
<td>jeppesen stadium</td>
<td>25,243</td>
</tr>
<tr>
<th>13</th>
<td>15</td>
<td>1960-12-18 00:00:00</td>
<td>at dallas texans</td>
<td>l 24-7</td>
<td>cotton bowl</td>
<td>18,000</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>1</td>
</tr>
</tbody>
</table> | select count ( opponent ) where week = 3 <table_name> : table | | week | date | opponent | result | game site | attendance |
|---:|-------:|:--------------------|:------------------------|:---------|:------------------------------|:-------------|
| 0 | 1 | 1960-09-11 00:00:00 | at new york titans | l 27-3 | polo grounds | 10,200 |
| 1 | 2 | 1960-09-18 00:00:00 | denver broncos | l 27-21 | war memorial stadium | 15,229 |
| 2 | 3 | 1960-09-23 00:00:00 | at boston patriots | w 13-0 | nickerson field | 20,732 |
| 3 | 4 | 1960-10-02 00:00:00 | los angeles chargers | l 24-10 | war memorial stadium | 15,821 |
| 4 | 6 | 1960-10-16 00:00:00 | new york titans | l 17-13 | war memorial stadium | 14,988 |
| 5 | 7 | 1960-10-23 00:00:00 | oakland raiders | w 38-9 | war memorial stadium | 8,876 |
| 6 | 8 | 1960-10-30 00:00:00 | houston oilers | w 25-24 | war memorial stadium | 23,001 |
| 7 | 9 | 1960-11-06 00:00:00 | dallas texans | l 45-28 | war memorial stadium | 19,610 |
| 8 | 10 | 1960-11-13 00:00:00 | at oakland raiders | l 20-7 | kezar stadium | 8,800 |
| 9 | 11 | 1960-11-20 00:00:00 | at los angeles chargers | w 32-3 | los angeles memorial coliseum | 16,161 |
| 10 | 12 | 1960-11-27 00:00:00 | at denver broncos | t 38-38 | bears stadium | 7,785 |
| 11 | 13 | 1960-12-04 00:00:00 | boston patriots | w 38-14 | war memorial stadium | 14,335 |
| 12 | 14 | 1960-12-11 00:00:00 | at houston oilers | l 31-23 | jeppesen stadium | 25,243 |
| 13 | 15 | 1960-12-18 00:00:00 | at dallas texans | l 24-7 | cotton bowl | 18,000 | | | | count ( "opponent" ) |
|---:|-----------------------:|
| 0 | 1 | | [
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select country where place = 't7' col : place | player | country | score | to par row 1 : 1 | retief goosen | south africa | 68-70-69=207 | -3 row 2 : t2 | olin browne | united states | 67-71-72=210 | e row 3 : t2 | jason gore | united states | 71-67-72=210 | e row 4 : t4 | michael campbell | new zealand | 71-69-71=211 | 1 row 5 : t4 | mark hensby | australia | 71-68-72=211 | 1 row 6 : 6 | david toms | united states | 70-72-70=212 | 2 row 7 : t7 | k. j. choi | south korea | 69-70-74=213 | 3 row 8 : t7 | peter hedblom | sweden | 77-66-70=213 | 3 row 9 : t7 | lee westwood | england | 68-72-73=213 | 3 row 10 : t7 | tiger woods | united states | 70-71-72=213 | 3 | col : count ( "country" ) row 1 : 4 | select country where place = 't7' <table_name> : table \begin{tabular}{llllll}
\toprule
& place & player & country & score & to par \\
\midrule
0 & 1 & retief goosen & south africa & 68-70-69=207 & -3 \\
1 & t2 & olin browne & united states & 67-71-72=210 & e \\
2 & t2 & jason gore & united states & 71-67-72=210 & e \\
3 & t4 & michael campbell & new zealand & 71-69-71=211 & 1 \\
4 & t4 & mark hensby & australia & 71-68-72=211 & 1 \\
5 & 6 & david toms & united states & 70-72-70=212 & 2 \\
6 & t7 & k. j. choi & south korea & 69-70-74=213 & 3 \\
7 & t7 & peter hedblom & sweden & 77-66-70=213 & 3 \\
8 & t7 & lee westwood & england & 68-72-73=213 & 3 \\
9 & t7 & tiger woods & united states & 70-71-72=213 & 3 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "country" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select country where place = 't7' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>player</th>
<th>country</th>
<th>score</th>
<th>to par</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>retief goosen</td>
<td>south africa</td>
<td>68-70-69=207</td>
<td>-3</td>
</tr>
<tr>
<th>1</th>
<td>t2</td>
<td>olin browne</td>
<td>united states</td>
<td>67-71-72=210</td>
<td>e</td>
</tr>
<tr>
<th>2</th>
<td>t2</td>
<td>jason gore</td>
<td>united states</td>
<td>71-67-72=210</td>
<td>e</td>
</tr>
<tr>
<th>3</th>
<td>t4</td>
<td>michael campbell</td>
<td>new zealand</td>
<td>71-69-71=211</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>t4</td>
<td>mark hensby</td>
<td>australia</td>
<td>71-68-72=211</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>david toms</td>
<td>united states</td>
<td>70-72-70=212</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>t7</td>
<td>k. j. choi</td>
<td>south korea</td>
<td>69-70-74=213</td>
<td>3</td>
</tr>
<tr>
<th>7</th>
<td>t7</td>
<td>peter hedblom</td>
<td>sweden</td>
<td>77-66-70=213</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>t7</td>
<td>lee westwood</td>
<td>england</td>
<td>68-72-73=213</td>
<td>3</td>
</tr>
<tr>
<th>9</th>
<td>t7</td>
<td>tiger woods</td>
<td>united states</td>
<td>70-71-72=213</td>
<td>3</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "country" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select country where place = 't7' <table_name> : table | | place | player | country | score | to par |
|---:|:--------|:-----------------|:--------------|:-------------|:---------|
| 0 | 1 | retief goosen | south africa | 68-70-69=207 | -3 |
| 1 | t2 | olin browne | united states | 67-71-72=210 | e |
| 2 | t2 | jason gore | united states | 71-67-72=210 | e |
| 3 | t4 | michael campbell | new zealand | 71-69-71=211 | 1 |
| 4 | t4 | mark hensby | australia | 71-68-72=211 | 1 |
| 5 | 6 | david toms | united states | 70-72-70=212 | 2 |
| 6 | t7 | k. j. choi | south korea | 69-70-74=213 | 3 |
| 7 | t7 | peter hedblom | sweden | 77-66-70=213 | 3 |
| 8 | t7 | lee westwood | england | 68-72-73=213 | 3 |
| 9 | t7 | tiger woods | united states | 70-71-72=213 | 3 | | | | count ( "country" ) |
|---:|----------------------:|
| 0 | 4 | | [
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] |
select count ( sheriff ) where sheriff = 'samuel carll' col : sheriff | start of term row 1 : josiah hobart | 1683 row 2 : john mulford | 1701 row 3 : hugh gray | 1702 row 4 : john brush | 1710 row 5 : daniel youngs | 1718 row 6 : samuel dayton | 1723 row 7 : william sell | 1728 row 8 : joseph smith | 1730 row 9 : david corrie | 1731 row 10 : jacob conklin | 1734 row 11 : thomas higbe | 1740 row 12 : james muirson | 1774 row 13 : thomas wickes | 1785 row 14 : silas halsey | 1787 row 15 : thomas wickes | 1791 row 16 : phinaes carll | 1799 row 17 : josiah reeve | 1803 row 18 : phinaes smith | 1807 row 19 : josiah reeve | 1808 row 20 : benjamin brewster | 1810 row 21 : josiah reeve | 1811 row 22 : benjamin brewster | 1812 row 23 : josiah reeve | 1813 row 24 : nathaniel conklin | 1814 row 25 : josiah reeve | 1815 row 26 : samuel carll | 1819 row 27 : abraham gardiner | 1821 row 28 : samuel smith | 1826 row 29 : abraham gardiner | 1829 row 30 : richard smith | 1832 row 31 : silas horton | 1835 row 32 : samuel miller | 1838 row 33 : david brush | 1841 row 34 : henry penny | 1844 row 35 : david rose | 1847 row 36 : john clark | 1850 row 37 : samuel phillips | 1855 row 38 : george carman | 1856 row 39 : stephen wilson | 1859 row 40 : daniel osborn | 1862 row 41 : george smith | 1868 row 42 : j. henry perkins | 1871 row 43 : egbert lewis | 1874 row 44 : george cooper | 1877 row 45 : robert petty | 1888 row 46 : selah brewster | 1883 row 47 : henry halsey | 1886 row 48 : robert petty | 1888 row 49 : a. m. darling | 1891 row 50 : benjamin wood | 1897 row 51 : j. sheridan wells | 1900 row 52 : henry preston | 1903 row 53 : john wells | 1906 row 54 : charles platt | 1909 row 55 : melville brush | 1912 row 56 : d. henry brown | 1913 row 57 : charles o'dell | 1914 row 58 : amza biggs | 1917 row 59 : john kelly | 1920 row 60 : amza biggs | 1923 row 61 : burton howe | 1926 row 62 : ellis taylor | 1929 row 63 : joseph warta | 1932 row 64 : william mccollom | 1935 row 65 : jacob dreyer | 1938 row 66 : john levy | 1941 row 67 : william mccollom | 1942 row 68 : charles dominy | 1957 row 69 : frank gross | 1962 row 70 : philip corso | 1970 row 71 : donald dilworth | 1976 row 72 : john finnerty | 1977 row 73 : eugene dooley | 1986 row 74 : patrick mahoney | 1990 row 75 : alfred c. tisch | 2002 row 76 : vincent f. demarco | 2006 | col : count ( "sheriff" ) row 1 : 1 | select count ( sheriff ) where sheriff = 'samuel carll' <table_name> : table \begin{tabular}{lll}
\toprule
& sheriff & start of term \\
\midrule
0 & josiah hobart & 1683 \\
1 & john mulford & 1701 \\
2 & hugh gray & 1702 \\
3 & john brush & 1710 \\
4 & daniel youngs & 1718 \\
5 & samuel dayton & 1723 \\
6 & william sell & 1728 \\
7 & joseph smith & 1730 \\
8 & david corrie & 1731 \\
9 & jacob conklin & 1734 \\
10 & thomas higbe & 1740 \\
11 & james muirson & 1774 \\
12 & thomas wickes & 1785 \\
13 & silas halsey & 1787 \\
14 & thomas wickes & 1791 \\
15 & phinaes carll & 1799 \\
16 & josiah reeve & 1803 \\
17 & phinaes smith & 1807 \\
18 & josiah reeve & 1808 \\
19 & benjamin brewster & 1810 \\
20 & josiah reeve & 1811 \\
21 & benjamin brewster & 1812 \\
22 & josiah reeve & 1813 \\
23 & nathaniel conklin & 1814 \\
24 & josiah reeve & 1815 \\
25 & samuel carll & 1819 \\
26 & abraham gardiner & 1821 \\
27 & samuel smith & 1826 \\
28 & abraham gardiner & 1829 \\
29 & richard smith & 1832 \\
30 & silas horton & 1835 \\
31 & samuel miller & 1838 \\
32 & david brush & 1841 \\
33 & henry penny & 1844 \\
34 & david rose & 1847 \\
35 & john clark & 1850 \\
36 & samuel phillips & 1855 \\
37 & george carman & 1856 \\
38 & stephen wilson & 1859 \\
39 & daniel osborn & 1862 \\
40 & george smith & 1868 \\
41 & j. henry perkins & 1871 \\
42 & egbert lewis & 1874 \\
43 & george cooper & 1877 \\
44 & robert petty & 1888 \\
45 & selah brewster & 1883 \\
46 & henry halsey & 1886 \\
47 & robert petty & 1888 \\
48 & a. m. darling & 1891 \\
49 & benjamin wood & 1897 \\
50 & j. sheridan wells & 1900 \\
51 & henry preston & 1903 \\
52 & john wells & 1906 \\
53 & charles platt & 1909 \\
54 & melville brush & 1912 \\
55 & d. henry brown & 1913 \\
56 & charles o'dell & 1914 \\
57 & amza biggs & 1917 \\
58 & john kelly & 1920 \\
59 & amza biggs & 1923 \\
60 & burton howe & 1926 \\
61 & ellis taylor & 1929 \\
62 & joseph warta & 1932 \\
63 & william mccollom & 1935 \\
64 & jacob dreyer & 1938 \\
65 & john levy & 1941 \\
66 & william mccollom & 1942 \\
67 & charles dominy & 1957 \\
68 & frank gross & 1962 \\
69 & philip corso & 1970 \\
70 & donald dilworth & 1976 \\
71 & john finnerty & 1977 \\
72 & eugene dooley & 1986 \\
73 & patrick mahoney & 1990 \\
74 & alfred c. tisch & 2002 \\
75 & vincent f. demarco & 2006 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "sheriff" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( sheriff ) where sheriff = 'samuel carll' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>sheriff</th>
<th>start of term</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>josiah hobart</td>
<td>1683</td>
</tr>
<tr>
<th>1</th>
<td>john mulford</td>
<td>1701</td>
</tr>
<tr>
<th>2</th>
<td>hugh gray</td>
<td>1702</td>
</tr>
<tr>
<th>3</th>
<td>john brush</td>
<td>1710</td>
</tr>
<tr>
<th>4</th>
<td>daniel youngs</td>
<td>1718</td>
</tr>
<tr>
<th>5</th>
<td>samuel dayton</td>
<td>1723</td>
</tr>
<tr>
<th>6</th>
<td>william sell</td>
<td>1728</td>
</tr>
<tr>
<th>7</th>
<td>joseph smith</td>
<td>1730</td>
</tr>
<tr>
<th>8</th>
<td>david corrie</td>
<td>1731</td>
</tr>
<tr>
<th>9</th>
<td>jacob conklin</td>
<td>1734</td>
</tr>
<tr>
<th>10</th>
<td>thomas higbe</td>
<td>1740</td>
</tr>
<tr>
<th>11</th>
<td>james muirson</td>
<td>1774</td>
</tr>
<tr>
<th>12</th>
<td>thomas wickes</td>
<td>1785</td>
</tr>
<tr>
<th>13</th>
<td>silas halsey</td>
<td>1787</td>
</tr>
<tr>
<th>14</th>
<td>thomas wickes</td>
<td>1791</td>
</tr>
<tr>
<th>15</th>
<td>phinaes carll</td>
<td>1799</td>
</tr>
<tr>
<th>16</th>
<td>josiah reeve</td>
<td>1803</td>
</tr>
<tr>
<th>17</th>
<td>phinaes smith</td>
<td>1807</td>
</tr>
<tr>
<th>18</th>
<td>josiah reeve</td>
<td>1808</td>
</tr>
<tr>
<th>19</th>
<td>benjamin brewster</td>
<td>1810</td>
</tr>
<tr>
<th>20</th>
<td>josiah reeve</td>
<td>1811</td>
</tr>
<tr>
<th>21</th>
<td>benjamin brewster</td>
<td>1812</td>
</tr>
<tr>
<th>22</th>
<td>josiah reeve</td>
<td>1813</td>
</tr>
<tr>
<th>23</th>
<td>nathaniel conklin</td>
<td>1814</td>
</tr>
<tr>
<th>24</th>
<td>josiah reeve</td>
<td>1815</td>
</tr>
<tr>
<th>25</th>
<td>samuel carll</td>
<td>1819</td>
</tr>
<tr>
<th>26</th>
<td>abraham gardiner</td>
<td>1821</td>
</tr>
<tr>
<th>27</th>
<td>samuel smith</td>
<td>1826</td>
</tr>
<tr>
<th>28</th>
<td>abraham gardiner</td>
<td>1829</td>
</tr>
<tr>
<th>29</th>
<td>richard smith</td>
<td>1832</td>
</tr>
<tr>
<th>30</th>
<td>silas horton</td>
<td>1835</td>
</tr>
<tr>
<th>31</th>
<td>samuel miller</td>
<td>1838</td>
</tr>
<tr>
<th>32</th>
<td>david brush</td>
<td>1841</td>
</tr>
<tr>
<th>33</th>
<td>henry penny</td>
<td>1844</td>
</tr>
<tr>
<th>34</th>
<td>david rose</td>
<td>1847</td>
</tr>
<tr>
<th>35</th>
<td>john clark</td>
<td>1850</td>
</tr>
<tr>
<th>36</th>
<td>samuel phillips</td>
<td>1855</td>
</tr>
<tr>
<th>37</th>
<td>george carman</td>
<td>1856</td>
</tr>
<tr>
<th>38</th>
<td>stephen wilson</td>
<td>1859</td>
</tr>
<tr>
<th>39</th>
<td>daniel osborn</td>
<td>1862</td>
</tr>
<tr>
<th>40</th>
<td>george smith</td>
<td>1868</td>
</tr>
<tr>
<th>41</th>
<td>j. henry perkins</td>
<td>1871</td>
</tr>
<tr>
<th>42</th>
<td>egbert lewis</td>
<td>1874</td>
</tr>
<tr>
<th>43</th>
<td>george cooper</td>
<td>1877</td>
</tr>
<tr>
<th>44</th>
<td>robert petty</td>
<td>1888</td>
</tr>
<tr>
<th>45</th>
<td>selah brewster</td>
<td>1883</td>
</tr>
<tr>
<th>46</th>
<td>henry halsey</td>
<td>1886</td>
</tr>
<tr>
<th>47</th>
<td>robert petty</td>
<td>1888</td>
</tr>
<tr>
<th>48</th>
<td>a. m. darling</td>
<td>1891</td>
</tr>
<tr>
<th>49</th>
<td>benjamin wood</td>
<td>1897</td>
</tr>
<tr>
<th>50</th>
<td>j. sheridan wells</td>
<td>1900</td>
</tr>
<tr>
<th>51</th>
<td>henry preston</td>
<td>1903</td>
</tr>
<tr>
<th>52</th>
<td>john wells</td>
<td>1906</td>
</tr>
<tr>
<th>53</th>
<td>charles platt</td>
<td>1909</td>
</tr>
<tr>
<th>54</th>
<td>melville brush</td>
<td>1912</td>
</tr>
<tr>
<th>55</th>
<td>d. henry brown</td>
<td>1913</td>
</tr>
<tr>
<th>56</th>
<td>charles o'dell</td>
<td>1914</td>
</tr>
<tr>
<th>57</th>
<td>amza biggs</td>
<td>1917</td>
</tr>
<tr>
<th>58</th>
<td>john kelly</td>
<td>1920</td>
</tr>
<tr>
<th>59</th>
<td>amza biggs</td>
<td>1923</td>
</tr>
<tr>
<th>60</th>
<td>burton howe</td>
<td>1926</td>
</tr>
<tr>
<th>61</th>
<td>ellis taylor</td>
<td>1929</td>
</tr>
<tr>
<th>62</th>
<td>joseph warta</td>
<td>1932</td>
</tr>
<tr>
<th>63</th>
<td>william mccollom</td>
<td>1935</td>
</tr>
<tr>
<th>64</th>
<td>jacob dreyer</td>
<td>1938</td>
</tr>
<tr>
<th>65</th>
<td>john levy</td>
<td>1941</td>
</tr>
<tr>
<th>66</th>
<td>william mccollom</td>
<td>1942</td>
</tr>
<tr>
<th>67</th>
<td>charles dominy</td>
<td>1957</td>
</tr>
<tr>
<th>68</th>
<td>frank gross</td>
<td>1962</td>
</tr>
<tr>
<th>69</th>
<td>philip corso</td>
<td>1970</td>
</tr>
<tr>
<th>70</th>
<td>donald dilworth</td>
<td>1976</td>
</tr>
<tr>
<th>71</th>
<td>john finnerty</td>
<td>1977</td>
</tr>
<tr>
<th>72</th>
<td>eugene dooley</td>
<td>1986</td>
</tr>
<tr>
<th>73</th>
<td>patrick mahoney</td>
<td>1990</td>
</tr>
<tr>
<th>74</th>
<td>alfred c. tisch</td>
<td>2002</td>
</tr>
<tr>
<th>75</th>
<td>vincent f. demarco</td>
<td>2006</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "sheriff" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( sheriff ) where sheriff = 'samuel carll' <table_name> : table | | sheriff | start of term |
|---:|:-------------------|----------------:|
| 0 | josiah hobart | 1683 |
| 1 | john mulford | 1701 |
| 2 | hugh gray | 1702 |
| 3 | john brush | 1710 |
| 4 | daniel youngs | 1718 |
| 5 | samuel dayton | 1723 |
| 6 | william sell | 1728 |
| 7 | joseph smith | 1730 |
| 8 | david corrie | 1731 |
| 9 | jacob conklin | 1734 |
| 10 | thomas higbe | 1740 |
| 11 | james muirson | 1774 |
| 12 | thomas wickes | 1785 |
| 13 | silas halsey | 1787 |
| 14 | thomas wickes | 1791 |
| 15 | phinaes carll | 1799 |
| 16 | josiah reeve | 1803 |
| 17 | phinaes smith | 1807 |
| 18 | josiah reeve | 1808 |
| 19 | benjamin brewster | 1810 |
| 20 | josiah reeve | 1811 |
| 21 | benjamin brewster | 1812 |
| 22 | josiah reeve | 1813 |
| 23 | nathaniel conklin | 1814 |
| 24 | josiah reeve | 1815 |
| 25 | samuel carll | 1819 |
| 26 | abraham gardiner | 1821 |
| 27 | samuel smith | 1826 |
| 28 | abraham gardiner | 1829 |
| 29 | richard smith | 1832 |
| 30 | silas horton | 1835 |
| 31 | samuel miller | 1838 |
| 32 | david brush | 1841 |
| 33 | henry penny | 1844 |
| 34 | david rose | 1847 |
| 35 | john clark | 1850 |
| 36 | samuel phillips | 1855 |
| 37 | george carman | 1856 |
| 38 | stephen wilson | 1859 |
| 39 | daniel osborn | 1862 |
| 40 | george smith | 1868 |
| 41 | j. henry perkins | 1871 |
| 42 | egbert lewis | 1874 |
| 43 | george cooper | 1877 |
| 44 | robert petty | 1888 |
| 45 | selah brewster | 1883 |
| 46 | henry halsey | 1886 |
| 47 | robert petty | 1888 |
| 48 | a. m. darling | 1891 |
| 49 | benjamin wood | 1897 |
| 50 | j. sheridan wells | 1900 |
| 51 | henry preston | 1903 |
| 52 | john wells | 1906 |
| 53 | charles platt | 1909 |
| 54 | melville brush | 1912 |
| 55 | d. henry brown | 1913 |
| 56 | charles o'dell | 1914 |
| 57 | amza biggs | 1917 |
| 58 | john kelly | 1920 |
| 59 | amza biggs | 1923 |
| 60 | burton howe | 1926 |
| 61 | ellis taylor | 1929 |
| 62 | joseph warta | 1932 |
| 63 | william mccollom | 1935 |
| 64 | jacob dreyer | 1938 |
| 65 | john levy | 1941 |
| 66 | william mccollom | 1942 |
| 67 | charles dominy | 1957 |
| 68 | frank gross | 1962 |
| 69 | philip corso | 1970 |
| 70 | donald dilworth | 1976 |
| 71 | john finnerty | 1977 |
| 72 | eugene dooley | 1986 |
| 73 | patrick mahoney | 1990 |
| 74 | alfred c. tisch | 2002 |
| 75 | vincent f. demarco | 2006 | | | | count ( "sheriff" ) |
|---:|----------------------:|
| 0 | 1 | | [
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select country where biodiversity > 8642 col : country | amphibians | birds | mammals | reptile | total terrestrial vertebrates | vascular plants | biodiversity row 1 : belize | 46 | 544 | 147 | 140 | 877 | 2894 | 3771 row 2 : costa rica | 183 | 838 | 232 | 258 | 1511 | 12119 | 13630 row 3 : el salvador | 30 | 434 | 137 | 106 | 707 | 2911 | 3618 row 4 : guatemala | 133 | 684 | 193 | 236 | 1246 | 8681 | 9927 row 5 : honduras | 101 | 699 | 201 | 213 | 1214 | 5680 | 6894 row 6 : nicaragua | 61 | 632 | 181 | 178 | 1052 | 7590 | 8642 row 7 : panama | 182 | 904 | 241 | 242 | 1569 | 9915 | 11484 | col : count ( "country" ) row 1 : 1 | select country where biodiversity > 8642 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& country & amphibians & birds & mammals & reptile & total terrestrial vertebrates & vascular plants & biodiversity \\
\midrule
0 & belize & 46 & 544 & 147 & 140 & 877 & 2894 & 3771 \\
1 & costa rica & 183 & 838 & 232 & 258 & 1511 & 12119 & 13630 \\
2 & el salvador & 30 & 434 & 137 & 106 & 707 & 2911 & 3618 \\
3 & guatemala & 133 & 684 & 193 & 236 & 1246 & 8681 & 9927 \\
4 & honduras & 101 & 699 & 201 & 213 & 1214 & 5680 & 6894 \\
5 & nicaragua & 61 & 632 & 181 & 178 & 1052 & 7590 & 8642 \\
6 & panama & 182 & 904 & 241 & 242 & 1569 & 9915 & 11484 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "country" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select country where biodiversity > 8642 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>country</th>
<th>amphibians</th>
<th>birds</th>
<th>mammals</th>
<th>reptile</th>
<th>total terrestrial vertebrates</th>
<th>vascular plants</th>
<th>biodiversity</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>belize</td>
<td>46</td>
<td>544</td>
<td>147</td>
<td>140</td>
<td>877</td>
<td>2894</td>
<td>3771</td>
</tr>
<tr>
<th>1</th>
<td>costa rica</td>
<td>183</td>
<td>838</td>
<td>232</td>
<td>258</td>
<td>1511</td>
<td>12119</td>
<td>13630</td>
</tr>
<tr>
<th>2</th>
<td>el salvador</td>
<td>30</td>
<td>434</td>
<td>137</td>
<td>106</td>
<td>707</td>
<td>2911</td>
<td>3618</td>
</tr>
<tr>
<th>3</th>
<td>guatemala</td>
<td>133</td>
<td>684</td>
<td>193</td>
<td>236</td>
<td>1246</td>
<td>8681</td>
<td>9927</td>
</tr>
<tr>
<th>4</th>
<td>honduras</td>
<td>101</td>
<td>699</td>
<td>201</td>
<td>213</td>
<td>1214</td>
<td>5680</td>
<td>6894</td>
</tr>
<tr>
<th>5</th>
<td>nicaragua</td>
<td>61</td>
<td>632</td>
<td>181</td>
<td>178</td>
<td>1052</td>
<td>7590</td>
<td>8642</td>
</tr>
<tr>
<th>6</th>
<td>panama</td>
<td>182</td>
<td>904</td>
<td>241</td>
<td>242</td>
<td>1569</td>
<td>9915</td>
<td>11484</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "country" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select country where biodiversity > 8642 <table_name> : table | | country | amphibians | birds | mammals | reptile | total terrestrial vertebrates | vascular plants | biodiversity |
|---:|:------------|-------------:|--------:|----------:|----------:|--------------------------------:|------------------:|---------------:|
| 0 | belize | 46 | 544 | 147 | 140 | 877 | 2894 | 3771 |
| 1 | costa rica | 183 | 838 | 232 | 258 | 1511 | 12119 | 13630 |
| 2 | el salvador | 30 | 434 | 137 | 106 | 707 | 2911 | 3618 |
| 3 | guatemala | 133 | 684 | 193 | 236 | 1246 | 8681 | 9927 |
| 4 | honduras | 101 | 699 | 201 | 213 | 1214 | 5680 | 6894 |
| 5 | nicaragua | 61 | 632 | 181 | 178 | 1052 | 7590 | 8642 |
| 6 | panama | 182 | 904 | 241 | 242 | 1569 | 9915 | 11484 | | | | count ( "country" ) |
|---:|----------------------:|
| 0 | 1 | | [
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select sum ( chart positions can country ) where album = 'singles only' col : year | song | chart positions us country | chart positions can country | album row 1 : 1968 | "god help you woman" | 32 | 24 | singles only row 2 : 1969 | "please take me back" | 40 | none | singles only row 3 : 1969 | "i'm not through loving you" | 52 | none | singles only row 4 : 1969 | "molly" | 53 | none | singles only row 5 : 1973 | "i see his love all over you" | 67 | none | singles only row 6 : 1974 | "fool passin' through" | 68 | none | singles only row 7 : 1974 | "forgettin' 'bout you" | 51 | none | singles only row 8 : 1975 | "one, two, three (never gonna fall in love again)" | 88 | none | singles only row 9 : 1975 | "woman, woman" | 43 | 46 | singles only row 10 : 1976 | "she's free but she's not easy" | 66 | none | singles only row 11 : 1977 | "chasin' my tail" | 88 | none | singles only row 12 : 1977 | "don't let my love stand in your way" | 86 | none | singles only row 13 : 1983 | "when you're not a lady" | 16 | none | the man in the mirror row 14 : 1983 | "you got me running" | 28 | none | the man in the mirror row 15 : 1983 | "the man in the mirror" | 17 | none | the man in the mirror row 16 : 1984 | "if i could only dance with you" | 10 | 10 | the man in the mirror row 17 : 1984 | "you're gettin' to me again" | 1 | 3 | the man in the mirror row 18 : 1984 | "let me down easy" | 16 | 33 | the man in the mirror row 19 : 1985 | "i'll be your fool tonight" | 54 | none | past the point of no return row 20 : 1985 | "in another minute" | 27 | none | past the point of no return row 21 : 1986 | "if i don't love you" | 53 | none | past the point of no return row 22 : 1986 | "the lights of albuquerque" | 40 | none | everybody knows i'm yours | col : count ( "chart positions can country" ) row 1 : 12 | select sum ( chart positions can country ) where album = 'singles only' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & song & chart positions us country & chart positions can country & album \\
\midrule
0 & 1968 & "god help you woman" & 32 & 24 & singles only \\
1 & 1969 & "please take me back" & 40 & none & singles only \\
2 & 1969 & "i'm not through loving you" & 52 & none & singles only \\
3 & 1969 & "molly" & 53 & none & singles only \\
4 & 1973 & "i see his love all over you" & 67 & none & singles only \\
5 & 1974 & "fool passin' through" & 68 & none & singles only \\
6 & 1974 & "forgettin' 'bout you" & 51 & none & singles only \\
7 & 1975 & "one, two, three (never gonna fall in love again)" & 88 & none & singles only \\
8 & 1975 & "woman, woman" & 43 & 46 & singles only \\
9 & 1976 & "she's free but she's not easy" & 66 & none & singles only \\
10 & 1977 & "chasin' my tail" & 88 & none & singles only \\
11 & 1977 & "don't let my love stand in your way" & 86 & none & singles only \\
12 & 1983 & "when you're not a lady" & 16 & none & the man in the mirror \\
13 & 1983 & "you got me running" & 28 & none & the man in the mirror \\
14 & 1983 & "the man in the mirror" & 17 & none & the man in the mirror \\
15 & 1984 & "if i could only dance with you" & 10 & 10 & the man in the mirror \\
16 & 1984 & "you're gettin' to me again" & 1 & 3 & the man in the mirror \\
17 & 1984 & "let me down easy" & 16 & 33 & the man in the mirror \\
18 & 1985 & "i'll be your fool tonight" & 54 & none & past the point of no return \\
19 & 1985 & "in another minute" & 27 & none & past the point of no return \\
20 & 1986 & "if i don't love you" & 53 & none & past the point of no return \\
21 & 1986 & "the lights of albuquerque" & 40 & none & everybody knows i'm yours \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "chart positions can country" ) \\
\midrule
0 & 12 \\
\bottomrule
\end{tabular}
| select sum ( chart positions can country ) where album = 'singles only' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>song</th>
<th>chart positions us country</th>
<th>chart positions can country</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1968</td>
<td>"god help you woman"</td>
<td>32</td>
<td>24</td>
<td>singles only</td>
</tr>
<tr>
<th>1</th>
<td>1969</td>
<td>"please take me back"</td>
<td>40</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>2</th>
<td>1969</td>
<td>"i'm not through loving you"</td>
<td>52</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>3</th>
<td>1969</td>
<td>"molly"</td>
<td>53</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>4</th>
<td>1973</td>
<td>"i see his love all over you"</td>
<td>67</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>5</th>
<td>1974</td>
<td>"fool passin' through"</td>
<td>68</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>6</th>
<td>1974</td>
<td>"forgettin' 'bout you"</td>
<td>51</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>7</th>
<td>1975</td>
<td>"one, two, three (never gonna fall in love again)"</td>
<td>88</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>8</th>
<td>1975</td>
<td>"woman, woman"</td>
<td>43</td>
<td>46</td>
<td>singles only</td>
</tr>
<tr>
<th>9</th>
<td>1976</td>
<td>"she's free but she's not easy"</td>
<td>66</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>10</th>
<td>1977</td>
<td>"chasin' my tail"</td>
<td>88</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>11</th>
<td>1977</td>
<td>"don't let my love stand in your way"</td>
<td>86</td>
<td>none</td>
<td>singles only</td>
</tr>
<tr>
<th>12</th>
<td>1983</td>
<td>"when you're not a lady"</td>
<td>16</td>
<td>none</td>
<td>the man in the mirror</td>
</tr>
<tr>
<th>13</th>
<td>1983</td>
<td>"you got me running"</td>
<td>28</td>
<td>none</td>
<td>the man in the mirror</td>
</tr>
<tr>
<th>14</th>
<td>1983</td>
<td>"the man in the mirror"</td>
<td>17</td>
<td>none</td>
<td>the man in the mirror</td>
</tr>
<tr>
<th>15</th>
<td>1984</td>
<td>"if i could only dance with you"</td>
<td>10</td>
<td>10</td>
<td>the man in the mirror</td>
</tr>
<tr>
<th>16</th>
<td>1984</td>
<td>"you're gettin' to me again"</td>
<td>1</td>
<td>3</td>
<td>the man in the mirror</td>
</tr>
<tr>
<th>17</th>
<td>1984</td>
<td>"let me down easy"</td>
<td>16</td>
<td>33</td>
<td>the man in the mirror</td>
</tr>
<tr>
<th>18</th>
<td>1985</td>
<td>"i'll be your fool tonight"</td>
<td>54</td>
<td>none</td>
<td>past the point of no return</td>
</tr>
<tr>
<th>19</th>
<td>1985</td>
<td>"in another minute"</td>
<td>27</td>
<td>none</td>
<td>past the point of no return</td>
</tr>
<tr>
<th>20</th>
<td>1986</td>
<td>"if i don't love you"</td>
<td>53</td>
<td>none</td>
<td>past the point of no return</td>
</tr>
<tr>
<th>21</th>
<td>1986</td>
<td>"the lights of albuquerque"</td>
<td>40</td>
<td>none</td>
<td>everybody knows i'm yours</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "chart positions can country" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>12</td>
</tr>
</tbody>
</table> | select sum ( chart positions can country ) where album = 'singles only' <table_name> : table | | year | song | chart positions us country | chart positions can country | album |
|---:|-------:|:---------------------------------------------------|-----------------------------:|:------------------------------|:----------------------------|
| 0 | 1968 | "god help you woman" | 32 | 24 | singles only |
| 1 | 1969 | "please take me back" | 40 | none | singles only |
| 2 | 1969 | "i'm not through loving you" | 52 | none | singles only |
| 3 | 1969 | "molly" | 53 | none | singles only |
| 4 | 1973 | "i see his love all over you" | 67 | none | singles only |
| 5 | 1974 | "fool passin' through" | 68 | none | singles only |
| 6 | 1974 | "forgettin' 'bout you" | 51 | none | singles only |
| 7 | 1975 | "one, two, three (never gonna fall in love again)" | 88 | none | singles only |
| 8 | 1975 | "woman, woman" | 43 | 46 | singles only |
| 9 | 1976 | "she's free but she's not easy" | 66 | none | singles only |
| 10 | 1977 | "chasin' my tail" | 88 | none | singles only |
| 11 | 1977 | "don't let my love stand in your way" | 86 | none | singles only |
| 12 | 1983 | "when you're not a lady" | 16 | none | the man in the mirror |
| 13 | 1983 | "you got me running" | 28 | none | the man in the mirror |
| 14 | 1983 | "the man in the mirror" | 17 | none | the man in the mirror |
| 15 | 1984 | "if i could only dance with you" | 10 | 10 | the man in the mirror |
| 16 | 1984 | "you're gettin' to me again" | 1 | 3 | the man in the mirror |
| 17 | 1984 | "let me down easy" | 16 | 33 | the man in the mirror |
| 18 | 1985 | "i'll be your fool tonight" | 54 | none | past the point of no return |
| 19 | 1985 | "in another minute" | 27 | none | past the point of no return |
| 20 | 1986 | "if i don't love you" | 53 | none | past the point of no return |
| 21 | 1986 | "the lights of albuquerque" | 40 | none | everybody knows i'm yours | | | | count ( "chart positions can country" ) |
|---:|------------------------------------------:|
| 0 | 12 | | [
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] |
select count ( * ) where weapon name = 'm-30' col : weapon name | caliber (mm) | range (max) | warhead row 1 : m-8 | 82 mm | 5,900 m (6,500 yd) | 0.64 kg (1.4 lb) row 2 : m-13 | 132 mm | 8,740 m (9,560 yd) | 4.9 kg (11 lb) row 3 : m-13dd | 132 mm | 11,800 m (12,900 yd) | 4.9 kg (11 lb) row 4 : m-13uk | 132 mm | 7,900 m (8,600 yd) | 4.9 kg (11 lb) row 5 : m-20 | 132 mm | 5,050 m (5,520 yd) | 18.4 kg (41 lb) row 6 : m-30 | 300 mm | 2,800 m (3,100 yd) | 28.9 kg (64 lb) row 7 : m-31 | 300 mm | 4,325 m (4,730 yd) | 28.9 kg (64 lb) row 8 : m-31uk | 300 mm | 4,000 m (4,400 yd) | 28.9 kg (64 lb) | col : count ( "*" ) row 1 : 1 | select count ( * ) where weapon name = 'm-30' <table_name> : table \begin{tabular}{lllll}
\toprule
& weapon name & caliber (mm) & range (max) & warhead \\
\midrule
0 & m-8 & 82 mm & 5,900 m (6,500 yd) & 0.64 kg (1.4 lb) \\
1 & m-13 & 132 mm & 8,740 m (9,560 yd) & 4.9 kg (11 lb) \\
2 & m-13dd & 132 mm & 11,800 m (12,900 yd) & 4.9 kg (11 lb) \\
3 & m-13uk & 132 mm & 7,900 m (8,600 yd) & 4.9 kg (11 lb) \\
4 & m-20 & 132 mm & 5,050 m (5,520 yd) & 18.4 kg (41 lb) \\
5 & m-30 & 300 mm & 2,800 m (3,100 yd) & 28.9 kg (64 lb) \\
6 & m-31 & 300 mm & 4,325 m (4,730 yd) & 28.9 kg (64 lb) \\
7 & m-31uk & 300 mm & 4,000 m (4,400 yd) & 28.9 kg (64 lb) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where weapon name = 'm-30' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>weapon name</th>
<th>caliber (mm)</th>
<th>range (max)</th>
<th>warhead</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>m-8</td>
<td>82 mm</td>
<td>5,900 m (6,500 yd)</td>
<td>0.64 kg (1.4 lb)</td>
</tr>
<tr>
<th>1</th>
<td>m-13</td>
<td>132 mm</td>
<td>8,740 m (9,560 yd)</td>
<td>4.9 kg (11 lb)</td>
</tr>
<tr>
<th>2</th>
<td>m-13dd</td>
<td>132 mm</td>
<td>11,800 m (12,900 yd)</td>
<td>4.9 kg (11 lb)</td>
</tr>
<tr>
<th>3</th>
<td>m-13uk</td>
<td>132 mm</td>
<td>7,900 m (8,600 yd)</td>
<td>4.9 kg (11 lb)</td>
</tr>
<tr>
<th>4</th>
<td>m-20</td>
<td>132 mm</td>
<td>5,050 m (5,520 yd)</td>
<td>18.4 kg (41 lb)</td>
</tr>
<tr>
<th>5</th>
<td>m-30</td>
<td>300 mm</td>
<td>2,800 m (3,100 yd)</td>
<td>28.9 kg (64 lb)</td>
</tr>
<tr>
<th>6</th>
<td>m-31</td>
<td>300 mm</td>
<td>4,325 m (4,730 yd)</td>
<td>28.9 kg (64 lb)</td>
</tr>
<tr>
<th>7</th>
<td>m-31uk</td>
<td>300 mm</td>
<td>4,000 m (4,400 yd)</td>
<td>28.9 kg (64 lb)</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 weapon name = 'm-30' <table_name> : table | | weapon name | caliber (mm) | range (max) | warhead |
|---:|:--------------|:---------------|:---------------------|:-----------------|
| 0 | m-8 | 82 mm | 5,900 m (6,500 yd) | 0.64 kg (1.4 lb) |
| 1 | m-13 | 132 mm | 8,740 m (9,560 yd) | 4.9 kg (11 lb) |
| 2 | m-13dd | 132 mm | 11,800 m (12,900 yd) | 4.9 kg (11 lb) |
| 3 | m-13uk | 132 mm | 7,900 m (8,600 yd) | 4.9 kg (11 lb) |
| 4 | m-20 | 132 mm | 5,050 m (5,520 yd) | 18.4 kg (41 lb) |
| 5 | m-30 | 300 mm | 2,800 m (3,100 yd) | 28.9 kg (64 lb) |
| 6 | m-31 | 300 mm | 4,325 m (4,730 yd) | 28.9 kg (64 lb) |
| 7 | m-31uk | 300 mm | 4,000 m (4,400 yd) | 28.9 kg (64 lb) | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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] |
select count ( * ) where reason for termination = 'not re-elected' col : nationality | name | term as a deputy judge | reason for termination row 1 : norway | frederik beichmann | 30 january 1920 - 6 december 1930 | not re-elected row 2 : china | wang ch'ung-hui | 30 january 1920 - 6 december 1930 | not re-elected row 3 : finland | rafael erich | 15 january 1931 - 1 february 1936 | post abolished row 4 : portugal | jose caeiro da matta | 15 january 1931 - 1 february 1936 | post abolished row 5 : romania | demetre negulesco | 30 january 1920 - 6 december 1930 | not re-elected row 6 : yugoslavia | mileta novakovic | 15 january 1931 - 1 february 1936 | post abolished row 7 : austria | josef redlich | 15 january 1931 - 1 february 1936 | post abolished row 8 : yugoslavia | mihajlo jovanovic | 30 january 1920 - 6 december 1930 | not re-elected | col : count ( "*" ) row 1 : 4 | select count ( * ) where reason for termination = 'not re-elected' <table_name> : table \begin{tabular}{lllll}
\toprule
& nationality & name & term as a deputy judge & reason for termination \\
\midrule
0 & norway & frederik beichmann & 30 january 1920 - 6 december 1930 & not re-elected \\
1 & china & wang ch'ung-hui & 30 january 1920 - 6 december 1930 & not re-elected \\
2 & finland & rafael erich & 15 january 1931 - 1 february 1936 & post abolished \\
3 & portugal & jose caeiro da matta & 15 january 1931 - 1 february 1936 & post abolished \\
4 & romania & demetre negulesco & 30 january 1920 - 6 december 1930 & not re-elected \\
5 & yugoslavia & mileta novakovic & 15 january 1931 - 1 february 1936 & post abolished \\
6 & austria & josef redlich & 15 january 1931 - 1 february 1936 & post abolished \\
7 & yugoslavia & mihajlo jovanovic & 30 january 1920 - 6 december 1930 & not re-elected \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( * ) where reason for termination = 'not re-elected' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nationality</th>
<th>name</th>
<th>term as a deputy judge</th>
<th>reason for termination</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>norway</td>
<td>frederik beichmann</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</td>
</tr>
<tr>
<th>1</th>
<td>china</td>
<td>wang ch'ung-hui</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</td>
</tr>
<tr>
<th>2</th>
<td>finland</td>
<td>rafael erich</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>3</th>
<td>portugal</td>
<td>jose caeiro da matta</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>4</th>
<td>romania</td>
<td>demetre negulesco</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</td>
</tr>
<tr>
<th>5</th>
<td>yugoslavia</td>
<td>mileta novakovic</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>6</th>
<td>austria</td>
<td>josef redlich</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>7</th>
<td>yugoslavia</td>
<td>mihajlo jovanovic</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</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>4</td>
</tr>
</tbody>
</table> | select count ( * ) where reason for termination = 'not re-elected' <table_name> : table | | nationality | name | term as a deputy judge | reason for termination |
|---:|:--------------|:---------------------|:----------------------------------|:-------------------------|
| 0 | norway | frederik beichmann | 30 january 1920 - 6 december 1930 | not re-elected |
| 1 | china | wang ch'ung-hui | 30 january 1920 - 6 december 1930 | not re-elected |
| 2 | finland | rafael erich | 15 january 1931 - 1 february 1936 | post abolished |
| 3 | portugal | jose caeiro da matta | 15 january 1931 - 1 february 1936 | post abolished |
| 4 | romania | demetre negulesco | 30 january 1920 - 6 december 1930 | not re-elected |
| 5 | yugoslavia | mileta novakovic | 15 january 1931 - 1 february 1936 | post abolished |
| 6 | austria | josef redlich | 15 january 1931 - 1 february 1936 | post abolished |
| 7 | yugoslavia | mihajlo jovanovic | 30 january 1920 - 6 december 1930 | not re-elected | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 4 | | [
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select birds where country = 'guatemala' col : country | amphibians | birds | mammals | reptile | total terrestrial vertebrates | vascular plants | biodiversity row 1 : belize | 46 | 544 | 147 | 140 | 877 | 2894 | 3771 row 2 : costa rica | 183 | 838 | 232 | 258 | 1511 | 12119 | 13630 row 3 : el salvador | 30 | 434 | 137 | 106 | 707 | 2911 | 3618 row 4 : guatemala | 133 | 684 | 193 | 236 | 1246 | 8681 | 9927 row 5 : honduras | 101 | 699 | 201 | 213 | 1214 | 5680 | 6894 row 6 : nicaragua | 61 | 632 | 181 | 178 | 1052 | 7590 | 8642 row 7 : panama | 182 | 904 | 241 | 242 | 1569 | 9915 | 11484 | col : birds row 1 : 684 | select birds where country = 'guatemala' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& country & amphibians & birds & mammals & reptile & total terrestrial vertebrates & vascular plants & biodiversity \\
\midrule
0 & belize & 46 & 544 & 147 & 140 & 877 & 2894 & 3771 \\
1 & costa rica & 183 & 838 & 232 & 258 & 1511 & 12119 & 13630 \\
2 & el salvador & 30 & 434 & 137 & 106 & 707 & 2911 & 3618 \\
3 & guatemala & 133 & 684 & 193 & 236 & 1246 & 8681 & 9927 \\
4 & honduras & 101 & 699 & 201 & 213 & 1214 & 5680 & 6894 \\
5 & nicaragua & 61 & 632 & 181 & 178 & 1052 & 7590 & 8642 \\
6 & panama & 182 & 904 & 241 & 242 & 1569 & 9915 & 11484 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& birds \\
\midrule
0 & 684 \\
\bottomrule
\end{tabular}
| select birds where country = 'guatemala' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>country</th>
<th>amphibians</th>
<th>birds</th>
<th>mammals</th>
<th>reptile</th>
<th>total terrestrial vertebrates</th>
<th>vascular plants</th>
<th>biodiversity</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>belize</td>
<td>46</td>
<td>544</td>
<td>147</td>
<td>140</td>
<td>877</td>
<td>2894</td>
<td>3771</td>
</tr>
<tr>
<th>1</th>
<td>costa rica</td>
<td>183</td>
<td>838</td>
<td>232</td>
<td>258</td>
<td>1511</td>
<td>12119</td>
<td>13630</td>
</tr>
<tr>
<th>2</th>
<td>el salvador</td>
<td>30</td>
<td>434</td>
<td>137</td>
<td>106</td>
<td>707</td>
<td>2911</td>
<td>3618</td>
</tr>
<tr>
<th>3</th>
<td>guatemala</td>
<td>133</td>
<td>684</td>
<td>193</td>
<td>236</td>
<td>1246</td>
<td>8681</td>
<td>9927</td>
</tr>
<tr>
<th>4</th>
<td>honduras</td>
<td>101</td>
<td>699</td>
<td>201</td>
<td>213</td>
<td>1214</td>
<td>5680</td>
<td>6894</td>
</tr>
<tr>
<th>5</th>
<td>nicaragua</td>
<td>61</td>
<td>632</td>
<td>181</td>
<td>178</td>
<td>1052</td>
<td>7590</td>
<td>8642</td>
</tr>
<tr>
<th>6</th>
<td>panama</td>
<td>182</td>
<td>904</td>
<td>241</td>
<td>242</td>
<td>1569</td>
<td>9915</td>
<td>11484</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>birds</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>684</td>
</tr>
</tbody>
</table> | select birds where country = 'guatemala' <table_name> : table | | country | amphibians | birds | mammals | reptile | total terrestrial vertebrates | vascular plants | biodiversity |
|---:|:------------|-------------:|--------:|----------:|----------:|--------------------------------:|------------------:|---------------:|
| 0 | belize | 46 | 544 | 147 | 140 | 877 | 2894 | 3771 |
| 1 | costa rica | 183 | 838 | 232 | 258 | 1511 | 12119 | 13630 |
| 2 | el salvador | 30 | 434 | 137 | 106 | 707 | 2911 | 3618 |
| 3 | guatemala | 133 | 684 | 193 | 236 | 1246 | 8681 | 9927 |
| 4 | honduras | 101 | 699 | 201 | 213 | 1214 | 5680 | 6894 |
| 5 | nicaragua | 61 | 632 | 181 | 178 | 1052 | 7590 | 8642 |
| 6 | panama | 182 | 904 | 241 | 242 | 1569 | 9915 | 11484 | | | | birds |
|---:|--------:|
| 0 | 684 | | [
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] |
select count ( nation ) where nation < 490 col : rank | nation | gold | silver | bronze | total row 1 : 1 | russia | 17 | 5 | 5 | 27 row 2 : 2 | bulgaria | 5 | 2 | 3 | 10 row 3 : 3 | belarus | 2 | 4 | 2 | 8 row 4 : 4 | ukraine | 1 | 2 | 11 | 14 row 5 : 5 | kazakhstan | 1 | 1 | 3 | 5 row 6 : 6 | latvia | 1 | 0 | 0 | 1 row 7 : 7 | uzbekistan | 0 | 3 | 4 | 7 row 8 : 8 | lithuania | 0 | 1 | 6 | 7 row 9 : 8 | venezuela | 0 | 3 | 3 | 6 row 10 : 9 | mongolia | 0 | 2 | 4 | 6 row 11 : 10 | armenia | 0 | 1 | 3 | 4 row 12 : 11 | japan | 0 | 0 | 3 | 3 row 13 : 12 | estonia | 0 | 0 | 2 | 2 row 14 : 13 | azerbaijan | 0 | 1 | 0 | 1 row 15 : 13 | france | 0 | 1 | 0 | 1 row 16 : 13 | germany | 0 | 1 | 0 | 1 row 17 : 13 | romania | 0 | 1 | 0 | 1 row 18 : 17 | serbia | 0 | 0 | 1 | 1 row 19 : 17 | spain | 0 | 0 | 1 | 1 row 20 : 17 | tajikistan | 0 | 0 | 1 | 1 row 21 : 17 | turkmenistan | 0 | 0 | 1 | 1 row 22 : 21 | algeria | 0 | 0 | 0 | 0 row 23 : 21 | austria | 0 | 0 | 0 | 0 row 24 : 21 | belgium | 0 | 0 | 0 | 0 row 25 : 21 | cameroon | 0 | 0 | 0 | 0 row 26 : 21 | canada | 0 | 0 | 0 | 0 row 27 : 21 | colombia | 0 | 0 | 0 | 0 row 28 : 21 | czech republic | 0 | 0 | 0 | 0 row 29 : 21 | cyprus | 0 | 0 | 0 | 0 row 30 : 21 | ecuador | 0 | 0 | 0 | 0 row 31 : 21 | finland | 0 | 0 | 0 | 0 row 32 : 21 | great britain | 0 | 0 | 0 | 0 row 33 : 21 | india | 0 | 0 | 0 | 0 row 34 : 21 | indonesia | 0 | 0 | 0 | 0 row 35 : 21 | ireland | 0 | 0 | 0 | 0 row 36 : 21 | israel | 0 | 0 | 0 | 0 row 37 : 21 | italy | 0 | 0 | 0 | 0 row 38 : 21 | jordan | 0 | 0 | 0 | 0 row 39 : 21 | south korea | 0 | 0 | 0 | 0 row 40 : 21 | kyrgyzstan | 0 | 0 | 0 | 0 row 41 : 21 | lebanon | 0 | 0 | 0 | 0 row 42 : 21 | malaysia | 0 | 0 | 0 | 0 row 43 : 21 | morocco | 0 | 0 | 0 | 0 row 44 : 21 | moldova | 0 | 0 | 0 | 0 row 45 : 21 | nepal | 0 | 0 | 0 | 0 row 46 : 21 | new zealand | 0 | 0 | 0 | 0 row 47 : 21 | pakistan | 0 | 0 | 0 | 0 row 48 : 21 | panama | 0 | 0 | 0 | 0 row 49 : 21 | peru | 0 | 0 | 0 | 0 row 50 : 21 | poland | 0 | 0 | 0 | 0 row 51 : 21 | syria | 0 | 0 | 0 | 0 row 52 : 21 | slovenia | 0 | 0 | 0 | 0 row 53 : 21 | slovakia | 0 | 0 | 0 | 0 row 54 : 21 | thailand | 0 | 0 | 0 | 0 row 55 : 21 | tunisia | 0 | 0 | 0 | 0 row 56 : 21 | turkey | 0 | 0 | 0 | 0 row 57 : 21 | united states | 0 | 0 | 0 | 0 row 58 : 21 | yemen | 0 | 0 | 0 | 0 row 59 : total | total | 27 | 27 | 54 | 108 | col : count ( "nation" ) row 1 : 0 | select count ( nation ) where nation < 490 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & russia & 17 & 5 & 5 & 27 \\
1 & 2 & bulgaria & 5 & 2 & 3 & 10 \\
2 & 3 & belarus & 2 & 4 & 2 & 8 \\
3 & 4 & ukraine & 1 & 2 & 11 & 14 \\
4 & 5 & kazakhstan & 1 & 1 & 3 & 5 \\
5 & 6 & latvia & 1 & 0 & 0 & 1 \\
6 & 7 & uzbekistan & 0 & 3 & 4 & 7 \\
7 & 8 & lithuania & 0 & 1 & 6 & 7 \\
8 & 8 & venezuela & 0 & 3 & 3 & 6 \\
9 & 9 & mongolia & 0 & 2 & 4 & 6 \\
10 & 10 & armenia & 0 & 1 & 3 & 4 \\
11 & 11 & japan & 0 & 0 & 3 & 3 \\
12 & 12 & estonia & 0 & 0 & 2 & 2 \\
13 & 13 & azerbaijan & 0 & 1 & 0 & 1 \\
14 & 13 & france & 0 & 1 & 0 & 1 \\
15 & 13 & germany & 0 & 1 & 0 & 1 \\
16 & 13 & romania & 0 & 1 & 0 & 1 \\
17 & 17 & serbia & 0 & 0 & 1 & 1 \\
18 & 17 & spain & 0 & 0 & 1 & 1 \\
19 & 17 & tajikistan & 0 & 0 & 1 & 1 \\
20 & 17 & turkmenistan & 0 & 0 & 1 & 1 \\
21 & 21 & algeria & 0 & 0 & 0 & 0 \\
22 & 21 & austria & 0 & 0 & 0 & 0 \\
23 & 21 & belgium & 0 & 0 & 0 & 0 \\
24 & 21 & cameroon & 0 & 0 & 0 & 0 \\
25 & 21 & canada & 0 & 0 & 0 & 0 \\
26 & 21 & colombia & 0 & 0 & 0 & 0 \\
27 & 21 & czech republic & 0 & 0 & 0 & 0 \\
28 & 21 & cyprus & 0 & 0 & 0 & 0 \\
29 & 21 & ecuador & 0 & 0 & 0 & 0 \\
30 & 21 & finland & 0 & 0 & 0 & 0 \\
31 & 21 & great britain & 0 & 0 & 0 & 0 \\
32 & 21 & india & 0 & 0 & 0 & 0 \\
33 & 21 & indonesia & 0 & 0 & 0 & 0 \\
34 & 21 & ireland & 0 & 0 & 0 & 0 \\
35 & 21 & israel & 0 & 0 & 0 & 0 \\
36 & 21 & italy & 0 & 0 & 0 & 0 \\
37 & 21 & jordan & 0 & 0 & 0 & 0 \\
38 & 21 & south korea & 0 & 0 & 0 & 0 \\
39 & 21 & kyrgyzstan & 0 & 0 & 0 & 0 \\
40 & 21 & lebanon & 0 & 0 & 0 & 0 \\
41 & 21 & malaysia & 0 & 0 & 0 & 0 \\
42 & 21 & morocco & 0 & 0 & 0 & 0 \\
43 & 21 & moldova & 0 & 0 & 0 & 0 \\
44 & 21 & nepal & 0 & 0 & 0 & 0 \\
45 & 21 & new zealand & 0 & 0 & 0 & 0 \\
46 & 21 & pakistan & 0 & 0 & 0 & 0 \\
47 & 21 & panama & 0 & 0 & 0 & 0 \\
48 & 21 & peru & 0 & 0 & 0 & 0 \\
49 & 21 & poland & 0 & 0 & 0 & 0 \\
50 & 21 & syria & 0 & 0 & 0 & 0 \\
51 & 21 & slovenia & 0 & 0 & 0 & 0 \\
52 & 21 & slovakia & 0 & 0 & 0 & 0 \\
53 & 21 & thailand & 0 & 0 & 0 & 0 \\
54 & 21 & tunisia & 0 & 0 & 0 & 0 \\
55 & 21 & turkey & 0 & 0 & 0 & 0 \\
56 & 21 & united states & 0 & 0 & 0 & 0 \\
57 & 21 & yemen & 0 & 0 & 0 & 0 \\
58 & total & total & 27 & 27 & 54 & 108 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "nation" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( nation ) where nation < 490 <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>russia</td>
<td>17</td>
<td>5</td>
<td>5</td>
<td>27</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>bulgaria</td>
<td>5</td>
<td>2</td>
<td>3</td>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>belarus</td>
<td>2</td>
<td>4</td>
<td>2</td>
<td>8</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>ukraine</td>
<td>1</td>
<td>2</td>
<td>11</td>
<td>14</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>kazakhstan</td>
<td>1</td>
<td>1</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>latvia</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>uzbekistan</td>
<td>0</td>
<td>3</td>
<td>4</td>
<td>7</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>lithuania</td>
<td>0</td>
<td>1</td>
<td>6</td>
<td>7</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>venezuela</td>
<td>0</td>
<td>3</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>mongolia</td>
<td>0</td>
<td>2</td>
<td>4</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>armenia</td>
<td>0</td>
<td>1</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>japan</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>12</th>
<td>12</td>
<td>estonia</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>13</th>
<td>13</td>
<td>azerbaijan</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>13</td>
<td>france</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>13</td>
<td>germany</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>13</td>
<td>romania</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>17</th>
<td>17</td>
<td>serbia</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>17</td>
<td>spain</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>17</td>
<td>tajikistan</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>20</th>
<td>17</td>
<td>turkmenistan</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>21</td>
<td>algeria</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>22</th>
<td>21</td>
<td>austria</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>23</th>
<td>21</td>
<td>belgium</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>24</th>
<td>21</td>
<td>cameroon</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>25</th>
<td>21</td>
<td>canada</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>26</th>
<td>21</td>
<td>colombia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>27</th>
<td>21</td>
<td>czech republic</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>28</th>
<td>21</td>
<td>cyprus</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>29</th>
<td>21</td>
<td>ecuador</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>30</th>
<td>21</td>
<td>finland</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>31</th>
<td>21</td>
<td>great britain</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>32</th>
<td>21</td>
<td>india</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>33</th>
<td>21</td>
<td>indonesia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>34</th>
<td>21</td>
<td>ireland</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>35</th>
<td>21</td>
<td>israel</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>36</th>
<td>21</td>
<td>italy</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>37</th>
<td>21</td>
<td>jordan</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>38</th>
<td>21</td>
<td>south korea</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>39</th>
<td>21</td>
<td>kyrgyzstan</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>40</th>
<td>21</td>
<td>lebanon</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>41</th>
<td>21</td>
<td>malaysia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>42</th>
<td>21</td>
<td>morocco</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>43</th>
<td>21</td>
<td>moldova</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>44</th>
<td>21</td>
<td>nepal</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>45</th>
<td>21</td>
<td>new zealand</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>46</th>
<td>21</td>
<td>pakistan</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>47</th>
<td>21</td>
<td>panama</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>48</th>
<td>21</td>
<td>peru</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>49</th>
<td>21</td>
<td>poland</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>50</th>
<td>21</td>
<td>syria</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>51</th>
<td>21</td>
<td>slovenia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>52</th>
<td>21</td>
<td>slovakia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>53</th>
<td>21</td>
<td>thailand</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>54</th>
<td>21</td>
<td>tunisia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>55</th>
<td>21</td>
<td>turkey</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>56</th>
<td>21</td>
<td>united states</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>57</th>
<td>21</td>
<td>yemen</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>58</th>
<td>total</td>
<td>total</td>
<td>27</td>
<td>27</td>
<td>54</td>
<td>108</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>0</td>
</tr>
</tbody>
</table> | select count ( nation ) where nation < 490 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------|-------:|---------:|---------:|--------:|
| 0 | 1 | russia | 17 | 5 | 5 | 27 |
| 1 | 2 | bulgaria | 5 | 2 | 3 | 10 |
| 2 | 3 | belarus | 2 | 4 | 2 | 8 |
| 3 | 4 | ukraine | 1 | 2 | 11 | 14 |
| 4 | 5 | kazakhstan | 1 | 1 | 3 | 5 |
| 5 | 6 | latvia | 1 | 0 | 0 | 1 |
| 6 | 7 | uzbekistan | 0 | 3 | 4 | 7 |
| 7 | 8 | lithuania | 0 | 1 | 6 | 7 |
| 8 | 8 | venezuela | 0 | 3 | 3 | 6 |
| 9 | 9 | mongolia | 0 | 2 | 4 | 6 |
| 10 | 10 | armenia | 0 | 1 | 3 | 4 |
| 11 | 11 | japan | 0 | 0 | 3 | 3 |
| 12 | 12 | estonia | 0 | 0 | 2 | 2 |
| 13 | 13 | azerbaijan | 0 | 1 | 0 | 1 |
| 14 | 13 | france | 0 | 1 | 0 | 1 |
| 15 | 13 | germany | 0 | 1 | 0 | 1 |
| 16 | 13 | romania | 0 | 1 | 0 | 1 |
| 17 | 17 | serbia | 0 | 0 | 1 | 1 |
| 18 | 17 | spain | 0 | 0 | 1 | 1 |
| 19 | 17 | tajikistan | 0 | 0 | 1 | 1 |
| 20 | 17 | turkmenistan | 0 | 0 | 1 | 1 |
| 21 | 21 | algeria | 0 | 0 | 0 | 0 |
| 22 | 21 | austria | 0 | 0 | 0 | 0 |
| 23 | 21 | belgium | 0 | 0 | 0 | 0 |
| 24 | 21 | cameroon | 0 | 0 | 0 | 0 |
| 25 | 21 | canada | 0 | 0 | 0 | 0 |
| 26 | 21 | colombia | 0 | 0 | 0 | 0 |
| 27 | 21 | czech republic | 0 | 0 | 0 | 0 |
| 28 | 21 | cyprus | 0 | 0 | 0 | 0 |
| 29 | 21 | ecuador | 0 | 0 | 0 | 0 |
| 30 | 21 | finland | 0 | 0 | 0 | 0 |
| 31 | 21 | great britain | 0 | 0 | 0 | 0 |
| 32 | 21 | india | 0 | 0 | 0 | 0 |
| 33 | 21 | indonesia | 0 | 0 | 0 | 0 |
| 34 | 21 | ireland | 0 | 0 | 0 | 0 |
| 35 | 21 | israel | 0 | 0 | 0 | 0 |
| 36 | 21 | italy | 0 | 0 | 0 | 0 |
| 37 | 21 | jordan | 0 | 0 | 0 | 0 |
| 38 | 21 | south korea | 0 | 0 | 0 | 0 |
| 39 | 21 | kyrgyzstan | 0 | 0 | 0 | 0 |
| 40 | 21 | lebanon | 0 | 0 | 0 | 0 |
| 41 | 21 | malaysia | 0 | 0 | 0 | 0 |
| 42 | 21 | morocco | 0 | 0 | 0 | 0 |
| 43 | 21 | moldova | 0 | 0 | 0 | 0 |
| 44 | 21 | nepal | 0 | 0 | 0 | 0 |
| 45 | 21 | new zealand | 0 | 0 | 0 | 0 |
| 46 | 21 | pakistan | 0 | 0 | 0 | 0 |
| 47 | 21 | panama | 0 | 0 | 0 | 0 |
| 48 | 21 | peru | 0 | 0 | 0 | 0 |
| 49 | 21 | poland | 0 | 0 | 0 | 0 |
| 50 | 21 | syria | 0 | 0 | 0 | 0 |
| 51 | 21 | slovenia | 0 | 0 | 0 | 0 |
| 52 | 21 | slovakia | 0 | 0 | 0 | 0 |
| 53 | 21 | thailand | 0 | 0 | 0 | 0 |
| 54 | 21 | tunisia | 0 | 0 | 0 | 0 |
| 55 | 21 | turkey | 0 | 0 | 0 | 0 |
| 56 | 21 | united states | 0 | 0 | 0 | 0 |
| 57 | 21 | yemen | 0 | 0 | 0 | 0 |
| 58 | total | total | 27 | 27 | 54 | 108 | | | | count ( "nation" ) |
|---:|---------------------:|
| 0 | 0 | | [
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select count ( position ) where notes = '19.56 m' col : year | competition | venue | position | event | notes row 1 : 2002 | world junior championships | kingston, jamaica | 17th (q) | shot put (6 kg) | 17.77 m row 2 : 2003 | european junior championships | tampere, finland | 2nd | shot put (6 kg) | 20.10 m row 3 : 2005 | european u23 championships | erfurt, germany | 1st | shot put | 20.44 m row 4 : 2005 | world championships | helsinki, finland | 15th (q) | shot put | 19.56 m row 5 : 2005 | universiade | izmir, turkey | 3rd | shot put | 19.40 m row 6 : 2006 | world indoor championships | moscow, russia | 8th | shot put | 19.93 m row 7 : 2006 | european championships | gothenburg, sweden | 11th | shot put | 19.44 m row 8 : 2007 | european indoor championships | birmingham, united kingdom | 11th (q) | shot put | 19.12 m row 9 : 2007 | world championships | osaka, japan | 13th (q) | shot put | 19.91 m row 10 : 2008 | olympic games | beijing, china | 18th (q) | shot put | 19.87 m row 11 : 2009 | european indoor championships | turin, italy | 4th | shot put | 20.14 m | col : count ( "position" ) row 1 : 1 | select count ( position ) where notes = '19.56 m' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & competition & venue & position & event & notes \\
\midrule
0 & 2002 & world junior championships & kingston, jamaica & 17th (q) & shot put (6 kg) & 17.77 m \\
1 & 2003 & european junior championships & tampere, finland & 2nd & shot put (6 kg) & 20.10 m \\
2 & 2005 & european u23 championships & erfurt, germany & 1st & shot put & 20.44 m \\
3 & 2005 & world championships & helsinki, finland & 15th (q) & shot put & 19.56 m \\
4 & 2005 & universiade & izmir, turkey & 3rd & shot put & 19.40 m \\
5 & 2006 & world indoor championships & moscow, russia & 8th & shot put & 19.93 m \\
6 & 2006 & european championships & gothenburg, sweden & 11th & shot put & 19.44 m \\
7 & 2007 & european indoor championships & birmingham, united kingdom & 11th (q) & shot put & 19.12 m \\
8 & 2007 & world championships & osaka, japan & 13th (q) & shot put & 19.91 m \\
9 & 2008 & olympic games & beijing, china & 18th (q) & shot put & 19.87 m \\
10 & 2009 & european indoor championships & turin, italy & 4th & shot put & 20.14 m \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "position" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( position ) where notes = '19.56 m' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>competition</th>
<th>venue</th>
<th>position</th>
<th>event</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002</td>
<td>world junior championships</td>
<td>kingston, jamaica</td>
<td>17th (q)</td>
<td>shot put (6 kg)</td>
<td>17.77 m</td>
</tr>
<tr>
<th>1</th>
<td>2003</td>
<td>european junior championships</td>
<td>tampere, finland</td>
<td>2nd</td>
<td>shot put (6 kg)</td>
<td>20.10 m</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>european u23 championships</td>
<td>erfurt, germany</td>
<td>1st</td>
<td>shot put</td>
<td>20.44 m</td>
</tr>
<tr>
<th>3</th>
<td>2005</td>
<td>world championships</td>
<td>helsinki, finland</td>
<td>15th (q)</td>
<td>shot put</td>
<td>19.56 m</td>
</tr>
<tr>
<th>4</th>
<td>2005</td>
<td>universiade</td>
<td>izmir, turkey</td>
<td>3rd</td>
<td>shot put</td>
<td>19.40 m</td>
</tr>
<tr>
<th>5</th>
<td>2006</td>
<td>world indoor championships</td>
<td>moscow, russia</td>
<td>8th</td>
<td>shot put</td>
<td>19.93 m</td>
</tr>
<tr>
<th>6</th>
<td>2006</td>
<td>european championships</td>
<td>gothenburg, sweden</td>
<td>11th</td>
<td>shot put</td>
<td>19.44 m</td>
</tr>
<tr>
<th>7</th>
<td>2007</td>
<td>european indoor championships</td>
<td>birmingham, united kingdom</td>
<td>11th (q)</td>
<td>shot put</td>
<td>19.12 m</td>
</tr>
<tr>
<th>8</th>
<td>2007</td>
<td>world championships</td>
<td>osaka, japan</td>
<td>13th (q)</td>
<td>shot put</td>
<td>19.91 m</td>
</tr>
<tr>
<th>9</th>
<td>2008</td>
<td>olympic games</td>
<td>beijing, china</td>
<td>18th (q)</td>
<td>shot put</td>
<td>19.87 m</td>
</tr>
<tr>
<th>10</th>
<td>2009</td>
<td>european indoor championships</td>
<td>turin, italy</td>
<td>4th</td>
<td>shot put</td>
<td>20.14 m</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "position" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( position ) where notes = '19.56 m' <table_name> : table | | year | competition | venue | position | event | notes |
|---:|-------:|:------------------------------|:---------------------------|:-----------|:----------------|:--------|
| 0 | 2002 | world junior championships | kingston, jamaica | 17th (q) | shot put (6 kg) | 17.77 m |
| 1 | 2003 | european junior championships | tampere, finland | 2nd | shot put (6 kg) | 20.10 m |
| 2 | 2005 | european u23 championships | erfurt, germany | 1st | shot put | 20.44 m |
| 3 | 2005 | world championships | helsinki, finland | 15th (q) | shot put | 19.56 m |
| 4 | 2005 | universiade | izmir, turkey | 3rd | shot put | 19.40 m |
| 5 | 2006 | world indoor championships | moscow, russia | 8th | shot put | 19.93 m |
| 6 | 2006 | european championships | gothenburg, sweden | 11th | shot put | 19.44 m |
| 7 | 2007 | european indoor championships | birmingham, united kingdom | 11th (q) | shot put | 19.12 m |
| 8 | 2007 | world championships | osaka, japan | 13th (q) | shot put | 19.91 m |
| 9 | 2008 | olympic games | beijing, china | 18th (q) | shot put | 19.87 m |
| 10 | 2009 | european indoor championships | turin, italy | 4th | shot put | 20.14 m | | | | count ( "position" ) |
|---:|-----------------------:|
| 0 | 1 | | [
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select count ( team ) where team = 1180 col : pos | no | driver | team | laps | time/retired | grid | points row 1 : 1 | 32 | patrick carpentier | team player's | 87 | 1:48:11.023 | 1 | 22 row 2 : 2 | 1 | bruno junqueira | newman/haas racing | 87 | +0.8 secs | 2 | 17 row 3 : 3 | 3 | paul tracy | team player's | 87 | +28.6 secs | 3 | 14 row 4 : 4 | 9 | michel jourdain, jr | team rahal | 87 | +40.8 secs | 13 | 12 row 5 : 5 | 34 | mario haberfeld | mi-jack conquest racing | 87 | +42.1 secs | 6 | 10 row 6 : 6 | 20 | oriol servia | patrick racing | 87 | +1:00.2 | 10 | 8 row 7 : 7 | 51 | adrian fernandez | fernandez racing | 87 | +1:01.4 | 5 | 6 row 8 : 8 | 12 | jimmy vasser | american spirit team johansson | 87 | +1:01.8 | 8 | 5 row 9 : 9 | 7 | tiago monteiro | fittipaldi-dingman racing | 86 | + 1 lap | 15 | 4 row 10 : 10 | 55 | mario dominguez | herdez competition | 86 | + 1 lap | 11 | 3 row 11 : 11 | 27 | bryan herta | pk racing | 86 | + 1 lap | 12 | 2 row 12 : 12 | 31 | ryan hunter-reay | american spirit team johansson | 86 | + 1 lap | 17 | 1 row 13 : 13 | 19 | joel camathias | dale coyne racing | 85 | + 2 laps | 18 | 0 row 14 : 14 | 33 | alex tagliani | rocketsports racing | 85 | + 2 laps | 14 | 0 row 15 : 15 | 4 | roberto moreno | herdez competition | 85 | + 2 laps | 9 | 0 row 16 : 16 | 11 | geoff boss | dale coyne racing | 83 | mechanical | 19 | 0 row 17 : 17 | 2 | sebastien bourdais | newman/haas racing | 77 | mechanical | 4 | 0 row 18 : 18 | 15 | darren manning | walker racing | 12 | mechanical | 7 | 0 row 19 : 19 | 5 | rodolfo lavin | walker racing | 10 | mechanical | 16 | 0 | col : count ( "team" ) row 1 : 0 | select count ( team ) where team = 1180 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & team & laps & time/retired & grid & points \\
\midrule
0 & 1 & 32 & patrick carpentier & team player's & 87 & 1:48:11.023 & 1 & 22 \\
1 & 2 & 1 & bruno junqueira & newman/haas racing & 87 & +0.8 secs & 2 & 17 \\
2 & 3 & 3 & paul tracy & team player's & 87 & +28.6 secs & 3 & 14 \\
3 & 4 & 9 & michel jourdain, jr & team rahal & 87 & +40.8 secs & 13 & 12 \\
4 & 5 & 34 & mario haberfeld & mi-jack conquest racing & 87 & +42.1 secs & 6 & 10 \\
5 & 6 & 20 & oriol servia & patrick racing & 87 & +1:00.2 & 10 & 8 \\
6 & 7 & 51 & adrian fernandez & fernandez racing & 87 & +1:01.4 & 5 & 6 \\
7 & 8 & 12 & jimmy vasser & american spirit team johansson & 87 & +1:01.8 & 8 & 5 \\
8 & 9 & 7 & tiago monteiro & fittipaldi-dingman racing & 86 & + 1 lap & 15 & 4 \\
9 & 10 & 55 & mario dominguez & herdez competition & 86 & + 1 lap & 11 & 3 \\
10 & 11 & 27 & bryan herta & pk racing & 86 & + 1 lap & 12 & 2 \\
11 & 12 & 31 & ryan hunter-reay & american spirit team johansson & 86 & + 1 lap & 17 & 1 \\
12 & 13 & 19 & joel camathias & dale coyne racing & 85 & + 2 laps & 18 & 0 \\
13 & 14 & 33 & alex tagliani & rocketsports racing & 85 & + 2 laps & 14 & 0 \\
14 & 15 & 4 & roberto moreno & herdez competition & 85 & + 2 laps & 9 & 0 \\
15 & 16 & 11 & geoff boss & dale coyne racing & 83 & mechanical & 19 & 0 \\
16 & 17 & 2 & sebastien bourdais & newman/haas racing & 77 & mechanical & 4 & 0 \\
17 & 18 & 15 & darren manning & walker racing & 12 & mechanical & 7 & 0 \\
18 & 19 & 5 & rodolfo lavin & walker racing & 10 & mechanical & 16 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "team" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( team ) where team = 1180 <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>32</td>
<td>patrick carpentier</td>
<td>team player's</td>
<td>87</td>
<td>1:48:11.023</td>
<td>1</td>
<td>22</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1</td>
<td>bruno junqueira</td>
<td>newman/haas racing</td>
<td>87</td>
<td>+0.8 secs</td>
<td>2</td>
<td>17</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>3</td>
<td>paul tracy</td>
<td>team player's</td>
<td>87</td>
<td>+28.6 secs</td>
<td>3</td>
<td>14</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>9</td>
<td>michel jourdain, jr</td>
<td>team rahal</td>
<td>87</td>
<td>+40.8 secs</td>
<td>13</td>
<td>12</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>34</td>
<td>mario haberfeld</td>
<td>mi-jack conquest racing</td>
<td>87</td>
<td>+42.1 secs</td>
<td>6</td>
<td>10</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>20</td>
<td>oriol servia</td>
<td>patrick racing</td>
<td>87</td>
<td>+1:00.2</td>
<td>10</td>
<td>8</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>51</td>
<td>adrian fernandez</td>
<td>fernandez racing</td>
<td>87</td>
<td>+1:01.4</td>
<td>5</td>
<td>6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>12</td>
<td>jimmy vasser</td>
<td>american spirit team johansson</td>
<td>87</td>
<td>+1:01.8</td>
<td>8</td>
<td>5</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>7</td>
<td>tiago monteiro</td>
<td>fittipaldi-dingman racing</td>
<td>86</td>
<td>+ 1 lap</td>
<td>15</td>
<td>4</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>55</td>
<td>mario dominguez</td>
<td>herdez competition</td>
<td>86</td>
<td>+ 1 lap</td>
<td>11</td>
<td>3</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>27</td>
<td>bryan herta</td>
<td>pk racing</td>
<td>86</td>
<td>+ 1 lap</td>
<td>12</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>31</td>
<td>ryan hunter-reay</td>
<td>american spirit team johansson</td>
<td>86</td>
<td>+ 1 lap</td>
<td>17</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>19</td>
<td>joel camathias</td>
<td>dale coyne racing</td>
<td>85</td>
<td>+ 2 laps</td>
<td>18</td>
<td>0</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>33</td>
<td>alex tagliani</td>
<td>rocketsports racing</td>
<td>85</td>
<td>+ 2 laps</td>
<td>14</td>
<td>0</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>4</td>
<td>roberto moreno</td>
<td>herdez competition</td>
<td>85</td>
<td>+ 2 laps</td>
<td>9</td>
<td>0</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>11</td>
<td>geoff boss</td>
<td>dale coyne racing</td>
<td>83</td>
<td>mechanical</td>
<td>19</td>
<td>0</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>2</td>
<td>sebastien bourdais</td>
<td>newman/haas racing</td>
<td>77</td>
<td>mechanical</td>
<td>4</td>
<td>0</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>15</td>
<td>darren manning</td>
<td>walker racing</td>
<td>12</td>
<td>mechanical</td>
<td>7</td>
<td>0</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>5</td>
<td>rodolfo lavin</td>
<td>walker racing</td>
<td>10</td>
<td>mechanical</td>
<td>16</td>
<td>0</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>0</td>
</tr>
</tbody>
</table> | select count ( team ) where team = 1180 <table_name> : table | | pos | no | driver | team | laps | time/retired | grid | points |
|---:|------:|-----:|:--------------------|:-------------------------------|-------:|:---------------|-------:|---------:|
| 0 | 1 | 32 | patrick carpentier | team player's | 87 | 1:48:11.023 | 1 | 22 |
| 1 | 2 | 1 | bruno junqueira | newman/haas racing | 87 | +0.8 secs | 2 | 17 |
| 2 | 3 | 3 | paul tracy | team player's | 87 | +28.6 secs | 3 | 14 |
| 3 | 4 | 9 | michel jourdain, jr | team rahal | 87 | +40.8 secs | 13 | 12 |
| 4 | 5 | 34 | mario haberfeld | mi-jack conquest racing | 87 | +42.1 secs | 6 | 10 |
| 5 | 6 | 20 | oriol servia | patrick racing | 87 | +1:00.2 | 10 | 8 |
| 6 | 7 | 51 | adrian fernandez | fernandez racing | 87 | +1:01.4 | 5 | 6 |
| 7 | 8 | 12 | jimmy vasser | american spirit team johansson | 87 | +1:01.8 | 8 | 5 |
| 8 | 9 | 7 | tiago monteiro | fittipaldi-dingman racing | 86 | + 1 lap | 15 | 4 |
| 9 | 10 | 55 | mario dominguez | herdez competition | 86 | + 1 lap | 11 | 3 |
| 10 | 11 | 27 | bryan herta | pk racing | 86 | + 1 lap | 12 | 2 |
| 11 | 12 | 31 | ryan hunter-reay | american spirit team johansson | 86 | + 1 lap | 17 | 1 |
| 12 | 13 | 19 | joel camathias | dale coyne racing | 85 | + 2 laps | 18 | 0 |
| 13 | 14 | 33 | alex tagliani | rocketsports racing | 85 | + 2 laps | 14 | 0 |
| 14 | 15 | 4 | roberto moreno | herdez competition | 85 | + 2 laps | 9 | 0 |
| 15 | 16 | 11 | geoff boss | dale coyne racing | 83 | mechanical | 19 | 0 |
| 16 | 17 | 2 | sebastien bourdais | newman/haas racing | 77 | mechanical | 4 | 0 |
| 17 | 18 | 15 | darren manning | walker racing | 12 | mechanical | 7 | 0 |
| 18 | 19 | 5 | rodolfo lavin | walker racing | 10 | mechanical | 16 | 0 | | | | count ( "team" ) |
|---:|-------------------:|
| 0 | 0 | | [
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select count ( notes ) where source > 1965 col : source | date | population romania | population serbia | notes row 1 : jozu rill | 1864 | 30,000-35,000 | 30,000-35,000 | none row 2 : hungarian statistics | 1880 | 18298 | 18298 | none row 3 : hungarian statistics | 1900 | 19944 | 19944 | none row 4 : hungarian statistics | 1910 | 13536 | 13536 | "evidently underestimated" row 5 : various authors | second half of the 19th century | 22,000-26,000 | 22,000-26,000 | "sometimes including the krashovani" row 6 : romanian census | 1930 | 10012 | none | romanian banat only row 7 : dimo kazasov | 1936 | none | 3200 | serbian banat only; estimated row 8 : romanian census | 1939 | 9951 | none | romanian banat only row 9 : karol telbizov | 1940 | 12000 | none | romanian banat only; estimated row 10 : mihail georgiev | 1942 | none | up to 4,500 | serbian banat only; estimated row 11 : romanian census | 1956 | 12040 | none | romania only row 12 : yugoslav census | 1971 | none | 3745 | serbian banat only row 13 : romanian census | 1977 | 9267 | none | romania only row 14 : romanian census | 2002 | 6486 | none | romania only row 15 : serbian census | 2002 | none | 1658 | serbia only | col : count ( "notes" ) row 1 : 15 | select count ( notes ) where source > 1965 <table_name> : table \begin{tabular}{llllll}
\toprule
& source & date & population romania & population serbia & notes \\
\midrule
0 & jozu rill & 1864 & 30,000-35,000 & 30,000-35,000 & none \\
1 & hungarian statistics & 1880 & 18298 & 18298 & none \\
2 & hungarian statistics & 1900 & 19944 & 19944 & none \\
3 & hungarian statistics & 1910 & 13536 & 13536 & "evidently underestimated" \\
4 & various authors & second half of the 19th century & 22,000-26,000 & 22,000-26,000 & "sometimes including the krashovani" \\
5 & romanian census & 1930 & 10012 & none & romanian banat only \\
6 & dimo kazasov & 1936 & none & 3200 & serbian banat only; estimated \\
7 & romanian census & 1939 & 9951 & none & romanian banat only \\
8 & karol telbizov & 1940 & 12000 & none & romanian banat only; estimated \\
9 & mihail georgiev & 1942 & none & up to 4,500 & serbian banat only; estimated \\
10 & romanian census & 1956 & 12040 & none & romania only \\
11 & yugoslav census & 1971 & none & 3745 & serbian banat only \\
12 & romanian census & 1977 & 9267 & none & romania only \\
13 & romanian census & 2002 & 6486 & none & romania only \\
14 & serbian census & 2002 & none & 1658 & serbia only \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "notes" ) \\
\midrule
0 & 15 \\
\bottomrule
\end{tabular}
| select count ( notes ) where source > 1965 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>source</th>
<th>date</th>
<th>population romania</th>
<th>population serbia</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>jozu rill</td>
<td>1864</td>
<td>30,000-35,000</td>
<td>30,000-35,000</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>hungarian statistics</td>
<td>1880</td>
<td>18298</td>
<td>18298</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>hungarian statistics</td>
<td>1900</td>
<td>19944</td>
<td>19944</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>hungarian statistics</td>
<td>1910</td>
<td>13536</td>
<td>13536</td>
<td>"evidently underestimated"</td>
</tr>
<tr>
<th>4</th>
<td>various authors</td>
<td>second half of the 19th century</td>
<td>22,000-26,000</td>
<td>22,000-26,000</td>
<td>"sometimes including the krashovani"</td>
</tr>
<tr>
<th>5</th>
<td>romanian census</td>
<td>1930</td>
<td>10012</td>
<td>none</td>
<td>romanian banat only</td>
</tr>
<tr>
<th>6</th>
<td>dimo kazasov</td>
<td>1936</td>
<td>none</td>
<td>3200</td>
<td>serbian banat only; estimated</td>
</tr>
<tr>
<th>7</th>
<td>romanian census</td>
<td>1939</td>
<td>9951</td>
<td>none</td>
<td>romanian banat only</td>
</tr>
<tr>
<th>8</th>
<td>karol telbizov</td>
<td>1940</td>
<td>12000</td>
<td>none</td>
<td>romanian banat only; estimated</td>
</tr>
<tr>
<th>9</th>
<td>mihail georgiev</td>
<td>1942</td>
<td>none</td>
<td>up to 4,500</td>
<td>serbian banat only; estimated</td>
</tr>
<tr>
<th>10</th>
<td>romanian census</td>
<td>1956</td>
<td>12040</td>
<td>none</td>
<td>romania only</td>
</tr>
<tr>
<th>11</th>
<td>yugoslav census</td>
<td>1971</td>
<td>none</td>
<td>3745</td>
<td>serbian banat only</td>
</tr>
<tr>
<th>12</th>
<td>romanian census</td>
<td>1977</td>
<td>9267</td>
<td>none</td>
<td>romania only</td>
</tr>
<tr>
<th>13</th>
<td>romanian census</td>
<td>2002</td>
<td>6486</td>
<td>none</td>
<td>romania only</td>
</tr>
<tr>
<th>14</th>
<td>serbian census</td>
<td>2002</td>
<td>none</td>
<td>1658</td>
<td>serbia only</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>15</td>
</tr>
</tbody>
</table> | select count ( notes ) where source > 1965 <table_name> : table | | source | date | population romania | population serbia | notes |
|---:|:---------------------|:--------------------------------|:---------------------|:--------------------|:-------------------------------------|
| 0 | jozu rill | 1864 | 30,000-35,000 | 30,000-35,000 | none |
| 1 | hungarian statistics | 1880 | 18298 | 18298 | none |
| 2 | hungarian statistics | 1900 | 19944 | 19944 | none |
| 3 | hungarian statistics | 1910 | 13536 | 13536 | "evidently underestimated" |
| 4 | various authors | second half of the 19th century | 22,000-26,000 | 22,000-26,000 | "sometimes including the krashovani" |
| 5 | romanian census | 1930 | 10012 | none | romanian banat only |
| 6 | dimo kazasov | 1936 | none | 3200 | serbian banat only; estimated |
| 7 | romanian census | 1939 | 9951 | none | romanian banat only |
| 8 | karol telbizov | 1940 | 12000 | none | romanian banat only; estimated |
| 9 | mihail georgiev | 1942 | none | up to 4,500 | serbian banat only; estimated |
| 10 | romanian census | 1956 | 12040 | none | romania only |
| 11 | yugoslav census | 1971 | none | 3745 | serbian banat only |
| 12 | romanian census | 1977 | 9267 | none | romania only |
| 13 | romanian census | 2002 | 6486 | none | romania only |
| 14 | serbian census | 2002 | none | 1658 | serbia only | | | | count ( "notes" ) |
|---:|--------------------:|
| 0 | 15 | | [
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select week where opponent = 'dallas desperados' order by week asc limit 1 col : week | date | opponent | home/away | result | bye row 1 : 1 | february 8 | new orleans voodoo | home | l 42-34 | 0 row 2 : 2 | february 15 | dallas desperados | away | l 51-47 | 0 row 3 : 3 | february 21 | columbus destroyers | home | w 56-34 | 0 row 4 : 4 | february 29 | tampa bay storm | away | l 40-37 | 0 row 5 : 5 | march 7 | chicago rush | home | w 53-47 | 0 row 6 : 6 | march 13 | columbus destroyers | away | l 43-41 | 0 row 7 : 7 | march 21 | colorado crush | home | l 40-33 | 0 row 8 : 8 | march 28 | austin wranglers | away | w 65-60 | 0 row 9 : 9 | april 4 | dallas desperados | home | w 47-31 | 0 row 10 : 10 | none | none | week | none | 1 row 11 : 11 | april 17 | carolina cobras | away | l 63-59 | 0 row 12 : 12 | april 24 | new york dragons | home | w 60-58 | 0 row 13 : 13 | may 1 | colorado crush | away | l 58-40 | 0 row 14 : 14 | may 8 | las vegas gladiators | home | l 63-35 | 0 row 15 : 15 | may 15 | carolina cobras | home | l 46-43 | 0 row 16 : 16 | may 22 | san jose sabercats | away | l 48-36 | 0 row 17 : 17 | may 30 | new york dragons | away | l 69-54 | 0 | col : week row 1 : 2 | select week where opponent = 'dallas desperados' order by week asc limit 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& week & date & opponent & home/away & result & bye \\
\midrule
0 & 1 & february 8 & new orleans voodoo & home & l 42-34 & 0 \\
1 & 2 & february 15 & dallas desperados & away & l 51-47 & 0 \\
2 & 3 & february 21 & columbus destroyers & home & w 56-34 & 0 \\
3 & 4 & february 29 & tampa bay storm & away & l 40-37 & 0 \\
4 & 5 & march 7 & chicago rush & home & w 53-47 & 0 \\
5 & 6 & march 13 & columbus destroyers & away & l 43-41 & 0 \\
6 & 7 & march 21 & colorado crush & home & l 40-33 & 0 \\
7 & 8 & march 28 & austin wranglers & away & w 65-60 & 0 \\
8 & 9 & april 4 & dallas desperados & home & w 47-31 & 0 \\
9 & 10 & none & none & week & none & 1 \\
10 & 11 & april 17 & carolina cobras & away & l 63-59 & 0 \\
11 & 12 & april 24 & new york dragons & home & w 60-58 & 0 \\
12 & 13 & may 1 & colorado crush & away & l 58-40 & 0 \\
13 & 14 & may 8 & las vegas gladiators & home & l 63-35 & 0 \\
14 & 15 & may 15 & carolina cobras & home & l 46-43 & 0 \\
15 & 16 & may 22 & san jose sabercats & away & l 48-36 & 0 \\
16 & 17 & may 30 & new york dragons & away & l 69-54 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& week \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select week where opponent = 'dallas desperados' order by week asc limit 1 <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>home/away</th>
<th>result</th>
<th>bye</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>february 8</td>
<td>new orleans voodoo</td>
<td>home</td>
<td>l 42-34</td>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>february 15</td>
<td>dallas desperados</td>
<td>away</td>
<td>l 51-47</td>
<td>0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>february 21</td>
<td>columbus destroyers</td>
<td>home</td>
<td>w 56-34</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>february 29</td>
<td>tampa bay storm</td>
<td>away</td>
<td>l 40-37</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>march 7</td>
<td>chicago rush</td>
<td>home</td>
<td>w 53-47</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>march 13</td>
<td>columbus destroyers</td>
<td>away</td>
<td>l 43-41</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>march 21</td>
<td>colorado crush</td>
<td>home</td>
<td>l 40-33</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>march 28</td>
<td>austin wranglers</td>
<td>away</td>
<td>w 65-60</td>
<td>0</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>april 4</td>
<td>dallas desperados</td>
<td>home</td>
<td>w 47-31</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>none</td>
<td>none</td>
<td>week</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>april 17</td>
<td>carolina cobras</td>
<td>away</td>
<td>l 63-59</td>
<td>0</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>april 24</td>
<td>new york dragons</td>
<td>home</td>
<td>w 60-58</td>
<td>0</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>may 1</td>
<td>colorado crush</td>
<td>away</td>
<td>l 58-40</td>
<td>0</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>may 8</td>
<td>las vegas gladiators</td>
<td>home</td>
<td>l 63-35</td>
<td>0</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>may 15</td>
<td>carolina cobras</td>
<td>home</td>
<td>l 46-43</td>
<td>0</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>may 22</td>
<td>san jose sabercats</td>
<td>away</td>
<td>l 48-36</td>
<td>0</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>may 30</td>
<td>new york dragons</td>
<td>away</td>
<td>l 69-54</td>
<td>0</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>2</td>
</tr>
</tbody>
</table> | select week where opponent = 'dallas desperados' order by week asc limit 1 <table_name> : table | | week | date | opponent | home/away | result | bye |
|---:|-------:|:------------|:---------------------|:------------|:---------|------:|
| 0 | 1 | february 8 | new orleans voodoo | home | l 42-34 | 0 |
| 1 | 2 | february 15 | dallas desperados | away | l 51-47 | 0 |
| 2 | 3 | february 21 | columbus destroyers | home | w 56-34 | 0 |
| 3 | 4 | february 29 | tampa bay storm | away | l 40-37 | 0 |
| 4 | 5 | march 7 | chicago rush | home | w 53-47 | 0 |
| 5 | 6 | march 13 | columbus destroyers | away | l 43-41 | 0 |
| 6 | 7 | march 21 | colorado crush | home | l 40-33 | 0 |
| 7 | 8 | march 28 | austin wranglers | away | w 65-60 | 0 |
| 8 | 9 | april 4 | dallas desperados | home | w 47-31 | 0 |
| 9 | 10 | none | none | week | none | 1 |
| 10 | 11 | april 17 | carolina cobras | away | l 63-59 | 0 |
| 11 | 12 | april 24 | new york dragons | home | w 60-58 | 0 |
| 12 | 13 | may 1 | colorado crush | away | l 58-40 | 0 |
| 13 | 14 | may 8 | las vegas gladiators | home | l 63-35 | 0 |
| 14 | 15 | may 15 | carolina cobras | home | l 46-43 | 0 |
| 15 | 16 | may 22 | san jose sabercats | away | l 48-36 | 0 |
| 16 | 17 | may 30 | new york dragons | away | l 69-54 | 0 | | | | week |
|---:|-------:|
| 0 | 2 | | [
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select count ( name ) where security level(s) = 'minimum to maximum' col : name | location | opened | gender | security level(s) | capacity row 1 : northland region corrections facility | near kaikohe, northland | 2005 | male | minimum to high | 548 row 2 : auckland prison | paremoremo, auckland | 1968 | male | minimum to maximum | 681 row 3 : mount eden corrections facility | mount eden, auckland | 2011 | male | remand | 966 row 4 : auckland region women's corrections facility | wiri, auckland | 2006 | female | minimum to maximum | 456 row 5 : spring hill corrections facility | hampton downs, waikato | 2007 | male | minimum to high | 1050 row 6 : waikeria prison | south of te awamutu, waikato | 1911 | male | minimum to high | 750 row 7 : tongariro/rangipo prison | near turangi, waikato | 1922 | male | minimum to low-medium | 540 row 8 : whanganui prison | kaitoke, south of wanganui | 1978 | male | minimum to high | 538 row 9 : hawke's bay regional prison | south of hastings | 1989 | male | minimum to high | 666 row 10 : manawatu prison | linton, south of palmerston north | 1979 | male | none | 290 row 11 : rimutaka prison | trentham, upper hutt | 1967 | male | minimum to high | 942 row 12 : arohata prison | tawa, wellington | 1944 | female | minimum to high | 88 row 13 : christchurch men's prison | near templeton, christchurch | 1915 | male | minimum to high | 926 row 14 : christchurch women's prison | near templeton, christchurch | 1974 | female | minimum to high | 138 row 15 : rolleston prison | near rolleston, canterbury | 1958 | male | minimum to low-medium | 260 row 16 : otago corrections facility | north of milton, otago | 2007 | male | minimum to high-medium | 485 row 17 : invercargill prison | invercargill | 1910 | male | minimum to low-medium | 180 | col : count ( "name" ) row 1 : 2 | select count ( name ) where security level(s) = 'minimum to maximum' <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & location & opened & gender & security level(s) & capacity \\
\midrule
0 & northland region corrections facility & near kaikohe, northland & 2005 & male & minimum to high & 548 \\
1 & auckland prison & paremoremo, auckland & 1968 & male & minimum to maximum & 681 \\
2 & mount eden corrections facility & mount eden, auckland & 2011 & male & remand & 966 \\
3 & auckland region women's corrections facility & wiri, auckland & 2006 & female & minimum to maximum & 456 \\
4 & spring hill corrections facility & hampton downs, waikato & 2007 & male & minimum to high & 1050 \\
5 & waikeria prison & south of te awamutu, waikato & 1911 & male & minimum to high & 750 \\
6 & tongariro/rangipo prison & near turangi, waikato & 1922 & male & minimum to low-medium & 540 \\
7 & whanganui prison & kaitoke, south of wanganui & 1978 & male & minimum to high & 538 \\
8 & hawke's bay regional prison & south of hastings & 1989 & male & minimum to high & 666 \\
9 & manawatu prison & linton, south of palmerston north & 1979 & male & none & 290 \\
10 & rimutaka prison & trentham, upper hutt & 1967 & male & minimum to high & 942 \\
11 & arohata prison & tawa, wellington & 1944 & female & minimum to high & 88 \\
12 & christchurch men's prison & near templeton, christchurch & 1915 & male & minimum to high & 926 \\
13 & christchurch women's prison & near templeton, christchurch & 1974 & female & minimum to high & 138 \\
14 & rolleston prison & near rolleston, canterbury & 1958 & male & minimum to low-medium & 260 \\
15 & otago corrections facility & north of milton, otago & 2007 & male & minimum to high-medium & 485 \\
16 & invercargill prison & invercargill & 1910 & male & minimum to low-medium & 180 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "name" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( name ) where security level(s) = 'minimum to maximum' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>location</th>
<th>opened</th>
<th>gender</th>
<th>security level(s)</th>
<th>capacity</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>northland region corrections facility</td>
<td>near kaikohe, northland</td>
<td>2005</td>
<td>male</td>
<td>minimum to high</td>
<td>548</td>
</tr>
<tr>
<th>1</th>
<td>auckland prison</td>
<td>paremoremo, auckland</td>
<td>1968</td>
<td>male</td>
<td>minimum to maximum</td>
<td>681</td>
</tr>
<tr>
<th>2</th>
<td>mount eden corrections facility</td>
<td>mount eden, auckland</td>
<td>2011</td>
<td>male</td>
<td>remand</td>
<td>966</td>
</tr>
<tr>
<th>3</th>
<td>auckland region women's corrections facility</td>
<td>wiri, auckland</td>
<td>2006</td>
<td>female</td>
<td>minimum to maximum</td>
<td>456</td>
</tr>
<tr>
<th>4</th>
<td>spring hill corrections facility</td>
<td>hampton downs, waikato</td>
<td>2007</td>
<td>male</td>
<td>minimum to high</td>
<td>1050</td>
</tr>
<tr>
<th>5</th>
<td>waikeria prison</td>
<td>south of te awamutu, waikato</td>
<td>1911</td>
<td>male</td>
<td>minimum to high</td>
<td>750</td>
</tr>
<tr>
<th>6</th>
<td>tongariro/rangipo prison</td>
<td>near turangi, waikato</td>
<td>1922</td>
<td>male</td>
<td>minimum to low-medium</td>
<td>540</td>
</tr>
<tr>
<th>7</th>
<td>whanganui prison</td>
<td>kaitoke, south of wanganui</td>
<td>1978</td>
<td>male</td>
<td>minimum to high</td>
<td>538</td>
</tr>
<tr>
<th>8</th>
<td>hawke's bay regional prison</td>
<td>south of hastings</td>
<td>1989</td>
<td>male</td>
<td>minimum to high</td>
<td>666</td>
</tr>
<tr>
<th>9</th>
<td>manawatu prison</td>
<td>linton, south of palmerston north</td>
<td>1979</td>
<td>male</td>
<td>none</td>
<td>290</td>
</tr>
<tr>
<th>10</th>
<td>rimutaka prison</td>
<td>trentham, upper hutt</td>
<td>1967</td>
<td>male</td>
<td>minimum to high</td>
<td>942</td>
</tr>
<tr>
<th>11</th>
<td>arohata prison</td>
<td>tawa, wellington</td>
<td>1944</td>
<td>female</td>
<td>minimum to high</td>
<td>88</td>
</tr>
<tr>
<th>12</th>
<td>christchurch men's prison</td>
<td>near templeton, christchurch</td>
<td>1915</td>
<td>male</td>
<td>minimum to high</td>
<td>926</td>
</tr>
<tr>
<th>13</th>
<td>christchurch women's prison</td>
<td>near templeton, christchurch</td>
<td>1974</td>
<td>female</td>
<td>minimum to high</td>
<td>138</td>
</tr>
<tr>
<th>14</th>
<td>rolleston prison</td>
<td>near rolleston, canterbury</td>
<td>1958</td>
<td>male</td>
<td>minimum to low-medium</td>
<td>260</td>
</tr>
<tr>
<th>15</th>
<td>otago corrections facility</td>
<td>north of milton, otago</td>
<td>2007</td>
<td>male</td>
<td>minimum to high-medium</td>
<td>485</td>
</tr>
<tr>
<th>16</th>
<td>invercargill prison</td>
<td>invercargill</td>
<td>1910</td>
<td>male</td>
<td>minimum to low-medium</td>
<td>180</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>2</td>
</tr>
</tbody>
</table> | select count ( name ) where security level(s) = 'minimum to maximum' <table_name> : table | | name | location | opened | gender | security level(s) | capacity |
|---:|:---------------------------------------------|:----------------------------------|---------:|:---------|:-----------------------|-----------:|
| 0 | northland region corrections facility | near kaikohe, northland | 2005 | male | minimum to high | 548 |
| 1 | auckland prison | paremoremo, auckland | 1968 | male | minimum to maximum | 681 |
| 2 | mount eden corrections facility | mount eden, auckland | 2011 | male | remand | 966 |
| 3 | auckland region women's corrections facility | wiri, auckland | 2006 | female | minimum to maximum | 456 |
| 4 | spring hill corrections facility | hampton downs, waikato | 2007 | male | minimum to high | 1050 |
| 5 | waikeria prison | south of te awamutu, waikato | 1911 | male | minimum to high | 750 |
| 6 | tongariro/rangipo prison | near turangi, waikato | 1922 | male | minimum to low-medium | 540 |
| 7 | whanganui prison | kaitoke, south of wanganui | 1978 | male | minimum to high | 538 |
| 8 | hawke's bay regional prison | south of hastings | 1989 | male | minimum to high | 666 |
| 9 | manawatu prison | linton, south of palmerston north | 1979 | male | none | 290 |
| 10 | rimutaka prison | trentham, upper hutt | 1967 | male | minimum to high | 942 |
| 11 | arohata prison | tawa, wellington | 1944 | female | minimum to high | 88 |
| 12 | christchurch men's prison | near templeton, christchurch | 1915 | male | minimum to high | 926 |
| 13 | christchurch women's prison | near templeton, christchurch | 1974 | female | minimum to high | 138 |
| 14 | rolleston prison | near rolleston, canterbury | 1958 | male | minimum to low-medium | 260 |
| 15 | otago corrections facility | north of milton, otago | 2007 | male | minimum to high-medium | 485 |
| 16 | invercargill prison | invercargill | 1910 | male | minimum to low-medium | 180 | | | | count ( "name" ) |
|---:|-------------------:|
| 0 | 2 | | [
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select count ( manufacturer ) where power (horsepower) = 0 col : type | manufacturer | numbers | year built | quantity built | power (horsepower) | max speed (km/h) | note row 1 : rhn | hitachi | 1011-1048 (power cars) 11-48 (trailer cars) | 1967.0 | 38+38 | 220.0 | 90.0 | now use as a northeastern line commuter train row 2 : rts | tokyu | d9-d16 (power cars) ts4-ts7 (center/trailer cars) | 1971.0 | 8+4 | 220.0 | 70.0 | ex-mahachai railways, to be refurbished. similar bodyshell of thn and nkf but with different formation (power car-2 trailer cars) row 3 : thn | tokyu, hitachi and nippon sharyo | 1101-1140 | 1983.0 | 40 | 235.0 | 105.0 | similar to nkf row 4 : nkf | nippon sharyo, hitachi, fuji heavy industries,kawasaki heavy industries, niigata tekkousho, and kinki sharyo | 1201-1264, (center) 2101-2112 | 1985.0 | 64+12 | 235.0 | 105.0 | similar to thn, but with plastic chairs row 5 : asr (class 158 express sprinter) | brel, derby works | 2501-2512, (center) 2113-2120 | 1991.0 | 12+8 | 285.0 | 120.0 | metre gauge version of british rail class 158, with different gangways and couplers, and with inward-opening slam doors instead of plug doors. 3-car set until 2011, when all were refurbished with new seats, vinyl floors, an extra coach and new livery row 6 : apd .20 | daewoo heavy industries | 2513-2524 (center) 2121-2128 | 1995.0 | 10+8 | 298.0 | 120.0 | first batch, nar row 7 : body | | | | | | | row 8 : apd .60 | daewoo heavy industries | 2525-2544 | 1996.0 | 20+40 | 298.0 | 120.0 | second batch, wide body | col : count ( "manufacturer" ) row 1 : 0 | select count ( manufacturer ) where power (horsepower) = 0 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& type & manufacturer & numbers & year built & quantity built & power (horsepower) & max speed (km/h) & note \\
\midrule
0 & rhn & hitachi & 1011-1048 (power cars) 11-48 (trailer cars) & 1967.0 & 38+38 & 220.0 & 90.0 & now use as a northeastern line commuter train \\
1 & rts & tokyu & d9-d16 (power cars) ts4-ts7 (center/trailer cars) & 1971.0 & 8+4 & 220.0 & 70.0 & ex-mahachai railways, to be refurbished. similar bodyshell of thn and nkf but with different formation (power car-2 trailer cars) \\
2 & thn & tokyu, hitachi and nippon sharyo & 1101-1140 & 1983.0 & 40 & 235.0 & 105.0 & similar to nkf \\
3 & nkf & nippon sharyo, hitachi, fuji heavy industries,kawasaki heavy industries, niigata tekkousho, and kinki sharyo & 1201-1264, (center) 2101-2112 & 1985.0 & 64+12 & 235.0 & 105.0 & similar to thn, but with plastic chairs \\
4 & asr (class 158 express sprinter) & brel, derby works & 2501-2512, (center) 2113-2120 & 1991.0 & 12+8 & 285.0 & 120.0 & metre gauge version of british rail class 158, with different gangways and couplers, and with inward-opening slam doors instead of plug doors. 3-car set until 2011, when all were refurbished with new seats, vinyl floors, an extra coach and new livery \\
5 & apd .20 & daewoo heavy industries & 2513-2524 (center) 2121-2128 & 1995.0 & 10+8 & 298.0 & 120.0 & first batch, nar \\
6 & body & & & & & & & \\
7 & apd .60 & daewoo heavy industries & 2525-2544 & 1996.0 & 20+40 & 298.0 & 120.0 & second batch, wide body \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "manufacturer" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( manufacturer ) where power (horsepower) = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>type</th>
<th>manufacturer</th>
<th>numbers</th>
<th>year built</th>
<th>quantity built</th>
<th>power (horsepower)</th>
<th>max speed (km/h)</th>
<th>note</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>rhn</td>
<td>hitachi</td>
<td>1011-1048 (power cars) 11-48 (trailer cars)</td>
<td>1967.0</td>
<td>38+38</td>
<td>220.0</td>
<td>90.0</td>
<td>now use as a northeastern line commuter train</td>
</tr>
<tr>
<th>1</th>
<td>rts</td>
<td>tokyu</td>
<td>d9-d16 (power cars) ts4-ts7 (center/trailer cars)</td>
<td>1971.0</td>
<td>8+4</td>
<td>220.0</td>
<td>70.0</td>
<td>ex-mahachai railways, to be refurbished. similar bodyshell of thn and nkf but with different formation (power car-2 trailer cars)</td>
</tr>
<tr>
<th>2</th>
<td>thn</td>
<td>tokyu, hitachi and nippon sharyo</td>
<td>1101-1140</td>
<td>1983.0</td>
<td>40</td>
<td>235.0</td>
<td>105.0</td>
<td>similar to nkf</td>
</tr>
<tr>
<th>3</th>
<td>nkf</td>
<td>nippon sharyo, hitachi, fuji heavy industries,kawasaki heavy industries, niigata tekkousho, and kinki sharyo</td>
<td>1201-1264, (center) 2101-2112</td>
<td>1985.0</td>
<td>64+12</td>
<td>235.0</td>
<td>105.0</td>
<td>similar to thn, but with plastic chairs</td>
</tr>
<tr>
<th>4</th>
<td>asr (class 158 express sprinter)</td>
<td>brel, derby works</td>
<td>2501-2512, (center) 2113-2120</td>
<td>1991.0</td>
<td>12+8</td>
<td>285.0</td>
<td>120.0</td>
<td>metre gauge version of british rail class 158, with different gangways and couplers, and with inward-opening slam doors instead of plug doors. 3-car set until 2011, when all were refurbished with new seats, vinyl floors, an extra coach and new livery</td>
</tr>
<tr>
<th>5</th>
<td>apd .20</td>
<td>daewoo heavy industries</td>
<td>2513-2524 (center) 2121-2128</td>
<td>1995.0</td>
<td>10+8</td>
<td>298.0</td>
<td>120.0</td>
<td>first batch, nar</td>
</tr>
<tr>
<th>6</th>
<td>body</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>apd .60</td>
<td>daewoo heavy industries</td>
<td>2525-2544</td>
<td>1996.0</td>
<td>20+40</td>
<td>298.0</td>
<td>120.0</td>
<td>second batch, wide body</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "manufacturer" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( manufacturer ) where power (horsepower) = 0 <table_name> : table | | type | manufacturer | numbers | year built | quantity built | power (horsepower) | max speed (km/h) | note |
|---:|:---------------------------------|:-------------------------------------------------------------------------------------------------------------|:--------------------------------------------------|:-------------|:-----------------|:---------------------|:-------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | rhn | hitachi | 1011-1048 (power cars) 11-48 (trailer cars) | 1967.0 | 38+38 | 220.0 | 90.0 | now use as a northeastern line commuter train |
| 1 | rts | tokyu | d9-d16 (power cars) ts4-ts7 (center/trailer cars) | 1971.0 | 8+4 | 220.0 | 70.0 | ex-mahachai railways, to be refurbished. similar bodyshell of thn and nkf but with different formation (power car-2 trailer cars) |
| 2 | thn | tokyu, hitachi and nippon sharyo | 1101-1140 | 1983.0 | 40 | 235.0 | 105.0 | similar to nkf |
| 3 | nkf | nippon sharyo, hitachi, fuji heavy industries,kawasaki heavy industries, niigata tekkousho, and kinki sharyo | 1201-1264, (center) 2101-2112 | 1985.0 | 64+12 | 235.0 | 105.0 | similar to thn, but with plastic chairs |
| 4 | asr (class 158 express sprinter) | brel, derby works | 2501-2512, (center) 2113-2120 | 1991.0 | 12+8 | 285.0 | 120.0 | metre gauge version of british rail class 158, with different gangways and couplers, and with inward-opening slam doors instead of plug doors. 3-car set until 2011, when all were refurbished with new seats, vinyl floors, an extra coach and new livery |
| 5 | apd .20 | daewoo heavy industries | 2513-2524 (center) 2121-2128 | 1995.0 | 10+8 | 298.0 | 120.0 | first batch, nar |
| 6 | body | | | | | | | |
| 7 | apd .60 | daewoo heavy industries | 2525-2544 | 1996.0 | 20+40 | 298.0 | 120.0 | second batch, wide body | | | | count ( "manufacturer" ) |
|---:|---------------------------:|
| 0 | 0 | | [
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select count ( * ) where coach > 465 col : season | division | w-l | finish | home | road | gf | ga | coach | playoffs | avg attendance row 1 : 2006 | western | 1-15 | 6th | 0-8 | 1-7 | 150 | 202 | paul day | missed playoffs | 10367 row 2 : 2007 | western | 6-10 | 5th | 4-4 | 2-6 | 160 | 189 | paul day | missed playoffs | 10815 row 3 : 2008 | western | 4-12 | 5th | 3-5 | 1-7 | 141 | 197 | paul day (0-5) bob hamley (4-7) | missed playoffs | 8820 row 4 : 2009 | western | 5-11 | 6th | 4-4 | 1-7 | 159 | 200 | bob hamley | missed playoffs | 8347 row 5 : 2010 | western | 10-6 | 3rd | 5-3 | 5-3 | 186 | 201 | derek keenan | lost in western final | 7558 row 6 : 2011 | western | 5-11 | 5th | 4-4 | 1-7 | 175 | 204 | derek keenan | missed playoffs | 7151 row 7 : 2012 | western | 6-10 | 4th | 4-4 | 2-6 | 167 | 175 | derek keenan | lost in final | 7050 row 8 : 2013 | western | 9-7 | 3rd | 2-6 | 7-1 | 203 | 170 | derek keenan | lost in western semi-final | 6714 row 9 : total | 8 seasons | 46-82 | none | 26-38 | 20-44 | 1341 | 1538 | none | none | 8353 row 10 : playoff totals | none | 3-3 | none | 0-0 | 3-3 | 73 | 54 | none | none | none | col : count ( "*" ) row 1 : 10 | select count ( * ) where coach > 465 <table_name> : table \begin{tabular}{llllllllllll}
\toprule
& season & division & w-l & finish & home & road & gf & ga & coach & playoffs & avg attendance \\
\midrule
0 & 2006 & western & 1-15 & 6th & 0-8 & 1-7 & 150 & 202 & paul day & missed playoffs & 10367 \\
1 & 2007 & western & 6-10 & 5th & 4-4 & 2-6 & 160 & 189 & paul day & missed playoffs & 10815 \\
2 & 2008 & western & 4-12 & 5th & 3-5 & 1-7 & 141 & 197 & paul day (0-5) bob hamley (4-7) & missed playoffs & 8820 \\
3 & 2009 & western & 5-11 & 6th & 4-4 & 1-7 & 159 & 200 & bob hamley & missed playoffs & 8347 \\
4 & 2010 & western & 10-6 & 3rd & 5-3 & 5-3 & 186 & 201 & derek keenan & lost in western final & 7558 \\
5 & 2011 & western & 5-11 & 5th & 4-4 & 1-7 & 175 & 204 & derek keenan & missed playoffs & 7151 \\
6 & 2012 & western & 6-10 & 4th & 4-4 & 2-6 & 167 & 175 & derek keenan & lost in final & 7050 \\
7 & 2013 & western & 9-7 & 3rd & 2-6 & 7-1 & 203 & 170 & derek keenan & lost in western semi-final & 6714 \\
8 & total & 8 seasons & 46-82 & none & 26-38 & 20-44 & 1341 & 1538 & none & none & 8353 \\
9 & playoff totals & none & 3-3 & none & 0-0 & 3-3 & 73 & 54 & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 10 \\
\bottomrule
\end{tabular}
| select count ( * ) where coach > 465 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>division</th>
<th>w-l</th>
<th>finish</th>
<th>home</th>
<th>road</th>
<th>gf</th>
<th>ga</th>
<th>coach</th>
<th>playoffs</th>
<th>avg attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2006</td>
<td>western</td>
<td>1-15</td>
<td>6th</td>
<td>0-8</td>
<td>1-7</td>
<td>150</td>
<td>202</td>
<td>paul day</td>
<td>missed playoffs</td>
<td>10367</td>
</tr>
<tr>
<th>1</th>
<td>2007</td>
<td>western</td>
<td>6-10</td>
<td>5th</td>
<td>4-4</td>
<td>2-6</td>
<td>160</td>
<td>189</td>
<td>paul day</td>
<td>missed playoffs</td>
<td>10815</td>
</tr>
<tr>
<th>2</th>
<td>2008</td>
<td>western</td>
<td>4-12</td>
<td>5th</td>
<td>3-5</td>
<td>1-7</td>
<td>141</td>
<td>197</td>
<td>paul day (0-5) bob hamley (4-7)</td>
<td>missed playoffs</td>
<td>8820</td>
</tr>
<tr>
<th>3</th>
<td>2009</td>
<td>western</td>
<td>5-11</td>
<td>6th</td>
<td>4-4</td>
<td>1-7</td>
<td>159</td>
<td>200</td>
<td>bob hamley</td>
<td>missed playoffs</td>
<td>8347</td>
</tr>
<tr>
<th>4</th>
<td>2010</td>
<td>western</td>
<td>10-6</td>
<td>3rd</td>
<td>5-3</td>
<td>5-3</td>
<td>186</td>
<td>201</td>
<td>derek keenan</td>
<td>lost in western final</td>
<td>7558</td>
</tr>
<tr>
<th>5</th>
<td>2011</td>
<td>western</td>
<td>5-11</td>
<td>5th</td>
<td>4-4</td>
<td>1-7</td>
<td>175</td>
<td>204</td>
<td>derek keenan</td>
<td>missed playoffs</td>
<td>7151</td>
</tr>
<tr>
<th>6</th>
<td>2012</td>
<td>western</td>
<td>6-10</td>
<td>4th</td>
<td>4-4</td>
<td>2-6</td>
<td>167</td>
<td>175</td>
<td>derek keenan</td>
<td>lost in final</td>
<td>7050</td>
</tr>
<tr>
<th>7</th>
<td>2013</td>
<td>western</td>
<td>9-7</td>
<td>3rd</td>
<td>2-6</td>
<td>7-1</td>
<td>203</td>
<td>170</td>
<td>derek keenan</td>
<td>lost in western semi-final</td>
<td>6714</td>
</tr>
<tr>
<th>8</th>
<td>total</td>
<td>8 seasons</td>
<td>46-82</td>
<td>none</td>
<td>26-38</td>
<td>20-44</td>
<td>1341</td>
<td>1538</td>
<td>none</td>
<td>none</td>
<td>8353</td>
</tr>
<tr>
<th>9</th>
<td>playoff totals</td>
<td>none</td>
<td>3-3</td>
<td>none</td>
<td>0-0</td>
<td>3-3</td>
<td>73</td>
<td>54</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>10</td>
</tr>
</tbody>
</table> | select count ( * ) where coach > 465 <table_name> : table | | season | division | w-l | finish | home | road | gf | ga | coach | playoffs | avg attendance |
|---:|:---------------|:-----------|:------|:---------|:-------|:-------|-----:|-----:|:--------------------------------|:---------------------------|:-----------------|
| 0 | 2006 | western | 1-15 | 6th | 0-8 | 1-7 | 150 | 202 | paul day | missed playoffs | 10367 |
| 1 | 2007 | western | 6-10 | 5th | 4-4 | 2-6 | 160 | 189 | paul day | missed playoffs | 10815 |
| 2 | 2008 | western | 4-12 | 5th | 3-5 | 1-7 | 141 | 197 | paul day (0-5) bob hamley (4-7) | missed playoffs | 8820 |
| 3 | 2009 | western | 5-11 | 6th | 4-4 | 1-7 | 159 | 200 | bob hamley | missed playoffs | 8347 |
| 4 | 2010 | western | 10-6 | 3rd | 5-3 | 5-3 | 186 | 201 | derek keenan | lost in western final | 7558 |
| 5 | 2011 | western | 5-11 | 5th | 4-4 | 1-7 | 175 | 204 | derek keenan | missed playoffs | 7151 |
| 6 | 2012 | western | 6-10 | 4th | 4-4 | 2-6 | 167 | 175 | derek keenan | lost in final | 7050 |
| 7 | 2013 | western | 9-7 | 3rd | 2-6 | 7-1 | 203 | 170 | derek keenan | lost in western semi-final | 6714 |
| 8 | total | 8 seasons | 46-82 | none | 26-38 | 20-44 | 1341 | 1538 | none | none | 8353 |
| 9 | playoff totals | none | 3-3 | none | 0-0 | 3-3 | 73 | 54 | none | none | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 10 | | [
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] |
select silver where nation = 'kyrgyzstan (kgz)' 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 : silver row 1 : 1 | select silver where nation = 'kyrgyzstan (kgz)' <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
& silver \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select silver where nation = 'kyrgyzstan (kgz)' <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>silver</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select silver where nation = 'kyrgyzstan (kgz)' <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 | | | | silver |
|---:|---------:|
| 0 | 1 | | [
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select count ( manufacturer ) where time/retired < 554 col : pos | rider | manufacturer | time/retired | points row 1 : 1 | tohru ukawa | honda | 49:50.449 | 25 row 2 : 2 | franco battaini | aprilia | 5.125 | 20 row 3 : 3 | loris capirossi | honda | 10.224 | 16 row 4 : 4 | shinya nakano | yamaha | 14.848 | 13 row 5 : 5 | stefano perugini | honda | 34.042 | 11 row 6 : 6 | sebastian porto | yamaha | 37.495 | 10 row 7 : 7 | jason vincent | honda | 44.911 | 9 row 8 : 8 | valentino rossi | aprilia | +1:01.110 | 8 row 9 : 9 | anthony west | tsr-honda | +1:10.352 | 7 row 10 : 10 | alex hofmann | tsr-honda | +1:18.683 | 6 row 11 : 11 | luca boscoscuro | tsr-honda | +1:20.847 | 5 row 12 : 12 | lucas oliver bulto | yamaha | +1:23.052 | 4 row 13 : 13 | roberto rolfo | aprilia | +1:24.329 | 3 row 14 : 14 | masaki tokudome | tsr-honda | +1:26.837 | 2 row 15 : 15 | fonsi nieto | yamaha | +1:45.669 | 1 row 16 : 16 | david garcia | yamaha | +1:48.926 | none row 17 : 17 | scott smart | aprilia | +1:49.730 | none row 18 : 18 | alex debon | honda | +1 lap | none row 19 : 19 | jarno janssen | tsr-honda | +1 lap | none row 20 : ret | alvaro molina | honda | retirement | none row 21 : ret | julien allemand | tsr-honda | retirement | none row 22 : ret | ismael bonilla | honda | retirement | none row 23 : ret | daniel ribalta | aprilia | retirement | none row 24 : ret | maurice bolwerk | honda | retirement | none row 25 : ret | tomomi manako | yamaha | retirement | none row 26 : ret | johann stigefelt | yamaha | retirement | none row 27 : ret | olivier jacque | yamaha | retirement | none row 28 : ret | jeremy mcwilliams | aprilia | retirement | none row 29 : ret | david ortega | tsr-honda | retirement | none row 30 : ret | alfredo rios | aprilia | retirement | none row 31 : ret | ralf waldmann | aprilia | retirement | none | col : count ( "manufacturer" ) row 1 : 19 | select count ( manufacturer ) where time/retired < 554 <table_name> : table \begin{tabular}{llllll}
\toprule
& pos & rider & manufacturer & time/retired & points \\
\midrule
0 & 1 & tohru ukawa & honda & 49:50.449 & 25 \\
1 & 2 & franco battaini & aprilia & 5.125 & 20 \\
2 & 3 & loris capirossi & honda & 10.224 & 16 \\
3 & 4 & shinya nakano & yamaha & 14.848 & 13 \\
4 & 5 & stefano perugini & honda & 34.042 & 11 \\
5 & 6 & sebastian porto & yamaha & 37.495 & 10 \\
6 & 7 & jason vincent & honda & 44.911 & 9 \\
7 & 8 & valentino rossi & aprilia & +1:01.110 & 8 \\
8 & 9 & anthony west & tsr-honda & +1:10.352 & 7 \\
9 & 10 & alex hofmann & tsr-honda & +1:18.683 & 6 \\
10 & 11 & luca boscoscuro & tsr-honda & +1:20.847 & 5 \\
11 & 12 & lucas oliver bulto & yamaha & +1:23.052 & 4 \\
12 & 13 & roberto rolfo & aprilia & +1:24.329 & 3 \\
13 & 14 & masaki tokudome & tsr-honda & +1:26.837 & 2 \\
14 & 15 & fonsi nieto & yamaha & +1:45.669 & 1 \\
15 & 16 & david garcia & yamaha & +1:48.926 & none \\
16 & 17 & scott smart & aprilia & +1:49.730 & none \\
17 & 18 & alex debon & honda & +1 lap & none \\
18 & 19 & jarno janssen & tsr-honda & +1 lap & none \\
19 & ret & alvaro molina & honda & retirement & none \\
20 & ret & julien allemand & tsr-honda & retirement & none \\
21 & ret & ismael bonilla & honda & retirement & none \\
22 & ret & daniel ribalta & aprilia & retirement & none \\
23 & ret & maurice bolwerk & honda & retirement & none \\
24 & ret & tomomi manako & yamaha & retirement & none \\
25 & ret & johann stigefelt & yamaha & retirement & none \\
26 & ret & olivier jacque & yamaha & retirement & none \\
27 & ret & jeremy mcwilliams & aprilia & retirement & none \\
28 & ret & david ortega & tsr-honda & retirement & none \\
29 & ret & alfredo rios & aprilia & retirement & none \\
30 & ret & ralf waldmann & aprilia & retirement & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "manufacturer" ) \\
\midrule
0 & 19 \\
\bottomrule
\end{tabular}
| select count ( manufacturer ) where time/retired < 554 <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>time/retired</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>tohru ukawa</td>
<td>honda</td>
<td>49:50.449</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>franco battaini</td>
<td>aprilia</td>
<td>5.125</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>loris capirossi</td>
<td>honda</td>
<td>10.224</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>shinya nakano</td>
<td>yamaha</td>
<td>14.848</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>stefano perugini</td>
<td>honda</td>
<td>34.042</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>sebastian porto</td>
<td>yamaha</td>
<td>37.495</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>jason vincent</td>
<td>honda</td>
<td>44.911</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>valentino rossi</td>
<td>aprilia</td>
<td>+1:01.110</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>anthony west</td>
<td>tsr-honda</td>
<td>+1:10.352</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>alex hofmann</td>
<td>tsr-honda</td>
<td>+1:18.683</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>luca boscoscuro</td>
<td>tsr-honda</td>
<td>+1:20.847</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>lucas oliver bulto</td>
<td>yamaha</td>
<td>+1:23.052</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>roberto rolfo</td>
<td>aprilia</td>
<td>+1:24.329</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>masaki tokudome</td>
<td>tsr-honda</td>
<td>+1:26.837</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>fonsi nieto</td>
<td>yamaha</td>
<td>+1:45.669</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>david garcia</td>
<td>yamaha</td>
<td>+1:48.926</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>scott smart</td>
<td>aprilia</td>
<td>+1:49.730</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>alex debon</td>
<td>honda</td>
<td>+1 lap</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>jarno janssen</td>
<td>tsr-honda</td>
<td>+1 lap</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>alvaro molina</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>julien allemand</td>
<td>tsr-honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>ret</td>
<td>ismael bonilla</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>ret</td>
<td>daniel ribalta</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>ret</td>
<td>maurice bolwerk</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>tomomi manako</td>
<td>yamaha</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>johann stigefelt</td>
<td>yamaha</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>ret</td>
<td>olivier jacque</td>
<td>yamaha</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>ret</td>
<td>jeremy mcwilliams</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>ret</td>
<td>david ortega</td>
<td>tsr-honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>ret</td>
<td>alfredo rios</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>ret</td>
<td>ralf waldmann</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "manufacturer" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>19</td>
</tr>
</tbody>
</table> | select count ( manufacturer ) where time/retired < 554 <table_name> : table | | pos | rider | manufacturer | time/retired | points |
|---:|:------|:-------------------|:---------------|:---------------|:---------|
| 0 | 1 | tohru ukawa | honda | 49:50.449 | 25 |
| 1 | 2 | franco battaini | aprilia | 5.125 | 20 |
| 2 | 3 | loris capirossi | honda | 10.224 | 16 |
| 3 | 4 | shinya nakano | yamaha | 14.848 | 13 |
| 4 | 5 | stefano perugini | honda | 34.042 | 11 |
| 5 | 6 | sebastian porto | yamaha | 37.495 | 10 |
| 6 | 7 | jason vincent | honda | 44.911 | 9 |
| 7 | 8 | valentino rossi | aprilia | +1:01.110 | 8 |
| 8 | 9 | anthony west | tsr-honda | +1:10.352 | 7 |
| 9 | 10 | alex hofmann | tsr-honda | +1:18.683 | 6 |
| 10 | 11 | luca boscoscuro | tsr-honda | +1:20.847 | 5 |
| 11 | 12 | lucas oliver bulto | yamaha | +1:23.052 | 4 |
| 12 | 13 | roberto rolfo | aprilia | +1:24.329 | 3 |
| 13 | 14 | masaki tokudome | tsr-honda | +1:26.837 | 2 |
| 14 | 15 | fonsi nieto | yamaha | +1:45.669 | 1 |
| 15 | 16 | david garcia | yamaha | +1:48.926 | none |
| 16 | 17 | scott smart | aprilia | +1:49.730 | none |
| 17 | 18 | alex debon | honda | +1 lap | none |
| 18 | 19 | jarno janssen | tsr-honda | +1 lap | none |
| 19 | ret | alvaro molina | honda | retirement | none |
| 20 | ret | julien allemand | tsr-honda | retirement | none |
| 21 | ret | ismael bonilla | honda | retirement | none |
| 22 | ret | daniel ribalta | aprilia | retirement | none |
| 23 | ret | maurice bolwerk | honda | retirement | none |
| 24 | ret | tomomi manako | yamaha | retirement | none |
| 25 | ret | johann stigefelt | yamaha | retirement | none |
| 26 | ret | olivier jacque | yamaha | retirement | none |
| 27 | ret | jeremy mcwilliams | aprilia | retirement | none |
| 28 | ret | david ortega | tsr-honda | retirement | none |
| 29 | ret | alfredo rios | aprilia | retirement | none |
| 30 | ret | ralf waldmann | aprilia | retirement | none | | | | count ( "manufacturer" ) |
|---:|---------------------------:|
| 0 | 19 | | [
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] |
select film where film = 'daylight (asa 8) and type b (asa 10)' col : film -1 | film -2 | date row 1 : kodachrome film | 16 mm, daylight (asa 10) & type a (asa 16) | 1935-1962 row 2 : kodachrome film | 8 mm, daylight (asa 10) & type a (asa 16) | 1936-1962 row 3 : kodachrome film | 35 mm and 828, daylight & type a | 1936-1962 row 4 : kodachrome professional film (sheets) | daylight (asa 8) and type b (asa 10) | 1938-1951 row 5 : kodachrome film | 35 mm and 828, type f (asa 12) | 1955-1962 row 6 : kodachrome professional film | 35 mm, type a (asa 16) | 1956-1962 row 7 : kodak color print material | type d (slide duping film) | 1955-1957 row 8 : kodachrome ii film | 16 mm, daylight (asa 25) and type a (asa 40) | 1961-1974 row 9 : kodachrome ii film | 8 mm, daylight (asa 25) and type a (asa 40) | 1961-1974 row 10 : kodachrome ii film | s-8, type a (asa 40) | 1965-1974 row 11 : kodachrome ii film | 35 mm and 828, daylight (asa 25/early) (asa 64/late) | 1961-1974 row 12 : kodachrome ii film | professional, 35 mm, type a (asa 40) | 1962-1978 row 13 : kodachrome-x film | 35 mm (asa 64) | 1962-1974 row 14 : kodachrome-x film | 126 format | 1963-1974 row 15 : kodachrome-x film | 110 format | 1972-1974 row 16 : kodachrome 25 film | 35 mm, daylight | 1974-2001 row 17 : kodachrome 25 film | movie film, 16 mm, daylight | 1974-2002 row 18 : kodachrome 25 film | movie film, 8 mm, daylight | 1974-1992 row 19 : kodachrome 25 film | professional film, 35 mm, daylight | 1983-1999 row 20 : kodachrome 40 film | 35 mm, type a | 1978-1997 row 21 : kodachrome 40 film | movie film, 16 mm, type a | 1974-2006 row 22 : kodachrome 40 film | movie film, s-8, type a | 1974-2005 row 23 : kodachrome 40 film | sound movie film, s-8, type a | 1974-1998 row 24 : kodachrome 40 film | movie film, 8 mm, type a | 1974-1992 row 25 : kodachrome 64 | 35 mm, daylight | 1974-2009 row 26 : kodachrome 64 | 126 format, daylight | 1974-1993 row 27 : kodachrome 64 | 110 format, daylight | 1974-1987 row 28 : kodachrome 64 | professional film, 35 mm, daylight | 1983-2009 row 29 : kodachrome 64 | professional film, daylight, 120 format | 1986-1996 row 30 : kodachrome 200 | professional film, 35 mm, daylight | 1986-2004 row 31 : kodachrome 200 | 35 mm, daylight | 1988-2007 row 32 : cine-chrome 40a | double regular 8 mm, tungsten | 2003-2006 | col : film row 1 : daylight (asa 8) and type b (asa 10) | select film where film = 'daylight (asa 8) and type b (asa 10)' <table_name> : table \begin{tabular}{llll}
\toprule
& film -1 & film -2 & date \\
\midrule
0 & kodachrome film & 16 mm, daylight (asa 10) & type a (asa 16) & 1935-1962 \\
1 & kodachrome film & 8 mm, daylight (asa 10) & type a (asa 16) & 1936-1962 \\
2 & kodachrome film & 35 mm and 828, daylight & type a & 1936-1962 \\
3 & kodachrome professional film (sheets) & daylight (asa 8) and type b (asa 10) & 1938-1951 \\
4 & kodachrome film & 35 mm and 828, type f (asa 12) & 1955-1962 \\
5 & kodachrome professional film & 35 mm, type a (asa 16) & 1956-1962 \\
6 & kodak color print material & type d (slide duping film) & 1955-1957 \\
7 & kodachrome ii film & 16 mm, daylight (asa 25) and type a (asa 40) & 1961-1974 \\
8 & kodachrome ii film & 8 mm, daylight (asa 25) and type a (asa 40) & 1961-1974 \\
9 & kodachrome ii film & s-8, type a (asa 40) & 1965-1974 \\
10 & kodachrome ii film & 35 mm and 828, daylight (asa 25/early) (asa 64/late) & 1961-1974 \\
11 & kodachrome ii film & professional, 35 mm, type a (asa 40) & 1962-1978 \\
12 & kodachrome-x film & 35 mm (asa 64) & 1962-1974 \\
13 & kodachrome-x film & 126 format & 1963-1974 \\
14 & kodachrome-x film & 110 format & 1972-1974 \\
15 & kodachrome 25 film & 35 mm, daylight & 1974-2001 \\
16 & kodachrome 25 film & movie film, 16 mm, daylight & 1974-2002 \\
17 & kodachrome 25 film & movie film, 8 mm, daylight & 1974-1992 \\
18 & kodachrome 25 film & professional film, 35 mm, daylight & 1983-1999 \\
19 & kodachrome 40 film & 35 mm, type a & 1978-1997 \\
20 & kodachrome 40 film & movie film, 16 mm, type a & 1974-2006 \\
21 & kodachrome 40 film & movie film, s-8, type a & 1974-2005 \\
22 & kodachrome 40 film & sound movie film, s-8, type a & 1974-1998 \\
23 & kodachrome 40 film & movie film, 8 mm, type a & 1974-1992 \\
24 & kodachrome 64 & 35 mm, daylight & 1974-2009 \\
25 & kodachrome 64 & 126 format, daylight & 1974-1993 \\
26 & kodachrome 64 & 110 format, daylight & 1974-1987 \\
27 & kodachrome 64 & professional film, 35 mm, daylight & 1983-2009 \\
28 & kodachrome 64 & professional film, daylight, 120 format & 1986-1996 \\
29 & kodachrome 200 & professional film, 35 mm, daylight & 1986-2004 \\
30 & kodachrome 200 & 35 mm, daylight & 1988-2007 \\
31 & cine-chrome 40a & double regular 8 mm, tungsten & 2003-2006 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& film \\
\midrule
0 & daylight (asa 8) and type b (asa 10) \\
\bottomrule
\end{tabular}
| select film where film = 'daylight (asa 8) and type b (asa 10)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>film -1</th>
<th>film -2</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>kodachrome film</td>
<td>16 mm, daylight (asa 10) & type a (asa 16)</td>
<td>1935-1962</td>
</tr>
<tr>
<th>1</th>
<td>kodachrome film</td>
<td>8 mm, daylight (asa 10) & type a (asa 16)</td>
<td>1936-1962</td>
</tr>
<tr>
<th>2</th>
<td>kodachrome film</td>
<td>35 mm and 828, daylight & type a</td>
<td>1936-1962</td>
</tr>
<tr>
<th>3</th>
<td>kodachrome professional film (sheets)</td>
<td>daylight (asa 8) and type b (asa 10)</td>
<td>1938-1951</td>
</tr>
<tr>
<th>4</th>
<td>kodachrome film</td>
<td>35 mm and 828, type f (asa 12)</td>
<td>1955-1962</td>
</tr>
<tr>
<th>5</th>
<td>kodachrome professional film</td>
<td>35 mm, type a (asa 16)</td>
<td>1956-1962</td>
</tr>
<tr>
<th>6</th>
<td>kodak color print material</td>
<td>type d (slide duping film)</td>
<td>1955-1957</td>
</tr>
<tr>
<th>7</th>
<td>kodachrome ii film</td>
<td>16 mm, daylight (asa 25) and type a (asa 40)</td>
<td>1961-1974</td>
</tr>
<tr>
<th>8</th>
<td>kodachrome ii film</td>
<td>8 mm, daylight (asa 25) and type a (asa 40)</td>
<td>1961-1974</td>
</tr>
<tr>
<th>9</th>
<td>kodachrome ii film</td>
<td>s-8, type a (asa 40)</td>
<td>1965-1974</td>
</tr>
<tr>
<th>10</th>
<td>kodachrome ii film</td>
<td>35 mm and 828, daylight (asa 25/early) (asa 64/late)</td>
<td>1961-1974</td>
</tr>
<tr>
<th>11</th>
<td>kodachrome ii film</td>
<td>professional, 35 mm, type a (asa 40)</td>
<td>1962-1978</td>
</tr>
<tr>
<th>12</th>
<td>kodachrome-x film</td>
<td>35 mm (asa 64)</td>
<td>1962-1974</td>
</tr>
<tr>
<th>13</th>
<td>kodachrome-x film</td>
<td>126 format</td>
<td>1963-1974</td>
</tr>
<tr>
<th>14</th>
<td>kodachrome-x film</td>
<td>110 format</td>
<td>1972-1974</td>
</tr>
<tr>
<th>15</th>
<td>kodachrome 25 film</td>
<td>35 mm, daylight</td>
<td>1974-2001</td>
</tr>
<tr>
<th>16</th>
<td>kodachrome 25 film</td>
<td>movie film, 16 mm, daylight</td>
<td>1974-2002</td>
</tr>
<tr>
<th>17</th>
<td>kodachrome 25 film</td>
<td>movie film, 8 mm, daylight</td>
<td>1974-1992</td>
</tr>
<tr>
<th>18</th>
<td>kodachrome 25 film</td>
<td>professional film, 35 mm, daylight</td>
<td>1983-1999</td>
</tr>
<tr>
<th>19</th>
<td>kodachrome 40 film</td>
<td>35 mm, type a</td>
<td>1978-1997</td>
</tr>
<tr>
<th>20</th>
<td>kodachrome 40 film</td>
<td>movie film, 16 mm, type a</td>
<td>1974-2006</td>
</tr>
<tr>
<th>21</th>
<td>kodachrome 40 film</td>
<td>movie film, s-8, type a</td>
<td>1974-2005</td>
</tr>
<tr>
<th>22</th>
<td>kodachrome 40 film</td>
<td>sound movie film, s-8, type a</td>
<td>1974-1998</td>
</tr>
<tr>
<th>23</th>
<td>kodachrome 40 film</td>
<td>movie film, 8 mm, type a</td>
<td>1974-1992</td>
</tr>
<tr>
<th>24</th>
<td>kodachrome 64</td>
<td>35 mm, daylight</td>
<td>1974-2009</td>
</tr>
<tr>
<th>25</th>
<td>kodachrome 64</td>
<td>126 format, daylight</td>
<td>1974-1993</td>
</tr>
<tr>
<th>26</th>
<td>kodachrome 64</td>
<td>110 format, daylight</td>
<td>1974-1987</td>
</tr>
<tr>
<th>27</th>
<td>kodachrome 64</td>
<td>professional film, 35 mm, daylight</td>
<td>1983-2009</td>
</tr>
<tr>
<th>28</th>
<td>kodachrome 64</td>
<td>professional film, daylight, 120 format</td>
<td>1986-1996</td>
</tr>
<tr>
<th>29</th>
<td>kodachrome 200</td>
<td>professional film, 35 mm, daylight</td>
<td>1986-2004</td>
</tr>
<tr>
<th>30</th>
<td>kodachrome 200</td>
<td>35 mm, daylight</td>
<td>1988-2007</td>
</tr>
<tr>
<th>31</th>
<td>cine-chrome 40a</td>
<td>double regular 8 mm, tungsten</td>
<td>2003-2006</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>film</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>daylight (asa 8) and type b (asa 10)</td>
</tr>
</tbody>
</table> | select film where film = 'daylight (asa 8) and type b (asa 10)' <table_name> : table | | film -1 | film -2 | date |
|---:|:--------------------------------------|:-----------------------------------------------------|:----------|
| 0 | kodachrome film | 16 mm, daylight (asa 10) & type a (asa 16) | 1935-1962 |
| 1 | kodachrome film | 8 mm, daylight (asa 10) & type a (asa 16) | 1936-1962 |
| 2 | kodachrome film | 35 mm and 828, daylight & type a | 1936-1962 |
| 3 | kodachrome professional film (sheets) | daylight (asa 8) and type b (asa 10) | 1938-1951 |
| 4 | kodachrome film | 35 mm and 828, type f (asa 12) | 1955-1962 |
| 5 | kodachrome professional film | 35 mm, type a (asa 16) | 1956-1962 |
| 6 | kodak color print material | type d (slide duping film) | 1955-1957 |
| 7 | kodachrome ii film | 16 mm, daylight (asa 25) and type a (asa 40) | 1961-1974 |
| 8 | kodachrome ii film | 8 mm, daylight (asa 25) and type a (asa 40) | 1961-1974 |
| 9 | kodachrome ii film | s-8, type a (asa 40) | 1965-1974 |
| 10 | kodachrome ii film | 35 mm and 828, daylight (asa 25/early) (asa 64/late) | 1961-1974 |
| 11 | kodachrome ii film | professional, 35 mm, type a (asa 40) | 1962-1978 |
| 12 | kodachrome-x film | 35 mm (asa 64) | 1962-1974 |
| 13 | kodachrome-x film | 126 format | 1963-1974 |
| 14 | kodachrome-x film | 110 format | 1972-1974 |
| 15 | kodachrome 25 film | 35 mm, daylight | 1974-2001 |
| 16 | kodachrome 25 film | movie film, 16 mm, daylight | 1974-2002 |
| 17 | kodachrome 25 film | movie film, 8 mm, daylight | 1974-1992 |
| 18 | kodachrome 25 film | professional film, 35 mm, daylight | 1983-1999 |
| 19 | kodachrome 40 film | 35 mm, type a | 1978-1997 |
| 20 | kodachrome 40 film | movie film, 16 mm, type a | 1974-2006 |
| 21 | kodachrome 40 film | movie film, s-8, type a | 1974-2005 |
| 22 | kodachrome 40 film | sound movie film, s-8, type a | 1974-1998 |
| 23 | kodachrome 40 film | movie film, 8 mm, type a | 1974-1992 |
| 24 | kodachrome 64 | 35 mm, daylight | 1974-2009 |
| 25 | kodachrome 64 | 126 format, daylight | 1974-1993 |
| 26 | kodachrome 64 | 110 format, daylight | 1974-1987 |
| 27 | kodachrome 64 | professional film, 35 mm, daylight | 1983-2009 |
| 28 | kodachrome 64 | professional film, daylight, 120 format | 1986-1996 |
| 29 | kodachrome 200 | professional film, 35 mm, daylight | 1986-2004 |
| 30 | kodachrome 200 | 35 mm, daylight | 1988-2007 |
| 31 | cine-chrome 40a | double regular 8 mm, tungsten | 2003-2006 | | | | film |
|---:|:-------------------------------------|
| 0 | daylight (asa 8) and type b (asa 10) | | [
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select division where place = '19th' col : season | tier | division | place row 1 : 1992-96 | 5 | regional | none row 2 : 1996/97 | 4 | 3a | 16th row 3 : 1997/98 | 4 | 3a | 5th row 4 : 1998/99 | 4 | 3a | 12th row 5 : 1999/00 | 4 | 3a | 4th row 6 : 2000/01 | 4 | 3a | 6th row 7 : 2001/02 | 4 | 3a | 4th row 8 : 2002/03 | 4 | 3a | 3rd row 9 : 2003/04 | 3 | 2ab | 19th row 10 : 2004/05 | 4 | 3a | 2nd | col : division row 1 : 2ab | select division where place = '19th' <table_name> : table \begin{tabular}{lllll}
\toprule
& season & tier & division & place \\
\midrule
0 & 1992-96 & 5 & regional & none \\
1 & 1996/97 & 4 & 3a & 16th \\
2 & 1997/98 & 4 & 3a & 5th \\
3 & 1998/99 & 4 & 3a & 12th \\
4 & 1999/00 & 4 & 3a & 4th \\
5 & 2000/01 & 4 & 3a & 6th \\
6 & 2001/02 & 4 & 3a & 4th \\
7 & 2002/03 & 4 & 3a & 3rd \\
8 & 2003/04 & 3 & 2ab & 19th \\
9 & 2004/05 & 4 & 3a & 2nd \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& division \\
\midrule
0 & 2ab \\
\bottomrule
\end{tabular}
| select division where place = '19th' <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>1992-96</td>
<td>5</td>
<td>regional</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1996/97</td>
<td>4</td>
<td>3a</td>
<td>16th</td>
</tr>
<tr>
<th>2</th>
<td>1997/98</td>
<td>4</td>
<td>3a</td>
<td>5th</td>
</tr>
<tr>
<th>3</th>
<td>1998/99</td>
<td>4</td>
<td>3a</td>
<td>12th</td>
</tr>
<tr>
<th>4</th>
<td>1999/00</td>
<td>4</td>
<td>3a</td>
<td>4th</td>
</tr>
<tr>
<th>5</th>
<td>2000/01</td>
<td>4</td>
<td>3a</td>
<td>6th</td>
</tr>
<tr>
<th>6</th>
<td>2001/02</td>
<td>4</td>
<td>3a</td>
<td>4th</td>
</tr>
<tr>
<th>7</th>
<td>2002/03</td>
<td>4</td>
<td>3a</td>
<td>3rd</td>
</tr>
<tr>
<th>8</th>
<td>2003/04</td>
<td>3</td>
<td>2ab</td>
<td>19th</td>
</tr>
<tr>
<th>9</th>
<td>2004/05</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>division</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2ab</td>
</tr>
</tbody>
</table> | select division where place = '19th' <table_name> : table | | season | tier | division | place |
|---:|:---------|-------:|:-----------|:--------|
| 0 | 1992-96 | 5 | regional | none |
| 1 | 1996/97 | 4 | 3a | 16th |
| 2 | 1997/98 | 4 | 3a | 5th |
| 3 | 1998/99 | 4 | 3a | 12th |
| 4 | 1999/00 | 4 | 3a | 4th |
| 5 | 2000/01 | 4 | 3a | 6th |
| 6 | 2001/02 | 4 | 3a | 4th |
| 7 | 2002/03 | 4 | 3a | 3rd |
| 8 | 2003/04 | 3 | 2ab | 19th |
| 9 | 2004/05 | 4 | 3a | 2nd | | | | division |
|---:|:-----------|
| 0 | 2ab | | [
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] |
select count ( * ) where position = 'tackle' col : pick # | nfl team | player | position | college row 1 : 81 | philadelphia eagles | paul fanning | back | kansas state row 2 : 82 | brooklyn dodgers | ed nowogrowski | back | university of washington row 3 : 83 | chicago cardinals | dwight hafeli | back | washington (st. louis) row 4 : 84 | new york giants | dwight scheyer | end | washington state row 5 : 85 | pittsburgh pirates | matt patanelli | tackle | michigan row 6 : 86 | boston redskins | bill docherty | guard | temple row 7 : 87 | detroit lions | larry kelley | guard | yale row 8 : 88 | chicago bears | al guepe | end | marquette row 9 : 89 | green bay packers | gordon dahlgren | guard | michigan state row 10 : 90 | cleveland rams | ray johnson | tackle | denver | col : count ( "*" ) row 1 : 2 | select count ( * ) where position = 'tackle' <table_name> : table \begin{tabular}{llllll}
\toprule
& pick # & nfl team & player & position & college \\
\midrule
0 & 81 & philadelphia eagles & paul fanning & back & kansas state \\
1 & 82 & brooklyn dodgers & ed nowogrowski & back & university of washington \\
2 & 83 & chicago cardinals & dwight hafeli & back & washington (st. louis) \\
3 & 84 & new york giants & dwight scheyer & end & washington state \\
4 & 85 & pittsburgh pirates & matt patanelli & tackle & michigan \\
5 & 86 & boston redskins & bill docherty & guard & temple \\
6 & 87 & detroit lions & larry kelley & guard & yale \\
7 & 88 & chicago bears & al guepe & end & marquette \\
8 & 89 & green bay packers & gordon dahlgren & guard & michigan state \\
9 & 90 & cleveland rams & ray johnson & tackle & denver \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( * ) where position = 'tackle' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pick #</th>
<th>nfl team</th>
<th>player</th>
<th>position</th>
<th>college</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>81</td>
<td>philadelphia eagles</td>
<td>paul fanning</td>
<td>back</td>
<td>kansas state</td>
</tr>
<tr>
<th>1</th>
<td>82</td>
<td>brooklyn dodgers</td>
<td>ed nowogrowski</td>
<td>back</td>
<td>university of washington</td>
</tr>
<tr>
<th>2</th>
<td>83</td>
<td>chicago cardinals</td>
<td>dwight hafeli</td>
<td>back</td>
<td>washington (st. louis)</td>
</tr>
<tr>
<th>3</th>
<td>84</td>
<td>new york giants</td>
<td>dwight scheyer</td>
<td>end</td>
<td>washington state</td>
</tr>
<tr>
<th>4</th>
<td>85</td>
<td>pittsburgh pirates</td>
<td>matt patanelli</td>
<td>tackle</td>
<td>michigan</td>
</tr>
<tr>
<th>5</th>
<td>86</td>
<td>boston redskins</td>
<td>bill docherty</td>
<td>guard</td>
<td>temple</td>
</tr>
<tr>
<th>6</th>
<td>87</td>
<td>detroit lions</td>
<td>larry kelley</td>
<td>guard</td>
<td>yale</td>
</tr>
<tr>
<th>7</th>
<td>88</td>
<td>chicago bears</td>
<td>al guepe</td>
<td>end</td>
<td>marquette</td>
</tr>
<tr>
<th>8</th>
<td>89</td>
<td>green bay packers</td>
<td>gordon dahlgren</td>
<td>guard</td>
<td>michigan state</td>
</tr>
<tr>
<th>9</th>
<td>90</td>
<td>cleveland rams</td>
<td>ray johnson</td>
<td>tackle</td>
<td>denver</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 = 'tackle' <table_name> : table | | pick # | nfl team | player | position | college |
|---:|---------:|:--------------------|:----------------|:-----------|:-------------------------|
| 0 | 81 | philadelphia eagles | paul fanning | back | kansas state |
| 1 | 82 | brooklyn dodgers | ed nowogrowski | back | university of washington |
| 2 | 83 | chicago cardinals | dwight hafeli | back | washington (st. louis) |
| 3 | 84 | new york giants | dwight scheyer | end | washington state |
| 4 | 85 | pittsburgh pirates | matt patanelli | tackle | michigan |
| 5 | 86 | boston redskins | bill docherty | guard | temple |
| 6 | 87 | detroit lions | larry kelley | guard | yale |
| 7 | 88 | chicago bears | al guepe | end | marquette |
| 8 | 89 | green bay packers | gordon dahlgren | guard | michigan state |
| 9 | 90 | cleveland rams | ray johnson | tackle | denver | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 2 | | [
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] |
select division where section = 'norra' col : season | level | division | section | position | movements row 1 : 1985 | tier 4 | division 3 | norra norrland | 5th | none row 2 : 1986 | tier 4 | division 3 | norra norrland | 4th | promoted row 3 : 1987 | tier 3 | division 2 | norra | 5th | none row 4 : 1988 | tier 3 | division 2 | norra | 1st | promoted row 5 : 1989 | tier 2 | division 1 | norra | 3rd | none row 6 : 1990 | tier 2 | division 1 | norra | 6th | none row 7 : 1991 | tier 2 | division 1 | norra | 1st | spring row 8 : none | tier 2 | division 1 | kvalsvenskan | 8th | autumn row 9 : 1992 | tier 2 | division 1 | norra | 7th | spring row 10 : none | tier 2 | division 1 | norra | 8th | autumn - relegated row 11 : 1993 | tier 3 | division 2 | norrland | 1st | promoted row 12 : 1994 | tier 2 | division 1 | norra | 13th | relegated row 13 : 1995 | tier 3 | division 2 | norrland | 9th | none row 14 : 1996 | tier 3 | division 2 | norrland | 8th | none row 15 : 1997 | tier 3 | division 2 | norrland | 6th | none row 16 : 1998 | tier 3 | division 2 | norrland | 7th | none row 17 : 1999 | tier 3 | division 2 | norrland | 3rd | none row 18 : 2000 | tier 3 | division 2 | norrland | 8th | none row 19 : 2001 | tier 3 | division 2 | norrland | 10th | relegation playoffs row 20 : 2002 | tier 3 | division 2 | norrland | 10th | relegation playoffs row 21 : 2003 | tier 3 | division 2 | norrland | 10th | relegation playoffs row 22 : 2004 | tier 3 | division 2 | norrland | 7th | none row 23 : 2005 | tier 3 | division 2 | norrland | 4th | promoted row 24 : 2006 | tier 3 | division 1 | norra | 14th | relegated row 25 : 2007 | tier 4 | division 2 | norrland | 10th | relegation playoffs row 26 : 2008 | tier 4 | division 2 | norrland | 12th | relegated row 27 : 2009 | tier 5 | division 3 | norra norrland | 8th | none row 28 : 2010 | tier 5 | division 3 | norra norrland | 3rd | none row 29 : 2011 | tier 5 | division 3 | norra norrland | 2nd | promotion playoffs row 30 : 2012 | tier 5 | division 3 | norra norrland | 3rd | none | col : division row 1 : division 2 row 2 : division 2 row 3 : division 1 row 4 : division 1 row 5 : division 1 row 6 : division 1 row 7 : division 1 row 8 : division 1 row 9 : division 1 | select division where section = 'norra' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & level & division & section & position & movements \\
\midrule
0 & 1985 & tier 4 & division 3 & norra norrland & 5th & none \\
1 & 1986 & tier 4 & division 3 & norra norrland & 4th & promoted \\
2 & 1987 & tier 3 & division 2 & norra & 5th & none \\
3 & 1988 & tier 3 & division 2 & norra & 1st & promoted \\
4 & 1989 & tier 2 & division 1 & norra & 3rd & none \\
5 & 1990 & tier 2 & division 1 & norra & 6th & none \\
6 & 1991 & tier 2 & division 1 & norra & 1st & spring \\
7 & none & tier 2 & division 1 & kvalsvenskan & 8th & autumn \\
8 & 1992 & tier 2 & division 1 & norra & 7th & spring \\
9 & none & tier 2 & division 1 & norra & 8th & autumn - relegated \\
10 & 1993 & tier 3 & division 2 & norrland & 1st & promoted \\
11 & 1994 & tier 2 & division 1 & norra & 13th & relegated \\
12 & 1995 & tier 3 & division 2 & norrland & 9th & none \\
13 & 1996 & tier 3 & division 2 & norrland & 8th & none \\
14 & 1997 & tier 3 & division 2 & norrland & 6th & none \\
15 & 1998 & tier 3 & division 2 & norrland & 7th & none \\
16 & 1999 & tier 3 & division 2 & norrland & 3rd & none \\
17 & 2000 & tier 3 & division 2 & norrland & 8th & none \\
18 & 2001 & tier 3 & division 2 & norrland & 10th & relegation playoffs \\
19 & 2002 & tier 3 & division 2 & norrland & 10th & relegation playoffs \\
20 & 2003 & tier 3 & division 2 & norrland & 10th & relegation playoffs \\
21 & 2004 & tier 3 & division 2 & norrland & 7th & none \\
22 & 2005 & tier 3 & division 2 & norrland & 4th & promoted \\
23 & 2006 & tier 3 & division 1 & norra & 14th & relegated \\
24 & 2007 & tier 4 & division 2 & norrland & 10th & relegation playoffs \\
25 & 2008 & tier 4 & division 2 & norrland & 12th & relegated \\
26 & 2009 & tier 5 & division 3 & norra norrland & 8th & none \\
27 & 2010 & tier 5 & division 3 & norra norrland & 3rd & none \\
28 & 2011 & tier 5 & division 3 & norra norrland & 2nd & promotion playoffs \\
29 & 2012 & tier 5 & division 3 & norra norrland & 3rd & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& division \\
\midrule
0 & division 2 \\
1 & division 2 \\
2 & division 1 \\
3 & division 1 \\
4 & division 1 \\
5 & division 1 \\
6 & division 1 \\
7 & division 1 \\
8 & division 1 \\
\bottomrule
\end{tabular}
| select division where section = 'norra' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>level</th>
<th>division</th>
<th>section</th>
<th>position</th>
<th>movements</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1985</td>
<td>tier 4</td>
<td>division 3</td>
<td>norra norrland</td>
<td>5th</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1986</td>
<td>tier 4</td>
<td>division 3</td>
<td>norra norrland</td>
<td>4th</td>
<td>promoted</td>
</tr>
<tr>
<th>2</th>
<td>1987</td>
<td>tier 3</td>
<td>division 2</td>
<td>norra</td>
<td>5th</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1988</td>
<td>tier 3</td>
<td>division 2</td>
<td>norra</td>
<td>1st</td>
<td>promoted</td>
</tr>
<tr>
<th>4</th>
<td>1989</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1990</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1991</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>1st</td>
<td>spring</td>
</tr>
<tr>
<th>7</th>
<td>none</td>
<td>tier 2</td>
<td>division 1</td>
<td>kvalsvenskan</td>
<td>8th</td>
<td>autumn</td>
</tr>
<tr>
<th>8</th>
<td>1992</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>7th</td>
<td>spring</td>
</tr>
<tr>
<th>9</th>
<td>none</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>8th</td>
<td>autumn - relegated</td>
</tr>
<tr>
<th>10</th>
<td>1993</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>1st</td>
<td>promoted</td>
</tr>
<tr>
<th>11</th>
<td>1994</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>13th</td>
<td>relegated</td>
</tr>
<tr>
<th>12</th>
<td>1995</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1996</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>8th</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>1997</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>1998</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>7th</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>1999</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>2000</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>8th</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>2001</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>10th</td>
<td>relegation playoffs</td>
</tr>
<tr>
<th>19</th>
<td>2002</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>10th</td>
<td>relegation playoffs</td>
</tr>
<tr>
<th>20</th>
<td>2003</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>10th</td>
<td>relegation playoffs</td>
</tr>
<tr>
<th>21</th>
<td>2004</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>7th</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>2005</td>
<td>tier 3</td>
<td>division 2</td>
<td>norrland</td>
<td>4th</td>
<td>promoted</td>
</tr>
<tr>
<th>23</th>
<td>2006</td>
<td>tier 3</td>
<td>division 1</td>
<td>norra</td>
<td>14th</td>
<td>relegated</td>
</tr>
<tr>
<th>24</th>
<td>2007</td>
<td>tier 4</td>
<td>division 2</td>
<td>norrland</td>
<td>10th</td>
<td>relegation playoffs</td>
</tr>
<tr>
<th>25</th>
<td>2008</td>
<td>tier 4</td>
<td>division 2</td>
<td>norrland</td>
<td>12th</td>
<td>relegated</td>
</tr>
<tr>
<th>26</th>
<td>2009</td>
<td>tier 5</td>
<td>division 3</td>
<td>norra norrland</td>
<td>8th</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>2010</td>
<td>tier 5</td>
<td>division 3</td>
<td>norra norrland</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>2011</td>
<td>tier 5</td>
<td>division 3</td>
<td>norra norrland</td>
<td>2nd</td>
<td>promotion playoffs</td>
</tr>
<tr>
<th>29</th>
<td>2012</td>
<td>tier 5</td>
<td>division 3</td>
<td>norra norrland</td>
<td>3rd</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>division</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>division 2</td>
</tr>
<tr>
<th>1</th>
<td>division 2</td>
</tr>
<tr>
<th>2</th>
<td>division 1</td>
</tr>
<tr>
<th>3</th>
<td>division 1</td>
</tr>
<tr>
<th>4</th>
<td>division 1</td>
</tr>
<tr>
<th>5</th>
<td>division 1</td>
</tr>
<tr>
<th>6</th>
<td>division 1</td>
</tr>
<tr>
<th>7</th>
<td>division 1</td>
</tr>
<tr>
<th>8</th>
<td>division 1</td>
</tr>
</tbody>
</table> | select division where section = 'norra' <table_name> : table | | season | level | division | section | position | movements |
|---:|:---------|:--------|:-----------|:---------------|:-----------|:--------------------|
| 0 | 1985 | tier 4 | division 3 | norra norrland | 5th | none |
| 1 | 1986 | tier 4 | division 3 | norra norrland | 4th | promoted |
| 2 | 1987 | tier 3 | division 2 | norra | 5th | none |
| 3 | 1988 | tier 3 | division 2 | norra | 1st | promoted |
| 4 | 1989 | tier 2 | division 1 | norra | 3rd | none |
| 5 | 1990 | tier 2 | division 1 | norra | 6th | none |
| 6 | 1991 | tier 2 | division 1 | norra | 1st | spring |
| 7 | none | tier 2 | division 1 | kvalsvenskan | 8th | autumn |
| 8 | 1992 | tier 2 | division 1 | norra | 7th | spring |
| 9 | none | tier 2 | division 1 | norra | 8th | autumn - relegated |
| 10 | 1993 | tier 3 | division 2 | norrland | 1st | promoted |
| 11 | 1994 | tier 2 | division 1 | norra | 13th | relegated |
| 12 | 1995 | tier 3 | division 2 | norrland | 9th | none |
| 13 | 1996 | tier 3 | division 2 | norrland | 8th | none |
| 14 | 1997 | tier 3 | division 2 | norrland | 6th | none |
| 15 | 1998 | tier 3 | division 2 | norrland | 7th | none |
| 16 | 1999 | tier 3 | division 2 | norrland | 3rd | none |
| 17 | 2000 | tier 3 | division 2 | norrland | 8th | none |
| 18 | 2001 | tier 3 | division 2 | norrland | 10th | relegation playoffs |
| 19 | 2002 | tier 3 | division 2 | norrland | 10th | relegation playoffs |
| 20 | 2003 | tier 3 | division 2 | norrland | 10th | relegation playoffs |
| 21 | 2004 | tier 3 | division 2 | norrland | 7th | none |
| 22 | 2005 | tier 3 | division 2 | norrland | 4th | promoted |
| 23 | 2006 | tier 3 | division 1 | norra | 14th | relegated |
| 24 | 2007 | tier 4 | division 2 | norrland | 10th | relegation playoffs |
| 25 | 2008 | tier 4 | division 2 | norrland | 12th | relegated |
| 26 | 2009 | tier 5 | division 3 | norra norrland | 8th | none |
| 27 | 2010 | tier 5 | division 3 | norra norrland | 3rd | none |
| 28 | 2011 | tier 5 | division 3 | norra norrland | 2nd | promotion playoffs |
| 29 | 2012 | tier 5 | division 3 | norra norrland | 3rd | none | | | | division |
|---:|:-----------|
| 0 | division 2 |
| 1 | division 2 |
| 2 | division 1 |
| 3 | division 1 |
| 4 | division 1 |
| 5 | division 1 |
| 6 | division 1 |
| 7 | division 1 |
| 8 | division 1 | | [
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select attendance - week where result = 'l 20-7' col : week | date | opponent | result | game site | attendance row 1 : 1 | 1960-09-11 00:00:00 | at new york titans | l 27-3 | polo grounds | 10,200 row 2 : 2 | 1960-09-18 00:00:00 | denver broncos | l 27-21 | war memorial stadium | 15,229 row 3 : 3 | 1960-09-23 00:00:00 | at boston patriots | w 13-0 | nickerson field | 20,732 row 4 : 4 | 1960-10-02 00:00:00 | los angeles chargers | l 24-10 | war memorial stadium | 15,821 row 5 : 6 | 1960-10-16 00:00:00 | new york titans | l 17-13 | war memorial stadium | 14,988 row 6 : 7 | 1960-10-23 00:00:00 | oakland raiders | w 38-9 | war memorial stadium | 8,876 row 7 : 8 | 1960-10-30 00:00:00 | houston oilers | w 25-24 | war memorial stadium | 23,001 row 8 : 9 | 1960-11-06 00:00:00 | dallas texans | l 45-28 | war memorial stadium | 19,610 row 9 : 10 | 1960-11-13 00:00:00 | at oakland raiders | l 20-7 | kezar stadium | 8,800 row 10 : 11 | 1960-11-20 00:00:00 | at los angeles chargers | w 32-3 | los angeles memorial coliseum | 16,161 row 11 : 12 | 1960-11-27 00:00:00 | at denver broncos | t 38-38 | bears stadium | 7,785 row 12 : 13 | 1960-12-04 00:00:00 | boston patriots | w 38-14 | war memorial stadium | 14,335 row 13 : 14 | 1960-12-11 00:00:00 | at houston oilers | l 31-23 | jeppesen stadium | 25,243 row 14 : 15 | 1960-12-18 00:00:00 | at dallas texans | l 24-7 | cotton bowl | 18,000 | col : "attendance - week" row 1 : attendance - week | select attendance - week where result = 'l 20-7' <table_name> : table \begin{tabular}{lllllll}
\toprule
& week & date & opponent & result & game site & attendance \\
\midrule
0 & 1 & 1960-09-11 00:00:00 & at new york titans & l 27-3 & polo grounds & 10,200 \\
1 & 2 & 1960-09-18 00:00:00 & denver broncos & l 27-21 & war memorial stadium & 15,229 \\
2 & 3 & 1960-09-23 00:00:00 & at boston patriots & w 13-0 & nickerson field & 20,732 \\
3 & 4 & 1960-10-02 00:00:00 & los angeles chargers & l 24-10 & war memorial stadium & 15,821 \\
4 & 6 & 1960-10-16 00:00:00 & new york titans & l 17-13 & war memorial stadium & 14,988 \\
5 & 7 & 1960-10-23 00:00:00 & oakland raiders & w 38-9 & war memorial stadium & 8,876 \\
6 & 8 & 1960-10-30 00:00:00 & houston oilers & w 25-24 & war memorial stadium & 23,001 \\
7 & 9 & 1960-11-06 00:00:00 & dallas texans & l 45-28 & war memorial stadium & 19,610 \\
8 & 10 & 1960-11-13 00:00:00 & at oakland raiders & l 20-7 & kezar stadium & 8,800 \\
9 & 11 & 1960-11-20 00:00:00 & at los angeles chargers & w 32-3 & los angeles memorial coliseum & 16,161 \\
10 & 12 & 1960-11-27 00:00:00 & at denver broncos & t 38-38 & bears stadium & 7,785 \\
11 & 13 & 1960-12-04 00:00:00 & boston patriots & w 38-14 & war memorial stadium & 14,335 \\
12 & 14 & 1960-12-11 00:00:00 & at houston oilers & l 31-23 & jeppesen stadium & 25,243 \\
13 & 15 & 1960-12-18 00:00:00 & at dallas texans & l 24-7 & cotton bowl & 18,000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "attendance - week" \\
\midrule
0 & attendance - week \\
\bottomrule
\end{tabular}
| select attendance - week where result = 'l 20-7' <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>result</th>
<th>game site</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1960-09-11 00:00:00</td>
<td>at new york titans</td>
<td>l 27-3</td>
<td>polo grounds</td>
<td>10,200</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1960-09-18 00:00:00</td>
<td>denver broncos</td>
<td>l 27-21</td>
<td>war memorial stadium</td>
<td>15,229</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1960-09-23 00:00:00</td>
<td>at boston patriots</td>
<td>w 13-0</td>
<td>nickerson field</td>
<td>20,732</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1960-10-02 00:00:00</td>
<td>los angeles chargers</td>
<td>l 24-10</td>
<td>war memorial stadium</td>
<td>15,821</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>1960-10-16 00:00:00</td>
<td>new york titans</td>
<td>l 17-13</td>
<td>war memorial stadium</td>
<td>14,988</td>
</tr>
<tr>
<th>5</th>
<td>7</td>
<td>1960-10-23 00:00:00</td>
<td>oakland raiders</td>
<td>w 38-9</td>
<td>war memorial stadium</td>
<td>8,876</td>
</tr>
<tr>
<th>6</th>
<td>8</td>
<td>1960-10-30 00:00:00</td>
<td>houston oilers</td>
<td>w 25-24</td>
<td>war memorial stadium</td>
<td>23,001</td>
</tr>
<tr>
<th>7</th>
<td>9</td>
<td>1960-11-06 00:00:00</td>
<td>dallas texans</td>
<td>l 45-28</td>
<td>war memorial stadium</td>
<td>19,610</td>
</tr>
<tr>
<th>8</th>
<td>10</td>
<td>1960-11-13 00:00:00</td>
<td>at oakland raiders</td>
<td>l 20-7</td>
<td>kezar stadium</td>
<td>8,800</td>
</tr>
<tr>
<th>9</th>
<td>11</td>
<td>1960-11-20 00:00:00</td>
<td>at los angeles chargers</td>
<td>w 32-3</td>
<td>los angeles memorial coliseum</td>
<td>16,161</td>
</tr>
<tr>
<th>10</th>
<td>12</td>
<td>1960-11-27 00:00:00</td>
<td>at denver broncos</td>
<td>t 38-38</td>
<td>bears stadium</td>
<td>7,785</td>
</tr>
<tr>
<th>11</th>
<td>13</td>
<td>1960-12-04 00:00:00</td>
<td>boston patriots</td>
<td>w 38-14</td>
<td>war memorial stadium</td>
<td>14,335</td>
</tr>
<tr>
<th>12</th>
<td>14</td>
<td>1960-12-11 00:00:00</td>
<td>at houston oilers</td>
<td>l 31-23</td>
<td>jeppesen stadium</td>
<td>25,243</td>
</tr>
<tr>
<th>13</th>
<td>15</td>
<td>1960-12-18 00:00:00</td>
<td>at dallas texans</td>
<td>l 24-7</td>
<td>cotton bowl</td>
<td>18,000</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"attendance - week"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>attendance - week</td>
</tr>
</tbody>
</table> | select attendance - week where result = 'l 20-7' <table_name> : table | | week | date | opponent | result | game site | attendance |
|---:|-------:|:--------------------|:------------------------|:---------|:------------------------------|:-------------|
| 0 | 1 | 1960-09-11 00:00:00 | at new york titans | l 27-3 | polo grounds | 10,200 |
| 1 | 2 | 1960-09-18 00:00:00 | denver broncos | l 27-21 | war memorial stadium | 15,229 |
| 2 | 3 | 1960-09-23 00:00:00 | at boston patriots | w 13-0 | nickerson field | 20,732 |
| 3 | 4 | 1960-10-02 00:00:00 | los angeles chargers | l 24-10 | war memorial stadium | 15,821 |
| 4 | 6 | 1960-10-16 00:00:00 | new york titans | l 17-13 | war memorial stadium | 14,988 |
| 5 | 7 | 1960-10-23 00:00:00 | oakland raiders | w 38-9 | war memorial stadium | 8,876 |
| 6 | 8 | 1960-10-30 00:00:00 | houston oilers | w 25-24 | war memorial stadium | 23,001 |
| 7 | 9 | 1960-11-06 00:00:00 | dallas texans | l 45-28 | war memorial stadium | 19,610 |
| 8 | 10 | 1960-11-13 00:00:00 | at oakland raiders | l 20-7 | kezar stadium | 8,800 |
| 9 | 11 | 1960-11-20 00:00:00 | at los angeles chargers | w 32-3 | los angeles memorial coliseum | 16,161 |
| 10 | 12 | 1960-11-27 00:00:00 | at denver broncos | t 38-38 | bears stadium | 7,785 |
| 11 | 13 | 1960-12-04 00:00:00 | boston patriots | w 38-14 | war memorial stadium | 14,335 |
| 12 | 14 | 1960-12-11 00:00:00 | at houston oilers | l 31-23 | jeppesen stadium | 25,243 |
| 13 | 15 | 1960-12-18 00:00:00 | at dallas texans | l 24-7 | cotton bowl | 18,000 | | | | "attendance - week" |
|---:|:----------------------|
| 0 | attendance - week | | [
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] |
select count ( * ) where nation = 'kyrgyzstan' col : rank | nation | gold | silver | bronze | total row 1 : 1 | russia | 17 | 5 | 5 | 27 row 2 : 2 | bulgaria | 5 | 2 | 3 | 10 row 3 : 3 | belarus | 2 | 4 | 2 | 8 row 4 : 4 | ukraine | 1 | 2 | 11 | 14 row 5 : 5 | kazakhstan | 1 | 1 | 3 | 5 row 6 : 6 | latvia | 1 | 0 | 0 | 1 row 7 : 7 | uzbekistan | 0 | 3 | 4 | 7 row 8 : 8 | lithuania | 0 | 1 | 6 | 7 row 9 : 8 | venezuela | 0 | 3 | 3 | 6 row 10 : 9 | mongolia | 0 | 2 | 4 | 6 row 11 : 10 | armenia | 0 | 1 | 3 | 4 row 12 : 11 | japan | 0 | 0 | 3 | 3 row 13 : 12 | estonia | 0 | 0 | 2 | 2 row 14 : 13 | azerbaijan | 0 | 1 | 0 | 1 row 15 : 13 | france | 0 | 1 | 0 | 1 row 16 : 13 | germany | 0 | 1 | 0 | 1 row 17 : 13 | romania | 0 | 1 | 0 | 1 row 18 : 17 | serbia | 0 | 0 | 1 | 1 row 19 : 17 | spain | 0 | 0 | 1 | 1 row 20 : 17 | tajikistan | 0 | 0 | 1 | 1 row 21 : 17 | turkmenistan | 0 | 0 | 1 | 1 row 22 : 21 | algeria | 0 | 0 | 0 | 0 row 23 : 21 | austria | 0 | 0 | 0 | 0 row 24 : 21 | belgium | 0 | 0 | 0 | 0 row 25 : 21 | cameroon | 0 | 0 | 0 | 0 row 26 : 21 | canada | 0 | 0 | 0 | 0 row 27 : 21 | colombia | 0 | 0 | 0 | 0 row 28 : 21 | czech republic | 0 | 0 | 0 | 0 row 29 : 21 | cyprus | 0 | 0 | 0 | 0 row 30 : 21 | ecuador | 0 | 0 | 0 | 0 row 31 : 21 | finland | 0 | 0 | 0 | 0 row 32 : 21 | great britain | 0 | 0 | 0 | 0 row 33 : 21 | india | 0 | 0 | 0 | 0 row 34 : 21 | indonesia | 0 | 0 | 0 | 0 row 35 : 21 | ireland | 0 | 0 | 0 | 0 row 36 : 21 | israel | 0 | 0 | 0 | 0 row 37 : 21 | italy | 0 | 0 | 0 | 0 row 38 : 21 | jordan | 0 | 0 | 0 | 0 row 39 : 21 | south korea | 0 | 0 | 0 | 0 row 40 : 21 | kyrgyzstan | 0 | 0 | 0 | 0 row 41 : 21 | lebanon | 0 | 0 | 0 | 0 row 42 : 21 | malaysia | 0 | 0 | 0 | 0 row 43 : 21 | morocco | 0 | 0 | 0 | 0 row 44 : 21 | moldova | 0 | 0 | 0 | 0 row 45 : 21 | nepal | 0 | 0 | 0 | 0 row 46 : 21 | new zealand | 0 | 0 | 0 | 0 row 47 : 21 | pakistan | 0 | 0 | 0 | 0 row 48 : 21 | panama | 0 | 0 | 0 | 0 row 49 : 21 | peru | 0 | 0 | 0 | 0 row 50 : 21 | poland | 0 | 0 | 0 | 0 row 51 : 21 | syria | 0 | 0 | 0 | 0 row 52 : 21 | slovenia | 0 | 0 | 0 | 0 row 53 : 21 | slovakia | 0 | 0 | 0 | 0 row 54 : 21 | thailand | 0 | 0 | 0 | 0 row 55 : 21 | tunisia | 0 | 0 | 0 | 0 row 56 : 21 | turkey | 0 | 0 | 0 | 0 row 57 : 21 | united states | 0 | 0 | 0 | 0 row 58 : 21 | yemen | 0 | 0 | 0 | 0 row 59 : total | total | 27 | 27 | 54 | 108 | col : count ( "*" ) row 1 : 1 | select count ( * ) where nation = 'kyrgyzstan' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & russia & 17 & 5 & 5 & 27 \\
1 & 2 & bulgaria & 5 & 2 & 3 & 10 \\
2 & 3 & belarus & 2 & 4 & 2 & 8 \\
3 & 4 & ukraine & 1 & 2 & 11 & 14 \\
4 & 5 & kazakhstan & 1 & 1 & 3 & 5 \\
5 & 6 & latvia & 1 & 0 & 0 & 1 \\
6 & 7 & uzbekistan & 0 & 3 & 4 & 7 \\
7 & 8 & lithuania & 0 & 1 & 6 & 7 \\
8 & 8 & venezuela & 0 & 3 & 3 & 6 \\
9 & 9 & mongolia & 0 & 2 & 4 & 6 \\
10 & 10 & armenia & 0 & 1 & 3 & 4 \\
11 & 11 & japan & 0 & 0 & 3 & 3 \\
12 & 12 & estonia & 0 & 0 & 2 & 2 \\
13 & 13 & azerbaijan & 0 & 1 & 0 & 1 \\
14 & 13 & france & 0 & 1 & 0 & 1 \\
15 & 13 & germany & 0 & 1 & 0 & 1 \\
16 & 13 & romania & 0 & 1 & 0 & 1 \\
17 & 17 & serbia & 0 & 0 & 1 & 1 \\
18 & 17 & spain & 0 & 0 & 1 & 1 \\
19 & 17 & tajikistan & 0 & 0 & 1 & 1 \\
20 & 17 & turkmenistan & 0 & 0 & 1 & 1 \\
21 & 21 & algeria & 0 & 0 & 0 & 0 \\
22 & 21 & austria & 0 & 0 & 0 & 0 \\
23 & 21 & belgium & 0 & 0 & 0 & 0 \\
24 & 21 & cameroon & 0 & 0 & 0 & 0 \\
25 & 21 & canada & 0 & 0 & 0 & 0 \\
26 & 21 & colombia & 0 & 0 & 0 & 0 \\
27 & 21 & czech republic & 0 & 0 & 0 & 0 \\
28 & 21 & cyprus & 0 & 0 & 0 & 0 \\
29 & 21 & ecuador & 0 & 0 & 0 & 0 \\
30 & 21 & finland & 0 & 0 & 0 & 0 \\
31 & 21 & great britain & 0 & 0 & 0 & 0 \\
32 & 21 & india & 0 & 0 & 0 & 0 \\
33 & 21 & indonesia & 0 & 0 & 0 & 0 \\
34 & 21 & ireland & 0 & 0 & 0 & 0 \\
35 & 21 & israel & 0 & 0 & 0 & 0 \\
36 & 21 & italy & 0 & 0 & 0 & 0 \\
37 & 21 & jordan & 0 & 0 & 0 & 0 \\
38 & 21 & south korea & 0 & 0 & 0 & 0 \\
39 & 21 & kyrgyzstan & 0 & 0 & 0 & 0 \\
40 & 21 & lebanon & 0 & 0 & 0 & 0 \\
41 & 21 & malaysia & 0 & 0 & 0 & 0 \\
42 & 21 & morocco & 0 & 0 & 0 & 0 \\
43 & 21 & moldova & 0 & 0 & 0 & 0 \\
44 & 21 & nepal & 0 & 0 & 0 & 0 \\
45 & 21 & new zealand & 0 & 0 & 0 & 0 \\
46 & 21 & pakistan & 0 & 0 & 0 & 0 \\
47 & 21 & panama & 0 & 0 & 0 & 0 \\
48 & 21 & peru & 0 & 0 & 0 & 0 \\
49 & 21 & poland & 0 & 0 & 0 & 0 \\
50 & 21 & syria & 0 & 0 & 0 & 0 \\
51 & 21 & slovenia & 0 & 0 & 0 & 0 \\
52 & 21 & slovakia & 0 & 0 & 0 & 0 \\
53 & 21 & thailand & 0 & 0 & 0 & 0 \\
54 & 21 & tunisia & 0 & 0 & 0 & 0 \\
55 & 21 & turkey & 0 & 0 & 0 & 0 \\
56 & 21 & united states & 0 & 0 & 0 & 0 \\
57 & 21 & yemen & 0 & 0 & 0 & 0 \\
58 & total & total & 27 & 27 & 54 & 108 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where nation = 'kyrgyzstan' <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>russia</td>
<td>17</td>
<td>5</td>
<td>5</td>
<td>27</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>bulgaria</td>
<td>5</td>
<td>2</td>
<td>3</td>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>belarus</td>
<td>2</td>
<td>4</td>
<td>2</td>
<td>8</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>ukraine</td>
<td>1</td>
<td>2</td>
<td>11</td>
<td>14</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>kazakhstan</td>
<td>1</td>
<td>1</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>latvia</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>uzbekistan</td>
<td>0</td>
<td>3</td>
<td>4</td>
<td>7</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>lithuania</td>
<td>0</td>
<td>1</td>
<td>6</td>
<td>7</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>venezuela</td>
<td>0</td>
<td>3</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>mongolia</td>
<td>0</td>
<td>2</td>
<td>4</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>armenia</td>
<td>0</td>
<td>1</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>japan</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>12</th>
<td>12</td>
<td>estonia</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>13</th>
<td>13</td>
<td>azerbaijan</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>13</td>
<td>france</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>13</td>
<td>germany</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>13</td>
<td>romania</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>17</th>
<td>17</td>
<td>serbia</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>17</td>
<td>spain</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>17</td>
<td>tajikistan</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>20</th>
<td>17</td>
<td>turkmenistan</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>21</td>
<td>algeria</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>22</th>
<td>21</td>
<td>austria</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>23</th>
<td>21</td>
<td>belgium</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>24</th>
<td>21</td>
<td>cameroon</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>25</th>
<td>21</td>
<td>canada</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>26</th>
<td>21</td>
<td>colombia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>27</th>
<td>21</td>
<td>czech republic</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>28</th>
<td>21</td>
<td>cyprus</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>29</th>
<td>21</td>
<td>ecuador</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>30</th>
<td>21</td>
<td>finland</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>31</th>
<td>21</td>
<td>great britain</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>32</th>
<td>21</td>
<td>india</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>33</th>
<td>21</td>
<td>indonesia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>34</th>
<td>21</td>
<td>ireland</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>35</th>
<td>21</td>
<td>israel</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>36</th>
<td>21</td>
<td>italy</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>37</th>
<td>21</td>
<td>jordan</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>38</th>
<td>21</td>
<td>south korea</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>39</th>
<td>21</td>
<td>kyrgyzstan</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>40</th>
<td>21</td>
<td>lebanon</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>41</th>
<td>21</td>
<td>malaysia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>42</th>
<td>21</td>
<td>morocco</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>43</th>
<td>21</td>
<td>moldova</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>44</th>
<td>21</td>
<td>nepal</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>45</th>
<td>21</td>
<td>new zealand</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>46</th>
<td>21</td>
<td>pakistan</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>47</th>
<td>21</td>
<td>panama</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>48</th>
<td>21</td>
<td>peru</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>49</th>
<td>21</td>
<td>poland</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>50</th>
<td>21</td>
<td>syria</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>51</th>
<td>21</td>
<td>slovenia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>52</th>
<td>21</td>
<td>slovakia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>53</th>
<td>21</td>
<td>thailand</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>54</th>
<td>21</td>
<td>tunisia</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>55</th>
<td>21</td>
<td>turkey</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>56</th>
<td>21</td>
<td>united states</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>57</th>
<td>21</td>
<td>yemen</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>58</th>
<td>total</td>
<td>total</td>
<td>27</td>
<td>27</td>
<td>54</td>
<td>108</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 nation = 'kyrgyzstan' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------|-------:|---------:|---------:|--------:|
| 0 | 1 | russia | 17 | 5 | 5 | 27 |
| 1 | 2 | bulgaria | 5 | 2 | 3 | 10 |
| 2 | 3 | belarus | 2 | 4 | 2 | 8 |
| 3 | 4 | ukraine | 1 | 2 | 11 | 14 |
| 4 | 5 | kazakhstan | 1 | 1 | 3 | 5 |
| 5 | 6 | latvia | 1 | 0 | 0 | 1 |
| 6 | 7 | uzbekistan | 0 | 3 | 4 | 7 |
| 7 | 8 | lithuania | 0 | 1 | 6 | 7 |
| 8 | 8 | venezuela | 0 | 3 | 3 | 6 |
| 9 | 9 | mongolia | 0 | 2 | 4 | 6 |
| 10 | 10 | armenia | 0 | 1 | 3 | 4 |
| 11 | 11 | japan | 0 | 0 | 3 | 3 |
| 12 | 12 | estonia | 0 | 0 | 2 | 2 |
| 13 | 13 | azerbaijan | 0 | 1 | 0 | 1 |
| 14 | 13 | france | 0 | 1 | 0 | 1 |
| 15 | 13 | germany | 0 | 1 | 0 | 1 |
| 16 | 13 | romania | 0 | 1 | 0 | 1 |
| 17 | 17 | serbia | 0 | 0 | 1 | 1 |
| 18 | 17 | spain | 0 | 0 | 1 | 1 |
| 19 | 17 | tajikistan | 0 | 0 | 1 | 1 |
| 20 | 17 | turkmenistan | 0 | 0 | 1 | 1 |
| 21 | 21 | algeria | 0 | 0 | 0 | 0 |
| 22 | 21 | austria | 0 | 0 | 0 | 0 |
| 23 | 21 | belgium | 0 | 0 | 0 | 0 |
| 24 | 21 | cameroon | 0 | 0 | 0 | 0 |
| 25 | 21 | canada | 0 | 0 | 0 | 0 |
| 26 | 21 | colombia | 0 | 0 | 0 | 0 |
| 27 | 21 | czech republic | 0 | 0 | 0 | 0 |
| 28 | 21 | cyprus | 0 | 0 | 0 | 0 |
| 29 | 21 | ecuador | 0 | 0 | 0 | 0 |
| 30 | 21 | finland | 0 | 0 | 0 | 0 |
| 31 | 21 | great britain | 0 | 0 | 0 | 0 |
| 32 | 21 | india | 0 | 0 | 0 | 0 |
| 33 | 21 | indonesia | 0 | 0 | 0 | 0 |
| 34 | 21 | ireland | 0 | 0 | 0 | 0 |
| 35 | 21 | israel | 0 | 0 | 0 | 0 |
| 36 | 21 | italy | 0 | 0 | 0 | 0 |
| 37 | 21 | jordan | 0 | 0 | 0 | 0 |
| 38 | 21 | south korea | 0 | 0 | 0 | 0 |
| 39 | 21 | kyrgyzstan | 0 | 0 | 0 | 0 |
| 40 | 21 | lebanon | 0 | 0 | 0 | 0 |
| 41 | 21 | malaysia | 0 | 0 | 0 | 0 |
| 42 | 21 | morocco | 0 | 0 | 0 | 0 |
| 43 | 21 | moldova | 0 | 0 | 0 | 0 |
| 44 | 21 | nepal | 0 | 0 | 0 | 0 |
| 45 | 21 | new zealand | 0 | 0 | 0 | 0 |
| 46 | 21 | pakistan | 0 | 0 | 0 | 0 |
| 47 | 21 | panama | 0 | 0 | 0 | 0 |
| 48 | 21 | peru | 0 | 0 | 0 | 0 |
| 49 | 21 | poland | 0 | 0 | 0 | 0 |
| 50 | 21 | syria | 0 | 0 | 0 | 0 |
| 51 | 21 | slovenia | 0 | 0 | 0 | 0 |
| 52 | 21 | slovakia | 0 | 0 | 0 | 0 |
| 53 | 21 | thailand | 0 | 0 | 0 | 0 |
| 54 | 21 | tunisia | 0 | 0 | 0 | 0 |
| 55 | 21 | turkey | 0 | 0 | 0 | 0 |
| 56 | 21 | united states | 0 | 0 | 0 | 0 |
| 57 | 21 | yemen | 0 | 0 | 0 | 0 |
| 58 | total | total | 27 | 27 | 54 | 108 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where result > 1148 col : week | date | opponent | result | attendance row 1 : 1 | 1959-09-26 00:00:00 | at los angeles rams | w 23-21 | 71297 row 2 : 2 | 1959-10-04 00:00:00 | at philadelphia eagles | l 49-21 | 27023 row 3 : 3 | 1959-10-11 00:00:00 | at cleveland browns | w 10-6 | 65534 row 4 : 4 | 1959-10-18 00:00:00 | philadelphia eagles | w 24-7 | 68783 row 5 : 5 | 1959-10-25 00:00:00 | at pittsburgh steelers | w 21-16 | 33596 row 6 : 6 | 1959-11-01 00:00:00 | green bay packers | w 20-3 | 68837 row 7 : 7 | 1959-11-08 00:00:00 | chicago cardinals | w 9-3 | 56779 row 8 : 8 | 1959-11-15 00:00:00 | pittsburgh steelers | l 14-9 | 66786 row 9 : 9 | 1959-11-22 00:00:00 | at chicago cardinals (bloomington, mn) | w 30-20 | 26625 row 10 : 10 | 1959-11-29 00:00:00 | washington redskins | w 45-14 | 60982 row 11 : 11 | 1959-12-06 00:00:00 | cleveland browns | w 48-7 | 68436 row 12 : 12 | 1959-12-13 00:00:00 | at washington redskins | w 24-10 | 26198 | col : count ( "*" ) row 1 : 12 | select count ( * ) where result > 1148 <table_name> : table \begin{tabular}{llllll}
\toprule
& week & date & opponent & result & attendance \\
\midrule
0 & 1 & 1959-09-26 00:00:00 & at los angeles rams & w 23-21 & 71297 \\
1 & 2 & 1959-10-04 00:00:00 & at philadelphia eagles & l 49-21 & 27023 \\
2 & 3 & 1959-10-11 00:00:00 & at cleveland browns & w 10-6 & 65534 \\
3 & 4 & 1959-10-18 00:00:00 & philadelphia eagles & w 24-7 & 68783 \\
4 & 5 & 1959-10-25 00:00:00 & at pittsburgh steelers & w 21-16 & 33596 \\
5 & 6 & 1959-11-01 00:00:00 & green bay packers & w 20-3 & 68837 \\
6 & 7 & 1959-11-08 00:00:00 & chicago cardinals & w 9-3 & 56779 \\
7 & 8 & 1959-11-15 00:00:00 & pittsburgh steelers & l 14-9 & 66786 \\
8 & 9 & 1959-11-22 00:00:00 & at chicago cardinals (bloomington, mn) & w 30-20 & 26625 \\
9 & 10 & 1959-11-29 00:00:00 & washington redskins & w 45-14 & 60982 \\
10 & 11 & 1959-12-06 00:00:00 & cleveland browns & w 48-7 & 68436 \\
11 & 12 & 1959-12-13 00:00:00 & at washington redskins & w 24-10 & 26198 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 12 \\
\bottomrule
\end{tabular}
| select count ( * ) where result > 1148 <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>result</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1959-09-26 00:00:00</td>
<td>at los angeles rams</td>
<td>w 23-21</td>
<td>71297</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1959-10-04 00:00:00</td>
<td>at philadelphia eagles</td>
<td>l 49-21</td>
<td>27023</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1959-10-11 00:00:00</td>
<td>at cleveland browns</td>
<td>w 10-6</td>
<td>65534</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1959-10-18 00:00:00</td>
<td>philadelphia eagles</td>
<td>w 24-7</td>
<td>68783</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1959-10-25 00:00:00</td>
<td>at pittsburgh steelers</td>
<td>w 21-16</td>
<td>33596</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1959-11-01 00:00:00</td>
<td>green bay packers</td>
<td>w 20-3</td>
<td>68837</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>1959-11-08 00:00:00</td>
<td>chicago cardinals</td>
<td>w 9-3</td>
<td>56779</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>1959-11-15 00:00:00</td>
<td>pittsburgh steelers</td>
<td>l 14-9</td>
<td>66786</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>1959-11-22 00:00:00</td>
<td>at chicago cardinals (bloomington, mn)</td>
<td>w 30-20</td>
<td>26625</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>1959-11-29 00:00:00</td>
<td>washington redskins</td>
<td>w 45-14</td>
<td>60982</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>1959-12-06 00:00:00</td>
<td>cleveland browns</td>
<td>w 48-7</td>
<td>68436</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>1959-12-13 00:00:00</td>
<td>at washington redskins</td>
<td>w 24-10</td>
<td>26198</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>12</td>
</tr>
</tbody>
</table> | select count ( * ) where result > 1148 <table_name> : table | | week | date | opponent | result | attendance |
|---:|-------:|:--------------------|:---------------------------------------|:---------|-------------:|
| 0 | 1 | 1959-09-26 00:00:00 | at los angeles rams | w 23-21 | 71297 |
| 1 | 2 | 1959-10-04 00:00:00 | at philadelphia eagles | l 49-21 | 27023 |
| 2 | 3 | 1959-10-11 00:00:00 | at cleveland browns | w 10-6 | 65534 |
| 3 | 4 | 1959-10-18 00:00:00 | philadelphia eagles | w 24-7 | 68783 |
| 4 | 5 | 1959-10-25 00:00:00 | at pittsburgh steelers | w 21-16 | 33596 |
| 5 | 6 | 1959-11-01 00:00:00 | green bay packers | w 20-3 | 68837 |
| 6 | 7 | 1959-11-08 00:00:00 | chicago cardinals | w 9-3 | 56779 |
| 7 | 8 | 1959-11-15 00:00:00 | pittsburgh steelers | l 14-9 | 66786 |
| 8 | 9 | 1959-11-22 00:00:00 | at chicago cardinals (bloomington, mn) | w 30-20 | 26625 |
| 9 | 10 | 1959-11-29 00:00:00 | washington redskins | w 45-14 | 60982 |
| 10 | 11 | 1959-12-06 00:00:00 | cleveland browns | w 48-7 | 68436 |
| 11 | 12 | 1959-12-13 00:00:00 | at washington redskins | w 24-10 | 26198 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 12 | | [
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select abs ( nationality - name ) where result = '37.51' col : rank | name | nationality | result | notes row 1 : none | park ho-hyun | south korea | 55.58 | pb row 2 : none | lee young-sun | south korea | 55.29 | none row 3 : none | anne de silva | sri lanka | 54.86 | none row 4 : 4 | liliya dusmetova | uzbekistan | 54.52 | sb row 5 : 5 | zhang li | china | 54.11 | none row 6 : 6 | harumi yamamoto | japan | 52.6 | none row 7 : 7 | suman devi | india | 52.58 | none row 8 : 8 | emika yoshida | japan | 51.62 | none row 9 : 9 | nadeeka lakmali | sri lanka | 48.54 | none row 10 : 10 | jang ok-ju | north korea | 41.68 | pb row 11 : 11 | parveen akhtar | pakistan | 37.51 | none | col : "abs ( nationality - name )" row 1 : abs ( nationality - name ) | select abs ( nationality - name ) where result = '37.51' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & nationality & result & notes \\
\midrule
0 & none & park ho-hyun & south korea & 55.58 & pb \\
1 & none & lee young-sun & south korea & 55.29 & none \\
2 & none & anne de silva & sri lanka & 54.86 & none \\
3 & 4 & liliya dusmetova & uzbekistan & 54.52 & sb \\
4 & 5 & zhang li & china & 54.11 & none \\
5 & 6 & harumi yamamoto & japan & 52.6 & none \\
6 & 7 & suman devi & india & 52.58 & none \\
7 & 8 & emika yoshida & japan & 51.62 & none \\
8 & 9 & nadeeka lakmali & sri lanka & 48.54 & none \\
9 & 10 & jang ok-ju & north korea & 41.68 & pb \\
10 & 11 & parveen akhtar & pakistan & 37.51 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "abs ( nationality - name )" \\
\midrule
0 & abs ( nationality - name ) \\
\bottomrule
\end{tabular}
| select abs ( nationality - name ) where result = '37.51' <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>result</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>park ho-hyun</td>
<td>south korea</td>
<td>55.58</td>
<td>pb</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>lee young-sun</td>
<td>south korea</td>
<td>55.29</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>anne de silva</td>
<td>sri lanka</td>
<td>54.86</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>liliya dusmetova</td>
<td>uzbekistan</td>
<td>54.52</td>
<td>sb</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>zhang li</td>
<td>china</td>
<td>54.11</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>harumi yamamoto</td>
<td>japan</td>
<td>52.6</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>suman devi</td>
<td>india</td>
<td>52.58</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>emika yoshida</td>
<td>japan</td>
<td>51.62</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>nadeeka lakmali</td>
<td>sri lanka</td>
<td>48.54</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>jang ok-ju</td>
<td>north korea</td>
<td>41.68</td>
<td>pb</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>parveen akhtar</td>
<td>pakistan</td>
<td>37.51</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"abs ( nationality - name )"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>abs ( nationality - name )</td>
</tr>
</tbody>
</table> | select abs ( nationality - name ) where result = '37.51' <table_name> : table | | rank | name | nationality | result | notes |
|---:|:-------|:-----------------|:--------------|---------:|:--------|
| 0 | none | park ho-hyun | south korea | 55.58 | pb |
| 1 | none | lee young-sun | south korea | 55.29 | none |
| 2 | none | anne de silva | sri lanka | 54.86 | none |
| 3 | 4 | liliya dusmetova | uzbekistan | 54.52 | sb |
| 4 | 5 | zhang li | china | 54.11 | none |
| 5 | 6 | harumi yamamoto | japan | 52.6 | none |
| 6 | 7 | suman devi | india | 52.58 | none |
| 7 | 8 | emika yoshida | japan | 51.62 | none |
| 8 | 9 | nadeeka lakmali | sri lanka | 48.54 | none |
| 9 | 10 | jang ok-ju | north korea | 41.68 | pb |
| 10 | 11 | parveen akhtar | pakistan | 37.51 | none | | | | "abs ( nationality - name )" |
|---:|:-------------------------------|
| 0 | abs ( nationality - name ) | | [
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select position where chart = 'mainstream rock tracks' col : year | single | chart | position row 1 : 1999 | "heavy" | billboard hot 100 | 73 row 2 : 1999 | "heavy" | mainstream rock tracks | 1 row 3 : 1999 | "heavy" | modern rock tracks | 5 row 4 : 1999 | "run" | billboard hot 100 | 76 row 5 : 1999 | "run" | modern rock tracks | 36 row 6 : 1999 | "run" | adult top 40 | 12 row 7 : 1999 | "no more, no less" | mainstream rock tracks | 10 row 8 : 1999 | "no more, no less" | modern rock tracks | 32 row 9 : 1999 | "tremble for my beloved" | mainstream rock tracks | 35 | col : position row 1 : 1 row 2 : 10 row 3 : 35 | select position where chart = 'mainstream rock tracks' <table_name> : table \begin{tabular}{lllll}
\toprule
& year & single & chart & position \\
\midrule
0 & 1999 & "heavy" & billboard hot 100 & 73 \\
1 & 1999 & "heavy" & mainstream rock tracks & 1 \\
2 & 1999 & "heavy" & modern rock tracks & 5 \\
3 & 1999 & "run" & billboard hot 100 & 76 \\
4 & 1999 & "run" & modern rock tracks & 36 \\
5 & 1999 & "run" & adult top 40 & 12 \\
6 & 1999 & "no more, no less" & mainstream rock tracks & 10 \\
7 & 1999 & "no more, no less" & modern rock tracks & 32 \\
8 & 1999 & "tremble for my beloved" & mainstream rock tracks & 35 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& position \\
\midrule
0 & 1 \\
1 & 10 \\
2 & 35 \\
\bottomrule
\end{tabular}
| select position where chart = 'mainstream rock tracks' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>single</th>
<th>chart</th>
<th>position</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1999</td>
<td>"heavy"</td>
<td>billboard hot 100</td>
<td>73</td>
</tr>
<tr>
<th>1</th>
<td>1999</td>
<td>"heavy"</td>
<td>mainstream rock tracks</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>1999</td>
<td>"heavy"</td>
<td>modern rock tracks</td>
<td>5</td>
</tr>
<tr>
<th>3</th>
<td>1999</td>
<td>"run"</td>
<td>billboard hot 100</td>
<td>76</td>
</tr>
<tr>
<th>4</th>
<td>1999</td>
<td>"run"</td>
<td>modern rock tracks</td>
<td>36</td>
</tr>
<tr>
<th>5</th>
<td>1999</td>
<td>"run"</td>
<td>adult top 40</td>
<td>12</td>
</tr>
<tr>
<th>6</th>
<td>1999</td>
<td>"no more, no less"</td>
<td>mainstream rock tracks</td>
<td>10</td>
</tr>
<tr>
<th>7</th>
<td>1999</td>
<td>"no more, no less"</td>
<td>modern rock tracks</td>
<td>32</td>
</tr>
<tr>
<th>8</th>
<td>1999</td>
<td>"tremble for my beloved"</td>
<td>mainstream rock tracks</td>
<td>35</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>35</td>
</tr>
</tbody>
</table> | select position where chart = 'mainstream rock tracks' <table_name> : table | | year | single | chart | position |
|---:|-------:|:-------------------------|:-----------------------|-----------:|
| 0 | 1999 | "heavy" | billboard hot 100 | 73 |
| 1 | 1999 | "heavy" | mainstream rock tracks | 1 |
| 2 | 1999 | "heavy" | modern rock tracks | 5 |
| 3 | 1999 | "run" | billboard hot 100 | 76 |
| 4 | 1999 | "run" | modern rock tracks | 36 |
| 5 | 1999 | "run" | adult top 40 | 12 |
| 6 | 1999 | "no more, no less" | mainstream rock tracks | 10 |
| 7 | 1999 | "no more, no less" | modern rock tracks | 32 |
| 8 | 1999 | "tremble for my beloved" | mainstream rock tracks | 35 | | | | position |
|---:|-----------:|
| 0 | 1 |
| 1 | 10 |
| 2 | 35 | | [
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select count ( team ) where team = 'team penske' col : pos | no. | driver | team | engine | laps | time/retired | grid | laps led | points row 1 : 1 | 2 | ryan briscoe | team penske | chevrolet | 85 | 2:07:02.8248 | 2 | 27 | 50 row 2 : 2 | 12 | will power | team penske | chevrolet | 85 | + 0.4408 | 1 | 57 | 43 row 3 : 3 | 10 | dario franchitti | chip ganassi racing | honda | 85 | + 1.0497 | 6 | 0 | 35 row 4 : 4 | 8 | rubens barrichello | kv racing technology | chevrolet | 85 | + 8.8529 | 11 | 0 | 32 row 5 : 5 | 38 | graham rahal | chip ganassi racing | honda | 85 | + 9.4667 | 13 | 0 | 30 row 6 : 6 | 3 | helio castroneves | team penske | chevrolet | 85 | + 11.2575 | 4 | 0 | 28 row 7 : 7 | 77 | simon pagenaud (r) | schmidt hamilton motorsports | honda | 85 | + 12.3087 | 9 | 0 | 26 row 8 : 8 | 4 | j.r. hildebrand | panther racing | chevrolet | 85 | + 22.8121 | 15 | 0 | 24 row 9 : 9 | 98 | alex tagliani | team barracuda - bha | honda | 85 | + 39.6868 | 8 | 0 | 22 row 10 : 10 | 11 | tony kanaan | kv racing technology | chevrolet | 84 | + 1 lap | 16 | 0 | 20 row 11 : 11 | 18 | justin wilson | dale coyne racing | honda | 84 | + 1 lap | 20 | 0 | 19 row 12 : 12 | 19 | james jakes | dale coyne racing | honda | 84 | + 1 lap | 24 | 0 | 18 row 13 : 13 | 9 | scott dixon | chip ganassi racing | honda | 84 | + 1 lap | 5 | 0 | 17 row 14 : 14 | 14 | mike conway | a.j. foyt enterprises | honda | 84 | + 1 lap | 14 | 0 | 16 row 15 : 15 | 17 | sebastian saavedra | andretti autosport | chevrolet | 84 | + 1 lap | 23 | 0 | 15 row 16 : 16 | 5 | e.j. viso | kv racing technology | chevrolet | 84 | + 1 lap | 17 | 0 | 14 row 17 : 17 | 78 | simona de silvestro | hvm racing | lotus | 84 | + 1 lap | 27 | 0 | 13 row 18 : 18 | 28 | ryan hunter-reay | andretti autosport | chevrolet | 84 | + 1 lap | 7 | 1 | 12 row 19 : 19 | 22 | oriol servia | panther/dreyer & reinbold racing | chevrolet | 84 | + 1 lap | 18 | 0 | 12 row 20 : 20 | 20 | ed carpenter | ed carpenter racing | chevrolet | 84 | + 1 lap | 25 | 0 | 12 row 21 : 21 | 83 | charlie kimball | chip ganassi racing | honda | 82 | + 3 laps | 21 | 0 | 12 row 22 : 22 | 7 | sebastien bourdais | dragon racing | chevrolet | 63 | contact | 3 | 0 | 12 row 23 : 23 | 67 | josef newgarden (r) | sarah fisher hartman racing | honda | 62 | contact | 22 | 0 | 12 row 24 : 24 | 6 | katherine legge (r) | dragon racing | chevrolet | 48 | mechanical | 19 | 0 | 12 row 25 : 25 | 26 | marco andretti | andretti autosport | chevrolet | 46 | mechanical | 12 | 0 | 10 row 26 : 26 | 27 | james hinchcliffe | andretti autosport | chevrolet | 35 | mechanical | 10 | 0 | 10 row 27 : 27 | 15 | takuma sato | rahal letterman lanigan racing | honda | 2 | mechanical | 26 | 0 | 10 | col : count ( "team" ) row 1 : 3 | select count ( team ) where team = 'team penske' <table_name> : table \begin{tabular}{lllllllllll}
\toprule
& pos & no. & driver & team & engine & laps & time/retired & grid & laps led & points \\
\midrule
0 & 1 & 2 & ryan briscoe & team penske & chevrolet & 85 & 2:07:02.8248 & 2 & 27 & 50 \\
1 & 2 & 12 & will power & team penske & chevrolet & 85 & + 0.4408 & 1 & 57 & 43 \\
2 & 3 & 10 & dario franchitti & chip ganassi racing & honda & 85 & + 1.0497 & 6 & 0 & 35 \\
3 & 4 & 8 & rubens barrichello & kv racing technology & chevrolet & 85 & + 8.8529 & 11 & 0 & 32 \\
4 & 5 & 38 & graham rahal & chip ganassi racing & honda & 85 & + 9.4667 & 13 & 0 & 30 \\
5 & 6 & 3 & helio castroneves & team penske & chevrolet & 85 & + 11.2575 & 4 & 0 & 28 \\
6 & 7 & 77 & simon pagenaud (r) & schmidt hamilton motorsports & honda & 85 & + 12.3087 & 9 & 0 & 26 \\
7 & 8 & 4 & j.r. hildebrand & panther racing & chevrolet & 85 & + 22.8121 & 15 & 0 & 24 \\
8 & 9 & 98 & alex tagliani & team barracuda - bha & honda & 85 & + 39.6868 & 8 & 0 & 22 \\
9 & 10 & 11 & tony kanaan & kv racing technology & chevrolet & 84 & + 1 lap & 16 & 0 & 20 \\
10 & 11 & 18 & justin wilson & dale coyne racing & honda & 84 & + 1 lap & 20 & 0 & 19 \\
11 & 12 & 19 & james jakes & dale coyne racing & honda & 84 & + 1 lap & 24 & 0 & 18 \\
12 & 13 & 9 & scott dixon & chip ganassi racing & honda & 84 & + 1 lap & 5 & 0 & 17 \\
13 & 14 & 14 & mike conway & a.j. foyt enterprises & honda & 84 & + 1 lap & 14 & 0 & 16 \\
14 & 15 & 17 & sebastian saavedra & andretti autosport & chevrolet & 84 & + 1 lap & 23 & 0 & 15 \\
15 & 16 & 5 & e.j. viso & kv racing technology & chevrolet & 84 & + 1 lap & 17 & 0 & 14 \\
16 & 17 & 78 & simona de silvestro & hvm racing & lotus & 84 & + 1 lap & 27 & 0 & 13 \\
17 & 18 & 28 & ryan hunter-reay & andretti autosport & chevrolet & 84 & + 1 lap & 7 & 1 & 12 \\
18 & 19 & 22 & oriol servia & panther/dreyer & reinbold racing & chevrolet & 84 & + 1 lap & 18 & 0 & 12 \\
19 & 20 & 20 & ed carpenter & ed carpenter racing & chevrolet & 84 & + 1 lap & 25 & 0 & 12 \\
20 & 21 & 83 & charlie kimball & chip ganassi racing & honda & 82 & + 3 laps & 21 & 0 & 12 \\
21 & 22 & 7 & sebastien bourdais & dragon racing & chevrolet & 63 & contact & 3 & 0 & 12 \\
22 & 23 & 67 & josef newgarden (r) & sarah fisher hartman racing & honda & 62 & contact & 22 & 0 & 12 \\
23 & 24 & 6 & katherine legge (r) & dragon racing & chevrolet & 48 & mechanical & 19 & 0 & 12 \\
24 & 25 & 26 & marco andretti & andretti autosport & chevrolet & 46 & mechanical & 12 & 0 & 10 \\
25 & 26 & 27 & james hinchcliffe & andretti autosport & chevrolet & 35 & mechanical & 10 & 0 & 10 \\
26 & 27 & 15 & takuma sato & rahal letterman lanigan racing & honda & 2 & mechanical & 26 & 0 & 10 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "team" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( team ) where team = 'team penske' <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>engine</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>laps led</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2</td>
<td>ryan briscoe</td>
<td>team penske</td>
<td>chevrolet</td>
<td>85</td>
<td>2:07:02.8248</td>
<td>2</td>
<td>27</td>
<td>50</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>12</td>
<td>will power</td>
<td>team penske</td>
<td>chevrolet</td>
<td>85</td>
<td>+ 0.4408</td>
<td>1</td>
<td>57</td>
<td>43</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>10</td>
<td>dario franchitti</td>
<td>chip ganassi racing</td>
<td>honda</td>
<td>85</td>
<td>+ 1.0497</td>
<td>6</td>
<td>0</td>
<td>35</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>8</td>
<td>rubens barrichello</td>
<td>kv racing technology</td>
<td>chevrolet</td>
<td>85</td>
<td>+ 8.8529</td>
<td>11</td>
<td>0</td>
<td>32</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>38</td>
<td>graham rahal</td>
<td>chip ganassi racing</td>
<td>honda</td>
<td>85</td>
<td>+ 9.4667</td>
<td>13</td>
<td>0</td>
<td>30</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>3</td>
<td>helio castroneves</td>
<td>team penske</td>
<td>chevrolet</td>
<td>85</td>
<td>+ 11.2575</td>
<td>4</td>
<td>0</td>
<td>28</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>77</td>
<td>simon pagenaud (r)</td>
<td>schmidt hamilton motorsports</td>
<td>honda</td>
<td>85</td>
<td>+ 12.3087</td>
<td>9</td>
<td>0</td>
<td>26</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>4</td>
<td>j.r. hildebrand</td>
<td>panther racing</td>
<td>chevrolet</td>
<td>85</td>
<td>+ 22.8121</td>
<td>15</td>
<td>0</td>
<td>24</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>98</td>
<td>alex tagliani</td>
<td>team barracuda - bha</td>
<td>honda</td>
<td>85</td>
<td>+ 39.6868</td>
<td>8</td>
<td>0</td>
<td>22</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>11</td>
<td>tony kanaan</td>
<td>kv racing technology</td>
<td>chevrolet</td>
<td>84</td>
<td>+ 1 lap</td>
<td>16</td>
<td>0</td>
<td>20</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>18</td>
<td>justin wilson</td>
<td>dale coyne racing</td>
<td>honda</td>
<td>84</td>
<td>+ 1 lap</td>
<td>20</td>
<td>0</td>
<td>19</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>19</td>
<td>james jakes</td>
<td>dale coyne racing</td>
<td>honda</td>
<td>84</td>
<td>+ 1 lap</td>
<td>24</td>
<td>0</td>
<td>18</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>9</td>
<td>scott dixon</td>
<td>chip ganassi racing</td>
<td>honda</td>
<td>84</td>
<td>+ 1 lap</td>
<td>5</td>
<td>0</td>
<td>17</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>14</td>
<td>mike conway</td>
<td>a.j. foyt enterprises</td>
<td>honda</td>
<td>84</td>
<td>+ 1 lap</td>
<td>14</td>
<td>0</td>
<td>16</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>17</td>
<td>sebastian saavedra</td>
<td>andretti autosport</td>
<td>chevrolet</td>
<td>84</td>
<td>+ 1 lap</td>
<td>23</td>
<td>0</td>
<td>15</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>5</td>
<td>e.j. viso</td>
<td>kv racing technology</td>
<td>chevrolet</td>
<td>84</td>
<td>+ 1 lap</td>
<td>17</td>
<td>0</td>
<td>14</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>78</td>
<td>simona de silvestro</td>
<td>hvm racing</td>
<td>lotus</td>
<td>84</td>
<td>+ 1 lap</td>
<td>27</td>
<td>0</td>
<td>13</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>28</td>
<td>ryan hunter-reay</td>
<td>andretti autosport</td>
<td>chevrolet</td>
<td>84</td>
<td>+ 1 lap</td>
<td>7</td>
<td>1</td>
<td>12</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>22</td>
<td>oriol servia</td>
<td>panther/dreyer & reinbold racing</td>
<td>chevrolet</td>
<td>84</td>
<td>+ 1 lap</td>
<td>18</td>
<td>0</td>
<td>12</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>20</td>
<td>ed carpenter</td>
<td>ed carpenter racing</td>
<td>chevrolet</td>
<td>84</td>
<td>+ 1 lap</td>
<td>25</td>
<td>0</td>
<td>12</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>83</td>
<td>charlie kimball</td>
<td>chip ganassi racing</td>
<td>honda</td>
<td>82</td>
<td>+ 3 laps</td>
<td>21</td>
<td>0</td>
<td>12</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>7</td>
<td>sebastien bourdais</td>
<td>dragon racing</td>
<td>chevrolet</td>
<td>63</td>
<td>contact</td>
<td>3</td>
<td>0</td>
<td>12</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>67</td>
<td>josef newgarden (r)</td>
<td>sarah fisher hartman racing</td>
<td>honda</td>
<td>62</td>
<td>contact</td>
<td>22</td>
<td>0</td>
<td>12</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>6</td>
<td>katherine legge (r)</td>
<td>dragon racing</td>
<td>chevrolet</td>
<td>48</td>
<td>mechanical</td>
<td>19</td>
<td>0</td>
<td>12</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>26</td>
<td>marco andretti</td>
<td>andretti autosport</td>
<td>chevrolet</td>
<td>46</td>
<td>mechanical</td>
<td>12</td>
<td>0</td>
<td>10</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>27</td>
<td>james hinchcliffe</td>
<td>andretti autosport</td>
<td>chevrolet</td>
<td>35</td>
<td>mechanical</td>
<td>10</td>
<td>0</td>
<td>10</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>15</td>
<td>takuma sato</td>
<td>rahal letterman lanigan racing</td>
<td>honda</td>
<td>2</td>
<td>mechanical</td>
<td>26</td>
<td>0</td>
<td>10</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>3</td>
</tr>
</tbody>
</table> | select count ( team ) where team = 'team penske' <table_name> : table | | pos | no. | driver | team | engine | laps | time/retired | grid | laps led | points |
|---:|------:|------:|:--------------------|:---------------------------------|:----------|-------:|:---------------|-------:|-----------:|---------:|
| 0 | 1 | 2 | ryan briscoe | team penske | chevrolet | 85 | 2:07:02.8248 | 2 | 27 | 50 |
| 1 | 2 | 12 | will power | team penske | chevrolet | 85 | + 0.4408 | 1 | 57 | 43 |
| 2 | 3 | 10 | dario franchitti | chip ganassi racing | honda | 85 | + 1.0497 | 6 | 0 | 35 |
| 3 | 4 | 8 | rubens barrichello | kv racing technology | chevrolet | 85 | + 8.8529 | 11 | 0 | 32 |
| 4 | 5 | 38 | graham rahal | chip ganassi racing | honda | 85 | + 9.4667 | 13 | 0 | 30 |
| 5 | 6 | 3 | helio castroneves | team penske | chevrolet | 85 | + 11.2575 | 4 | 0 | 28 |
| 6 | 7 | 77 | simon pagenaud (r) | schmidt hamilton motorsports | honda | 85 | + 12.3087 | 9 | 0 | 26 |
| 7 | 8 | 4 | j.r. hildebrand | panther racing | chevrolet | 85 | + 22.8121 | 15 | 0 | 24 |
| 8 | 9 | 98 | alex tagliani | team barracuda - bha | honda | 85 | + 39.6868 | 8 | 0 | 22 |
| 9 | 10 | 11 | tony kanaan | kv racing technology | chevrolet | 84 | + 1 lap | 16 | 0 | 20 |
| 10 | 11 | 18 | justin wilson | dale coyne racing | honda | 84 | + 1 lap | 20 | 0 | 19 |
| 11 | 12 | 19 | james jakes | dale coyne racing | honda | 84 | + 1 lap | 24 | 0 | 18 |
| 12 | 13 | 9 | scott dixon | chip ganassi racing | honda | 84 | + 1 lap | 5 | 0 | 17 |
| 13 | 14 | 14 | mike conway | a.j. foyt enterprises | honda | 84 | + 1 lap | 14 | 0 | 16 |
| 14 | 15 | 17 | sebastian saavedra | andretti autosport | chevrolet | 84 | + 1 lap | 23 | 0 | 15 |
| 15 | 16 | 5 | e.j. viso | kv racing technology | chevrolet | 84 | + 1 lap | 17 | 0 | 14 |
| 16 | 17 | 78 | simona de silvestro | hvm racing | lotus | 84 | + 1 lap | 27 | 0 | 13 |
| 17 | 18 | 28 | ryan hunter-reay | andretti autosport | chevrolet | 84 | + 1 lap | 7 | 1 | 12 |
| 18 | 19 | 22 | oriol servia | panther/dreyer & reinbold racing | chevrolet | 84 | + 1 lap | 18 | 0 | 12 |
| 19 | 20 | 20 | ed carpenter | ed carpenter racing | chevrolet | 84 | + 1 lap | 25 | 0 | 12 |
| 20 | 21 | 83 | charlie kimball | chip ganassi racing | honda | 82 | + 3 laps | 21 | 0 | 12 |
| 21 | 22 | 7 | sebastien bourdais | dragon racing | chevrolet | 63 | contact | 3 | 0 | 12 |
| 22 | 23 | 67 | josef newgarden (r) | sarah fisher hartman racing | honda | 62 | contact | 22 | 0 | 12 |
| 23 | 24 | 6 | katherine legge (r) | dragon racing | chevrolet | 48 | mechanical | 19 | 0 | 12 |
| 24 | 25 | 26 | marco andretti | andretti autosport | chevrolet | 46 | mechanical | 12 | 0 | 10 |
| 25 | 26 | 27 | james hinchcliffe | andretti autosport | chevrolet | 35 | mechanical | 10 | 0 | 10 |
| 26 | 27 | 15 | takuma sato | rahal letterman lanigan racing | honda | 2 | mechanical | 26 | 0 | 10 | | | | count ( "team" ) |
|---:|-------------------:|
| 0 | 3 | | [
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select count ( venue ) where venue = 'rybnik' 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 ( "venue" ) row 1 : 1 | select count ( venue ) where venue = 'rybnik' <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 ( "venue" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( venue ) where venue = 'rybnik' <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 ( "venue" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( venue ) where venue = 'rybnik' <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 ( "venue" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select team where goals against = 30 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 : team row 1 : fylkir | select team where goals against = 30 <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
& team \\
\midrule
0 & fylkir \\
\bottomrule
\end{tabular}
| select team where goals against = 30 <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>team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>fylkir</td>
</tr>
</tbody>
</table> | select team where goals against = 30 <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 | | | | team |
|---:|:-------|
| 0 | fylkir | | [
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select ( select count ( name ) where first section opened = 1989 ) - ( select count ( name ) where first section opened = 1957 ) col : color & icon | name -1 | name -2 | mark | first section opened | last ex- tension | length | stations row 1 : yellow | line 1 | higashiyama line | h | 1957 | 1982 | 20.6 km (12.8 mi) | 22 row 2 : purple | line 2 | meijo line | m | 1965 | 1971 | 8.9 km (5.5 mi) | 12 row 3 : purple | line 4 | meijo line | m | 1974 | 2004 | 17.5 km (10.9 mi) | 17 row 4 : purple & white | line 2 | meiko line | e | 1971 | none | 6.0 km (3.7 mi) | 7 row 5 : blue | via trackage rights | meitetsu inuyama line | none | 1993 | none | 21.4 km (13.3 mi) | 13 row 6 : blue | line 3 | tsurumai line | t | 1977 | 1993 | 20.4 km (12.7 mi) | 20 row 7 : blue | via trackage rights | meitetsu toyota line | none | 1979 | none | 15.2 km (9.4 mi) | 8 row 8 : blue | via trackage rights | meitetsu mikawa line | none | none | none | 1.4 km (0.87 mi) | 2 row 9 : red | line 6 | sakura-dori line | s | 1989 | 2011 | 19.1 km (11.9 mi) | 21 row 10 : pink | via trackage rights | meitetsu komaki line | none | 2003 | none | 18.3 km (11.4 mi) | 13 row 11 : pink | via trackage rights | meitetsu komaki line | none | 2003 | none | 2.3 km (1.4 mi) | 2 row 12 : pink | line 7 | kamiiida line | k | 2003 | none | 0.8 km (0.50 mi) | 2 | col : count ( "select count ( name" ) row 1 : 0 | select ( select count ( name ) where first section opened = 1989 ) - ( select count ( name ) where first section opened = 1957 ) <table_name> : table \begin{tabular}{lllllllll}
\toprule
& color & icon & name -1 & name -2 & mark & first section opened & last ex- tension & length & stations \\
\midrule
0 & yellow & line 1 & higashiyama line & h & 1957 & 1982 & 20.6 km (12.8 mi) & 22 \\
1 & purple & line 2 & meijo line & m & 1965 & 1971 & 8.9 km (5.5 mi) & 12 \\
2 & purple & line 4 & meijo line & m & 1974 & 2004 & 17.5 km (10.9 mi) & 17 \\
3 & purple & white & line 2 & meiko line & e & 1971 & none & 6.0 km (3.7 mi) & 7 \\
4 & blue & via trackage rights & meitetsu inuyama line & none & 1993 & none & 21.4 km (13.3 mi) & 13 \\
5 & blue & line 3 & tsurumai line & t & 1977 & 1993 & 20.4 km (12.7 mi) & 20 \\
6 & blue & via trackage rights & meitetsu toyota line & none & 1979 & none & 15.2 km (9.4 mi) & 8 \\
7 & blue & via trackage rights & meitetsu mikawa line & none & none & none & 1.4 km (0.87 mi) & 2 \\
8 & red & line 6 & sakura-dori line & s & 1989 & 2011 & 19.1 km (11.9 mi) & 21 \\
9 & pink & via trackage rights & meitetsu komaki line & none & 2003 & none & 18.3 km (11.4 mi) & 13 \\
10 & pink & via trackage rights & meitetsu komaki line & none & 2003 & none & 2.3 km (1.4 mi) & 2 \\
11 & pink & line 7 & kamiiida line & k & 2003 & none & 0.8 km (0.50 mi) & 2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "select count ( name" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select ( select count ( name ) where first section opened = 1989 ) - ( select count ( name ) where first section opened = 1957 ) <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>color & icon</th>
<th>name -1</th>
<th>name -2</th>
<th>mark</th>
<th>first section opened</th>
<th>last ex- tension</th>
<th>length</th>
<th>stations</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>yellow</td>
<td>line 1</td>
<td>higashiyama line</td>
<td>h</td>
<td>1957</td>
<td>1982</td>
<td>20.6 km (12.8 mi)</td>
<td>22</td>
</tr>
<tr>
<th>1</th>
<td>purple</td>
<td>line 2</td>
<td>meijo line</td>
<td>m</td>
<td>1965</td>
<td>1971</td>
<td>8.9 km (5.5 mi)</td>
<td>12</td>
</tr>
<tr>
<th>2</th>
<td>purple</td>
<td>line 4</td>
<td>meijo line</td>
<td>m</td>
<td>1974</td>
<td>2004</td>
<td>17.5 km (10.9 mi)</td>
<td>17</td>
</tr>
<tr>
<th>3</th>
<td>purple & white</td>
<td>line 2</td>
<td>meiko line</td>
<td>e</td>
<td>1971</td>
<td>none</td>
<td>6.0 km (3.7 mi)</td>
<td>7</td>
</tr>
<tr>
<th>4</th>
<td>blue</td>
<td>via trackage rights</td>
<td>meitetsu inuyama line</td>
<td>none</td>
<td>1993</td>
<td>none</td>
<td>21.4 km (13.3 mi)</td>
<td>13</td>
</tr>
<tr>
<th>5</th>
<td>blue</td>
<td>line 3</td>
<td>tsurumai line</td>
<td>t</td>
<td>1977</td>
<td>1993</td>
<td>20.4 km (12.7 mi)</td>
<td>20</td>
</tr>
<tr>
<th>6</th>
<td>blue</td>
<td>via trackage rights</td>
<td>meitetsu toyota line</td>
<td>none</td>
<td>1979</td>
<td>none</td>
<td>15.2 km (9.4 mi)</td>
<td>8</td>
</tr>
<tr>
<th>7</th>
<td>blue</td>
<td>via trackage rights</td>
<td>meitetsu mikawa line</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>1.4 km (0.87 mi)</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>red</td>
<td>line 6</td>
<td>sakura-dori line</td>
<td>s</td>
<td>1989</td>
<td>2011</td>
<td>19.1 km (11.9 mi)</td>
<td>21</td>
</tr>
<tr>
<th>9</th>
<td>pink</td>
<td>via trackage rights</td>
<td>meitetsu komaki line</td>
<td>none</td>
<td>2003</td>
<td>none</td>
<td>18.3 km (11.4 mi)</td>
<td>13</td>
</tr>
<tr>
<th>10</th>
<td>pink</td>
<td>via trackage rights</td>
<td>meitetsu komaki line</td>
<td>none</td>
<td>2003</td>
<td>none</td>
<td>2.3 km (1.4 mi)</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>pink</td>
<td>line 7</td>
<td>kamiiida line</td>
<td>k</td>
<td>2003</td>
<td>none</td>
<td>0.8 km (0.50 mi)</td>
<td>2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "select count ( name" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select ( select count ( name ) where first section opened = 1989 ) - ( select count ( name ) where first section opened = 1957 ) <table_name> : table | | color & icon | name -1 | name -2 | mark | first section opened | last ex- tension | length | stations |
|---:|:---------------|:--------------------|:----------------------|:-------|:-----------------------|:-------------------|:------------------|-----------:|
| 0 | yellow | line 1 | higashiyama line | h | 1957 | 1982 | 20.6 km (12.8 mi) | 22 |
| 1 | purple | line 2 | meijo line | m | 1965 | 1971 | 8.9 km (5.5 mi) | 12 |
| 2 | purple | line 4 | meijo line | m | 1974 | 2004 | 17.5 km (10.9 mi) | 17 |
| 3 | purple & white | line 2 | meiko line | e | 1971 | none | 6.0 km (3.7 mi) | 7 |
| 4 | blue | via trackage rights | meitetsu inuyama line | none | 1993 | none | 21.4 km (13.3 mi) | 13 |
| 5 | blue | line 3 | tsurumai line | t | 1977 | 1993 | 20.4 km (12.7 mi) | 20 |
| 6 | blue | via trackage rights | meitetsu toyota line | none | 1979 | none | 15.2 km (9.4 mi) | 8 |
| 7 | blue | via trackage rights | meitetsu mikawa line | none | none | none | 1.4 km (0.87 mi) | 2 |
| 8 | red | line 6 | sakura-dori line | s | 1989 | 2011 | 19.1 km (11.9 mi) | 21 |
| 9 | pink | via trackage rights | meitetsu komaki line | none | 2003 | none | 18.3 km (11.4 mi) | 13 |
| 10 | pink | via trackage rights | meitetsu komaki line | none | 2003 | none | 2.3 km (1.4 mi) | 2 |
| 11 | pink | line 7 | kamiiida line | k | 2003 | none | 0.8 km (0.50 mi) | 2 | | | | count ( "select count ( name" ) |
|---:|----------------------------------:|
| 0 | 0 | | [
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select venue where position = '7th' col : year | competition | venue | position | event | notes row 1 : 1999 | european junior championships | riga, latvia | 4th | 400 m hurdles | 52.17 row 2 : 2000 | world junior championships | santiago, chile | 1st | 400 m hurdles | 49.23 row 3 : 2001 | world championships | edmonton, canada | 18th (sf) | 400 m hurdles | 49.8 row 4 : 2001 | universiade | beijing, china | 8th | 400 m hurdles | 49.68 row 5 : 2002 | european indoor championships | vienna, austria | 1st | 400 m | 45.39 (cr, nr) row 6 : 2002 | european indoor championships | vienna, austria | 1st | 4x400 m relay | 3:05.50 (cr) row 7 : 2002 | european championships | munich, germany | 4th | 400 m | 45.4 row 8 : 2002 | european championships | munich, germany | 8th | 4x400 m relay | dq row 9 : 2003 | world indoor championships | birmingham, united kingdom | 7th (sf) | 400 m | 46.82 row 10 : 2003 | world indoor championships | birmingham, united kingdom | 3rd | 4x400 m relay | 03:06.6 row 11 : 2003 | european u23 championships | bydgoszcz, poland | 1st | 400 m hurdles | 48.45 row 12 : 2003 | european u23 championships | bydgoszcz, poland | 1st | 4x400 m relay | 03:03.3 row 13 : 2004 | olympic games | athens, greece | 6th | 400 m hurdles | 49 row 14 : 2004 | olympic games | athens, greece | 10th (h) | 4x400 m relay | 03:03.7 row 15 : 2006 | european championships | gothenburg, sweden | 2nd | 400 m hurdles | 48.71 row 16 : 2007 | world championships | osaka, japan | 3rd | 400 m hurdles | 48.12 (nr) row 17 : 2007 | world championships | osaka, japan | 3rd | 4x400 m relay | 03:00.1 row 18 : 2008 | olympic games | beijing, china | 6th | 400 m hurdles | 48.42 row 19 : 2008 | olympic games | beijing, china | 7th | 4x400 m relay | 03:00.3 row 20 : 2012 | european championships | helsinki, finland | 18th (sf) | 400 m hurdles | 50.77 | col : venue row 1 : beijing, china | select venue where position = '7th' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & competition & venue & position & event & notes \\
\midrule
0 & 1999 & european junior championships & riga, latvia & 4th & 400 m hurdles & 52.17 \\
1 & 2000 & world junior championships & santiago, chile & 1st & 400 m hurdles & 49.23 \\
2 & 2001 & world championships & edmonton, canada & 18th (sf) & 400 m hurdles & 49.8 \\
3 & 2001 & universiade & beijing, china & 8th & 400 m hurdles & 49.68 \\
4 & 2002 & european indoor championships & vienna, austria & 1st & 400 m & 45.39 (cr, nr) \\
5 & 2002 & european indoor championships & vienna, austria & 1st & 4x400 m relay & 3:05.50 (cr) \\
6 & 2002 & european championships & munich, germany & 4th & 400 m & 45.4 \\
7 & 2002 & european championships & munich, germany & 8th & 4x400 m relay & dq \\
8 & 2003 & world indoor championships & birmingham, united kingdom & 7th (sf) & 400 m & 46.82 \\
9 & 2003 & world indoor championships & birmingham, united kingdom & 3rd & 4x400 m relay & 03:06.6 \\
10 & 2003 & european u23 championships & bydgoszcz, poland & 1st & 400 m hurdles & 48.45 \\
11 & 2003 & european u23 championships & bydgoszcz, poland & 1st & 4x400 m relay & 03:03.3 \\
12 & 2004 & olympic games & athens, greece & 6th & 400 m hurdles & 49 \\
13 & 2004 & olympic games & athens, greece & 10th (h) & 4x400 m relay & 03:03.7 \\
14 & 2006 & european championships & gothenburg, sweden & 2nd & 400 m hurdles & 48.71 \\
15 & 2007 & world championships & osaka, japan & 3rd & 400 m hurdles & 48.12 (nr) \\
16 & 2007 & world championships & osaka, japan & 3rd & 4x400 m relay & 03:00.1 \\
17 & 2008 & olympic games & beijing, china & 6th & 400 m hurdles & 48.42 \\
18 & 2008 & olympic games & beijing, china & 7th & 4x400 m relay & 03:00.3 \\
19 & 2012 & european championships & helsinki, finland & 18th (sf) & 400 m hurdles & 50.77 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& venue \\
\midrule
0 & beijing, china \\
\bottomrule
\end{tabular}
| select venue where position = '7th' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>competition</th>
<th>venue</th>
<th>position</th>
<th>event</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1999</td>
<td>european junior championships</td>
<td>riga, latvia</td>
<td>4th</td>
<td>400 m hurdles</td>
<td>52.17</td>
</tr>
<tr>
<th>1</th>
<td>2000</td>
<td>world junior championships</td>
<td>santiago, chile</td>
<td>1st</td>
<td>400 m hurdles</td>
<td>49.23</td>
</tr>
<tr>
<th>2</th>
<td>2001</td>
<td>world championships</td>
<td>edmonton, canada</td>
<td>18th (sf)</td>
<td>400 m hurdles</td>
<td>49.8</td>
</tr>
<tr>
<th>3</th>
<td>2001</td>
<td>universiade</td>
<td>beijing, china</td>
<td>8th</td>
<td>400 m hurdles</td>
<td>49.68</td>
</tr>
<tr>
<th>4</th>
<td>2002</td>
<td>european indoor championships</td>
<td>vienna, austria</td>
<td>1st</td>
<td>400 m</td>
<td>45.39 (cr, nr)</td>
</tr>
<tr>
<th>5</th>
<td>2002</td>
<td>european indoor championships</td>
<td>vienna, austria</td>
<td>1st</td>
<td>4x400 m relay</td>
<td>3:05.50 (cr)</td>
</tr>
<tr>
<th>6</th>
<td>2002</td>
<td>european championships</td>
<td>munich, germany</td>
<td>4th</td>
<td>400 m</td>
<td>45.4</td>
</tr>
<tr>
<th>7</th>
<td>2002</td>
<td>european championships</td>
<td>munich, germany</td>
<td>8th</td>
<td>4x400 m relay</td>
<td>dq</td>
</tr>
<tr>
<th>8</th>
<td>2003</td>
<td>world indoor championships</td>
<td>birmingham, united kingdom</td>
<td>7th (sf)</td>
<td>400 m</td>
<td>46.82</td>
</tr>
<tr>
<th>9</th>
<td>2003</td>
<td>world indoor championships</td>
<td>birmingham, united kingdom</td>
<td>3rd</td>
<td>4x400 m relay</td>
<td>03:06.6</td>
</tr>
<tr>
<th>10</th>
<td>2003</td>
<td>european u23 championships</td>
<td>bydgoszcz, poland</td>
<td>1st</td>
<td>400 m hurdles</td>
<td>48.45</td>
</tr>
<tr>
<th>11</th>
<td>2003</td>
<td>european u23 championships</td>
<td>bydgoszcz, poland</td>
<td>1st</td>
<td>4x400 m relay</td>
<td>03:03.3</td>
</tr>
<tr>
<th>12</th>
<td>2004</td>
<td>olympic games</td>
<td>athens, greece</td>
<td>6th</td>
<td>400 m hurdles</td>
<td>49</td>
</tr>
<tr>
<th>13</th>
<td>2004</td>
<td>olympic games</td>
<td>athens, greece</td>
<td>10th (h)</td>
<td>4x400 m relay</td>
<td>03:03.7</td>
</tr>
<tr>
<th>14</th>
<td>2006</td>
<td>european championships</td>
<td>gothenburg, sweden</td>
<td>2nd</td>
<td>400 m hurdles</td>
<td>48.71</td>
</tr>
<tr>
<th>15</th>
<td>2007</td>
<td>world championships</td>
<td>osaka, japan</td>
<td>3rd</td>
<td>400 m hurdles</td>
<td>48.12 (nr)</td>
</tr>
<tr>
<th>16</th>
<td>2007</td>
<td>world championships</td>
<td>osaka, japan</td>
<td>3rd</td>
<td>4x400 m relay</td>
<td>03:00.1</td>
</tr>
<tr>
<th>17</th>
<td>2008</td>
<td>olympic games</td>
<td>beijing, china</td>
<td>6th</td>
<td>400 m hurdles</td>
<td>48.42</td>
</tr>
<tr>
<th>18</th>
<td>2008</td>
<td>olympic games</td>
<td>beijing, china</td>
<td>7th</td>
<td>4x400 m relay</td>
<td>03:00.3</td>
</tr>
<tr>
<th>19</th>
<td>2012</td>
<td>european championships</td>
<td>helsinki, finland</td>
<td>18th (sf)</td>
<td>400 m hurdles</td>
<td>50.77</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>venue</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>beijing, china</td>
</tr>
</tbody>
</table> | select venue where position = '7th' <table_name> : table | | year | competition | venue | position | event | notes |
|---:|-------:|:------------------------------|:---------------------------|:-----------|:--------------|:---------------|
| 0 | 1999 | european junior championships | riga, latvia | 4th | 400 m hurdles | 52.17 |
| 1 | 2000 | world junior championships | santiago, chile | 1st | 400 m hurdles | 49.23 |
| 2 | 2001 | world championships | edmonton, canada | 18th (sf) | 400 m hurdles | 49.8 |
| 3 | 2001 | universiade | beijing, china | 8th | 400 m hurdles | 49.68 |
| 4 | 2002 | european indoor championships | vienna, austria | 1st | 400 m | 45.39 (cr, nr) |
| 5 | 2002 | european indoor championships | vienna, austria | 1st | 4x400 m relay | 3:05.50 (cr) |
| 6 | 2002 | european championships | munich, germany | 4th | 400 m | 45.4 |
| 7 | 2002 | european championships | munich, germany | 8th | 4x400 m relay | dq |
| 8 | 2003 | world indoor championships | birmingham, united kingdom | 7th (sf) | 400 m | 46.82 |
| 9 | 2003 | world indoor championships | birmingham, united kingdom | 3rd | 4x400 m relay | 03:06.6 |
| 10 | 2003 | european u23 championships | bydgoszcz, poland | 1st | 400 m hurdles | 48.45 |
| 11 | 2003 | european u23 championships | bydgoszcz, poland | 1st | 4x400 m relay | 03:03.3 |
| 12 | 2004 | olympic games | athens, greece | 6th | 400 m hurdles | 49 |
| 13 | 2004 | olympic games | athens, greece | 10th (h) | 4x400 m relay | 03:03.7 |
| 14 | 2006 | european championships | gothenburg, sweden | 2nd | 400 m hurdles | 48.71 |
| 15 | 2007 | world championships | osaka, japan | 3rd | 400 m hurdles | 48.12 (nr) |
| 16 | 2007 | world championships | osaka, japan | 3rd | 4x400 m relay | 03:00.1 |
| 17 | 2008 | olympic games | beijing, china | 6th | 400 m hurdles | 48.42 |
| 18 | 2008 | olympic games | beijing, china | 7th | 4x400 m relay | 03:00.3 |
| 19 | 2012 | european championships | helsinki, finland | 18th (sf) | 400 m hurdles | 50.77 | | | | venue |
|---:|:---------------|
| 0 | beijing, china | | [
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select no. - no. where runners up = 'nellamakkada' col : no. | year | name | held at | number of teams | winner | runners up row 1 : 1 | 1997 | pandanda cup | karada | 60 | kaliyanda | anjaparavanda row 2 : 2 | 1998 | kodira cup | kadanga | 116 | kullettira | koothanda row 3 : 3 | 1999 | ballachanda cup | kakotparambu | 140 | koothanda and kullettira | none row 4 : 4 | 2000 | cheppudira cup | ponnampet | 170 | koothanda | nellamakkada row 5 : 5 | 2001 | nellamakkada cup | ammathi | 220 | koothanda | cheppudira row 6 : 6 | 2002 | chekkera cup | hudikeri | 252 | kullettira | nellamakkada row 7 : 7 | 2003 | kaliyanda cup | napoklu | 280 | nellamakkada | konerira row 8 : 8 | 2004 | maleyanda cup | madapur | 235 | koothanda | nellamakkada row 9 : 9 | 2005 | biddanda cup | madikeri | 222 | nellamakkada | koothanda row 10 : 10 | 2006 | kallichanda cup | ponnampet | 217 | palanganda | machamada row 11 : 11 | 2007 | mandettira cup | kakotparambu | 186 | mandepanda | anjaparavanda row 12 : 12 | 2008 | alamengada cup | ponnampet | 216 | anjaparavanda | koothanda row 13 : 13 | 2009 | mandepanda cup | ammathi | 231 | nellamakkada | koothanda row 14 : 14 | 2010 | maneyapanda cup | ponnampet | 214 | palanganda | mukkatira(bonda) row 15 : 15 | 2011 | machamada cup | ponnampet | 228 | palanganda | kaliyanda row 16 : 16 | 2012 | iychetira cup | ammathi | 217 | palanganda | kaliyanda row 17 : 17 | 2013 | madanda cup | balugodu | 225 | anjaparavanda | palanganda row 18 : 18 | 2014 | thathanda cup | virajpet | none | none | none | col : "no. - no." row 1 : no. - no. row 2 : no. - no. row 3 : no. - no. | select no. - no. where runners up = 'nellamakkada' <table_name> : table \begin{tabular}{llllllll}
\toprule
& no. & year & name & held at & number of teams & winner & runners up \\
\midrule
0 & 1 & 1997 & pandanda cup & karada & 60 & kaliyanda & anjaparavanda \\
1 & 2 & 1998 & kodira cup & kadanga & 116 & kullettira & koothanda \\
2 & 3 & 1999 & ballachanda cup & kakotparambu & 140 & koothanda and kullettira & none \\
3 & 4 & 2000 & cheppudira cup & ponnampet & 170 & koothanda & nellamakkada \\
4 & 5 & 2001 & nellamakkada cup & ammathi & 220 & koothanda & cheppudira \\
5 & 6 & 2002 & chekkera cup & hudikeri & 252 & kullettira & nellamakkada \\
6 & 7 & 2003 & kaliyanda cup & napoklu & 280 & nellamakkada & konerira \\
7 & 8 & 2004 & maleyanda cup & madapur & 235 & koothanda & nellamakkada \\
8 & 9 & 2005 & biddanda cup & madikeri & 222 & nellamakkada & koothanda \\
9 & 10 & 2006 & kallichanda cup & ponnampet & 217 & palanganda & machamada \\
10 & 11 & 2007 & mandettira cup & kakotparambu & 186 & mandepanda & anjaparavanda \\
11 & 12 & 2008 & alamengada cup & ponnampet & 216 & anjaparavanda & koothanda \\
12 & 13 & 2009 & mandepanda cup & ammathi & 231 & nellamakkada & koothanda \\
13 & 14 & 2010 & maneyapanda cup & ponnampet & 214 & palanganda & mukkatira(bonda) \\
14 & 15 & 2011 & machamada cup & ponnampet & 228 & palanganda & kaliyanda \\
15 & 16 & 2012 & iychetira cup & ammathi & 217 & palanganda & kaliyanda \\
16 & 17 & 2013 & madanda cup & balugodu & 225 & anjaparavanda & palanganda \\
17 & 18 & 2014 & thathanda cup & virajpet & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "no. - no." \\
\midrule
0 & no. - no. \\
1 & no. - no. \\
2 & no. - no. \\
\bottomrule
\end{tabular}
| select no. - no. where runners up = 'nellamakkada' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no.</th>
<th>year</th>
<th>name</th>
<th>held at</th>
<th>number of teams</th>
<th>winner</th>
<th>runners up</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1997</td>
<td>pandanda cup</td>
<td>karada</td>
<td>60</td>
<td>kaliyanda</td>
<td>anjaparavanda</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1998</td>
<td>kodira cup</td>
<td>kadanga</td>
<td>116</td>
<td>kullettira</td>
<td>koothanda</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1999</td>
<td>ballachanda cup</td>
<td>kakotparambu</td>
<td>140</td>
<td>koothanda and kullettira</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2000</td>
<td>cheppudira cup</td>
<td>ponnampet</td>
<td>170</td>
<td>koothanda</td>
<td>nellamakkada</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2001</td>
<td>nellamakkada cup</td>
<td>ammathi</td>
<td>220</td>
<td>koothanda</td>
<td>cheppudira</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2002</td>
<td>chekkera cup</td>
<td>hudikeri</td>
<td>252</td>
<td>kullettira</td>
<td>nellamakkada</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2003</td>
<td>kaliyanda cup</td>
<td>napoklu</td>
<td>280</td>
<td>nellamakkada</td>
<td>konerira</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2004</td>
<td>maleyanda cup</td>
<td>madapur</td>
<td>235</td>
<td>koothanda</td>
<td>nellamakkada</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2005</td>
<td>biddanda cup</td>
<td>madikeri</td>
<td>222</td>
<td>nellamakkada</td>
<td>koothanda</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2006</td>
<td>kallichanda cup</td>
<td>ponnampet</td>
<td>217</td>
<td>palanganda</td>
<td>machamada</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>2007</td>
<td>mandettira cup</td>
<td>kakotparambu</td>
<td>186</td>
<td>mandepanda</td>
<td>anjaparavanda</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>2008</td>
<td>alamengada cup</td>
<td>ponnampet</td>
<td>216</td>
<td>anjaparavanda</td>
<td>koothanda</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>2009</td>
<td>mandepanda cup</td>
<td>ammathi</td>
<td>231</td>
<td>nellamakkada</td>
<td>koothanda</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>2010</td>
<td>maneyapanda cup</td>
<td>ponnampet</td>
<td>214</td>
<td>palanganda</td>
<td>mukkatira(bonda)</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>2011</td>
<td>machamada cup</td>
<td>ponnampet</td>
<td>228</td>
<td>palanganda</td>
<td>kaliyanda</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>2012</td>
<td>iychetira cup</td>
<td>ammathi</td>
<td>217</td>
<td>palanganda</td>
<td>kaliyanda</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>2013</td>
<td>madanda cup</td>
<td>balugodu</td>
<td>225</td>
<td>anjaparavanda</td>
<td>palanganda</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>2014</td>
<td>thathanda cup</td>
<td>virajpet</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. - no."</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>no. - no.</td>
</tr>
<tr>
<th>1</th>
<td>no. - no.</td>
</tr>
<tr>
<th>2</th>
<td>no. - no.</td>
</tr>
</tbody>
</table> | select no. - no. where runners up = 'nellamakkada' <table_name> : table | | no. | year | name | held at | number of teams | winner | runners up |
|---:|------:|-------:|:-----------------|:-------------|:------------------|:-------------------------|:-----------------|
| 0 | 1 | 1997 | pandanda cup | karada | 60 | kaliyanda | anjaparavanda |
| 1 | 2 | 1998 | kodira cup | kadanga | 116 | kullettira | koothanda |
| 2 | 3 | 1999 | ballachanda cup | kakotparambu | 140 | koothanda and kullettira | none |
| 3 | 4 | 2000 | cheppudira cup | ponnampet | 170 | koothanda | nellamakkada |
| 4 | 5 | 2001 | nellamakkada cup | ammathi | 220 | koothanda | cheppudira |
| 5 | 6 | 2002 | chekkera cup | hudikeri | 252 | kullettira | nellamakkada |
| 6 | 7 | 2003 | kaliyanda cup | napoklu | 280 | nellamakkada | konerira |
| 7 | 8 | 2004 | maleyanda cup | madapur | 235 | koothanda | nellamakkada |
| 8 | 9 | 2005 | biddanda cup | madikeri | 222 | nellamakkada | koothanda |
| 9 | 10 | 2006 | kallichanda cup | ponnampet | 217 | palanganda | machamada |
| 10 | 11 | 2007 | mandettira cup | kakotparambu | 186 | mandepanda | anjaparavanda |
| 11 | 12 | 2008 | alamengada cup | ponnampet | 216 | anjaparavanda | koothanda |
| 12 | 13 | 2009 | mandepanda cup | ammathi | 231 | nellamakkada | koothanda |
| 13 | 14 | 2010 | maneyapanda cup | ponnampet | 214 | palanganda | mukkatira(bonda) |
| 14 | 15 | 2011 | machamada cup | ponnampet | 228 | palanganda | kaliyanda |
| 15 | 16 | 2012 | iychetira cup | ammathi | 217 | palanganda | kaliyanda |
| 16 | 17 | 2013 | madanda cup | balugodu | 225 | anjaparavanda | palanganda |
| 17 | 18 | 2014 | thathanda cup | virajpet | none | none | none | | | | "no. - no." |
|---:|:--------------|
| 0 | no. - no. |
| 1 | no. - no. |
| 2 | no. - no. | | [
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select displacement - displacement where note = 'chartered' col : class | type | ships | displacement | note row 1 : rari class | tug supply vessel | a635 revi | 1,450 tonnes | none row 2 : malabar class | ocean going tug | a664 malabar a669 tenace | 1,440 tonnes | ice-breaking capabilities to 2 meters level ice row 3 : ut507 class | salvage tug | abeille flandre abeille languedoc | 1,500 tonnes | chartered row 4 : ut515 class | salvage tug | abeille bourbon abeille liberte | 4,000 tonnes | chartered row 5 : ut710 class | support, assistance, pollution control vessel | argonaute jason | 2,100 tonnes | chartered, configured to accommodate nato submarine rescue system row 6 : ut711 class | support, assistance, pollution control vessel | alcyon ailette | 2,000 tonnes | chartered row 7 : none | training ships | vn partisan | 2,250 tonnes | chartered row 8 : none | training ships | vn rebel | none | chartered | col : "displacement - displacement" row 1 : displacement - displacement row 2 : displacement - displacement row 3 : displacement - displacement row 4 : displacement - displacement row 5 : displacement - displacement | select displacement - displacement where note = 'chartered' <table_name> : table \begin{tabular}{llllll}
\toprule
& class & type & ships & displacement & note \\
\midrule
0 & rari class & tug supply vessel & a635 revi & 1,450 tonnes & none \\
1 & malabar class & ocean going tug & a664 malabar a669 tenace & 1,440 tonnes & ice-breaking capabilities to 2 meters level ice \\
2 & ut507 class & salvage tug & abeille flandre abeille languedoc & 1,500 tonnes & chartered \\
3 & ut515 class & salvage tug & abeille bourbon abeille liberte & 4,000 tonnes & chartered \\
4 & ut710 class & support, assistance, pollution control vessel & argonaute jason & 2,100 tonnes & chartered, configured to accommodate nato submarine rescue system \\
5 & ut711 class & support, assistance, pollution control vessel & alcyon ailette & 2,000 tonnes & chartered \\
6 & none & training ships & vn partisan & 2,250 tonnes & chartered \\
7 & none & training ships & vn rebel & none & chartered \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "displacement - displacement" \\
\midrule
0 & displacement - displacement \\
1 & displacement - displacement \\
2 & displacement - displacement \\
3 & displacement - displacement \\
4 & displacement - displacement \\
\bottomrule
\end{tabular}
| select displacement - displacement where note = 'chartered' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>class</th>
<th>type</th>
<th>ships</th>
<th>displacement</th>
<th>note</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>rari class</td>
<td>tug supply vessel</td>
<td>a635 revi</td>
<td>1,450 tonnes</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>malabar class</td>
<td>ocean going tug</td>
<td>a664 malabar a669 tenace</td>
<td>1,440 tonnes</td>
<td>ice-breaking capabilities to 2 meters level ice</td>
</tr>
<tr>
<th>2</th>
<td>ut507 class</td>
<td>salvage tug</td>
<td>abeille flandre abeille languedoc</td>
<td>1,500 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>3</th>
<td>ut515 class</td>
<td>salvage tug</td>
<td>abeille bourbon abeille liberte</td>
<td>4,000 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>4</th>
<td>ut710 class</td>
<td>support, assistance, pollution control vessel</td>
<td>argonaute jason</td>
<td>2,100 tonnes</td>
<td>chartered, configured to accommodate nato submarine rescue system</td>
</tr>
<tr>
<th>5</th>
<td>ut711 class</td>
<td>support, assistance, pollution control vessel</td>
<td>alcyon ailette</td>
<td>2,000 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
<td>training ships</td>
<td>vn partisan</td>
<td>2,250 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>7</th>
<td>none</td>
<td>training ships</td>
<td>vn rebel</td>
<td>none</td>
<td>chartered</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"displacement - displacement"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>displacement - displacement</td>
</tr>
<tr>
<th>1</th>
<td>displacement - displacement</td>
</tr>
<tr>
<th>2</th>
<td>displacement - displacement</td>
</tr>
<tr>
<th>3</th>
<td>displacement - displacement</td>
</tr>
<tr>
<th>4</th>
<td>displacement - displacement</td>
</tr>
</tbody>
</table> | select displacement - displacement where note = 'chartered' <table_name> : table | | class | type | ships | displacement | note |
|---:|:--------------|:----------------------------------------------|:----------------------------------|:---------------|:------------------------------------------------------------------|
| 0 | rari class | tug supply vessel | a635 revi | 1,450 tonnes | none |
| 1 | malabar class | ocean going tug | a664 malabar a669 tenace | 1,440 tonnes | ice-breaking capabilities to 2 meters level ice |
| 2 | ut507 class | salvage tug | abeille flandre abeille languedoc | 1,500 tonnes | chartered |
| 3 | ut515 class | salvage tug | abeille bourbon abeille liberte | 4,000 tonnes | chartered |
| 4 | ut710 class | support, assistance, pollution control vessel | argonaute jason | 2,100 tonnes | chartered, configured to accommodate nato submarine rescue system |
| 5 | ut711 class | support, assistance, pollution control vessel | alcyon ailette | 2,000 tonnes | chartered |
| 6 | none | training ships | vn partisan | 2,250 tonnes | chartered |
| 7 | none | training ships | vn rebel | none | chartered | | | | "displacement - displacement" |
|---:|:--------------------------------|
| 0 | displacement - displacement |
| 1 | displacement - displacement |
| 2 | displacement - displacement |
| 3 | displacement - displacement |
| 4 | displacement - displacement | | [
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select count ( opponent ) where date and time > '09.11.1946 at 15:00' col : record | date and time | competition | home or away | opponent | score row 1 : biggest win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 row 2 : biggest defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 row 3 : most goals in one match | 22.11.1922 at 15:00 | fa cup / 4th qf (replay) | away | dulwich hamlet | 7-8 row 4 : biggest home win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 row 5 : biggest home defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 row 6 : biggest away win | 24.11.1970 at 15:00 | mithras cup 2nd rd (2nd leg) | away | ruislip manor | 10-0 row 7 : biggest away win | 17.04.1920 at 15:00 | spartan league | away | tufnell spartans | 11-1 row 8 : biggest away defeat | 04.11.2008 at 19:45 | herts charity cup | away | hemel hempstead town | 0-10 | col : count ( "opponent" ) row 1 : 5 | select count ( opponent ) where date and time > '09.11.1946 at 15:00' <table_name> : table \begin{tabular}{lllllll}
\toprule
& record & date and time & competition & home or away & opponent & score \\
\midrule
0 & biggest win & 19.10.1912 at 15:00 & spartan league & home & aylesbury united & 14-0 \\
1 & biggest defeat & 09.11.1946 at 15:00 & isthmian league & home & wimbledon & 0-11 \\
2 & most goals in one match & 22.11.1922 at 15:00 & fa cup / 4th qf (replay) & away & dulwich hamlet & 7-8 \\
3 & biggest home win & 19.10.1912 at 15:00 & spartan league & home & aylesbury united & 14-0 \\
4 & biggest home defeat & 09.11.1946 at 15:00 & isthmian league & home & wimbledon & 0-11 \\
5 & biggest away win & 24.11.1970 at 15:00 & mithras cup 2nd rd (2nd leg) & away & ruislip manor & 10-0 \\
6 & biggest away win & 17.04.1920 at 15:00 & spartan league & away & tufnell spartans & 11-1 \\
7 & biggest away defeat & 04.11.2008 at 19:45 & herts charity cup & away & hemel hempstead town & 0-10 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "opponent" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( opponent ) where date and time > '09.11.1946 at 15:00' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>record</th>
<th>date and time</th>
<th>competition</th>
<th>home or away</th>
<th>opponent</th>
<th>score</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>biggest win</td>
<td>19.10.1912 at 15:00</td>
<td>spartan league</td>
<td>home</td>
<td>aylesbury united</td>
<td>14-0</td>
</tr>
<tr>
<th>1</th>
<td>biggest defeat</td>
<td>09.11.1946 at 15:00</td>
<td>isthmian league</td>
<td>home</td>
<td>wimbledon</td>
<td>0-11</td>
</tr>
<tr>
<th>2</th>
<td>most goals in one match</td>
<td>22.11.1922 at 15:00</td>
<td>fa cup / 4th qf (replay)</td>
<td>away</td>
<td>dulwich hamlet</td>
<td>7-8</td>
</tr>
<tr>
<th>3</th>
<td>biggest home win</td>
<td>19.10.1912 at 15:00</td>
<td>spartan league</td>
<td>home</td>
<td>aylesbury united</td>
<td>14-0</td>
</tr>
<tr>
<th>4</th>
<td>biggest home defeat</td>
<td>09.11.1946 at 15:00</td>
<td>isthmian league</td>
<td>home</td>
<td>wimbledon</td>
<td>0-11</td>
</tr>
<tr>
<th>5</th>
<td>biggest away win</td>
<td>24.11.1970 at 15:00</td>
<td>mithras cup 2nd rd (2nd leg)</td>
<td>away</td>
<td>ruislip manor</td>
<td>10-0</td>
</tr>
<tr>
<th>6</th>
<td>biggest away win</td>
<td>17.04.1920 at 15:00</td>
<td>spartan league</td>
<td>away</td>
<td>tufnell spartans</td>
<td>11-1</td>
</tr>
<tr>
<th>7</th>
<td>biggest away defeat</td>
<td>04.11.2008 at 19:45</td>
<td>herts charity cup</td>
<td>away</td>
<td>hemel hempstead town</td>
<td>0-10</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>5</td>
</tr>
</tbody>
</table> | select count ( opponent ) where date and time > '09.11.1946 at 15:00' <table_name> : table | | record | date and time | competition | home or away | opponent | score |
|---:|:------------------------|:--------------------|:-----------------------------|:---------------|:---------------------|:--------|
| 0 | biggest win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 |
| 1 | biggest defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 |
| 2 | most goals in one match | 22.11.1922 at 15:00 | fa cup / 4th qf (replay) | away | dulwich hamlet | 7-8 |
| 3 | biggest home win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 |
| 4 | biggest home defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 |
| 5 | biggest away win | 24.11.1970 at 15:00 | mithras cup 2nd rd (2nd leg) | away | ruislip manor | 10-0 |
| 6 | biggest away win | 17.04.1920 at 15:00 | spartan league | away | tufnell spartans | 11-1 |
| 7 | biggest away defeat | 04.11.2008 at 19:45 | herts charity cup | away | hemel hempstead town | 0-10 | | | | count ( "opponent" ) |
|---:|-----------------------:|
| 0 | 5 | | [
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select state where state = 'andhra pradesh' col : state | no. of candidates | no. of elected | total no. of seats in assembly | year of election row 1 : andhra pradesh | 12 | 6 | 294 | 2004 row 2 : assam | 19 | 1 | 126 | 2001 row 3 : bihar | 153 | 5 | 324 | 2000 row 4 : chhattisgarh | 18 | 0 | 90 | 2003 row 5 : delhi | 2 | 0 | 70 | 2003 row 6 : goa | 3 | 0 | 40 | 2002 row 7 : gujarat | 1 | 0 | 181 | 2002 row 8 : haryana | 10 | 0 | 90 | 2000 row 9 : himachal pradesh | 7 | 0 | 68 | 2003 row 10 : jammu and kashmir | 5 | 0 | 87 | 2002 row 11 : karnataka | 5 | 0 | 224 | 2004 row 12 : kerala | 22 | 17 | 140 | 2006 row 13 : madhya pradesh | 17 | 0 | 230 | 2003 row 14 : maharashtra | 19 | 0 | 288 | 1999 row 15 : manipur | 16 | 4 | 60 | 2006 row 16 : meghalaya | 3 | 0 | 60 | 2003 row 17 : mizoram | 4 | 0 | 40 | 2003 row 18 : odisha | 6 | 1 | 147 | 2004 row 19 : puducherry | 2 | 0 | 30 | 2001 row 20 : punjab | 11 | 0 | 117 | 2006 row 21 : rajasthan | 15 | 0 | 200 | 2003 row 22 : tamil nadu | 8 | 6 | 234 | 2006 row 23 : tripura | 2 | 1 | 60 | 2003 row 24 : uttar pradesh | 5 | 0 | 402 | 2002 row 25 : uttarakhand | 14 | 0 | 70 | 2002 row 26 : west bengal | 13 | 8 | 294 | 2006 | col : state row 1 : andhra pradesh | select state where state = 'andhra pradesh' <table_name> : table \begin{tabular}{llllll}
\toprule
& state & no. of candidates & no. of elected & total no. of seats in assembly & year of election \\
\midrule
0 & andhra pradesh & 12 & 6 & 294 & 2004 \\
1 & assam & 19 & 1 & 126 & 2001 \\
2 & bihar & 153 & 5 & 324 & 2000 \\
3 & chhattisgarh & 18 & 0 & 90 & 2003 \\
4 & delhi & 2 & 0 & 70 & 2003 \\
5 & goa & 3 & 0 & 40 & 2002 \\
6 & gujarat & 1 & 0 & 181 & 2002 \\
7 & haryana & 10 & 0 & 90 & 2000 \\
8 & himachal pradesh & 7 & 0 & 68 & 2003 \\
9 & jammu and kashmir & 5 & 0 & 87 & 2002 \\
10 & karnataka & 5 & 0 & 224 & 2004 \\
11 & kerala & 22 & 17 & 140 & 2006 \\
12 & madhya pradesh & 17 & 0 & 230 & 2003 \\
13 & maharashtra & 19 & 0 & 288 & 1999 \\
14 & manipur & 16 & 4 & 60 & 2006 \\
15 & meghalaya & 3 & 0 & 60 & 2003 \\
16 & mizoram & 4 & 0 & 40 & 2003 \\
17 & odisha & 6 & 1 & 147 & 2004 \\
18 & puducherry & 2 & 0 & 30 & 2001 \\
19 & punjab & 11 & 0 & 117 & 2006 \\
20 & rajasthan & 15 & 0 & 200 & 2003 \\
21 & tamil nadu & 8 & 6 & 234 & 2006 \\
22 & tripura & 2 & 1 & 60 & 2003 \\
23 & uttar pradesh & 5 & 0 & 402 & 2002 \\
24 & uttarakhand & 14 & 0 & 70 & 2002 \\
25 & west bengal & 13 & 8 & 294 & 2006 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& state \\
\midrule
0 & andhra pradesh \\
\bottomrule
\end{tabular}
| select state where state = 'andhra pradesh' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>state</th>
<th>no. of candidates</th>
<th>no. of elected</th>
<th>total no. of seats in assembly</th>
<th>year of election</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>andhra pradesh</td>
<td>12</td>
<td>6</td>
<td>294</td>
<td>2004</td>
</tr>
<tr>
<th>1</th>
<td>assam</td>
<td>19</td>
<td>1</td>
<td>126</td>
<td>2001</td>
</tr>
<tr>
<th>2</th>
<td>bihar</td>
<td>153</td>
<td>5</td>
<td>324</td>
<td>2000</td>
</tr>
<tr>
<th>3</th>
<td>chhattisgarh</td>
<td>18</td>
<td>0</td>
<td>90</td>
<td>2003</td>
</tr>
<tr>
<th>4</th>
<td>delhi</td>
<td>2</td>
<td>0</td>
<td>70</td>
<td>2003</td>
</tr>
<tr>
<th>5</th>
<td>goa</td>
<td>3</td>
<td>0</td>
<td>40</td>
<td>2002</td>
</tr>
<tr>
<th>6</th>
<td>gujarat</td>
<td>1</td>
<td>0</td>
<td>181</td>
<td>2002</td>
</tr>
<tr>
<th>7</th>
<td>haryana</td>
<td>10</td>
<td>0</td>
<td>90</td>
<td>2000</td>
</tr>
<tr>
<th>8</th>
<td>himachal pradesh</td>
<td>7</td>
<td>0</td>
<td>68</td>
<td>2003</td>
</tr>
<tr>
<th>9</th>
<td>jammu and kashmir</td>
<td>5</td>
<td>0</td>
<td>87</td>
<td>2002</td>
</tr>
<tr>
<th>10</th>
<td>karnataka</td>
<td>5</td>
<td>0</td>
<td>224</td>
<td>2004</td>
</tr>
<tr>
<th>11</th>
<td>kerala</td>
<td>22</td>
<td>17</td>
<td>140</td>
<td>2006</td>
</tr>
<tr>
<th>12</th>
<td>madhya pradesh</td>
<td>17</td>
<td>0</td>
<td>230</td>
<td>2003</td>
</tr>
<tr>
<th>13</th>
<td>maharashtra</td>
<td>19</td>
<td>0</td>
<td>288</td>
<td>1999</td>
</tr>
<tr>
<th>14</th>
<td>manipur</td>
<td>16</td>
<td>4</td>
<td>60</td>
<td>2006</td>
</tr>
<tr>
<th>15</th>
<td>meghalaya</td>
<td>3</td>
<td>0</td>
<td>60</td>
<td>2003</td>
</tr>
<tr>
<th>16</th>
<td>mizoram</td>
<td>4</td>
<td>0</td>
<td>40</td>
<td>2003</td>
</tr>
<tr>
<th>17</th>
<td>odisha</td>
<td>6</td>
<td>1</td>
<td>147</td>
<td>2004</td>
</tr>
<tr>
<th>18</th>
<td>puducherry</td>
<td>2</td>
<td>0</td>
<td>30</td>
<td>2001</td>
</tr>
<tr>
<th>19</th>
<td>punjab</td>
<td>11</td>
<td>0</td>
<td>117</td>
<td>2006</td>
</tr>
<tr>
<th>20</th>
<td>rajasthan</td>
<td>15</td>
<td>0</td>
<td>200</td>
<td>2003</td>
</tr>
<tr>
<th>21</th>
<td>tamil nadu</td>
<td>8</td>
<td>6</td>
<td>234</td>
<td>2006</td>
</tr>
<tr>
<th>22</th>
<td>tripura</td>
<td>2</td>
<td>1</td>
<td>60</td>
<td>2003</td>
</tr>
<tr>
<th>23</th>
<td>uttar pradesh</td>
<td>5</td>
<td>0</td>
<td>402</td>
<td>2002</td>
</tr>
<tr>
<th>24</th>
<td>uttarakhand</td>
<td>14</td>
<td>0</td>
<td>70</td>
<td>2002</td>
</tr>
<tr>
<th>25</th>
<td>west bengal</td>
<td>13</td>
<td>8</td>
<td>294</td>
<td>2006</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>state</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>andhra pradesh</td>
</tr>
</tbody>
</table> | select state where state = 'andhra pradesh' <table_name> : table | | state | no. of candidates | no. of elected | total no. of seats in assembly | year of election |
|---:|:------------------|--------------------:|-----------------:|---------------------------------:|-------------------:|
| 0 | andhra pradesh | 12 | 6 | 294 | 2004 |
| 1 | assam | 19 | 1 | 126 | 2001 |
| 2 | bihar | 153 | 5 | 324 | 2000 |
| 3 | chhattisgarh | 18 | 0 | 90 | 2003 |
| 4 | delhi | 2 | 0 | 70 | 2003 |
| 5 | goa | 3 | 0 | 40 | 2002 |
| 6 | gujarat | 1 | 0 | 181 | 2002 |
| 7 | haryana | 10 | 0 | 90 | 2000 |
| 8 | himachal pradesh | 7 | 0 | 68 | 2003 |
| 9 | jammu and kashmir | 5 | 0 | 87 | 2002 |
| 10 | karnataka | 5 | 0 | 224 | 2004 |
| 11 | kerala | 22 | 17 | 140 | 2006 |
| 12 | madhya pradesh | 17 | 0 | 230 | 2003 |
| 13 | maharashtra | 19 | 0 | 288 | 1999 |
| 14 | manipur | 16 | 4 | 60 | 2006 |
| 15 | meghalaya | 3 | 0 | 60 | 2003 |
| 16 | mizoram | 4 | 0 | 40 | 2003 |
| 17 | odisha | 6 | 1 | 147 | 2004 |
| 18 | puducherry | 2 | 0 | 30 | 2001 |
| 19 | punjab | 11 | 0 | 117 | 2006 |
| 20 | rajasthan | 15 | 0 | 200 | 2003 |
| 21 | tamil nadu | 8 | 6 | 234 | 2006 |
| 22 | tripura | 2 | 1 | 60 | 2003 |
| 23 | uttar pradesh | 5 | 0 | 402 | 2002 |
| 24 | uttarakhand | 14 | 0 | 70 | 2002 |
| 25 | west bengal | 13 | 8 | 294 | 2006 | | | | state |
|---:|:---------------|
| 0 | andhra pradesh | | [
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select count ( year ) where final score = '3-0' col : year | winner | runner-up | final score | third row 1 : 1992 | budivelnyk | nki mykolaiv | round-robin | spartak lugansk row 2 : 1993 | budivelnyk | ska kyiv | round-robin | nki mykolaiv row 3 : 1994 | budivelnyk | kyiv-basket | 3-0 | bipa-moda odesa row 4 : 1995 | budivelnyk | kyiv-basket | 3-0 | shakhtar-asko donetsk row 5 : 1996 | budivelnyk | shakhtar donetsk | round-robin | kyiv-basket row 6 : 1997 | budivelnyk | bipa-moda odesa | 3-2 | kyiv-basket row 7 : 1998 | bipa-moda odesa | budivelnyk | 3-0 | sc mykolaiv row 8 : 1999 | bipa-moda odesa | cska-riko kyiv | 3-2 | budivelnyk row 9 : 2000 | kyiv | mbc odesa | 3-2 | cska-ukrtatnafta kyiv row 10 : 2001 | mbc odesa | kyiv | 3-2 | azovmash row 11 : 2002 | mbc odesa | kyiv | 3-2 | azovmash row 12 : 2003 | azovmash | mbc odesa | 4-0 | kyiv row 13 : 2004 | azovmash | kyiv | 4-2 | mbc odesa row 14 : 2005 | kyiv | azovmash | 3-0 | khimik row 15 : 2006 | azovmash | kyiv | 3-1 | khimik row 16 : 2007 | azovmash | kyiv | 3-2 | khimik row 17 : 2008 | azovmash | kyiv | 3-1 | khimik row 18 : 2009 | azovmash | donetsk | 3-0 | khimik row 19 : 2010 | azovmash | budivelnyk | 3-2 | ferro-zntu row 20 : 2011 | budivelnyk | donetsk | 4-3 | hoverla row 21 : 2012 | donetsk | azovmash | 4-0 | ferro-zntu row 22 : 2013 | budivelnyk | azovmash | 4-3 | ferro-zntu | col : count ( "year" ) row 1 : 5 | select count ( year ) where final score = '3-0' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & winner & runner-up & final score & third \\
\midrule
0 & 1992 & budivelnyk & nki mykolaiv & round-robin & spartak lugansk \\
1 & 1993 & budivelnyk & ska kyiv & round-robin & nki mykolaiv \\
2 & 1994 & budivelnyk & kyiv-basket & 3-0 & bipa-moda odesa \\
3 & 1995 & budivelnyk & kyiv-basket & 3-0 & shakhtar-asko donetsk \\
4 & 1996 & budivelnyk & shakhtar donetsk & round-robin & kyiv-basket \\
5 & 1997 & budivelnyk & bipa-moda odesa & 3-2 & kyiv-basket \\
6 & 1998 & bipa-moda odesa & budivelnyk & 3-0 & sc mykolaiv \\
7 & 1999 & bipa-moda odesa & cska-riko kyiv & 3-2 & budivelnyk \\
8 & 2000 & kyiv & mbc odesa & 3-2 & cska-ukrtatnafta kyiv \\
9 & 2001 & mbc odesa & kyiv & 3-2 & azovmash \\
10 & 2002 & mbc odesa & kyiv & 3-2 & azovmash \\
11 & 2003 & azovmash & mbc odesa & 4-0 & kyiv \\
12 & 2004 & azovmash & kyiv & 4-2 & mbc odesa \\
13 & 2005 & kyiv & azovmash & 3-0 & khimik \\
14 & 2006 & azovmash & kyiv & 3-1 & khimik \\
15 & 2007 & azovmash & kyiv & 3-2 & khimik \\
16 & 2008 & azovmash & kyiv & 3-1 & khimik \\
17 & 2009 & azovmash & donetsk & 3-0 & khimik \\
18 & 2010 & azovmash & budivelnyk & 3-2 & ferro-zntu \\
19 & 2011 & budivelnyk & donetsk & 4-3 & hoverla \\
20 & 2012 & donetsk & azovmash & 4-0 & ferro-zntu \\
21 & 2013 & budivelnyk & azovmash & 4-3 & ferro-zntu \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "year" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( year ) where final score = '3-0' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>winner</th>
<th>runner-up</th>
<th>final score</th>
<th>third</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1992</td>
<td>budivelnyk</td>
<td>nki mykolaiv</td>
<td>round-robin</td>
<td>spartak lugansk</td>
</tr>
<tr>
<th>1</th>
<td>1993</td>
<td>budivelnyk</td>
<td>ska kyiv</td>
<td>round-robin</td>
<td>nki mykolaiv</td>
</tr>
<tr>
<th>2</th>
<td>1994</td>
<td>budivelnyk</td>
<td>kyiv-basket</td>
<td>3-0</td>
<td>bipa-moda odesa</td>
</tr>
<tr>
<th>3</th>
<td>1995</td>
<td>budivelnyk</td>
<td>kyiv-basket</td>
<td>3-0</td>
<td>shakhtar-asko donetsk</td>
</tr>
<tr>
<th>4</th>
<td>1996</td>
<td>budivelnyk</td>
<td>shakhtar donetsk</td>
<td>round-robin</td>
<td>kyiv-basket</td>
</tr>
<tr>
<th>5</th>
<td>1997</td>
<td>budivelnyk</td>
<td>bipa-moda odesa</td>
<td>3-2</td>
<td>kyiv-basket</td>
</tr>
<tr>
<th>6</th>
<td>1998</td>
<td>bipa-moda odesa</td>
<td>budivelnyk</td>
<td>3-0</td>
<td>sc mykolaiv</td>
</tr>
<tr>
<th>7</th>
<td>1999</td>
<td>bipa-moda odesa</td>
<td>cska-riko kyiv</td>
<td>3-2</td>
<td>budivelnyk</td>
</tr>
<tr>
<th>8</th>
<td>2000</td>
<td>kyiv</td>
<td>mbc odesa</td>
<td>3-2</td>
<td>cska-ukrtatnafta kyiv</td>
</tr>
<tr>
<th>9</th>
<td>2001</td>
<td>mbc odesa</td>
<td>kyiv</td>
<td>3-2</td>
<td>azovmash</td>
</tr>
<tr>
<th>10</th>
<td>2002</td>
<td>mbc odesa</td>
<td>kyiv</td>
<td>3-2</td>
<td>azovmash</td>
</tr>
<tr>
<th>11</th>
<td>2003</td>
<td>azovmash</td>
<td>mbc odesa</td>
<td>4-0</td>
<td>kyiv</td>
</tr>
<tr>
<th>12</th>
<td>2004</td>
<td>azovmash</td>
<td>kyiv</td>
<td>4-2</td>
<td>mbc odesa</td>
</tr>
<tr>
<th>13</th>
<td>2005</td>
<td>kyiv</td>
<td>azovmash</td>
<td>3-0</td>
<td>khimik</td>
</tr>
<tr>
<th>14</th>
<td>2006</td>
<td>azovmash</td>
<td>kyiv</td>
<td>3-1</td>
<td>khimik</td>
</tr>
<tr>
<th>15</th>
<td>2007</td>
<td>azovmash</td>
<td>kyiv</td>
<td>3-2</td>
<td>khimik</td>
</tr>
<tr>
<th>16</th>
<td>2008</td>
<td>azovmash</td>
<td>kyiv</td>
<td>3-1</td>
<td>khimik</td>
</tr>
<tr>
<th>17</th>
<td>2009</td>
<td>azovmash</td>
<td>donetsk</td>
<td>3-0</td>
<td>khimik</td>
</tr>
<tr>
<th>18</th>
<td>2010</td>
<td>azovmash</td>
<td>budivelnyk</td>
<td>3-2</td>
<td>ferro-zntu</td>
</tr>
<tr>
<th>19</th>
<td>2011</td>
<td>budivelnyk</td>
<td>donetsk</td>
<td>4-3</td>
<td>hoverla</td>
</tr>
<tr>
<th>20</th>
<td>2012</td>
<td>donetsk</td>
<td>azovmash</td>
<td>4-0</td>
<td>ferro-zntu</td>
</tr>
<tr>
<th>21</th>
<td>2013</td>
<td>budivelnyk</td>
<td>azovmash</td>
<td>4-3</td>
<td>ferro-zntu</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "year" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( year ) where final score = '3-0' <table_name> : table | | year | winner | runner-up | final score | third |
|---:|-------:|:----------------|:-----------------|:--------------|:----------------------|
| 0 | 1992 | budivelnyk | nki mykolaiv | round-robin | spartak lugansk |
| 1 | 1993 | budivelnyk | ska kyiv | round-robin | nki mykolaiv |
| 2 | 1994 | budivelnyk | kyiv-basket | 3-0 | bipa-moda odesa |
| 3 | 1995 | budivelnyk | kyiv-basket | 3-0 | shakhtar-asko donetsk |
| 4 | 1996 | budivelnyk | shakhtar donetsk | round-robin | kyiv-basket |
| 5 | 1997 | budivelnyk | bipa-moda odesa | 3-2 | kyiv-basket |
| 6 | 1998 | bipa-moda odesa | budivelnyk | 3-0 | sc mykolaiv |
| 7 | 1999 | bipa-moda odesa | cska-riko kyiv | 3-2 | budivelnyk |
| 8 | 2000 | kyiv | mbc odesa | 3-2 | cska-ukrtatnafta kyiv |
| 9 | 2001 | mbc odesa | kyiv | 3-2 | azovmash |
| 10 | 2002 | mbc odesa | kyiv | 3-2 | azovmash |
| 11 | 2003 | azovmash | mbc odesa | 4-0 | kyiv |
| 12 | 2004 | azovmash | kyiv | 4-2 | mbc odesa |
| 13 | 2005 | kyiv | azovmash | 3-0 | khimik |
| 14 | 2006 | azovmash | kyiv | 3-1 | khimik |
| 15 | 2007 | azovmash | kyiv | 3-2 | khimik |
| 16 | 2008 | azovmash | kyiv | 3-1 | khimik |
| 17 | 2009 | azovmash | donetsk | 3-0 | khimik |
| 18 | 2010 | azovmash | budivelnyk | 3-2 | ferro-zntu |
| 19 | 2011 | budivelnyk | donetsk | 4-3 | hoverla |
| 20 | 2012 | donetsk | azovmash | 4-0 | ferro-zntu |
| 21 | 2013 | budivelnyk | azovmash | 4-3 | ferro-zntu | | | | count ( "year" ) |
|---:|-------------------:|
| 0 | 5 | | [
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select count ( nation ) where nation = 'north korea (prk)' col : rank | nation | gold | silver | bronze | total row 1 : 1 | china (chn) | 127 | 63 | 33 | 223 row 2 : 2 | japan (jpn) | 46 | 56 | 77 | 179 row 3 : 3 | south korea (kor) | 32 | 48 | 65 | 145 row 4 : 4 | chinese taipei (tpe) | 12 | 34 | 26 | 72 row 5 : 5 | macau (mac) | 11 | 16 | 17 | 44 row 6 : 6 | north korea (prk) | 6 | 10 | 20 | 36 row 7 : 7 | hong kong (hkg) | 2 | 2 | 9 | 13 row 8 : 8 | mongolia (mgl) | 1 | 1 | 6 | 8 row 9 : 9 | guam (gum) | 0 | 0 | 1 | 1 row 10 : total | total | 237 | 230 | 254 | 721 | col : count ( "nation" ) row 1 : 1 | select count ( nation ) where nation = 'north korea (prk)' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & china (chn) & 127 & 63 & 33 & 223 \\
1 & 2 & japan (jpn) & 46 & 56 & 77 & 179 \\
2 & 3 & south korea (kor) & 32 & 48 & 65 & 145 \\
3 & 4 & chinese taipei (tpe) & 12 & 34 & 26 & 72 \\
4 & 5 & macau (mac) & 11 & 16 & 17 & 44 \\
5 & 6 & north korea (prk) & 6 & 10 & 20 & 36 \\
6 & 7 & hong kong (hkg) & 2 & 2 & 9 & 13 \\
7 & 8 & mongolia (mgl) & 1 & 1 & 6 & 8 \\
8 & 9 & guam (gum) & 0 & 0 & 1 & 1 \\
9 & total & total & 237 & 230 & 254 & 721 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "nation" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( nation ) where nation = 'north korea (prk)' <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>127</td>
<td>63</td>
<td>33</td>
<td>223</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>japan (jpn)</td>
<td>46</td>
<td>56</td>
<td>77</td>
<td>179</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>south korea (kor)</td>
<td>32</td>
<td>48</td>
<td>65</td>
<td>145</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>chinese taipei (tpe)</td>
<td>12</td>
<td>34</td>
<td>26</td>
<td>72</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>macau (mac)</td>
<td>11</td>
<td>16</td>
<td>17</td>
<td>44</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>north korea (prk)</td>
<td>6</td>
<td>10</td>
<td>20</td>
<td>36</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>hong kong (hkg)</td>
<td>2</td>
<td>2</td>
<td>9</td>
<td>13</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>mongolia (mgl)</td>
<td>1</td>
<td>1</td>
<td>6</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>guam (gum)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>total</td>
<td>total</td>
<td>237</td>
<td>230</td>
<td>254</td>
<td>721</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>1</td>
</tr>
</tbody>
</table> | select count ( nation ) where nation = 'north korea (prk)' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | china (chn) | 127 | 63 | 33 | 223 |
| 1 | 2 | japan (jpn) | 46 | 56 | 77 | 179 |
| 2 | 3 | south korea (kor) | 32 | 48 | 65 | 145 |
| 3 | 4 | chinese taipei (tpe) | 12 | 34 | 26 | 72 |
| 4 | 5 | macau (mac) | 11 | 16 | 17 | 44 |
| 5 | 6 | north korea (prk) | 6 | 10 | 20 | 36 |
| 6 | 7 | hong kong (hkg) | 2 | 2 | 9 | 13 |
| 7 | 8 | mongolia (mgl) | 1 | 1 | 6 | 8 |
| 8 | 9 | guam (gum) | 0 | 0 | 1 | 1 |
| 9 | total | total | 237 | 230 | 254 | 721 | | | | count ( "nation" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select count ( role ) where notes = 'none' col : year | title | role | notes row 1 : 1990 | the kid who loved christmas | ernie | television movie row 2 : 1990 | brewster place | matthew thomas | 5 episodes row 3 : 1990 | the long walk home | franklin cotter | none row 4 : 1992 | the jacksons: an american dream | michael jackson (aged 9-14) | miniseries row 5 : 1993 to 1994 | thea | jerome turrell | 19 episodes row 6 : 1994 | summertime switch | fast freddie egan | television movie row 7 : 1994 | the lion king | young simba | cub singing voice row 8 : 1996 | sister, sister | darnell nicky | 2 episodes row 9 : 1997 to 1999 | smart guy | marcus henderson | 51 episodes row 10 : 2000 | freedom song | isaac hawkins | television movie row 11 : 2002 | drumline | ernest | none row 12 : 2004 | the ladykillers | weemack funthes | none row 13 : 2006 | atl | teddy | none row 14 : 2008 | jada | jamal | none row 15 : 2008 | love for sale | vince | none row 16 : 2008 | diary of a champion | tj lawson | none row 17 : 2010 | lottery ticket | ray ray | none row 18 : 2011 | the lebrons | condor | 9 episodes row 19 : 2011 | he's mine not yours | kent | television movie row 20 : 2011 | timothy hodge show | jason weaver | none row 21 : 2012 | dysfunctional friends | gary | none row 22 : 2012 | note to self | jay lewis | none row 23 : 2012 | wal-bob's | keith harrington | none | col : count ( "role" ) row 1 : 12 | select count ( role ) where notes = 'none' <table_name> : table \begin{tabular}{lllll}
\toprule
& year & title & role & notes \\
\midrule
0 & 1990 & the kid who loved christmas & ernie & television movie \\
1 & 1990 & brewster place & matthew thomas & 5 episodes \\
2 & 1990 & the long walk home & franklin cotter & none \\
3 & 1992 & the jacksons: an american dream & michael jackson (aged 9-14) & miniseries \\
4 & 1993 to 1994 & thea & jerome turrell & 19 episodes \\
5 & 1994 & summertime switch & fast freddie egan & television movie \\
6 & 1994 & the lion king & young simba & cub singing voice \\
7 & 1996 & sister, sister & darnell nicky & 2 episodes \\
8 & 1997 to 1999 & smart guy & marcus henderson & 51 episodes \\
9 & 2000 & freedom song & isaac hawkins & television movie \\
10 & 2002 & drumline & ernest & none \\
11 & 2004 & the ladykillers & weemack funthes & none \\
12 & 2006 & atl & teddy & none \\
13 & 2008 & jada & jamal & none \\
14 & 2008 & love for sale & vince & none \\
15 & 2008 & diary of a champion & tj lawson & none \\
16 & 2010 & lottery ticket & ray ray & none \\
17 & 2011 & the lebrons & condor & 9 episodes \\
18 & 2011 & he's mine not yours & kent & television movie \\
19 & 2011 & timothy hodge show & jason weaver & none \\
20 & 2012 & dysfunctional friends & gary & none \\
21 & 2012 & note to self & jay lewis & none \\
22 & 2012 & wal-bob's & keith harrington & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "role" ) \\
\midrule
0 & 12 \\
\bottomrule
\end{tabular}
| select count ( role ) where notes = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>role</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1990</td>
<td>the kid who loved christmas</td>
<td>ernie</td>
<td>television movie</td>
</tr>
<tr>
<th>1</th>
<td>1990</td>
<td>brewster place</td>
<td>matthew thomas</td>
<td>5 episodes</td>
</tr>
<tr>
<th>2</th>
<td>1990</td>
<td>the long walk home</td>
<td>franklin cotter</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1992</td>
<td>the jacksons: an american dream</td>
<td>michael jackson (aged 9-14)</td>
<td>miniseries</td>
</tr>
<tr>
<th>4</th>
<td>1993 to 1994</td>
<td>thea</td>
<td>jerome turrell</td>
<td>19 episodes</td>
</tr>
<tr>
<th>5</th>
<td>1994</td>
<td>summertime switch</td>
<td>fast freddie egan</td>
<td>television movie</td>
</tr>
<tr>
<th>6</th>
<td>1994</td>
<td>the lion king</td>
<td>young simba</td>
<td>cub singing voice</td>
</tr>
<tr>
<th>7</th>
<td>1996</td>
<td>sister, sister</td>
<td>darnell nicky</td>
<td>2 episodes</td>
</tr>
<tr>
<th>8</th>
<td>1997 to 1999</td>
<td>smart guy</td>
<td>marcus henderson</td>
<td>51 episodes</td>
</tr>
<tr>
<th>9</th>
<td>2000</td>
<td>freedom song</td>
<td>isaac hawkins</td>
<td>television movie</td>
</tr>
<tr>
<th>10</th>
<td>2002</td>
<td>drumline</td>
<td>ernest</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>2004</td>
<td>the ladykillers</td>
<td>weemack funthes</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>2006</td>
<td>atl</td>
<td>teddy</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>2008</td>
<td>jada</td>
<td>jamal</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>2008</td>
<td>love for sale</td>
<td>vince</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>2008</td>
<td>diary of a champion</td>
<td>tj lawson</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>2010</td>
<td>lottery ticket</td>
<td>ray ray</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>2011</td>
<td>the lebrons</td>
<td>condor</td>
<td>9 episodes</td>
</tr>
<tr>
<th>18</th>
<td>2011</td>
<td>he's mine not yours</td>
<td>kent</td>
<td>television movie</td>
</tr>
<tr>
<th>19</th>
<td>2011</td>
<td>timothy hodge show</td>
<td>jason weaver</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>2012</td>
<td>dysfunctional friends</td>
<td>gary</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>2012</td>
<td>note to self</td>
<td>jay lewis</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>2012</td>
<td>wal-bob's</td>
<td>keith harrington</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "role" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>12</td>
</tr>
</tbody>
</table> | select count ( role ) where notes = 'none' <table_name> : table | | year | title | role | notes |
|---:|:-------------|:--------------------------------|:----------------------------|:------------------|
| 0 | 1990 | the kid who loved christmas | ernie | television movie |
| 1 | 1990 | brewster place | matthew thomas | 5 episodes |
| 2 | 1990 | the long walk home | franklin cotter | none |
| 3 | 1992 | the jacksons: an american dream | michael jackson (aged 9-14) | miniseries |
| 4 | 1993 to 1994 | thea | jerome turrell | 19 episodes |
| 5 | 1994 | summertime switch | fast freddie egan | television movie |
| 6 | 1994 | the lion king | young simba | cub singing voice |
| 7 | 1996 | sister, sister | darnell nicky | 2 episodes |
| 8 | 1997 to 1999 | smart guy | marcus henderson | 51 episodes |
| 9 | 2000 | freedom song | isaac hawkins | television movie |
| 10 | 2002 | drumline | ernest | none |
| 11 | 2004 | the ladykillers | weemack funthes | none |
| 12 | 2006 | atl | teddy | none |
| 13 | 2008 | jada | jamal | none |
| 14 | 2008 | love for sale | vince | none |
| 15 | 2008 | diary of a champion | tj lawson | none |
| 16 | 2010 | lottery ticket | ray ray | none |
| 17 | 2011 | the lebrons | condor | 9 episodes |
| 18 | 2011 | he's mine not yours | kent | television movie |
| 19 | 2011 | timothy hodge show | jason weaver | none |
| 20 | 2012 | dysfunctional friends | gary | none |
| 21 | 2012 | note to self | jay lewis | none |
| 22 | 2012 | wal-bob's | keith harrington | none | | | | count ( "role" ) |
|---:|-------------------:|
| 0 | 12 | | [
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select count ( team ) where team = 'sf' col : year | team | games | combined tackles | tackles | assisted tackles | sacks | forced fumbles | fumble recoveries | fumble return yards | interceptions | interception return yards | yards per interception return | longest interception return | interceptions returned for touchdown | passes defended row 1 : 2001 | cin | 15 | 53 | 41 | 12 | 8.5 | 0 | 0 | 0 | 2 | 28 | 14 | 21 | 0 | 5 row 2 : 2002 | cin | 16 | 59 | 47 | 12 | 6.5 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 row 3 : 2003 | cin | 16 | 60 | 41 | 19 | 5.0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 row 4 : 2004 | cin | 16 | 70 | 41 | 29 | 8.0 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 2 row 5 : 2005 | cin | 16 | 65 | 45 | 20 | 6.0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 row 6 : 2006 | cin | 16 | 81 | 50 | 31 | 7.5 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 3 row 7 : 2007 | cin | 16 | 78 | 49 | 29 | 2.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 row 8 : 2008 | sf | 16 | 73 | 50 | 23 | 7.0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 row 9 : 2009 | sf | 16 | 55 | 40 | 15 | 6.0 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 row 10 : 2010 | sf | 16 | 70 | 57 | 13 | 8.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 row 11 : 2011 | sf | 16 | 58 | 45 | 13 | 7.5 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 row 12 : 2012 | sf | 14 | 66 | 47 | 19 | 3.0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 row 13 : 2013 | sf | 16 | 49 | 32 | 17 | 6.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 14 : career | none | 205 | 837 | 585 | 252 | 82.0 | 15 | 9 | 0 | 3 | 28 | 9 | 21 | 0 | 29 | col : count ( "team" ) row 1 : 6 | select count ( team ) where team = 'sf' <table_name> : table \begin{tabular}{lllllllllllllllll}
\toprule
& year & team & games & combined tackles & tackles & assisted tackles & sacks & forced fumbles & fumble recoveries & fumble return yards & interceptions & interception return yards & yards per interception return & longest interception return & interceptions returned for touchdown & passes defended \\
\midrule
0 & 2001 & cin & 15 & 53 & 41 & 12 & 8.5 & 0 & 0 & 0 & 2 & 28 & 14 & 21 & 0 & 5 \\
1 & 2002 & cin & 16 & 59 & 47 & 12 & 6.5 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 \\
2 & 2003 & cin & 16 & 60 & 41 & 19 & 5.0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 3 \\
3 & 2004 & cin & 16 & 70 & 41 & 29 & 8.0 & 2 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 2 \\
4 & 2005 & cin & 16 & 65 & 45 & 20 & 6.0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 2 \\
5 & 2006 & cin & 16 & 81 & 50 & 31 & 7.5 & 1 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 3 \\
6 & 2007 & cin & 16 & 78 & 49 & 29 & 2.0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 3 \\
7 & 2008 & sf & 16 & 73 & 50 & 23 & 7.0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 3 \\
8 & 2009 & sf & 16 & 55 & 40 & 15 & 6.0 & 2 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
9 & 2010 & sf & 16 & 70 & 57 & 13 & 8.5 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
10 & 2011 & sf & 16 & 58 & 45 & 13 & 7.5 & 3 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 2 \\
11 & 2012 & sf & 14 & 66 & 47 & 19 & 3.0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 2 \\
12 & 2013 & sf & 16 & 49 & 32 & 17 & 6.5 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
13 & career & none & 205 & 837 & 585 & 252 & 82.0 & 15 & 9 & 0 & 3 & 28 & 9 & 21 & 0 & 29 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "team" ) \\
\midrule
0 & 6 \\
\bottomrule
\end{tabular}
| select count ( team ) where team = 'sf' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>team</th>
<th>games</th>
<th>combined tackles</th>
<th>tackles</th>
<th>assisted tackles</th>
<th>sacks</th>
<th>forced fumbles</th>
<th>fumble recoveries</th>
<th>fumble return yards</th>
<th>interceptions</th>
<th>interception return yards</th>
<th>yards per interception return</th>
<th>longest interception return</th>
<th>interceptions returned for touchdown</th>
<th>passes defended</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2001</td>
<td>cin</td>
<td>15</td>
<td>53</td>
<td>41</td>
<td>12</td>
<td>8.5</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>28</td>
<td>14</td>
<td>21</td>
<td>0</td>
<td>5</td>
</tr>
<tr>
<th>1</th>
<td>2002</td>
<td>cin</td>
<td>16</td>
<td>59</td>
<td>47</td>
<td>12</td>
<td>6.5</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>2</th>
<td>2003</td>
<td>cin</td>
<td>16</td>
<td>60</td>
<td>41</td>
<td>19</td>
<td>5.0</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>2004</td>
<td>cin</td>
<td>16</td>
<td>70</td>
<td>41</td>
<td>29</td>
<td>8.0</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>2005</td>
<td>cin</td>
<td>16</td>
<td>65</td>
<td>45</td>
<td>20</td>
<td>6.0</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>2006</td>
<td>cin</td>
<td>16</td>
<td>81</td>
<td>50</td>
<td>31</td>
<td>7.5</td>
<td>1</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>2007</td>
<td>cin</td>
<td>16</td>
<td>78</td>
<td>49</td>
<td>29</td>
<td>2.0</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>3</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>sf</td>
<td>16</td>
<td>73</td>
<td>50</td>
<td>23</td>
<td>7.0</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>2009</td>
<td>sf</td>
<td>16</td>
<td>55</td>
<td>40</td>
<td>15</td>
<td>6.0</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>2010</td>
<td>sf</td>
<td>16</td>
<td>70</td>
<td>57</td>
<td>13</td>
<td>8.5</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>2011</td>
<td>sf</td>
<td>16</td>
<td>58</td>
<td>45</td>
<td>13</td>
<td>7.5</td>
<td>3</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>2012</td>
<td>sf</td>
<td>14</td>
<td>66</td>
<td>47</td>
<td>19</td>
<td>3.0</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>12</th>
<td>2013</td>
<td>sf</td>
<td>16</td>
<td>49</td>
<td>32</td>
<td>17</td>
<td>6.5</td>
<td>1</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>
</tr>
<tr>
<th>13</th>
<td>career</td>
<td>none</td>
<td>205</td>
<td>837</td>
<td>585</td>
<td>252</td>
<td>82.0</td>
<td>15</td>
<td>9</td>
<td>0</td>
<td>3</td>
<td>28</td>
<td>9</td>
<td>21</td>
<td>0</td>
<td>29</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>6</td>
</tr>
</tbody>
</table> | select count ( team ) where team = 'sf' <table_name> : table | | year | team | games | combined tackles | tackles | assisted tackles | sacks | forced fumbles | fumble recoveries | fumble return yards | interceptions | interception return yards | yards per interception return | longest interception return | interceptions returned for touchdown | passes defended |
|---:|:-------|:-------|--------:|-------------------:|----------:|-------------------:|--------:|-----------------:|--------------------:|----------------------:|----------------:|----------------------------:|--------------------------------:|------------------------------:|---------------------------------------:|------------------:|
| 0 | 2001 | cin | 15 | 53 | 41 | 12 | 8.5 | 0 | 0 | 0 | 2 | 28 | 14 | 21 | 0 | 5 |
| 1 | 2002 | cin | 16 | 59 | 47 | 12 | 6.5 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| 2 | 2003 | cin | 16 | 60 | 41 | 19 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
| 3 | 2004 | cin | 16 | 70 | 41 | 29 | 8 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| 4 | 2005 | cin | 16 | 65 | 45 | 20 | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| 5 | 2006 | cin | 16 | 81 | 50 | 31 | 7.5 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
| 6 | 2007 | cin | 16 | 78 | 49 | 29 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
| 7 | 2008 | sf | 16 | 73 | 50 | 23 | 7 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
| 8 | 2009 | sf | 16 | 55 | 40 | 15 | 6 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 9 | 2010 | sf | 16 | 70 | 57 | 13 | 8.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 10 | 2011 | sf | 16 | 58 | 45 | 13 | 7.5 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| 11 | 2012 | sf | 14 | 66 | 47 | 19 | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| 12 | 2013 | sf | 16 | 49 | 32 | 17 | 6.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 13 | career | none | 205 | 837 | 585 | 252 | 82 | 15 | 9 | 0 | 3 | 28 | 9 | 21 | 0 | 29 | | | | count ( "team" ) |
|---:|-------------------:|
| 0 | 6 | | [
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select result where result = 'w 45-14' col : date | opponent | site | result row 1 : september 5 | alcorn state | independence stadium • shreveport. la | l 24-28 row 2 : september 12 | vs. central state | yankee stadium • new york, ny | l 21-37 row 3 : september 26 | bethune-cookman | eddie robinson stadium • grambling, la | w 21-14 row 4 : october 3 | vs. prairie view a&m | cotton bowl • dallas, tx | w 28-7 row 5 : october 10 | at tennessee state | dudley field • nashville, tn | w 51-9 row 6 : october 17 | mississippi valley state | eddie robinson stadium • grambling, la | w 45-14 row 7 : october 24 | at jackson state | mississippi veterans memorial stadium • jackson, ms | l 17-31 row 8 : october 31 | texas southern | eddie robinson stadium • grambling, la | w 30-9 row 9 : november 7 | at alabama state | cramton bowl • montgomery, al | l 7-17 row 10 : november 14 | south carolina state | eddie robinson stadium • grambling, la | l 13-15 row 11 : november 28 | vs. southern | louisiana superdome • new orleans, la (xiv bayou classic) | l 21-27 | col : result row 1 : w 45-14 | select result where result = 'w 45-14' <table_name> : table \begin{tabular}{lllll}
\toprule
& date & opponent & site & result \\
\midrule
0 & september 5 & alcorn state & independence stadium • shreveport. la & l 24-28 \\
1 & september 12 & vs. central state & yankee stadium • new york, ny & l 21-37 \\
2 & september 26 & bethune-cookman & eddie robinson stadium • grambling, la & w 21-14 \\
3 & october 3 & vs. prairie view a&m & cotton bowl • dallas, tx & w 28-7 \\
4 & october 10 & at tennessee state & dudley field • nashville, tn & w 51-9 \\
5 & october 17 & mississippi valley state & eddie robinson stadium • grambling, la & w 45-14 \\
6 & october 24 & at jackson state & mississippi veterans memorial stadium • jackson, ms & l 17-31 \\
7 & october 31 & texas southern & eddie robinson stadium • grambling, la & w 30-9 \\
8 & november 7 & at alabama state & cramton bowl • montgomery, al & l 7-17 \\
9 & november 14 & south carolina state & eddie robinson stadium • grambling, la & l 13-15 \\
10 & november 28 & vs. southern & louisiana superdome • new orleans, la (xiv bayou classic) & l 21-27 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& result \\
\midrule
0 & w 45-14 \\
\bottomrule
\end{tabular}
| select result where result = 'w 45-14' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>opponent</th>
<th>site</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>september 5</td>
<td>alcorn state</td>
<td>independence stadium • shreveport. la</td>
<td>l 24-28</td>
</tr>
<tr>
<th>1</th>
<td>september 12</td>
<td>vs. central state</td>
<td>yankee stadium • new york, ny</td>
<td>l 21-37</td>
</tr>
<tr>
<th>2</th>
<td>september 26</td>
<td>bethune-cookman</td>
<td>eddie robinson stadium • grambling, la</td>
<td>w 21-14</td>
</tr>
<tr>
<th>3</th>
<td>october 3</td>
<td>vs. prairie view a&m</td>
<td>cotton bowl • dallas, tx</td>
<td>w 28-7</td>
</tr>
<tr>
<th>4</th>
<td>october 10</td>
<td>at tennessee state</td>
<td>dudley field • nashville, tn</td>
<td>w 51-9</td>
</tr>
<tr>
<th>5</th>
<td>october 17</td>
<td>mississippi valley state</td>
<td>eddie robinson stadium • grambling, la</td>
<td>w 45-14</td>
</tr>
<tr>
<th>6</th>
<td>october 24</td>
<td>at jackson state</td>
<td>mississippi veterans memorial stadium • jackson, ms</td>
<td>l 17-31</td>
</tr>
<tr>
<th>7</th>
<td>october 31</td>
<td>texas southern</td>
<td>eddie robinson stadium • grambling, la</td>
<td>w 30-9</td>
</tr>
<tr>
<th>8</th>
<td>november 7</td>
<td>at alabama state</td>
<td>cramton bowl • montgomery, al</td>
<td>l 7-17</td>
</tr>
<tr>
<th>9</th>
<td>november 14</td>
<td>south carolina state</td>
<td>eddie robinson stadium • grambling, la</td>
<td>l 13-15</td>
</tr>
<tr>
<th>10</th>
<td>november 28</td>
<td>vs. southern</td>
<td>louisiana superdome • new orleans, la (xiv bayou classic)</td>
<td>l 21-27</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>w 45-14</td>
</tr>
</tbody>
</table> | select result where result = 'w 45-14' <table_name> : table | | date | opponent | site | result |
|---:|:-------------|:-------------------------|:----------------------------------------------------------|:---------|
| 0 | september 5 | alcorn state | independence stadium • shreveport. la | l 24-28 |
| 1 | september 12 | vs. central state | yankee stadium • new york, ny | l 21-37 |
| 2 | september 26 | bethune-cookman | eddie robinson stadium • grambling, la | w 21-14 |
| 3 | october 3 | vs. prairie view a&m | cotton bowl • dallas, tx | w 28-7 |
| 4 | october 10 | at tennessee state | dudley field • nashville, tn | w 51-9 |
| 5 | october 17 | mississippi valley state | eddie robinson stadium • grambling, la | w 45-14 |
| 6 | october 24 | at jackson state | mississippi veterans memorial stadium • jackson, ms | l 17-31 |
| 7 | october 31 | texas southern | eddie robinson stadium • grambling, la | w 30-9 |
| 8 | november 7 | at alabama state | cramton bowl • montgomery, al | l 7-17 |
| 9 | november 14 | south carolina state | eddie robinson stadium • grambling, la | l 13-15 |
| 10 | november 28 | vs. southern | louisiana superdome • new orleans, la (xiv bayou classic) | l 21-27 | | | | result |
|---:|:---------|
| 0 | w 45-14 | | [
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select count ( pos ) where time/retired = '3.985' col : pos | rider | manufactuer | time/retired | points row 1 : 1 | doriano romboni | honda | 33:53.776 | 25 row 2 : 2 | loris capirossi | honda | 0.09 | 20 row 3 : 3 | helmut bradl | honda | 0.384 | 16 row 4 : 4 | max biaggi | honda | 2.346 | 13 row 5 : 5 | loris reggiani | aprilia | 2.411 | 11 row 6 : 6 | tetsuya harada | yamaha | 2.537 | 10 row 7 : 7 | pierfrancesco chili | yamaha | 3.845 | 9 row 8 : 8 | jean-philippe ruggia | aprilia | 3.985 | 8 row 9 : 9 | carlos cardus | honda | 4.893 | 7 row 10 : 10 | luis d'antin | honda | 25.044 | 6 row 11 : 11 | alberto puig | honda | 25.136 | 5 row 12 : 12 | john kocinski | suzuki | 25.463 | 4 row 13 : 13 | jochen schmid | yamaha | 47.065 | 3 row 14 : 14 | jean-michel bayle | aprilia | +1:15.546 | 2 row 15 : 15 | juan borja | honda | +1:15.769 | 1 row 16 : 16 | frederic protat | aprilia | +1:15.858 | none row 17 : 17 | adi stadler | honda | +1:16.349 | none row 18 : 18 | bernd kassner | aprilia | +1:16:464 | none row 19 : 19 | paolo casoli | gilera | +1:26.061 | none row 20 : 20 | gabriele debbia | honda | +1:40.049 | none row 21 : 21 | adrian bosshard | honda | +1:47.492 | none row 22 : 22 | massimo pennacchioli | honda | +1:59.498 | none row 23 : 23 | bernard haenggeli | aprilia | +2:41.806 | none row 24 : 24 | alessandro gramigni | gilera | +1 lap | none row 25 : ret | andreas preining | aprilia | retirement | none row 26 : ret | volker bahr | honda | retirement | none row 27 : ret | jurgen van den goorbergh | aprilia | retirement | none row 28 : ret | luis maurel | aprilia | retirement | none row 29 : ret | patrick van den goorbergh | aprilia | retirement | none row 30 : ret | eskil suter | aprilia | retirement | none row 31 : ret | wilco zeelenberg | aprilia | retirement | none row 32 : ret | jean-pierre jeandat | aprilia | retirement | none row 33 : dns | nobuatsu aoki | honda | did not start | none | col : count ( "pos" ) row 1 : 1 | select count ( pos ) where time/retired = '3.985' <table_name> : table \begin{tabular}{llllll}
\toprule
& pos & rider & manufactuer & time/retired & points \\
\midrule
0 & 1 & doriano romboni & honda & 33:53.776 & 25 \\
1 & 2 & loris capirossi & honda & 0.09 & 20 \\
2 & 3 & helmut bradl & honda & 0.384 & 16 \\
3 & 4 & max biaggi & honda & 2.346 & 13 \\
4 & 5 & loris reggiani & aprilia & 2.411 & 11 \\
5 & 6 & tetsuya harada & yamaha & 2.537 & 10 \\
6 & 7 & pierfrancesco chili & yamaha & 3.845 & 9 \\
7 & 8 & jean-philippe ruggia & aprilia & 3.985 & 8 \\
8 & 9 & carlos cardus & honda & 4.893 & 7 \\
9 & 10 & luis d'antin & honda & 25.044 & 6 \\
10 & 11 & alberto puig & honda & 25.136 & 5 \\
11 & 12 & john kocinski & suzuki & 25.463 & 4 \\
12 & 13 & jochen schmid & yamaha & 47.065 & 3 \\
13 & 14 & jean-michel bayle & aprilia & +1:15.546 & 2 \\
14 & 15 & juan borja & honda & +1:15.769 & 1 \\
15 & 16 & frederic protat & aprilia & +1:15.858 & none \\
16 & 17 & adi stadler & honda & +1:16.349 & none \\
17 & 18 & bernd kassner & aprilia & +1:16:464 & none \\
18 & 19 & paolo casoli & gilera & +1:26.061 & none \\
19 & 20 & gabriele debbia & honda & +1:40.049 & none \\
20 & 21 & adrian bosshard & honda & +1:47.492 & none \\
21 & 22 & massimo pennacchioli & honda & +1:59.498 & none \\
22 & 23 & bernard haenggeli & aprilia & +2:41.806 & none \\
23 & 24 & alessandro gramigni & gilera & +1 lap & none \\
24 & ret & andreas preining & aprilia & retirement & none \\
25 & ret & volker bahr & honda & retirement & none \\
26 & ret & jurgen van den goorbergh & aprilia & retirement & none \\
27 & ret & luis maurel & aprilia & retirement & none \\
28 & ret & patrick van den goorbergh & aprilia & retirement & none \\
29 & ret & eskil suter & aprilia & retirement & none \\
30 & ret & wilco zeelenberg & aprilia & retirement & none \\
31 & ret & jean-pierre jeandat & aprilia & retirement & none \\
32 & dns & nobuatsu aoki & honda & did not start & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "pos" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( pos ) where time/retired = '3.985' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>rider</th>
<th>manufactuer</th>
<th>time/retired</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>doriano romboni</td>
<td>honda</td>
<td>33:53.776</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>loris capirossi</td>
<td>honda</td>
<td>0.09</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>helmut bradl</td>
<td>honda</td>
<td>0.384</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>max biaggi</td>
<td>honda</td>
<td>2.346</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>loris reggiani</td>
<td>aprilia</td>
<td>2.411</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>tetsuya harada</td>
<td>yamaha</td>
<td>2.537</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>pierfrancesco chili</td>
<td>yamaha</td>
<td>3.845</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>jean-philippe ruggia</td>
<td>aprilia</td>
<td>3.985</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>carlos cardus</td>
<td>honda</td>
<td>4.893</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>luis d'antin</td>
<td>honda</td>
<td>25.044</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>alberto puig</td>
<td>honda</td>
<td>25.136</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>john kocinski</td>
<td>suzuki</td>
<td>25.463</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>jochen schmid</td>
<td>yamaha</td>
<td>47.065</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>jean-michel bayle</td>
<td>aprilia</td>
<td>+1:15.546</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>juan borja</td>
<td>honda</td>
<td>+1:15.769</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>frederic protat</td>
<td>aprilia</td>
<td>+1:15.858</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>adi stadler</td>
<td>honda</td>
<td>+1:16.349</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>bernd kassner</td>
<td>aprilia</td>
<td>+1:16:464</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>paolo casoli</td>
<td>gilera</td>
<td>+1:26.061</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>gabriele debbia</td>
<td>honda</td>
<td>+1:40.049</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>adrian bosshard</td>
<td>honda</td>
<td>+1:47.492</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>massimo pennacchioli</td>
<td>honda</td>
<td>+1:59.498</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>bernard haenggeli</td>
<td>aprilia</td>
<td>+2:41.806</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>alessandro gramigni</td>
<td>gilera</td>
<td>+1 lap</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>andreas preining</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>volker bahr</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>ret</td>
<td>jurgen van den goorbergh</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>ret</td>
<td>luis maurel</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>ret</td>
<td>patrick van den goorbergh</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>ret</td>
<td>eskil suter</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>ret</td>
<td>wilco zeelenberg</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>ret</td>
<td>jean-pierre jeandat</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>dns</td>
<td>nobuatsu aoki</td>
<td>honda</td>
<td>did not start</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "pos" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( pos ) where time/retired = '3.985' <table_name> : table | | pos | rider | manufactuer | time/retired | points |
|---:|:------|:--------------------------|:--------------|:---------------|:---------|
| 0 | 1 | doriano romboni | honda | 33:53.776 | 25 |
| 1 | 2 | loris capirossi | honda | 0.09 | 20 |
| 2 | 3 | helmut bradl | honda | 0.384 | 16 |
| 3 | 4 | max biaggi | honda | 2.346 | 13 |
| 4 | 5 | loris reggiani | aprilia | 2.411 | 11 |
| 5 | 6 | tetsuya harada | yamaha | 2.537 | 10 |
| 6 | 7 | pierfrancesco chili | yamaha | 3.845 | 9 |
| 7 | 8 | jean-philippe ruggia | aprilia | 3.985 | 8 |
| 8 | 9 | carlos cardus | honda | 4.893 | 7 |
| 9 | 10 | luis d'antin | honda | 25.044 | 6 |
| 10 | 11 | alberto puig | honda | 25.136 | 5 |
| 11 | 12 | john kocinski | suzuki | 25.463 | 4 |
| 12 | 13 | jochen schmid | yamaha | 47.065 | 3 |
| 13 | 14 | jean-michel bayle | aprilia | +1:15.546 | 2 |
| 14 | 15 | juan borja | honda | +1:15.769 | 1 |
| 15 | 16 | frederic protat | aprilia | +1:15.858 | none |
| 16 | 17 | adi stadler | honda | +1:16.349 | none |
| 17 | 18 | bernd kassner | aprilia | +1:16:464 | none |
| 18 | 19 | paolo casoli | gilera | +1:26.061 | none |
| 19 | 20 | gabriele debbia | honda | +1:40.049 | none |
| 20 | 21 | adrian bosshard | honda | +1:47.492 | none |
| 21 | 22 | massimo pennacchioli | honda | +1:59.498 | none |
| 22 | 23 | bernard haenggeli | aprilia | +2:41.806 | none |
| 23 | 24 | alessandro gramigni | gilera | +1 lap | none |
| 24 | ret | andreas preining | aprilia | retirement | none |
| 25 | ret | volker bahr | honda | retirement | none |
| 26 | ret | jurgen van den goorbergh | aprilia | retirement | none |
| 27 | ret | luis maurel | aprilia | retirement | none |
| 28 | ret | patrick van den goorbergh | aprilia | retirement | none |
| 29 | ret | eskil suter | aprilia | retirement | none |
| 30 | ret | wilco zeelenberg | aprilia | retirement | none |
| 31 | ret | jean-pierre jeandat | aprilia | retirement | none |
| 32 | dns | nobuatsu aoki | honda | did not start | none | | | | count ( "pos" ) |
|---:|------------------:|
| 0 | 1 | | [
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select champion where year > 1061 col : year | host | champion | second place | third place | fourth place row 1 : 2005 | ninh binh | tianjin bridgestone | chung shan | korea highway corporation | rahat cska row 2 : 2006 | manila | tianjin bridgestone | chung shan | sang som | rahat cska row 3 : 2008 | vinh phuc | tianjin bridgestone | sang som | toray arrows | sobaeksu row 4 : 2009 | nakhon pathom | federbrau | tianjin bridgestone | toray arrows | zhetysu almaty row 5 : 2010 | gresik | federbrau | zhetysu almaty | jt marvelous | tianjin bridgestone row 6 : 2011 | vinh phuc | chang | tianjin bridgestone | zhetysu almaty | thong tin lien viet bank row 7 : 2012 | nakhon ratchasima | tianjin bridgestone | toray arrows | chang | zhetysu almaty | col : champion row 1 : tianjin bridgestone row 2 : tianjin bridgestone row 3 : tianjin bridgestone row 4 : federbrau row 5 : federbrau row 6 : chang row 7 : tianjin bridgestone | select champion where year > 1061 <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & host & champion & second place & third place & fourth place \\
\midrule
0 & 2005 & ninh binh & tianjin bridgestone & chung shan & korea highway corporation & rahat cska \\
1 & 2006 & manila & tianjin bridgestone & chung shan & sang som & rahat cska \\
2 & 2008 & vinh phuc & tianjin bridgestone & sang som & toray arrows & sobaeksu \\
3 & 2009 & nakhon pathom & federbrau & tianjin bridgestone & toray arrows & zhetysu almaty \\
4 & 2010 & gresik & federbrau & zhetysu almaty & jt marvelous & tianjin bridgestone \\
5 & 2011 & vinh phuc & chang & tianjin bridgestone & zhetysu almaty & thong tin lien viet bank \\
6 & 2012 & nakhon ratchasima & tianjin bridgestone & toray arrows & chang & zhetysu almaty \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& champion \\
\midrule
0 & tianjin bridgestone \\
1 & tianjin bridgestone \\
2 & tianjin bridgestone \\
3 & federbrau \\
4 & federbrau \\
5 & chang \\
6 & tianjin bridgestone \\
\bottomrule
\end{tabular}
| select champion where year > 1061 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>host</th>
<th>champion</th>
<th>second place</th>
<th>third place</th>
<th>fourth place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2005</td>
<td>ninh binh</td>
<td>tianjin bridgestone</td>
<td>chung shan</td>
<td>korea highway corporation</td>
<td>rahat cska</td>
</tr>
<tr>
<th>1</th>
<td>2006</td>
<td>manila</td>
<td>tianjin bridgestone</td>
<td>chung shan</td>
<td>sang som</td>
<td>rahat cska</td>
</tr>
<tr>
<th>2</th>
<td>2008</td>
<td>vinh phuc</td>
<td>tianjin bridgestone</td>
<td>sang som</td>
<td>toray arrows</td>
<td>sobaeksu</td>
</tr>
<tr>
<th>3</th>
<td>2009</td>
<td>nakhon pathom</td>
<td>federbrau</td>
<td>tianjin bridgestone</td>
<td>toray arrows</td>
<td>zhetysu almaty</td>
</tr>
<tr>
<th>4</th>
<td>2010</td>
<td>gresik</td>
<td>federbrau</td>
<td>zhetysu almaty</td>
<td>jt marvelous</td>
<td>tianjin bridgestone</td>
</tr>
<tr>
<th>5</th>
<td>2011</td>
<td>vinh phuc</td>
<td>chang</td>
<td>tianjin bridgestone</td>
<td>zhetysu almaty</td>
<td>thong tin lien viet bank</td>
</tr>
<tr>
<th>6</th>
<td>2012</td>
<td>nakhon ratchasima</td>
<td>tianjin bridgestone</td>
<td>toray arrows</td>
<td>chang</td>
<td>zhetysu almaty</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>champion</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>tianjin bridgestone</td>
</tr>
<tr>
<th>1</th>
<td>tianjin bridgestone</td>
</tr>
<tr>
<th>2</th>
<td>tianjin bridgestone</td>
</tr>
<tr>
<th>3</th>
<td>federbrau</td>
</tr>
<tr>
<th>4</th>
<td>federbrau</td>
</tr>
<tr>
<th>5</th>
<td>chang</td>
</tr>
<tr>
<th>6</th>
<td>tianjin bridgestone</td>
</tr>
</tbody>
</table> | select champion where year > 1061 <table_name> : table | | year | host | champion | second place | third place | fourth place |
|---:|-------:|:------------------|:--------------------|:--------------------|:--------------------------|:-------------------------|
| 0 | 2005 | ninh binh | tianjin bridgestone | chung shan | korea highway corporation | rahat cska |
| 1 | 2006 | manila | tianjin bridgestone | chung shan | sang som | rahat cska |
| 2 | 2008 | vinh phuc | tianjin bridgestone | sang som | toray arrows | sobaeksu |
| 3 | 2009 | nakhon pathom | federbrau | tianjin bridgestone | toray arrows | zhetysu almaty |
| 4 | 2010 | gresik | federbrau | zhetysu almaty | jt marvelous | tianjin bridgestone |
| 5 | 2011 | vinh phuc | chang | tianjin bridgestone | zhetysu almaty | thong tin lien viet bank |
| 6 | 2012 | nakhon ratchasima | tianjin bridgestone | toray arrows | chang | zhetysu almaty | | | | champion |
|---:|:--------------------|
| 0 | tianjin bridgestone |
| 1 | tianjin bridgestone |
| 2 | tianjin bridgestone |
| 3 | federbrau |
| 4 | federbrau |
| 5 | chang |
| 6 | tianjin bridgestone | | [
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select count ( office ended ) where office started = 1593 col : # | name | birth and death | office started | office ended row 1 : 1 | geir vidalin | 27 october 1761 - 20 september 1823 | 1801 | 1823 row 2 : 2 | steingrimur jonsson | none | 1824 | 1845 row 3 : 3 | helgi thordersen | 8 april 1794 - 4 december 1867 | 1846 | 1866 row 4 : 4 | 'petur petursson | 3 october 1808 - 15 may 1891 | 1866 | 1889 row 5 : 5 | hallgrimur sveinsson | 5 april 1841 - 16 december 1909 | 1889 | 1908 row 6 : 6 | þorhallur bjarnarson | 2 december 1855 - 15 december 1916 | 1908 | 1916 row 7 : 7 | jon helgason | 1866 - 1942 | 1917 | 1939 row 8 : 8 | sigurgeir sigurðsson | 3 august 1890 - 13 october 1953 | 1939 | 1953 row 9 : 9 | asmundur guðmundsson | 6 october 1888 reykholt - 29 may 1969 reykjavik | 1954 | 1989 row 10 : 10 | sigurbjorn einarsson | 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik | 1959 | 1981 row 11 : 11 | petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) | 2 june 1919 - 3 june 2010 | 1981 | 1989 row 12 : 12 | olafur skulason | 29 december 1929 - 9 june 2008 | 1989 | 1997 row 13 : 13 | karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) | 5 february 1947 reykjavik | 1998 | 2012 row 14 : 14 | agnes sigurðardottir | 19 october 1954 isafjorður | 24 june 2012 | incumbent | col : count ( "office ended" ) row 1 : 0 | select count ( office ended ) where office started = 1593 <table_name> : table \begin{tabular}{llllll}
\toprule
& # & name & birth and death & office started & office ended \\
\midrule
0 & 1 & geir vidalin & 27 october 1761 - 20 september 1823 & 1801 & 1823 \\
1 & 2 & steingrimur jonsson & none & 1824 & 1845 \\
2 & 3 & helgi thordersen & 8 april 1794 - 4 december 1867 & 1846 & 1866 \\
3 & 4 & 'petur petursson & 3 october 1808 - 15 may 1891 & 1866 & 1889 \\
4 & 5 & hallgrimur sveinsson & 5 april 1841 - 16 december 1909 & 1889 & 1908 \\
5 & 6 & þorhallur bjarnarson & 2 december 1855 - 15 december 1916 & 1908 & 1916 \\
6 & 7 & jon helgason & 1866 - 1942 & 1917 & 1939 \\
7 & 8 & sigurgeir sigurðsson & 3 august 1890 - 13 october 1953 & 1939 & 1953 \\
8 & 9 & asmundur guðmundsson & 6 october 1888 reykholt - 29 may 1969 reykjavik & 1954 & 1989 \\
9 & 10 & sigurbjorn einarsson & 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik & 1959 & 1981 \\
10 & 11 & petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) & 2 june 1919 - 3 june 2010 & 1981 & 1989 \\
11 & 12 & olafur skulason & 29 december 1929 - 9 june 2008 & 1989 & 1997 \\
12 & 13 & karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) & 5 february 1947 reykjavik & 1998 & 2012 \\
13 & 14 & agnes sigurðardottir & 19 october 1954 isafjorður & 24 june 2012 & incumbent \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "office ended" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( office ended ) where office started = 1593 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>name</th>
<th>birth and death</th>
<th>office started</th>
<th>office ended</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>geir vidalin</td>
<td>27 october 1761 - 20 september 1823</td>
<td>1801</td>
<td>1823</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>steingrimur jonsson</td>
<td>none</td>
<td>1824</td>
<td>1845</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>helgi thordersen</td>
<td>8 april 1794 - 4 december 1867</td>
<td>1846</td>
<td>1866</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>'petur petursson</td>
<td>3 october 1808 - 15 may 1891</td>
<td>1866</td>
<td>1889</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>hallgrimur sveinsson</td>
<td>5 april 1841 - 16 december 1909</td>
<td>1889</td>
<td>1908</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>þorhallur bjarnarson</td>
<td>2 december 1855 - 15 december 1916</td>
<td>1908</td>
<td>1916</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>jon helgason</td>
<td>1866 - 1942</td>
<td>1917</td>
<td>1939</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>sigurgeir sigurðsson</td>
<td>3 august 1890 - 13 october 1953</td>
<td>1939</td>
<td>1953</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>asmundur guðmundsson</td>
<td>6 october 1888 reykholt - 29 may 1969 reykjavik</td>
<td>1954</td>
<td>1989</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>sigurbjorn einarsson</td>
<td>30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik</td>
<td>1959</td>
<td>1981</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland)</td>
<td>2 june 1919 - 3 june 2010</td>
<td>1981</td>
<td>1989</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>olafur skulason</td>
<td>29 december 1929 - 9 june 2008</td>
<td>1989</td>
<td>1997</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland)</td>
<td>5 february 1947 reykjavik</td>
<td>1998</td>
<td>2012</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>agnes sigurðardottir</td>
<td>19 october 1954 isafjorður</td>
<td>24 june 2012</td>
<td>incumbent</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "office ended" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( office ended ) where office started = 1593 <table_name> : table | | # | name | birth and death | office started | office ended |
|---:|----:|:--------------------------------------------------------------------------|:----------------------------------------------------------------|:-----------------|:---------------|
| 0 | 1 | geir vidalin | 27 october 1761 - 20 september 1823 | 1801 | 1823 |
| 1 | 2 | steingrimur jonsson | none | 1824 | 1845 |
| 2 | 3 | helgi thordersen | 8 april 1794 - 4 december 1867 | 1846 | 1866 |
| 3 | 4 | 'petur petursson | 3 october 1808 - 15 may 1891 | 1866 | 1889 |
| 4 | 5 | hallgrimur sveinsson | 5 april 1841 - 16 december 1909 | 1889 | 1908 |
| 5 | 6 | þorhallur bjarnarson | 2 december 1855 - 15 december 1916 | 1908 | 1916 |
| 6 | 7 | jon helgason | 1866 - 1942 | 1917 | 1939 |
| 7 | 8 | sigurgeir sigurðsson | 3 august 1890 - 13 october 1953 | 1939 | 1953 |
| 8 | 9 | asmundur guðmundsson | 6 october 1888 reykholt - 29 may 1969 reykjavik | 1954 | 1989 |
| 9 | 10 | sigurbjorn einarsson | 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik | 1959 | 1981 |
| 10 | 11 | petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) | 2 june 1919 - 3 june 2010 | 1981 | 1989 |
| 11 | 12 | olafur skulason | 29 december 1929 - 9 june 2008 | 1989 | 1997 |
| 12 | 13 | karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) | 5 february 1947 reykjavik | 1998 | 2012 |
| 13 | 14 | agnes sigurðardottir | 19 october 1954 isafjorður | 24 june 2012 | incumbent | | | | count ( "office ended" ) |
|---:|---------------------------:|
| 0 | 0 | | [
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select player where player = 'herbie hewett' 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 : player row 1 : herbie hewett | select player where player = 'herbie hewett' <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
& player \\
\midrule
0 & herbie hewett \\
\bottomrule
\end{tabular}
| select player where player = 'herbie hewett' <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>player</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>herbie hewett</td>
</tr>
</tbody>
</table> | select player where player = 'herbie hewett' <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 | | | | player |
|---:|:--------------|
| 0 | herbie hewett | | [
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select count ( opponents in the final ) where no. > 2 col : outcome | no. | date | tournament | surface | partner | opponents in the final | score in the final row 1 : runner-up | 1 | 1969 | los angeles, u.s | hard | jim mcmanus | pancho gonzales ron holmberg | 3-6, 4-6 row 2 : runner-up | 2 | 1970 | merion, u.s | hard | jim mcmanus | william bowrey ray ruffels | 6-3, 2-6, 5-7 row 3 : winner | 1 | 1971 | columbus, u.s | hard | jim mcmanus | jimmy connors roscoe tanner | 4-6, 7-5, 6-2 row 4 : winner | 2 | 1971 | merion, u.s | hard | clark graebner | robert mckinley dick stockton | 7-6, 6-3 row 5 : winner | 3 | 1971 | sacramento, u.s | hard | jim mcmanus | bob maud frew mcmillan | 7-6, 6-3 row 6 : winner | 4 | 1972 | los angeles, u.s | outdoor | jim mcmanus | ilie nastase ion tiriac | 6-2, 5-7, 6-4 row 7 : winner | 5 | 1972 | london/queen's club, england | grass | jim mcmanus | jurgen fassbender karl meiler | 4-6, 6-3, 7-5 row 8 : runner-up | 3 | 1972 | tanglewood, u.s | other | jim mcmanus | bob hewitt andrew pattison | 4-6, 4-6 | col : count ( "opponents in the final" ) row 1 : 4 | select count ( opponents in the final ) where no. > 2 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& outcome & no. & date & tournament & surface & partner & opponents in the final & score in the final \\
\midrule
0 & runner-up & 1 & 1969 & los angeles, u.s & hard & jim mcmanus & pancho gonzales ron holmberg & 3-6, 4-6 \\
1 & runner-up & 2 & 1970 & merion, u.s & hard & jim mcmanus & william bowrey ray ruffels & 6-3, 2-6, 5-7 \\
2 & winner & 1 & 1971 & columbus, u.s & hard & jim mcmanus & jimmy connors roscoe tanner & 4-6, 7-5, 6-2 \\
3 & winner & 2 & 1971 & merion, u.s & hard & clark graebner & robert mckinley dick stockton & 7-6, 6-3 \\
4 & winner & 3 & 1971 & sacramento, u.s & hard & jim mcmanus & bob maud frew mcmillan & 7-6, 6-3 \\
5 & winner & 4 & 1972 & los angeles, u.s & outdoor & jim mcmanus & ilie nastase ion tiriac & 6-2, 5-7, 6-4 \\
6 & winner & 5 & 1972 & london/queen's club, england & grass & jim mcmanus & jurgen fassbender karl meiler & 4-6, 6-3, 7-5 \\
7 & runner-up & 3 & 1972 & tanglewood, u.s & other & jim mcmanus & bob hewitt andrew pattison & 4-6, 4-6 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "opponents in the final" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( opponents in the final ) where no. > 2 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>outcome</th>
<th>no.</th>
<th>date</th>
<th>tournament</th>
<th>surface</th>
<th>partner</th>
<th>opponents in the final</th>
<th>score in the final</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>runner-up</td>
<td>1</td>
<td>1969</td>
<td>los angeles, u.s</td>
<td>hard</td>
<td>jim mcmanus</td>
<td>pancho gonzales ron holmberg</td>
<td>3-6, 4-6</td>
</tr>
<tr>
<th>1</th>
<td>runner-up</td>
<td>2</td>
<td>1970</td>
<td>merion, u.s</td>
<td>hard</td>
<td>jim mcmanus</td>
<td>william bowrey ray ruffels</td>
<td>6-3, 2-6, 5-7</td>
</tr>
<tr>
<th>2</th>
<td>winner</td>
<td>1</td>
<td>1971</td>
<td>columbus, u.s</td>
<td>hard</td>
<td>jim mcmanus</td>
<td>jimmy connors roscoe tanner</td>
<td>4-6, 7-5, 6-2</td>
</tr>
<tr>
<th>3</th>
<td>winner</td>
<td>2</td>
<td>1971</td>
<td>merion, u.s</td>
<td>hard</td>
<td>clark graebner</td>
<td>robert mckinley dick stockton</td>
<td>7-6, 6-3</td>
</tr>
<tr>
<th>4</th>
<td>winner</td>
<td>3</td>
<td>1971</td>
<td>sacramento, u.s</td>
<td>hard</td>
<td>jim mcmanus</td>
<td>bob maud frew mcmillan</td>
<td>7-6, 6-3</td>
</tr>
<tr>
<th>5</th>
<td>winner</td>
<td>4</td>
<td>1972</td>
<td>los angeles, u.s</td>
<td>outdoor</td>
<td>jim mcmanus</td>
<td>ilie nastase ion tiriac</td>
<td>6-2, 5-7, 6-4</td>
</tr>
<tr>
<th>6</th>
<td>winner</td>
<td>5</td>
<td>1972</td>
<td>london/queen's club, england</td>
<td>grass</td>
<td>jim mcmanus</td>
<td>jurgen fassbender karl meiler</td>
<td>4-6, 6-3, 7-5</td>
</tr>
<tr>
<th>7</th>
<td>runner-up</td>
<td>3</td>
<td>1972</td>
<td>tanglewood, u.s</td>
<td>other</td>
<td>jim mcmanus</td>
<td>bob hewitt andrew pattison</td>
<td>4-6, 4-6</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "opponents in the final" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select count ( opponents in the final ) where no. > 2 <table_name> : table | | outcome | no. | date | tournament | surface | partner | opponents in the final | score in the final |
|---:|:----------|------:|-------:|:-----------------------------|:----------|:---------------|:------------------------------|:---------------------|
| 0 | runner-up | 1 | 1969 | los angeles, u.s | hard | jim mcmanus | pancho gonzales ron holmberg | 3-6, 4-6 |
| 1 | runner-up | 2 | 1970 | merion, u.s | hard | jim mcmanus | william bowrey ray ruffels | 6-3, 2-6, 5-7 |
| 2 | winner | 1 | 1971 | columbus, u.s | hard | jim mcmanus | jimmy connors roscoe tanner | 4-6, 7-5, 6-2 |
| 3 | winner | 2 | 1971 | merion, u.s | hard | clark graebner | robert mckinley dick stockton | 7-6, 6-3 |
| 4 | winner | 3 | 1971 | sacramento, u.s | hard | jim mcmanus | bob maud frew mcmillan | 7-6, 6-3 |
| 5 | winner | 4 | 1972 | los angeles, u.s | outdoor | jim mcmanus | ilie nastase ion tiriac | 6-2, 5-7, 6-4 |
| 6 | winner | 5 | 1972 | london/queen's club, england | grass | jim mcmanus | jurgen fassbender karl meiler | 4-6, 6-3, 7-5 |
| 7 | runner-up | 3 | 1972 | tanglewood, u.s | other | jim mcmanus | bob hewitt andrew pattison | 4-6, 4-6 | | | | count ( "opponents in the final" ) |
|---:|-------------------------------------:|
| 0 | 4 | | [
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select count ( * ) where beanie baby resembled = 1213 col : name | animal type | introduced | reintroduced | retired | beanie baby resembled row 1 : antlers | moose | none | 1999 (neon) | 1999 | chocolate row 2 : baba | lamb | none | 1999 (neon) | 1999 | fleece row 3 : bruiser | bulldog | 1997 | none | none | wrinkles row 4 : carrots | bunny | none | 1999 (neon) | 1999 | ears, but pink instead of brown row 5 : chewy | none | none | 1999 (neon) | 1999 | none row 6 : clover | bunny | 1998 | none | none | ears, but white instead of brown row 7 : foxy | fox | none | none | none | sly row 8 : glide | porpoise | none | none | none | echo the dolphin row 9 : huggy | bear | 1995 | 1999 (neon) | 1999 | cubbie, but yellow instead of brown row 10 : meow | cat | 1997 | 1999 (neon) | 1999 | snip row 11 : moo | cow | 1995 | none | none | daisy, but with white body instead of black row 12 : oink | pig | 1995 | none | none | squealer row 13 : paddles | platypus | none | 1999 (neon) | 1999 | patti row 14 : purr | tiger | none | none | none | stripes, but yellow-orange instead of orange-black row 15 : red | bull | none | none | none | snort row 16 : ribbit (all-green) | frog | 1995 | 1999 (neon) | 1999 | legs row 17 : ribbit (green-yellow) | frog | none | none | none | smoochy row 18 : sherbert | tie-dye bear | 1998 | 1999 (neon) | 1999 | sammy row 19 : snap (all-yellow) | turtle | 1995 | none | none | speedy, but yellow instead of green row 20 : snap (yellow-green) | turtle | none | 1999 (neon) | none | peekaboo row 21 : snuggy | bear | 1995 | none | none | cubbie, but pink instead of brown row 22 : sparkler | bear | none | none | 1999 | spangle row 23 : speckles | leopard | none | none | none | freckles row 24 : spotty | dalmatian | none | none | none | dotty row 25 : squirt | elephant | none | 1999 (neon) | 1999 | peanut row 26 : swinger | monkey | none | 1999 (neon) | 1999 | bongo row 27 : tide | whale | none | none | none | splash row 28 : tubby | hippopotamus | none | none | none | happy row 29 : woof | dog | 1995 | 1999 (neon) | 1999 | bones row 30 : zulu | zebra | none | none | none | ziggy, but pink-green instead of black-white | col : count ( "*" ) row 1 : 0 | select count ( * ) where beanie baby resembled = 1213 <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & animal type & introduced & reintroduced & retired & beanie baby resembled \\
\midrule
0 & antlers & moose & none & 1999 (neon) & 1999 & chocolate \\
1 & baba & lamb & none & 1999 (neon) & 1999 & fleece \\
2 & bruiser & bulldog & 1997 & none & none & wrinkles \\
3 & carrots & bunny & none & 1999 (neon) & 1999 & ears, but pink instead of brown \\
4 & chewy & none & none & 1999 (neon) & 1999 & none \\
5 & clover & bunny & 1998 & none & none & ears, but white instead of brown \\
6 & foxy & fox & none & none & none & sly \\
7 & glide & porpoise & none & none & none & echo the dolphin \\
8 & huggy & bear & 1995 & 1999 (neon) & 1999 & cubbie, but yellow instead of brown \\
9 & meow & cat & 1997 & 1999 (neon) & 1999 & snip \\
10 & moo & cow & 1995 & none & none & daisy, but with white body instead of black \\
11 & oink & pig & 1995 & none & none & squealer \\
12 & paddles & platypus & none & 1999 (neon) & 1999 & patti \\
13 & purr & tiger & none & none & none & stripes, but yellow-orange instead of orange-black \\
14 & red & bull & none & none & none & snort \\
15 & ribbit (all-green) & frog & 1995 & 1999 (neon) & 1999 & legs \\
16 & ribbit (green-yellow) & frog & none & none & none & smoochy \\
17 & sherbert & tie-dye bear & 1998 & 1999 (neon) & 1999 & sammy \\
18 & snap (all-yellow) & turtle & 1995 & none & none & speedy, but yellow instead of green \\
19 & snap (yellow-green) & turtle & none & 1999 (neon) & none & peekaboo \\
20 & snuggy & bear & 1995 & none & none & cubbie, but pink instead of brown \\
21 & sparkler & bear & none & none & 1999 & spangle \\
22 & speckles & leopard & none & none & none & freckles \\
23 & spotty & dalmatian & none & none & none & dotty \\
24 & squirt & elephant & none & 1999 (neon) & 1999 & peanut \\
25 & swinger & monkey & none & 1999 (neon) & 1999 & bongo \\
26 & tide & whale & none & none & none & splash \\
27 & tubby & hippopotamus & none & none & none & happy \\
28 & woof & dog & 1995 & 1999 (neon) & 1999 & bones \\
29 & zulu & zebra & none & none & none & ziggy, but pink-green instead of black-white \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where beanie baby resembled = 1213 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>animal type</th>
<th>introduced</th>
<th>reintroduced</th>
<th>retired</th>
<th>beanie baby resembled</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>antlers</td>
<td>moose</td>
<td>none</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>chocolate</td>
</tr>
<tr>
<th>1</th>
<td>baba</td>
<td>lamb</td>
<td>none</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>fleece</td>
</tr>
<tr>
<th>2</th>
<td>bruiser</td>
<td>bulldog</td>
<td>1997</td>
<td>none</td>
<td>none</td>
<td>wrinkles</td>
</tr>
<tr>
<th>3</th>
<td>carrots</td>
<td>bunny</td>
<td>none</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>ears, but pink instead of brown</td>
</tr>
<tr>
<th>4</th>
<td>chewy</td>
<td>none</td>
<td>none</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>clover</td>
<td>bunny</td>
<td>1998</td>
<td>none</td>
<td>none</td>
<td>ears, but white instead of brown</td>
</tr>
<tr>
<th>6</th>
<td>foxy</td>
<td>fox</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>sly</td>
</tr>
<tr>
<th>7</th>
<td>glide</td>
<td>porpoise</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>echo the dolphin</td>
</tr>
<tr>
<th>8</th>
<td>huggy</td>
<td>bear</td>
<td>1995</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>cubbie, but yellow instead of brown</td>
</tr>
<tr>
<th>9</th>
<td>meow</td>
<td>cat</td>
<td>1997</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>snip</td>
</tr>
<tr>
<th>10</th>
<td>moo</td>
<td>cow</td>
<td>1995</td>
<td>none</td>
<td>none</td>
<td>daisy, but with white body instead of black</td>
</tr>
<tr>
<th>11</th>
<td>oink</td>
<td>pig</td>
<td>1995</td>
<td>none</td>
<td>none</td>
<td>squealer</td>
</tr>
<tr>
<th>12</th>
<td>paddles</td>
<td>platypus</td>
<td>none</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>patti</td>
</tr>
<tr>
<th>13</th>
<td>purr</td>
<td>tiger</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>stripes, but yellow-orange instead of orange-black</td>
</tr>
<tr>
<th>14</th>
<td>red</td>
<td>bull</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>snort</td>
</tr>
<tr>
<th>15</th>
<td>ribbit (all-green)</td>
<td>frog</td>
<td>1995</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>legs</td>
</tr>
<tr>
<th>16</th>
<td>ribbit (green-yellow)</td>
<td>frog</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>smoochy</td>
</tr>
<tr>
<th>17</th>
<td>sherbert</td>
<td>tie-dye bear</td>
<td>1998</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>sammy</td>
</tr>
<tr>
<th>18</th>
<td>snap (all-yellow)</td>
<td>turtle</td>
<td>1995</td>
<td>none</td>
<td>none</td>
<td>speedy, but yellow instead of green</td>
</tr>
<tr>
<th>19</th>
<td>snap (yellow-green)</td>
<td>turtle</td>
<td>none</td>
<td>1999 (neon)</td>
<td>none</td>
<td>peekaboo</td>
</tr>
<tr>
<th>20</th>
<td>snuggy</td>
<td>bear</td>
<td>1995</td>
<td>none</td>
<td>none</td>
<td>cubbie, but pink instead of brown</td>
</tr>
<tr>
<th>21</th>
<td>sparkler</td>
<td>bear</td>
<td>none</td>
<td>none</td>
<td>1999</td>
<td>spangle</td>
</tr>
<tr>
<th>22</th>
<td>speckles</td>
<td>leopard</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>freckles</td>
</tr>
<tr>
<th>23</th>
<td>spotty</td>
<td>dalmatian</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>dotty</td>
</tr>
<tr>
<th>24</th>
<td>squirt</td>
<td>elephant</td>
<td>none</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>peanut</td>
</tr>
<tr>
<th>25</th>
<td>swinger</td>
<td>monkey</td>
<td>none</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>bongo</td>
</tr>
<tr>
<th>26</th>
<td>tide</td>
<td>whale</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>splash</td>
</tr>
<tr>
<th>27</th>
<td>tubby</td>
<td>hippopotamus</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>happy</td>
</tr>
<tr>
<th>28</th>
<td>woof</td>
<td>dog</td>
<td>1995</td>
<td>1999 (neon)</td>
<td>1999</td>
<td>bones</td>
</tr>
<tr>
<th>29</th>
<td>zulu</td>
<td>zebra</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>ziggy, but pink-green instead of black-white</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 beanie baby resembled = 1213 <table_name> : table | | name | animal type | introduced | reintroduced | retired | beanie baby resembled |
|---:|:----------------------|:--------------|:-------------|:---------------|:----------|:---------------------------------------------------|
| 0 | antlers | moose | none | 1999 (neon) | 1999 | chocolate |
| 1 | baba | lamb | none | 1999 (neon) | 1999 | fleece |
| 2 | bruiser | bulldog | 1997 | none | none | wrinkles |
| 3 | carrots | bunny | none | 1999 (neon) | 1999 | ears, but pink instead of brown |
| 4 | chewy | none | none | 1999 (neon) | 1999 | none |
| 5 | clover | bunny | 1998 | none | none | ears, but white instead of brown |
| 6 | foxy | fox | none | none | none | sly |
| 7 | glide | porpoise | none | none | none | echo the dolphin |
| 8 | huggy | bear | 1995 | 1999 (neon) | 1999 | cubbie, but yellow instead of brown |
| 9 | meow | cat | 1997 | 1999 (neon) | 1999 | snip |
| 10 | moo | cow | 1995 | none | none | daisy, but with white body instead of black |
| 11 | oink | pig | 1995 | none | none | squealer |
| 12 | paddles | platypus | none | 1999 (neon) | 1999 | patti |
| 13 | purr | tiger | none | none | none | stripes, but yellow-orange instead of orange-black |
| 14 | red | bull | none | none | none | snort |
| 15 | ribbit (all-green) | frog | 1995 | 1999 (neon) | 1999 | legs |
| 16 | ribbit (green-yellow) | frog | none | none | none | smoochy |
| 17 | sherbert | tie-dye bear | 1998 | 1999 (neon) | 1999 | sammy |
| 18 | snap (all-yellow) | turtle | 1995 | none | none | speedy, but yellow instead of green |
| 19 | snap (yellow-green) | turtle | none | 1999 (neon) | none | peekaboo |
| 20 | snuggy | bear | 1995 | none | none | cubbie, but pink instead of brown |
| 21 | sparkler | bear | none | none | 1999 | spangle |
| 22 | speckles | leopard | none | none | none | freckles |
| 23 | spotty | dalmatian | none | none | none | dotty |
| 24 | squirt | elephant | none | 1999 (neon) | 1999 | peanut |
| 25 | swinger | monkey | none | 1999 (neon) | 1999 | bongo |
| 26 | tide | whale | none | none | none | splash |
| 27 | tubby | hippopotamus | none | none | none | happy |
| 28 | woof | dog | 1995 | 1999 (neon) | 1999 | bones |
| 29 | zulu | zebra | none | none | none | ziggy, but pink-green instead of black-white | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( distinct drivers ) where drivers = 57 col : year | entrant | chassis | engine | tyres | drivers | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | points | wcc row 1 : 1998 | mild seven benetton | benetton b198 | gc37-01 v10 | b | none | aus | bra | arg | smr | esp | mon | can | fra | gbr | aut | ger | hun | bel | ita | lux | jpn | none | 33 | 5th row 2 : 1998 | mild seven benetton | benetton b198 | gc37-01 v10 | b | giancarlo fisichella | ret | 6 | 7 | ret | ret | 2 | 2 | 9 | 5 | ret | 7 | 8 | ret | 8 | 6 | 8 | none | 33 | 5th row 3 : 1998 | mild seven benetton | benetton b198 | gc37-01 v10 | b | alexander wurz | 7 | 4 | 4 | ret | 4 | ret | 4 | 5 | 4 | 9 | 11 | 16 | ret | ret | 7 | 9 | none | 33 | 5th row 4 : 1999 | mild seven benetton | benetton b199 | fb01 v10 | b | none | aus | bra | smr | mon | esp | can | fra | gbr | aut | ger | hun | bel | ita | eur | mal | jpn | none | 16 | 6th row 5 : 1999 | mild seven benetton | benetton b199 | fb01 v10 | b | giancarlo fisichella | 4 | ret | 5 | 5 | 9 | 2 | ret | 7 | 12 | ret | ret | 11 | ret | ret | 11 | 14 | none | 16 | 6th row 6 : 1999 | mild seven benetton | benetton b199 | fb01 v10 | b | alexander wurz | ret | 7 | ret | 6 | 10 | ret | ret | 10 | 5 | 7 | 7 | 14 | ret | ret | 8 | 10 | none | 16 | 6th row 7 : 2000 | mild seven benetton | benetton b200 | fb02 v10 | b | none | aus | bra | smr | gbr | esp | eur | mon | can | fra | aut | ger | hun | bel | ita | usa | jpn | mal | 20 | 4th row 8 : 2000 | mild seven benetton | benetton b200 | fb02 v10 | b | giancarlo fisichella | 5 | 2 | 11 | 7 | 9 | 5 | 3 | 3 | 9 | ret | ret | ret | ret | 11 | ret | 14 | 9 | 20 | 4th row 9 : 2000 | mild seven benetton | benetton b200 | fb02 v10 | b | alexander wurz | 7 | ret | 9 | 9 | 10 | 12 | ret | 9 | ret | 10 | ret | 11 | 13 | 5 | 10 | ret | 7 | 20 | 4th | col : count ( "distinct drivers" ) row 1 : 0 | select count ( distinct drivers ) where drivers = 57 <table_name> : table \begin{tabular}{llllllllllllllllllllllllll}
\toprule
& year & entrant & chassis & engine & tyres & drivers & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 & 13 & 14 & 15 & 16 & 17 & points & wcc \\
\midrule
0 & 1998 & mild seven benetton & benetton b198 & gc37-01 v10 & b & none & aus & bra & arg & smr & esp & mon & can & fra & gbr & aut & ger & hun & bel & ita & lux & jpn & none & 33 & 5th \\
1 & 1998 & mild seven benetton & benetton b198 & gc37-01 v10 & b & giancarlo fisichella & ret & 6 & 7 & ret & ret & 2 & 2 & 9 & 5 & ret & 7 & 8 & ret & 8 & 6 & 8 & none & 33 & 5th \\
2 & 1998 & mild seven benetton & benetton b198 & gc37-01 v10 & b & alexander wurz & 7 & 4 & 4 & ret & 4 & ret & 4 & 5 & 4 & 9 & 11 & 16 & ret & ret & 7 & 9 & none & 33 & 5th \\
3 & 1999 & mild seven benetton & benetton b199 & fb01 v10 & b & none & aus & bra & smr & mon & esp & can & fra & gbr & aut & ger & hun & bel & ita & eur & mal & jpn & none & 16 & 6th \\
4 & 1999 & mild seven benetton & benetton b199 & fb01 v10 & b & giancarlo fisichella & 4 & ret & 5 & 5 & 9 & 2 & ret & 7 & 12 & ret & ret & 11 & ret & ret & 11 & 14 & none & 16 & 6th \\
5 & 1999 & mild seven benetton & benetton b199 & fb01 v10 & b & alexander wurz & ret & 7 & ret & 6 & 10 & ret & ret & 10 & 5 & 7 & 7 & 14 & ret & ret & 8 & 10 & none & 16 & 6th \\
6 & 2000 & mild seven benetton & benetton b200 & fb02 v10 & b & none & aus & bra & smr & gbr & esp & eur & mon & can & fra & aut & ger & hun & bel & ita & usa & jpn & mal & 20 & 4th \\
7 & 2000 & mild seven benetton & benetton b200 & fb02 v10 & b & giancarlo fisichella & 5 & 2 & 11 & 7 & 9 & 5 & 3 & 3 & 9 & ret & ret & ret & ret & 11 & ret & 14 & 9 & 20 & 4th \\
8 & 2000 & mild seven benetton & benetton b200 & fb02 v10 & b & alexander wurz & 7 & ret & 9 & 9 & 10 & 12 & ret & 9 & ret & 10 & ret & 11 & 13 & 5 & 10 & ret & 7 & 20 & 4th \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "distinct drivers" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( distinct drivers ) where drivers = 57 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>entrant</th>
<th>chassis</th>
<th>engine</th>
<th>tyres</th>
<th>drivers</th>
<th>1</th>
<th>2</th>
<th>3</th>
<th>4</th>
<th>5</th>
<th>6</th>
<th>7</th>
<th>8</th>
<th>9</th>
<th>10</th>
<th>11</th>
<th>12</th>
<th>13</th>
<th>14</th>
<th>15</th>
<th>16</th>
<th>17</th>
<th>points</th>
<th>wcc</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1998</td>
<td>mild seven benetton</td>
<td>benetton b198</td>
<td>gc37-01 v10</td>
<td>b</td>
<td>none</td>
<td>aus</td>
<td>bra</td>
<td>arg</td>
<td>smr</td>
<td>esp</td>
<td>mon</td>
<td>can</td>
<td>fra</td>
<td>gbr</td>
<td>aut</td>
<td>ger</td>
<td>hun</td>
<td>bel</td>
<td>ita</td>
<td>lux</td>
<td>jpn</td>
<td>none</td>
<td>33</td>
<td>5th</td>
</tr>
<tr>
<th>1</th>
<td>1998</td>
<td>mild seven benetton</td>
<td>benetton b198</td>
<td>gc37-01 v10</td>
<td>b</td>
<td>giancarlo fisichella</td>
<td>ret</td>
<td>6</td>
<td>7</td>
<td>ret</td>
<td>ret</td>
<td>2</td>
<td>2</td>
<td>9</td>
<td>5</td>
<td>ret</td>
<td>7</td>
<td>8</td>
<td>ret</td>
<td>8</td>
<td>6</td>
<td>8</td>
<td>none</td>
<td>33</td>
<td>5th</td>
</tr>
<tr>
<th>2</th>
<td>1998</td>
<td>mild seven benetton</td>
<td>benetton b198</td>
<td>gc37-01 v10</td>
<td>b</td>
<td>alexander wurz</td>
<td>7</td>
<td>4</td>
<td>4</td>
<td>ret</td>
<td>4</td>
<td>ret</td>
<td>4</td>
<td>5</td>
<td>4</td>
<td>9</td>
<td>11</td>
<td>16</td>
<td>ret</td>
<td>ret</td>
<td>7</td>
<td>9</td>
<td>none</td>
<td>33</td>
<td>5th</td>
</tr>
<tr>
<th>3</th>
<td>1999</td>
<td>mild seven benetton</td>
<td>benetton b199</td>
<td>fb01 v10</td>
<td>b</td>
<td>none</td>
<td>aus</td>
<td>bra</td>
<td>smr</td>
<td>mon</td>
<td>esp</td>
<td>can</td>
<td>fra</td>
<td>gbr</td>
<td>aut</td>
<td>ger</td>
<td>hun</td>
<td>bel</td>
<td>ita</td>
<td>eur</td>
<td>mal</td>
<td>jpn</td>
<td>none</td>
<td>16</td>
<td>6th</td>
</tr>
<tr>
<th>4</th>
<td>1999</td>
<td>mild seven benetton</td>
<td>benetton b199</td>
<td>fb01 v10</td>
<td>b</td>
<td>giancarlo fisichella</td>
<td>4</td>
<td>ret</td>
<td>5</td>
<td>5</td>
<td>9</td>
<td>2</td>
<td>ret</td>
<td>7</td>
<td>12</td>
<td>ret</td>
<td>ret</td>
<td>11</td>
<td>ret</td>
<td>ret</td>
<td>11</td>
<td>14</td>
<td>none</td>
<td>16</td>
<td>6th</td>
</tr>
<tr>
<th>5</th>
<td>1999</td>
<td>mild seven benetton</td>
<td>benetton b199</td>
<td>fb01 v10</td>
<td>b</td>
<td>alexander wurz</td>
<td>ret</td>
<td>7</td>
<td>ret</td>
<td>6</td>
<td>10</td>
<td>ret</td>
<td>ret</td>
<td>10</td>
<td>5</td>
<td>7</td>
<td>7</td>
<td>14</td>
<td>ret</td>
<td>ret</td>
<td>8</td>
<td>10</td>
<td>none</td>
<td>16</td>
<td>6th</td>
</tr>
<tr>
<th>6</th>
<td>2000</td>
<td>mild seven benetton</td>
<td>benetton b200</td>
<td>fb02 v10</td>
<td>b</td>
<td>none</td>
<td>aus</td>
<td>bra</td>
<td>smr</td>
<td>gbr</td>
<td>esp</td>
<td>eur</td>
<td>mon</td>
<td>can</td>
<td>fra</td>
<td>aut</td>
<td>ger</td>
<td>hun</td>
<td>bel</td>
<td>ita</td>
<td>usa</td>
<td>jpn</td>
<td>mal</td>
<td>20</td>
<td>4th</td>
</tr>
<tr>
<th>7</th>
<td>2000</td>
<td>mild seven benetton</td>
<td>benetton b200</td>
<td>fb02 v10</td>
<td>b</td>
<td>giancarlo fisichella</td>
<td>5</td>
<td>2</td>
<td>11</td>
<td>7</td>
<td>9</td>
<td>5</td>
<td>3</td>
<td>3</td>
<td>9</td>
<td>ret</td>
<td>ret</td>
<td>ret</td>
<td>ret</td>
<td>11</td>
<td>ret</td>
<td>14</td>
<td>9</td>
<td>20</td>
<td>4th</td>
</tr>
<tr>
<th>8</th>
<td>2000</td>
<td>mild seven benetton</td>
<td>benetton b200</td>
<td>fb02 v10</td>
<td>b</td>
<td>alexander wurz</td>
<td>7</td>
<td>ret</td>
<td>9</td>
<td>9</td>
<td>10</td>
<td>12</td>
<td>ret</td>
<td>9</td>
<td>ret</td>
<td>10</td>
<td>ret</td>
<td>11</td>
<td>13</td>
<td>5</td>
<td>10</td>
<td>ret</td>
<td>7</td>
<td>20</td>
<td>4th</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "distinct drivers" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( distinct drivers ) where drivers = 57 <table_name> : table | | year | entrant | chassis | engine | tyres | drivers | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | points | wcc |
|---:|-------:|:--------------------|:--------------|:------------|:--------|:---------------------|:----|:----|:----|:----|:----|:----|:----|:----|:----|:-----|:-----|:-----|:-----|:-----|:-----|:-----|:-----|---------:|:------|
| 0 | 1998 | mild seven benetton | benetton b198 | gc37-01 v10 | b | none | aus | bra | arg | smr | esp | mon | can | fra | gbr | aut | ger | hun | bel | ita | lux | jpn | none | 33 | 5th |
| 1 | 1998 | mild seven benetton | benetton b198 | gc37-01 v10 | b | giancarlo fisichella | ret | 6 | 7 | ret | ret | 2 | 2 | 9 | 5 | ret | 7 | 8 | ret | 8 | 6 | 8 | none | 33 | 5th |
| 2 | 1998 | mild seven benetton | benetton b198 | gc37-01 v10 | b | alexander wurz | 7 | 4 | 4 | ret | 4 | ret | 4 | 5 | 4 | 9 | 11 | 16 | ret | ret | 7 | 9 | none | 33 | 5th |
| 3 | 1999 | mild seven benetton | benetton b199 | fb01 v10 | b | none | aus | bra | smr | mon | esp | can | fra | gbr | aut | ger | hun | bel | ita | eur | mal | jpn | none | 16 | 6th |
| 4 | 1999 | mild seven benetton | benetton b199 | fb01 v10 | b | giancarlo fisichella | 4 | ret | 5 | 5 | 9 | 2 | ret | 7 | 12 | ret | ret | 11 | ret | ret | 11 | 14 | none | 16 | 6th |
| 5 | 1999 | mild seven benetton | benetton b199 | fb01 v10 | b | alexander wurz | ret | 7 | ret | 6 | 10 | ret | ret | 10 | 5 | 7 | 7 | 14 | ret | ret | 8 | 10 | none | 16 | 6th |
| 6 | 2000 | mild seven benetton | benetton b200 | fb02 v10 | b | none | aus | bra | smr | gbr | esp | eur | mon | can | fra | aut | ger | hun | bel | ita | usa | jpn | mal | 20 | 4th |
| 7 | 2000 | mild seven benetton | benetton b200 | fb02 v10 | b | giancarlo fisichella | 5 | 2 | 11 | 7 | 9 | 5 | 3 | 3 | 9 | ret | ret | ret | ret | 11 | ret | 14 | 9 | 20 | 4th |
| 8 | 2000 | mild seven benetton | benetton b200 | fb02 v10 | b | alexander wurz | 7 | ret | 9 | 9 | 10 | 12 | ret | 9 | ret | 10 | ret | 11 | 13 | 5 | 10 | ret | 7 | 20 | 4th | | | | count ( "distinct drivers" ) |
|---:|-------------------------------:|
| 0 | 0 | | [
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[
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select result where week = 16 col : week | date | opponent | result | attendance row 1 : 1 | 1981-09-06 00:00:00 | new orleans saints | w 27-0 | 57,406 row 2 : 2 | 1981-09-13 00:00:00 | at green bay packers | w 31-17 | 55,382 row 3 : 3 | 1981-09-20 00:00:00 | san francisco 49ers | w 34-17 | 56,653 row 4 : 4 | 1981-09-27 00:00:00 | at cleveland browns | l 28-17 | 78,283 row 5 : 5 | 1981-10-05 00:00:00 | at philadelphia eagles | l 16-13 | 71,488 row 6 : 6 | 1981-10-11 00:00:00 | los angeles rams | l 37-35 | 57,841 row 7 : 7 | 1981-10-18 00:00:00 | st. louis cardinals | w 41-20 | 51,428 row 8 : 8 | 1981-10-25 00:00:00 | new york giants | l 27-24 | 48,410 row 9 : 9 | 1981-11-01 00:00:00 | at new orleans saints | w 41-10 | 63,637 row 10 : 10 | 1981-11-08 00:00:00 | at san francisco 49ers | l 17-14 | 59,127 row 11 : 11 | 1981-11-15 00:00:00 | pittsburgh steelers | l 34-20 | 57,485 row 12 : 12 | 1981-11-23 00:00:00 | minnesota vikings | w 31-30 | 54,086 row 13 : 13 | 1981-11-29 00:00:00 | at houston oilers | w 31-27 | 40,201 row 14 : 14 | 1981-12-06 00:00:00 | at tampa bay buccaneers | l 24-23 | 69,221 row 15 : 15 | 1981-12-14 00:00:00 | at los angeles rams | l 21-16 | 57,054 row 16 : 16 | 1981-12-20 00:00:00 | cincinnati bengals | l 30-28 | 35,972 | col : result row 1 : l 30-28 | select result where week = 16 <table_name> : table \begin{tabular}{llllll}
\toprule
& week & date & opponent & result & attendance \\
\midrule
0 & 1 & 1981-09-06 00:00:00 & new orleans saints & w 27-0 & 57,406 \\
1 & 2 & 1981-09-13 00:00:00 & at green bay packers & w 31-17 & 55,382 \\
2 & 3 & 1981-09-20 00:00:00 & san francisco 49ers & w 34-17 & 56,653 \\
3 & 4 & 1981-09-27 00:00:00 & at cleveland browns & l 28-17 & 78,283 \\
4 & 5 & 1981-10-05 00:00:00 & at philadelphia eagles & l 16-13 & 71,488 \\
5 & 6 & 1981-10-11 00:00:00 & los angeles rams & l 37-35 & 57,841 \\
6 & 7 & 1981-10-18 00:00:00 & st. louis cardinals & w 41-20 & 51,428 \\
7 & 8 & 1981-10-25 00:00:00 & new york giants & l 27-24 & 48,410 \\
8 & 9 & 1981-11-01 00:00:00 & at new orleans saints & w 41-10 & 63,637 \\
9 & 10 & 1981-11-08 00:00:00 & at san francisco 49ers & l 17-14 & 59,127 \\
10 & 11 & 1981-11-15 00:00:00 & pittsburgh steelers & l 34-20 & 57,485 \\
11 & 12 & 1981-11-23 00:00:00 & minnesota vikings & w 31-30 & 54,086 \\
12 & 13 & 1981-11-29 00:00:00 & at houston oilers & w 31-27 & 40,201 \\
13 & 14 & 1981-12-06 00:00:00 & at tampa bay buccaneers & l 24-23 & 69,221 \\
14 & 15 & 1981-12-14 00:00:00 & at los angeles rams & l 21-16 & 57,054 \\
15 & 16 & 1981-12-20 00:00:00 & cincinnati bengals & l 30-28 & 35,972 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& result \\
\midrule
0 & l 30-28 \\
\bottomrule
\end{tabular}
| select result where week = 16 <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>result</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1981-09-06 00:00:00</td>
<td>new orleans saints</td>
<td>w 27-0</td>
<td>57,406</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1981-09-13 00:00:00</td>
<td>at green bay packers</td>
<td>w 31-17</td>
<td>55,382</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1981-09-20 00:00:00</td>
<td>san francisco 49ers</td>
<td>w 34-17</td>
<td>56,653</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1981-09-27 00:00:00</td>
<td>at cleveland browns</td>
<td>l 28-17</td>
<td>78,283</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1981-10-05 00:00:00</td>
<td>at philadelphia eagles</td>
<td>l 16-13</td>
<td>71,488</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1981-10-11 00:00:00</td>
<td>los angeles rams</td>
<td>l 37-35</td>
<td>57,841</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>1981-10-18 00:00:00</td>
<td>st. louis cardinals</td>
<td>w 41-20</td>
<td>51,428</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>1981-10-25 00:00:00</td>
<td>new york giants</td>
<td>l 27-24</td>
<td>48,410</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>1981-11-01 00:00:00</td>
<td>at new orleans saints</td>
<td>w 41-10</td>
<td>63,637</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>1981-11-08 00:00:00</td>
<td>at san francisco 49ers</td>
<td>l 17-14</td>
<td>59,127</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>1981-11-15 00:00:00</td>
<td>pittsburgh steelers</td>
<td>l 34-20</td>
<td>57,485</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>1981-11-23 00:00:00</td>
<td>minnesota vikings</td>
<td>w 31-30</td>
<td>54,086</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>1981-11-29 00:00:00</td>
<td>at houston oilers</td>
<td>w 31-27</td>
<td>40,201</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>1981-12-06 00:00:00</td>
<td>at tampa bay buccaneers</td>
<td>l 24-23</td>
<td>69,221</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>1981-12-14 00:00:00</td>
<td>at los angeles rams</td>
<td>l 21-16</td>
<td>57,054</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>1981-12-20 00:00:00</td>
<td>cincinnati bengals</td>
<td>l 30-28</td>
<td>35,972</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>l 30-28</td>
</tr>
</tbody>
</table> | select result where week = 16 <table_name> : table | | week | date | opponent | result | attendance |
|---:|-------:|:--------------------|:------------------------|:---------|:-------------|
| 0 | 1 | 1981-09-06 00:00:00 | new orleans saints | w 27-0 | 57,406 |
| 1 | 2 | 1981-09-13 00:00:00 | at green bay packers | w 31-17 | 55,382 |
| 2 | 3 | 1981-09-20 00:00:00 | san francisco 49ers | w 34-17 | 56,653 |
| 3 | 4 | 1981-09-27 00:00:00 | at cleveland browns | l 28-17 | 78,283 |
| 4 | 5 | 1981-10-05 00:00:00 | at philadelphia eagles | l 16-13 | 71,488 |
| 5 | 6 | 1981-10-11 00:00:00 | los angeles rams | l 37-35 | 57,841 |
| 6 | 7 | 1981-10-18 00:00:00 | st. louis cardinals | w 41-20 | 51,428 |
| 7 | 8 | 1981-10-25 00:00:00 | new york giants | l 27-24 | 48,410 |
| 8 | 9 | 1981-11-01 00:00:00 | at new orleans saints | w 41-10 | 63,637 |
| 9 | 10 | 1981-11-08 00:00:00 | at san francisco 49ers | l 17-14 | 59,127 |
| 10 | 11 | 1981-11-15 00:00:00 | pittsburgh steelers | l 34-20 | 57,485 |
| 11 | 12 | 1981-11-23 00:00:00 | minnesota vikings | w 31-30 | 54,086 |
| 12 | 13 | 1981-11-29 00:00:00 | at houston oilers | w 31-27 | 40,201 |
| 13 | 14 | 1981-12-06 00:00:00 | at tampa bay buccaneers | l 24-23 | 69,221 |
| 14 | 15 | 1981-12-14 00:00:00 | at los angeles rams | l 21-16 | 57,054 |
| 15 | 16 | 1981-12-20 00:00:00 | cincinnati bengals | l 30-28 | 35,972 | | | | result |
|---:|:---------|
| 0 | l 30-28 | | [
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select distance where distance = 1200 col : grp | race name | age | sex | weight | distance | date row 1 : 2 | ajc challenge stakes | open | open | wfa | 1000 | march row 2 : 2 | surround stakes | 3yo | fillies | sw | 1400 | march row 3 : 2 | warwick stakes | open | open | wfa | 1400 | august row 4 : 3 | liverpool city cup | open | open | qlty | 1300 | march row 5 : 3 | silver shadow stakes | 3yo | fillies | swp | 1200 | august row 6 : 3 | up and coming stakes | 3yo | c&g | swp | 1200 | august | col : distance row 1 : 1200 row 2 : 1200 | select distance where distance = 1200 <table_name> : table \begin{tabular}{llllllll}
\toprule
& grp & race name & age & sex & weight & distance & date \\
\midrule
0 & 2 & ajc challenge stakes & open & open & wfa & 1000 & march \\
1 & 2 & surround stakes & 3yo & fillies & sw & 1400 & march \\
2 & 2 & warwick stakes & open & open & wfa & 1400 & august \\
3 & 3 & liverpool city cup & open & open & qlty & 1300 & march \\
4 & 3 & silver shadow stakes & 3yo & fillies & swp & 1200 & august \\
5 & 3 & up and coming stakes & 3yo & c&g & swp & 1200 & august \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& distance \\
\midrule
0 & 1200 \\
1 & 1200 \\
\bottomrule
\end{tabular}
| select distance where distance = 1200 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>grp</th>
<th>race name</th>
<th>age</th>
<th>sex</th>
<th>weight</th>
<th>distance</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
<td>ajc challenge stakes</td>
<td>open</td>
<td>open</td>
<td>wfa</td>
<td>1000</td>
<td>march</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>surround stakes</td>
<td>3yo</td>
<td>fillies</td>
<td>sw</td>
<td>1400</td>
<td>march</td>
</tr>
<tr>
<th>2</th>
<td>2</td>
<td>warwick stakes</td>
<td>open</td>
<td>open</td>
<td>wfa</td>
<td>1400</td>
<td>august</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>liverpool city cup</td>
<td>open</td>
<td>open</td>
<td>qlty</td>
<td>1300</td>
<td>march</td>
</tr>
<tr>
<th>4</th>
<td>3</td>
<td>silver shadow stakes</td>
<td>3yo</td>
<td>fillies</td>
<td>swp</td>
<td>1200</td>
<td>august</td>
</tr>
<tr>
<th>5</th>
<td>3</td>
<td>up and coming stakes</td>
<td>3yo</td>
<td>c&g</td>
<td>swp</td>
<td>1200</td>
<td>august</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>distance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1200</td>
</tr>
<tr>
<th>1</th>
<td>1200</td>
</tr>
</tbody>
</table> | select distance where distance = 1200 <table_name> : table | | grp | race name | age | sex | weight | distance | date |
|---:|------:|:---------------------|:------|:--------|:---------|-----------:|:-------|
| 0 | 2 | ajc challenge stakes | open | open | wfa | 1000 | march |
| 1 | 2 | surround stakes | 3yo | fillies | sw | 1400 | march |
| 2 | 2 | warwick stakes | open | open | wfa | 1400 | august |
| 3 | 3 | liverpool city cup | open | open | qlty | 1300 | march |
| 4 | 3 | silver shadow stakes | 3yo | fillies | swp | 1200 | august |
| 5 | 3 | up and coming stakes | 3yo | c&g | swp | 1200 | august | | | | distance |
|---:|-----------:|
| 0 | 1200 |
| 1 | 1200 | | [
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select count ( * ) where apps = 'none' col : season | team | country | division | apps | goals | assists row 1 : 01/02 | esteghlal | iran | 1 | none | 3 | none row 2 : 02/03 | esteghlal | iran | 1 | none | 2 | none row 3 : 03/04 | esteghlal | iran | 1 | none | 6 | none row 4 : 04/05 | eseghlal | iran | 1 | 27 | 3 | none row 5 : 05/06 | esteghlal | iran | 1 | 21 | 0 | 2 row 6 : 06/07 | esteghlal | iran | 1 | 14 | 1 | 1 row 7 : 07/08 | steel azin | iran | 1 | none | 2 | none row 8 : 10/11 | gostaresh foolad | iran | 2 | 0 | 0 | 0 | col : count ( "*" ) row 1 : 4 | select count ( * ) where apps = 'none' <table_name> : table \begin{tabular}{llllllll}
\toprule
& season & team & country & division & apps & goals & assists \\
\midrule
0 & 01/02 & esteghlal & iran & 1 & none & 3 & none \\
1 & 02/03 & esteghlal & iran & 1 & none & 2 & none \\
2 & 03/04 & esteghlal & iran & 1 & none & 6 & none \\
3 & 04/05 & eseghlal & iran & 1 & 27 & 3 & none \\
4 & 05/06 & esteghlal & iran & 1 & 21 & 0 & 2 \\
5 & 06/07 & esteghlal & iran & 1 & 14 & 1 & 1 \\
6 & 07/08 & steel azin & iran & 1 & none & 2 & none \\
7 & 10/11 & gostaresh foolad & iran & 2 & 0 & 0 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( * ) where apps = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>team</th>
<th>country</th>
<th>division</th>
<th>apps</th>
<th>goals</th>
<th>assists</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>01/02</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>02/03</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>03/04</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>04/05</td>
<td>eseghlal</td>
<td>iran</td>
<td>1</td>
<td>27</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>05/06</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>21</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>06/07</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>14</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>07/08</td>
<td>steel azin</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>10/11</td>
<td>gostaresh foolad</td>
<td>iran</td>
<td>2</td>
<td>0</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>4</td>
</tr>
</tbody>
</table> | select count ( * ) where apps = 'none' <table_name> : table | | season | team | country | division | apps | goals | assists |
|---:|:---------|:-----------------|:----------|-----------:|:-------|--------:|:----------|
| 0 | 01/02 | esteghlal | iran | 1 | none | 3 | none |
| 1 | 02/03 | esteghlal | iran | 1 | none | 2 | none |
| 2 | 03/04 | esteghlal | iran | 1 | none | 6 | none |
| 3 | 04/05 | eseghlal | iran | 1 | 27 | 3 | none |
| 4 | 05/06 | esteghlal | iran | 1 | 21 | 0 | 2 |
| 5 | 06/07 | esteghlal | iran | 1 | 14 | 1 | 1 |
| 6 | 07/08 | steel azin | iran | 1 | none | 2 | none |
| 7 | 10/11 | gostaresh foolad | iran | 2 | 0 | 0 | 0 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 4 | | [
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] |
select count ( callsign ) where callsign = '7la' col : callsign | area served | frequency | band | fate | freq currently | purpose row 1 : 7cae | hobart | 92.1 | fm | changed call to 7the ca. 1980 | 7the | community row 2 : 7dy | derby | none | am | moved to scottsdale and changed call to 7sd in 1954 | 7sd | commercial row 3 : 7ex | launceston | 1008 | am | moved to fm in 2008 as 7exx | silent | commercial row 4 : 7ho | hobart | 864 | am | moved to fm in 1990 as 7hho | 7rph | commercial row 5 : 7ht | hobart | 1080 | am | moved to fm in 1998 as 7xxx | 7tab (hpon) | commercial row 6 : 7la | launceston | 1098 | am | moved to fm in 2008 as 7laa | silent | commercial row 7 : 7nt | launceston | 711 | am | moved to fm in 2006, retained call | silent | national row 8 : 7qn | queenstown | 630 | am | moved to fm in 1991, retained call | 7rn | national row 9 : 7qt | queenstown | 837 | am | changed call to 7xs in 1988 | 7xs | commercial row 10 : 7uv | ulverstone | none | am | moved to devonport and changed call to 7ad in 1940 | 7ad | commercial row 11 : 7zl | hobart | 603 | am | changed call to 7rn in 1991 | 7rn | national | col : count ( "callsign" ) row 1 : 1 | select count ( callsign ) where callsign = '7la' <table_name> : table \begin{tabular}{llllllll}
\toprule
& callsign & area served & frequency & band & fate & freq currently & purpose \\
\midrule
0 & 7cae & hobart & 92.1 & fm & changed call to 7the ca. 1980 & 7the & community \\
1 & 7dy & derby & none & am & moved to scottsdale and changed call to 7sd in 1954 & 7sd & commercial \\
2 & 7ex & launceston & 1008 & am & moved to fm in 2008 as 7exx & silent & commercial \\
3 & 7ho & hobart & 864 & am & moved to fm in 1990 as 7hho & 7rph & commercial \\
4 & 7ht & hobart & 1080 & am & moved to fm in 1998 as 7xxx & 7tab (hpon) & commercial \\
5 & 7la & launceston & 1098 & am & moved to fm in 2008 as 7laa & silent & commercial \\
6 & 7nt & launceston & 711 & am & moved to fm in 2006, retained call & silent & national \\
7 & 7qn & queenstown & 630 & am & moved to fm in 1991, retained call & 7rn & national \\
8 & 7qt & queenstown & 837 & am & changed call to 7xs in 1988 & 7xs & commercial \\
9 & 7uv & ulverstone & none & am & moved to devonport and changed call to 7ad in 1940 & 7ad & commercial \\
10 & 7zl & hobart & 603 & am & changed call to 7rn in 1991 & 7rn & national \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "callsign" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( callsign ) where callsign = '7la' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>callsign</th>
<th>area served</th>
<th>frequency</th>
<th>band</th>
<th>fate</th>
<th>freq currently</th>
<th>purpose</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7cae</td>
<td>hobart</td>
<td>92.1</td>
<td>fm</td>
<td>changed call to 7the ca. 1980</td>
<td>7the</td>
<td>community</td>
</tr>
<tr>
<th>1</th>
<td>7dy</td>
<td>derby</td>
<td>none</td>
<td>am</td>
<td>moved to scottsdale and changed call to 7sd in 1954</td>
<td>7sd</td>
<td>commercial</td>
</tr>
<tr>
<th>2</th>
<td>7ex</td>
<td>launceston</td>
<td>1008</td>
<td>am</td>
<td>moved to fm in 2008 as 7exx</td>
<td>silent</td>
<td>commercial</td>
</tr>
<tr>
<th>3</th>
<td>7ho</td>
<td>hobart</td>
<td>864</td>
<td>am</td>
<td>moved to fm in 1990 as 7hho</td>
<td>7rph</td>
<td>commercial</td>
</tr>
<tr>
<th>4</th>
<td>7ht</td>
<td>hobart</td>
<td>1080</td>
<td>am</td>
<td>moved to fm in 1998 as 7xxx</td>
<td>7tab (hpon)</td>
<td>commercial</td>
</tr>
<tr>
<th>5</th>
<td>7la</td>
<td>launceston</td>
<td>1098</td>
<td>am</td>
<td>moved to fm in 2008 as 7laa</td>
<td>silent</td>
<td>commercial</td>
</tr>
<tr>
<th>6</th>
<td>7nt</td>
<td>launceston</td>
<td>711</td>
<td>am</td>
<td>moved to fm in 2006, retained call</td>
<td>silent</td>
<td>national</td>
</tr>
<tr>
<th>7</th>
<td>7qn</td>
<td>queenstown</td>
<td>630</td>
<td>am</td>
<td>moved to fm in 1991, retained call</td>
<td>7rn</td>
<td>national</td>
</tr>
<tr>
<th>8</th>
<td>7qt</td>
<td>queenstown</td>
<td>837</td>
<td>am</td>
<td>changed call to 7xs in 1988</td>
<td>7xs</td>
<td>commercial</td>
</tr>
<tr>
<th>9</th>
<td>7uv</td>
<td>ulverstone</td>
<td>none</td>
<td>am</td>
<td>moved to devonport and changed call to 7ad in 1940</td>
<td>7ad</td>
<td>commercial</td>
</tr>
<tr>
<th>10</th>
<td>7zl</td>
<td>hobart</td>
<td>603</td>
<td>am</td>
<td>changed call to 7rn in 1991</td>
<td>7rn</td>
<td>national</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "callsign" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( callsign ) where callsign = '7la' <table_name> : table | | callsign | area served | frequency | band | fate | freq currently | purpose |
|---:|:-----------|:--------------|:------------|:-------|:----------------------------------------------------|:-----------------|:-----------|
| 0 | 7cae | hobart | 92.1 | fm | changed call to 7the ca. 1980 | 7the | community |
| 1 | 7dy | derby | none | am | moved to scottsdale and changed call to 7sd in 1954 | 7sd | commercial |
| 2 | 7ex | launceston | 1008 | am | moved to fm in 2008 as 7exx | silent | commercial |
| 3 | 7ho | hobart | 864 | am | moved to fm in 1990 as 7hho | 7rph | commercial |
| 4 | 7ht | hobart | 1080 | am | moved to fm in 1998 as 7xxx | 7tab (hpon) | commercial |
| 5 | 7la | launceston | 1098 | am | moved to fm in 2008 as 7laa | silent | commercial |
| 6 | 7nt | launceston | 711 | am | moved to fm in 2006, retained call | silent | national |
| 7 | 7qn | queenstown | 630 | am | moved to fm in 1991, retained call | 7rn | national |
| 8 | 7qt | queenstown | 837 | am | changed call to 7xs in 1988 | 7xs | commercial |
| 9 | 7uv | ulverstone | none | am | moved to devonport and changed call to 7ad in 1940 | 7ad | commercial |
| 10 | 7zl | hobart | 603 | am | changed call to 7rn in 1991 | 7rn | national | | | | count ( "callsign" ) |
|---:|-----------------------:|
| 0 | 1 | | [
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select count ( platform(s) ) where release = 1995 col : japanese title | western title | regions | release | platform(s) | genre row 1 : chinese hero | none | jp | 1984 | arcade | action row 2 : super chinese | kung-fu heroes | jp, na | 1986 | fc/nes | action row 3 : super chinese 2 | little ninja brothers | jp, na | 1989 | fc/nes | role-playing row 4 : super chinese 3 | none | jp | 1991 | fc | role-playing row 5 : super chinese land | ninja boy | jp, na | 1990 | gb | action row 6 : super chinese land 2 | ninja boy 2 | jp, na | 1990 | gb | role-playing row 7 : super chinese land 3 | none | jp | 1995 | gb | role-playing row 8 : super chinese world | super ninja boy | jp, na | 1991 | sfc/snes | role-playing row 9 : super chinese world 2 | none | jp | 1993 | sfc | role-playing row 10 : super chinese world 3 | none | jp | 1995 | sfc | role-playing row 11 : super chinese fighter | none | jp | 1995 | sfc | fighting row 12 : super chinese fighter gb | none | jp | 1996 | gb | fighting row 13 : super chinese fighter ex | none | jp | 1999 | gbc | fighting | col : count ( "platform(s" ) row 1 : 3 | select count ( platform(s) ) where release = 1995 <table_name> : table \begin{tabular}{lllllll}
\toprule
& japanese title & western title & regions & release & platform(s) & genre \\
\midrule
0 & chinese hero & none & jp & 1984 & arcade & action \\
1 & super chinese & kung-fu heroes & jp, na & 1986 & fc/nes & action \\
2 & super chinese 2 & little ninja brothers & jp, na & 1989 & fc/nes & role-playing \\
3 & super chinese 3 & none & jp & 1991 & fc & role-playing \\
4 & super chinese land & ninja boy & jp, na & 1990 & gb & action \\
5 & super chinese land 2 & ninja boy 2 & jp, na & 1990 & gb & role-playing \\
6 & super chinese land 3 & none & jp & 1995 & gb & role-playing \\
7 & super chinese world & super ninja boy & jp, na & 1991 & sfc/snes & role-playing \\
8 & super chinese world 2 & none & jp & 1993 & sfc & role-playing \\
9 & super chinese world 3 & none & jp & 1995 & sfc & role-playing \\
10 & super chinese fighter & none & jp & 1995 & sfc & fighting \\
11 & super chinese fighter gb & none & jp & 1996 & gb & fighting \\
12 & super chinese fighter ex & none & jp & 1999 & gbc & fighting \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "platform(s" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( platform(s) ) where release = 1995 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>japanese title</th>
<th>western title</th>
<th>regions</th>
<th>release</th>
<th>platform(s)</th>
<th>genre</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>chinese hero</td>
<td>none</td>
<td>jp</td>
<td>1984</td>
<td>arcade</td>
<td>action</td>
</tr>
<tr>
<th>1</th>
<td>super chinese</td>
<td>kung-fu heroes</td>
<td>jp, na</td>
<td>1986</td>
<td>fc/nes</td>
<td>action</td>
</tr>
<tr>
<th>2</th>
<td>super chinese 2</td>
<td>little ninja brothers</td>
<td>jp, na</td>
<td>1989</td>
<td>fc/nes</td>
<td>role-playing</td>
</tr>
<tr>
<th>3</th>
<td>super chinese 3</td>
<td>none</td>
<td>jp</td>
<td>1991</td>
<td>fc</td>
<td>role-playing</td>
</tr>
<tr>
<th>4</th>
<td>super chinese land</td>
<td>ninja boy</td>
<td>jp, na</td>
<td>1990</td>
<td>gb</td>
<td>action</td>
</tr>
<tr>
<th>5</th>
<td>super chinese land 2</td>
<td>ninja boy 2</td>
<td>jp, na</td>
<td>1990</td>
<td>gb</td>
<td>role-playing</td>
</tr>
<tr>
<th>6</th>
<td>super chinese land 3</td>
<td>none</td>
<td>jp</td>
<td>1995</td>
<td>gb</td>
<td>role-playing</td>
</tr>
<tr>
<th>7</th>
<td>super chinese world</td>
<td>super ninja boy</td>
<td>jp, na</td>
<td>1991</td>
<td>sfc/snes</td>
<td>role-playing</td>
</tr>
<tr>
<th>8</th>
<td>super chinese world 2</td>
<td>none</td>
<td>jp</td>
<td>1993</td>
<td>sfc</td>
<td>role-playing</td>
</tr>
<tr>
<th>9</th>
<td>super chinese world 3</td>
<td>none</td>
<td>jp</td>
<td>1995</td>
<td>sfc</td>
<td>role-playing</td>
</tr>
<tr>
<th>10</th>
<td>super chinese fighter</td>
<td>none</td>
<td>jp</td>
<td>1995</td>
<td>sfc</td>
<td>fighting</td>
</tr>
<tr>
<th>11</th>
<td>super chinese fighter gb</td>
<td>none</td>
<td>jp</td>
<td>1996</td>
<td>gb</td>
<td>fighting</td>
</tr>
<tr>
<th>12</th>
<td>super chinese fighter ex</td>
<td>none</td>
<td>jp</td>
<td>1999</td>
<td>gbc</td>
<td>fighting</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "platform(s" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( platform(s) ) where release = 1995 <table_name> : table | | japanese title | western title | regions | release | platform(s) | genre |
|---:|:-------------------------|:----------------------|:----------|----------:|:--------------|:-------------|
| 0 | chinese hero | none | jp | 1984 | arcade | action |
| 1 | super chinese | kung-fu heroes | jp, na | 1986 | fc/nes | action |
| 2 | super chinese 2 | little ninja brothers | jp, na | 1989 | fc/nes | role-playing |
| 3 | super chinese 3 | none | jp | 1991 | fc | role-playing |
| 4 | super chinese land | ninja boy | jp, na | 1990 | gb | action |
| 5 | super chinese land 2 | ninja boy 2 | jp, na | 1990 | gb | role-playing |
| 6 | super chinese land 3 | none | jp | 1995 | gb | role-playing |
| 7 | super chinese world | super ninja boy | jp, na | 1991 | sfc/snes | role-playing |
| 8 | super chinese world 2 | none | jp | 1993 | sfc | role-playing |
| 9 | super chinese world 3 | none | jp | 1995 | sfc | role-playing |
| 10 | super chinese fighter | none | jp | 1995 | sfc | fighting |
| 11 | super chinese fighter gb | none | jp | 1996 | gb | fighting |
| 12 | super chinese fighter ex | none | jp | 1999 | gbc | fighting | | | | count ( "platform(s" ) |
|---:|-------------------------:|
| 0 | 3 | | [
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select goals where club = 'lokomotiv' col : season | club | league | apps | goals row 1 : 2003-04 | podgrmec | fbih first league | 23 | 16 row 2 : 2004-05 | nk zagreb | prva hnl | 26 | 3 row 3 : 2005-06 | nk zagreb | prva hnl | 25 | 3 row 4 : 2006-07 | nk zagreb | prva hnl | 17 | 4 row 5 : 2007-08 | nk zagreb | prva hnl | 31 | 12 row 6 : 2008-09 | hajduk split | prva hnl | 30 | 12 row 7 : 2009-10 | hajduk split | prva hnl | 29 | 17 row 8 : 2010-11 | hajduk split | prva hnl | 17 | 6 row 9 : 2011-12 | lokomotiv | rfpl | 28 | 4 row 10 : 2012-13 | gaziantepspor | super lig | 1 | 1 | col : goals row 1 : 4 | select goals where club = 'lokomotiv' <table_name> : table \begin{tabular}{llllll}
\toprule
& season & club & league & apps & goals \\
\midrule
0 & 2003-04 & podgrmec & fbih first league & 23 & 16 \\
1 & 2004-05 & nk zagreb & prva hnl & 26 & 3 \\
2 & 2005-06 & nk zagreb & prva hnl & 25 & 3 \\
3 & 2006-07 & nk zagreb & prva hnl & 17 & 4 \\
4 & 2007-08 & nk zagreb & prva hnl & 31 & 12 \\
5 & 2008-09 & hajduk split & prva hnl & 30 & 12 \\
6 & 2009-10 & hajduk split & prva hnl & 29 & 17 \\
7 & 2010-11 & hajduk split & prva hnl & 17 & 6 \\
8 & 2011-12 & lokomotiv & rfpl & 28 & 4 \\
9 & 2012-13 & gaziantepspor & super lig & 1 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& goals \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select goals where club = 'lokomotiv' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>club</th>
<th>league</th>
<th>apps</th>
<th>goals</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2003-04</td>
<td>podgrmec</td>
<td>fbih first league</td>
<td>23</td>
<td>16</td>
</tr>
<tr>
<th>1</th>
<td>2004-05</td>
<td>nk zagreb</td>
<td>prva hnl</td>
<td>26</td>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>2005-06</td>
<td>nk zagreb</td>
<td>prva hnl</td>
<td>25</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>2006-07</td>
<td>nk zagreb</td>
<td>prva hnl</td>
<td>17</td>
<td>4</td>
</tr>
<tr>
<th>4</th>
<td>2007-08</td>
<td>nk zagreb</td>
<td>prva hnl</td>
<td>31</td>
<td>12</td>
</tr>
<tr>
<th>5</th>
<td>2008-09</td>
<td>hajduk split</td>
<td>prva hnl</td>
<td>30</td>
<td>12</td>
</tr>
<tr>
<th>6</th>
<td>2009-10</td>
<td>hajduk split</td>
<td>prva hnl</td>
<td>29</td>
<td>17</td>
</tr>
<tr>
<th>7</th>
<td>2010-11</td>
<td>hajduk split</td>
<td>prva hnl</td>
<td>17</td>
<td>6</td>
</tr>
<tr>
<th>8</th>
<td>2011-12</td>
<td>lokomotiv</td>
<td>rfpl</td>
<td>28</td>
<td>4</td>
</tr>
<tr>
<th>9</th>
<td>2012-13</td>
<td>gaziantepspor</td>
<td>super lig</td>
<td>1</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>goals</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select goals where club = 'lokomotiv' <table_name> : table | | season | club | league | apps | goals |
|---:|:---------|:--------------|:------------------|-------:|--------:|
| 0 | 2003-04 | podgrmec | fbih first league | 23 | 16 |
| 1 | 2004-05 | nk zagreb | prva hnl | 26 | 3 |
| 2 | 2005-06 | nk zagreb | prva hnl | 25 | 3 |
| 3 | 2006-07 | nk zagreb | prva hnl | 17 | 4 |
| 4 | 2007-08 | nk zagreb | prva hnl | 31 | 12 |
| 5 | 2008-09 | hajduk split | prva hnl | 30 | 12 |
| 6 | 2009-10 | hajduk split | prva hnl | 29 | 17 |
| 7 | 2010-11 | hajduk split | prva hnl | 17 | 6 |
| 8 | 2011-12 | lokomotiv | rfpl | 28 | 4 |
| 9 | 2012-13 | gaziantepspor | super lig | 1 | 1 | | | | goals |
|---:|--------:|
| 0 | 4 | | [
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select count ( information ) where information = 'nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords' col : date | operation | location | type | information row 1 : 16 july 1992 - 22 november 1992 | operation maritime monitor | international waters off serbia | naval blockade | naval blockade aimed at enforcing sanctions stipulated in un security council resolutions 713 and 757 row 2 : 16 october 1992 - 12 april 1993 | operation sky monitor (resolution 781) | bosnian airspace | no-fly zone | established a no-fly zone over the airspace of bosnia and herzegovina. effectiveness of the no-fly zone is debatable as by april 1993 500 violations (by all sides) of the no-fly zone had been recorded. nato members voted for an "all necessary measures" resolution by the united nations to allow nato a mandate to enforce the no-fly zone more stringently row 3 : 22 november 1992 - 1993 | operation maritime guard (resolution 787) | international waters in adriatic sea | naval blockade | authorized nato to use force, and included stopping, inspecting, and diverting ships bound for the former yugoslavia. all ships bound to or coming from the territorial waters of the former yugoslavia were halted for inspection and verification of their cargoes and destinations row 4 : 13 april 1993 - 20 december 1995 | operation deny flight (resolutions 816 and 836) | bosnian airspace | no-fly zone | resolution 816 extended the ban to cover flights by all fixed-wing and rotary-wing aircraft over the country, and to use all measures necessary to ensure compliance with the ban. resolution 836 authorized the use of force by unprofor in the protection of specially designated un "safe areas" row 5 : 15 june 1993 - 2 october 1996 | operation sharp guard (numerous resolutions) | yugoslavia | naval blockade | a widespread naval blockade aimed at all former yugoslavia row 6 : 30 august - 20 september 1995 | operation deliberate force | bosnia and herzegovina | air campaign | involving approximately 400 aircraft, deliberate force targeted at the army of republika srpska whose presence in bosnia posed a danger to united nations "safe areas" row 7 : 20 december 1995 - 20 december 1996 | operation joint endeavour | bosnia and herzegovina | peacekeeping force | nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords row 8 : 21 december 1996 - 19 june 1998 | operation joint guard | bosnia and herzegovina | peacekeeping force | nato-led stabilisation force(sfor) peacekeeping force which replaced the ifor which was a force tasked with enforcing peace under the dayton accords row 9 : 20 june 1998 - 2 december 2004 | operation joint forge | bosnia and herzegovina | peacekeeping force | a continuation of operation joint guard | col : count ( "information" ) row 1 : 1 | select count ( information ) where information = 'nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords' <table_name> : table \begin{tabular}{llllll}
\toprule
& date & operation & location & type & information \\
\midrule
0 & 16 july 1992 - 22 november 1992 & operation maritime monitor & international waters off serbia & naval blockade & naval blockade aimed at enforcing sanctions stipulated in un security council resolutions 713 and 757 \\
1 & 16 october 1992 - 12 april 1993 & operation sky monitor (resolution 781) & bosnian airspace & no-fly zone & established a no-fly zone over the airspace of bosnia and herzegovina. effectiveness of the no-fly zone is debatable as by april 1993 500 violations (by all sides) of the no-fly zone had been recorded. nato members voted for an "all necessary measures" resolution by the united nations to allow nato a mandate to enforce the no-fly zone more stringently \\
2 & 22 november 1992 - 1993 & operation maritime guard (resolution 787) & international waters in adriatic sea & naval blockade & authorized nato to use force, and included stopping, inspecting, and diverting ships bound for the former yugoslavia. all ships bound to or coming from the territorial waters of the former yugoslavia were halted for inspection and verification of their cargoes and destinations \\
3 & 13 april 1993 - 20 december 1995 & operation deny flight (resolutions 816 and 836) & bosnian airspace & no-fly zone & resolution 816 extended the ban to cover flights by all fixed-wing and rotary-wing aircraft over the country, and to use all measures necessary to ensure compliance with the ban. resolution 836 authorized the use of force by unprofor in the protection of specially designated un "safe areas" \\
4 & 15 june 1993 - 2 october 1996 & operation sharp guard (numerous resolutions) & yugoslavia & naval blockade & a widespread naval blockade aimed at all former yugoslavia \\
5 & 30 august - 20 september 1995 & operation deliberate force & bosnia and herzegovina & air campaign & involving approximately 400 aircraft, deliberate force targeted at the army of republika srpska whose presence in bosnia posed a danger to united nations "safe areas" \\
6 & 20 december 1995 - 20 december 1996 & operation joint endeavour & bosnia and herzegovina & peacekeeping force & nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords \\
7 & 21 december 1996 - 19 june 1998 & operation joint guard & bosnia and herzegovina & peacekeeping force & nato-led stabilisation force(sfor) peacekeeping force which replaced the ifor which was a force tasked with enforcing peace under the dayton accords \\
8 & 20 june 1998 - 2 december 2004 & operation joint forge & bosnia and herzegovina & peacekeeping force & a continuation of operation joint guard \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "information" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( information ) where information = 'nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>operation</th>
<th>location</th>
<th>type</th>
<th>information</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16 july 1992 - 22 november 1992</td>
<td>operation maritime monitor</td>
<td>international waters off serbia</td>
<td>naval blockade</td>
<td>naval blockade aimed at enforcing sanctions stipulated in un security council resolutions 713 and 757</td>
</tr>
<tr>
<th>1</th>
<td>16 october 1992 - 12 april 1993</td>
<td>operation sky monitor (resolution 781)</td>
<td>bosnian airspace</td>
<td>no-fly zone</td>
<td>established a no-fly zone over the airspace of bosnia and herzegovina. effectiveness of the no-fly zone is debatable as by april 1993 500 violations (by all sides) of the no-fly zone had been recorded. nato members voted for an "all necessary measures" resolution by the united nations to allow nato a mandate to enforce the no-fly zone more stringently</td>
</tr>
<tr>
<th>2</th>
<td>22 november 1992 - 1993</td>
<td>operation maritime guard (resolution 787)</td>
<td>international waters in adriatic sea</td>
<td>naval blockade</td>
<td>authorized nato to use force, and included stopping, inspecting, and diverting ships bound for the former yugoslavia. all ships bound to or coming from the territorial waters of the former yugoslavia were halted for inspection and verification of their cargoes and destinations</td>
</tr>
<tr>
<th>3</th>
<td>13 april 1993 - 20 december 1995</td>
<td>operation deny flight (resolutions 816 and 836)</td>
<td>bosnian airspace</td>
<td>no-fly zone</td>
<td>resolution 816 extended the ban to cover flights by all fixed-wing and rotary-wing aircraft over the country, and to use all measures necessary to ensure compliance with the ban. resolution 836 authorized the use of force by unprofor in the protection of specially designated un "safe areas"</td>
</tr>
<tr>
<th>4</th>
<td>15 june 1993 - 2 october 1996</td>
<td>operation sharp guard (numerous resolutions)</td>
<td>yugoslavia</td>
<td>naval blockade</td>
<td>a widespread naval blockade aimed at all former yugoslavia</td>
</tr>
<tr>
<th>5</th>
<td>30 august - 20 september 1995</td>
<td>operation deliberate force</td>
<td>bosnia and herzegovina</td>
<td>air campaign</td>
<td>involving approximately 400 aircraft, deliberate force targeted at the army of republika srpska whose presence in bosnia posed a danger to united nations "safe areas"</td>
</tr>
<tr>
<th>6</th>
<td>20 december 1995 - 20 december 1996</td>
<td>operation joint endeavour</td>
<td>bosnia and herzegovina</td>
<td>peacekeeping force</td>
<td>nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords</td>
</tr>
<tr>
<th>7</th>
<td>21 december 1996 - 19 june 1998</td>
<td>operation joint guard</td>
<td>bosnia and herzegovina</td>
<td>peacekeeping force</td>
<td>nato-led stabilisation force(sfor) peacekeeping force which replaced the ifor which was a force tasked with enforcing peace under the dayton accords</td>
</tr>
<tr>
<th>8</th>
<td>20 june 1998 - 2 december 2004</td>
<td>operation joint forge</td>
<td>bosnia and herzegovina</td>
<td>peacekeeping force</td>
<td>a continuation of operation joint guard</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "information" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( information ) where information = 'nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords' <table_name> : table | | date | operation | location | type | information |
|---:|:------------------------------------|:------------------------------------------------|:-------------------------------------|:-------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 16 july 1992 - 22 november 1992 | operation maritime monitor | international waters off serbia | naval blockade | naval blockade aimed at enforcing sanctions stipulated in un security council resolutions 713 and 757 |
| 1 | 16 october 1992 - 12 april 1993 | operation sky monitor (resolution 781) | bosnian airspace | no-fly zone | established a no-fly zone over the airspace of bosnia and herzegovina. effectiveness of the no-fly zone is debatable as by april 1993 500 violations (by all sides) of the no-fly zone had been recorded. nato members voted for an "all necessary measures" resolution by the united nations to allow nato a mandate to enforce the no-fly zone more stringently |
| 2 | 22 november 1992 - 1993 | operation maritime guard (resolution 787) | international waters in adriatic sea | naval blockade | authorized nato to use force, and included stopping, inspecting, and diverting ships bound for the former yugoslavia. all ships bound to or coming from the territorial waters of the former yugoslavia were halted for inspection and verification of their cargoes and destinations |
| 3 | 13 april 1993 - 20 december 1995 | operation deny flight (resolutions 816 and 836) | bosnian airspace | no-fly zone | resolution 816 extended the ban to cover flights by all fixed-wing and rotary-wing aircraft over the country, and to use all measures necessary to ensure compliance with the ban. resolution 836 authorized the use of force by unprofor in the protection of specially designated un "safe areas" |
| 4 | 15 june 1993 - 2 october 1996 | operation sharp guard (numerous resolutions) | yugoslavia | naval blockade | a widespread naval blockade aimed at all former yugoslavia |
| 5 | 30 august - 20 september 1995 | operation deliberate force | bosnia and herzegovina | air campaign | involving approximately 400 aircraft, deliberate force targeted at the army of republika srpska whose presence in bosnia posed a danger to united nations "safe areas" |
| 6 | 20 december 1995 - 20 december 1996 | operation joint endeavour | bosnia and herzegovina | peacekeeping force | nato-led implementation force(ifor) peacekeeping force was established which was a force tasked with enforcing the peace under the dayton accords |
| 7 | 21 december 1996 - 19 june 1998 | operation joint guard | bosnia and herzegovina | peacekeeping force | nato-led stabilisation force(sfor) peacekeeping force which replaced the ifor which was a force tasked with enforcing peace under the dayton accords |
| 8 | 20 june 1998 - 2 december 2004 | operation joint forge | bosnia and herzegovina | peacekeeping force | a continuation of operation joint guard | | | | count ( "information" ) |
|---:|--------------------------:|
| 0 | 1 | | [
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select count ( opponent ) where site = 'davis wade stadium • starkville, ms' 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 : count ( "opponent" ) row 1 : 5 | select count ( opponent ) where site = 'davis wade stadium • starkville, ms' <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
& count ( "opponent" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( opponent ) where site = 'davis wade stadium • starkville, ms' <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>count ( "opponent" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( opponent ) where site = 'davis wade stadium • starkville, ms' <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 | | | | count ( "opponent" ) |
|---:|-----------------------:|
| 0 | 5 | | [
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select conference where attendance = 380 col : conference | date | place | attendance | archive of presentations row 1 : wikimania 2005 | 2007-08-05 00:00:00 | frankfurt, germany | 380 | slides, video row 2 : wikimania 2006 | 2006-08-04 00:00:00 | cambridge, united states | 400 | slides and papers, video row 3 : wikimania 2007 | 2005-08-03 00:00:00 | taipei, roc (taiwan) | 440 | commons gallery row 4 : wikimania 2008 | 2019-07-17 00:00:00 | alexandria, egypt | 650 | abstracts, slides,video row 5 : wikimania 2009 | 2028-08-26 00:00:00 | buenos aires, argentina | 559 | slides, video row 6 : wikimania 2010 | 2011-07-09 00:00:00 | gdansk, poland | about 500 | slides row 7 : wikimania 2011 | 2007-08-04 00:00:00 | haifa, israel | 720 | presentations, video row 8 : wikimania 2012 | 2015-07-12 00:00:00 | washington, d.c., united states | 1400 | presentations, videos row 9 : wikimania 2013 | 2011-08-07 00:00:00 | hong kong | 700 | presentations, videos row 10 : wikimania 2014 | 2010-08-06 00:00:00 | london, united kingdom | none | none | col : conference row 1 : wikimania 2005 | select conference where attendance = 380 <table_name> : table \begin{tabular}{llllll}
\toprule
& conference & date & place & attendance & archive of presentations \\
\midrule
0 & wikimania 2005 & 2007-08-05 00:00:00 & frankfurt, germany & 380 & slides, video \\
1 & wikimania 2006 & 2006-08-04 00:00:00 & cambridge, united states & 400 & slides and papers, video \\
2 & wikimania 2007 & 2005-08-03 00:00:00 & taipei, roc (taiwan) & 440 & commons gallery \\
3 & wikimania 2008 & 2019-07-17 00:00:00 & alexandria, egypt & 650 & abstracts, slides,video \\
4 & wikimania 2009 & 2028-08-26 00:00:00 & buenos aires, argentina & 559 & slides, video \\
5 & wikimania 2010 & 2011-07-09 00:00:00 & gdansk, poland & about 500 & slides \\
6 & wikimania 2011 & 2007-08-04 00:00:00 & haifa, israel & 720 & presentations, video \\
7 & wikimania 2012 & 2015-07-12 00:00:00 & washington, d.c., united states & 1400 & presentations, videos \\
8 & wikimania 2013 & 2011-08-07 00:00:00 & hong kong & 700 & presentations, videos \\
9 & wikimania 2014 & 2010-08-06 00:00:00 & london, united kingdom & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& conference \\
\midrule
0 & wikimania 2005 \\
\bottomrule
\end{tabular}
| select conference where attendance = 380 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>conference</th>
<th>date</th>
<th>place</th>
<th>attendance</th>
<th>archive of presentations</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>wikimania 2005</td>
<td>2007-08-05 00:00:00</td>
<td>frankfurt, germany</td>
<td>380</td>
<td>slides, video</td>
</tr>
<tr>
<th>1</th>
<td>wikimania 2006</td>
<td>2006-08-04 00:00:00</td>
<td>cambridge, united states</td>
<td>400</td>
<td>slides and papers, video</td>
</tr>
<tr>
<th>2</th>
<td>wikimania 2007</td>
<td>2005-08-03 00:00:00</td>
<td>taipei, roc (taiwan)</td>
<td>440</td>
<td>commons gallery</td>
</tr>
<tr>
<th>3</th>
<td>wikimania 2008</td>
<td>2019-07-17 00:00:00</td>
<td>alexandria, egypt</td>
<td>650</td>
<td>abstracts, slides,video</td>
</tr>
<tr>
<th>4</th>
<td>wikimania 2009</td>
<td>2028-08-26 00:00:00</td>
<td>buenos aires, argentina</td>
<td>559</td>
<td>slides, video</td>
</tr>
<tr>
<th>5</th>
<td>wikimania 2010</td>
<td>2011-07-09 00:00:00</td>
<td>gdansk, poland</td>
<td>about 500</td>
<td>slides</td>
</tr>
<tr>
<th>6</th>
<td>wikimania 2011</td>
<td>2007-08-04 00:00:00</td>
<td>haifa, israel</td>
<td>720</td>
<td>presentations, video</td>
</tr>
<tr>
<th>7</th>
<td>wikimania 2012</td>
<td>2015-07-12 00:00:00</td>
<td>washington, d.c., united states</td>
<td>1400</td>
<td>presentations, videos</td>
</tr>
<tr>
<th>8</th>
<td>wikimania 2013</td>
<td>2011-08-07 00:00:00</td>
<td>hong kong</td>
<td>700</td>
<td>presentations, videos</td>
</tr>
<tr>
<th>9</th>
<td>wikimania 2014</td>
<td>2010-08-06 00:00:00</td>
<td>london, united kingdom</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>conference</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>wikimania 2005</td>
</tr>
</tbody>
</table> | select conference where attendance = 380 <table_name> : table | | conference | date | place | attendance | archive of presentations |
|---:|:---------------|:--------------------|:--------------------------------|:-------------|:---------------------------|
| 0 | wikimania 2005 | 2007-08-05 00:00:00 | frankfurt, germany | 380 | slides, video |
| 1 | wikimania 2006 | 2006-08-04 00:00:00 | cambridge, united states | 400 | slides and papers, video |
| 2 | wikimania 2007 | 2005-08-03 00:00:00 | taipei, roc (taiwan) | 440 | commons gallery |
| 3 | wikimania 2008 | 2019-07-17 00:00:00 | alexandria, egypt | 650 | abstracts, slides,video |
| 4 | wikimania 2009 | 2028-08-26 00:00:00 | buenos aires, argentina | 559 | slides, video |
| 5 | wikimania 2010 | 2011-07-09 00:00:00 | gdansk, poland | about 500 | slides |
| 6 | wikimania 2011 | 2007-08-04 00:00:00 | haifa, israel | 720 | presentations, video |
| 7 | wikimania 2012 | 2015-07-12 00:00:00 | washington, d.c., united states | 1400 | presentations, videos |
| 8 | wikimania 2013 | 2011-08-07 00:00:00 | hong kong | 700 | presentations, videos |
| 9 | wikimania 2014 | 2010-08-06 00:00:00 | london, united kingdom | none | none | | | | conference |
|---:|:---------------|
| 0 | wikimania 2005 | | [
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select count ( team ) where team = '16' col : year | team | games | combined tackles | tackles | assisted tackles | sacks | forced fumbles | fumble recoveries | fumble return yards | interceptions | interception return yards | yards per interception return | longest interception return | interceptions returned for touchdown | passes defended row 1 : 2002 | buf | 16 | 96 | 71 | 25 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 row 2 : 2003 | buf | 16 | 28 | 24 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 row 3 : 2004 | buf | 12 | 25 | 14 | 11 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 4 : 2005 | buf | 13 | 9 | 6 | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 5 : 2006 | buf | 16 | 23 | 13 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 6 : 2007 | buf | 7 | 4 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 7 : 2008 | atl | 16 | 34 | 28 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 row 8 : 2009 | atl | 16 | 17 | 15 | 2 | 0 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 row 9 : 2010 | atl | 15 | 12 | 8 | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 10 : career | none | 127 | 248 | 182 | 66 | 5 | 2 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | col : count ( "team" ) row 1 : 0 | select count ( team ) where team = '16' <table_name> : table \begin{tabular}{lllllllllllllllll}
\toprule
& year & team & games & combined tackles & tackles & assisted tackles & sacks & forced fumbles & fumble recoveries & fumble return yards & interceptions & interception return yards & yards per interception return & longest interception return & interceptions returned for touchdown & passes defended \\
\midrule
0 & 2002 & buf & 16 & 96 & 71 & 25 & 3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
1 & 2003 & buf & 16 & 28 & 24 & 4 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 \\
2 & 2004 & buf & 12 & 25 & 14 & 11 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
3 & 2005 & buf & 13 & 9 & 6 & 3 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
4 & 2006 & buf & 16 & 23 & 13 & 10 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
5 & 2007 & buf & 7 & 4 & 3 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
6 & 2008 & atl & 16 & 34 & 28 & 6 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
7 & 2009 & atl & 16 & 17 & 15 & 2 & 0 & 1 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
8 & 2010 & atl & 15 & 12 & 8 & 4 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
9 & career & none & 127 & 248 & 182 & 66 & 5 & 2 & 4 & 0 & 0 & 0 & 0 & 0 & 0 & 5 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "team" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( team ) where team = '16' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>team</th>
<th>games</th>
<th>combined tackles</th>
<th>tackles</th>
<th>assisted tackles</th>
<th>sacks</th>
<th>forced fumbles</th>
<th>fumble recoveries</th>
<th>fumble return yards</th>
<th>interceptions</th>
<th>interception return yards</th>
<th>yards per interception return</th>
<th>longest interception return</th>
<th>interceptions returned for touchdown</th>
<th>passes defended</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002</td>
<td>buf</td>
<td>16</td>
<td>96</td>
<td>71</td>
<td>25</td>
<td>3</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>1</td>
</tr>
<tr>
<th>1</th>
<td>2003</td>
<td>buf</td>
<td>16</td>
<td>28</td>
<td>24</td>
<td>4</td>
<td>1</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>2</td>
</tr>
<tr>
<th>2</th>
<td>2004</td>
<td>buf</td>
<td>12</td>
<td>25</td>
<td>14</td>
<td>11</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>2005</td>
<td>buf</td>
<td>13</td>
<td>9</td>
<td>6</td>
<td>3</td>
<td>0</td>
<td>1</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>
</tr>
<tr>
<th>4</th>
<td>2006</td>
<td>buf</td>
<td>16</td>
<td>23</td>
<td>13</td>
<td>10</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>0</td>
</tr>
<tr>
<th>5</th>
<td>2007</td>
<td>buf</td>
<td>7</td>
<td>4</td>
<td>3</td>
<td>1</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>0</td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>atl</td>
<td>16</td>
<td>34</td>
<td>28</td>
<td>6</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>1</td>
</tr>
<tr>
<th>7</th>
<td>2009</td>
<td>atl</td>
<td>16</td>
<td>17</td>
<td>15</td>
<td>2</td>
<td>0</td>
<td>1</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>2010</td>
<td>atl</td>
<td>15</td>
<td>12</td>
<td>8</td>
<td>4</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>career</td>
<td>none</td>
<td>127</td>
<td>248</td>
<td>182</td>
<td>66</td>
<td>5</td>
<td>2</td>
<td>4</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>5</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>0</td>
</tr>
</tbody>
</table> | select count ( team ) where team = '16' <table_name> : table | | year | team | games | combined tackles | tackles | assisted tackles | sacks | forced fumbles | fumble recoveries | fumble return yards | interceptions | interception return yards | yards per interception return | longest interception return | interceptions returned for touchdown | passes defended |
|---:|:-------|:-------|--------:|-------------------:|----------:|-------------------:|--------:|-----------------:|--------------------:|----------------------:|----------------:|----------------------------:|--------------------------------:|------------------------------:|---------------------------------------:|------------------:|
| 0 | 2002 | buf | 16 | 96 | 71 | 25 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 1 | 2003 | buf | 16 | 28 | 24 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| 2 | 2004 | buf | 12 | 25 | 14 | 11 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | 2005 | buf | 13 | 9 | 6 | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | 2006 | buf | 16 | 23 | 13 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 5 | 2007 | buf | 7 | 4 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 6 | 2008 | atl | 16 | 34 | 28 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 7 | 2009 | atl | 16 | 17 | 15 | 2 | 0 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 8 | 2010 | atl | 15 | 12 | 8 | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 9 | career | none | 127 | 248 | 182 | 66 | 5 | 2 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | | | | count ( "team" ) |
|---:|-------------------:|
| 0 | 0 | | [
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] |
select pos where time = '41.399' col : pos | no | rider | manufacturer | laps | time | grid | points row 1 : 1 | 46 | valentino rossi | yamaha | 21 | 43:06.007 | 2 | 25 row 2 : 2 | 2 | dani pedrosa | honda | 21 | 4.008 | 1 | 20 row 3 : 3 | 4 | andrea dovizioso | honda | 21 | 8.536 | 6 | 16 row 4 : 4 | 69 | nicky hayden | honda | 21 | 8.858 | 4 | 13 row 5 : 5 | 56 | shinya nakano | honda | 21 | 10.583 | 15 | 11 row 6 : 6 | 1 | casey stoner | ducati | 21 | 13.64 | 7 | 10 row 7 : 7 | 65 | loris capirossi | suzuki | 21 | 15.936 | 8 | 9 row 8 : 8 | 5 | colin edwards | yamaha | 21 | 18.802 | 5 | 8 row 9 : 9 | 7 | chris vermeulen | suzuki | 21 | 23.174 | 11 | 7 row 10 : 10 | 14 | randy de puniet | honda | 21 | 25.516 | 9 | 6 row 11 : 11 | 21 | john hopkins | kawasaki | 21 | 27.609 | 10 | 5 row 12 : 12 | 13 | anthony west | kawasaki | 21 | 41.399 | 13 | 4 row 13 : 13 | 50 | sylvain guintoli | ducati | 21 | 45.617 | 16 | 3 row 14 : 14 | 15 | alex de angelis | honda | 21 | 49.003 | 17 | 2 row 15 : 15 | 24 | toni elias | ducati | 21 | 59.139 | 19 | 1 row 16 : 16 | 33 | marco melandri | ducati | 21 | +1:03.328 | 14 | none row 17 : 17 | 9 | nobuatsu aoki | suzuki | 21 | +1:48.363 | 18 | none row 18 : ret | 48 | jorge lorenzo | yamaha | 12 | accident | 3 | none row 19 : ret | 52 | james toseland | yamaha | 2 | accident | 12 | none | col : pos row 1 : 12 | select pos where time = '41.399' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & rider & manufacturer & laps & time & grid & points \\
\midrule
0 & 1 & 46 & valentino rossi & yamaha & 21 & 43:06.007 & 2 & 25 \\
1 & 2 & 2 & dani pedrosa & honda & 21 & 4.008 & 1 & 20 \\
2 & 3 & 4 & andrea dovizioso & honda & 21 & 8.536 & 6 & 16 \\
3 & 4 & 69 & nicky hayden & honda & 21 & 8.858 & 4 & 13 \\
4 & 5 & 56 & shinya nakano & honda & 21 & 10.583 & 15 & 11 \\
5 & 6 & 1 & casey stoner & ducati & 21 & 13.64 & 7 & 10 \\
6 & 7 & 65 & loris capirossi & suzuki & 21 & 15.936 & 8 & 9 \\
7 & 8 & 5 & colin edwards & yamaha & 21 & 18.802 & 5 & 8 \\
8 & 9 & 7 & chris vermeulen & suzuki & 21 & 23.174 & 11 & 7 \\
9 & 10 & 14 & randy de puniet & honda & 21 & 25.516 & 9 & 6 \\
10 & 11 & 21 & john hopkins & kawasaki & 21 & 27.609 & 10 & 5 \\
11 & 12 & 13 & anthony west & kawasaki & 21 & 41.399 & 13 & 4 \\
12 & 13 & 50 & sylvain guintoli & ducati & 21 & 45.617 & 16 & 3 \\
13 & 14 & 15 & alex de angelis & honda & 21 & 49.003 & 17 & 2 \\
14 & 15 & 24 & toni elias & ducati & 21 & 59.139 & 19 & 1 \\
15 & 16 & 33 & marco melandri & ducati & 21 & +1:03.328 & 14 & none \\
16 & 17 & 9 & nobuatsu aoki & suzuki & 21 & +1:48.363 & 18 & none \\
17 & ret & 48 & jorge lorenzo & yamaha & 12 & accident & 3 & none \\
18 & ret & 52 & james toseland & yamaha & 2 & accident & 12 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& pos \\
\midrule
0 & 12 \\
\bottomrule
\end{tabular}
| select pos where time = '41.399' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>rider</th>
<th>manufacturer</th>
<th>laps</th>
<th>time</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>46</td>
<td>valentino rossi</td>
<td>yamaha</td>
<td>21</td>
<td>43:06.007</td>
<td>2</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2</td>
<td>dani pedrosa</td>
<td>honda</td>
<td>21</td>
<td>4.008</td>
<td>1</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>4</td>
<td>andrea dovizioso</td>
<td>honda</td>
<td>21</td>
<td>8.536</td>
<td>6</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>69</td>
<td>nicky hayden</td>
<td>honda</td>
<td>21</td>
<td>8.858</td>
<td>4</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>56</td>
<td>shinya nakano</td>
<td>honda</td>
<td>21</td>
<td>10.583</td>
<td>15</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1</td>
<td>casey stoner</td>
<td>ducati</td>
<td>21</td>
<td>13.64</td>
<td>7</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>65</td>
<td>loris capirossi</td>
<td>suzuki</td>
<td>21</td>
<td>15.936</td>
<td>8</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>5</td>
<td>colin edwards</td>
<td>yamaha</td>
<td>21</td>
<td>18.802</td>
<td>5</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>7</td>
<td>chris vermeulen</td>
<td>suzuki</td>
<td>21</td>
<td>23.174</td>
<td>11</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>14</td>
<td>randy de puniet</td>
<td>honda</td>
<td>21</td>
<td>25.516</td>
<td>9</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>21</td>
<td>john hopkins</td>
<td>kawasaki</td>
<td>21</td>
<td>27.609</td>
<td>10</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>13</td>
<td>anthony west</td>
<td>kawasaki</td>
<td>21</td>
<td>41.399</td>
<td>13</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>50</td>
<td>sylvain guintoli</td>
<td>ducati</td>
<td>21</td>
<td>45.617</td>
<td>16</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>15</td>
<td>alex de angelis</td>
<td>honda</td>
<td>21</td>
<td>49.003</td>
<td>17</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>24</td>
<td>toni elias</td>
<td>ducati</td>
<td>21</td>
<td>59.139</td>
<td>19</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>33</td>
<td>marco melandri</td>
<td>ducati</td>
<td>21</td>
<td>+1:03.328</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>9</td>
<td>nobuatsu aoki</td>
<td>suzuki</td>
<td>21</td>
<td>+1:48.363</td>
<td>18</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>48</td>
<td>jorge lorenzo</td>
<td>yamaha</td>
<td>12</td>
<td>accident</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>52</td>
<td>james toseland</td>
<td>yamaha</td>
<td>2</td>
<td>accident</td>
<td>12</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>12</td>
</tr>
</tbody>
</table> | select pos where time = '41.399' <table_name> : table | | pos | no | rider | manufacturer | laps | time | grid | points |
|---:|:------|-----:|:-----------------|:---------------|-------:|:----------|-------:|:---------|
| 0 | 1 | 46 | valentino rossi | yamaha | 21 | 43:06.007 | 2 | 25 |
| 1 | 2 | 2 | dani pedrosa | honda | 21 | 4.008 | 1 | 20 |
| 2 | 3 | 4 | andrea dovizioso | honda | 21 | 8.536 | 6 | 16 |
| 3 | 4 | 69 | nicky hayden | honda | 21 | 8.858 | 4 | 13 |
| 4 | 5 | 56 | shinya nakano | honda | 21 | 10.583 | 15 | 11 |
| 5 | 6 | 1 | casey stoner | ducati | 21 | 13.64 | 7 | 10 |
| 6 | 7 | 65 | loris capirossi | suzuki | 21 | 15.936 | 8 | 9 |
| 7 | 8 | 5 | colin edwards | yamaha | 21 | 18.802 | 5 | 8 |
| 8 | 9 | 7 | chris vermeulen | suzuki | 21 | 23.174 | 11 | 7 |
| 9 | 10 | 14 | randy de puniet | honda | 21 | 25.516 | 9 | 6 |
| 10 | 11 | 21 | john hopkins | kawasaki | 21 | 27.609 | 10 | 5 |
| 11 | 12 | 13 | anthony west | kawasaki | 21 | 41.399 | 13 | 4 |
| 12 | 13 | 50 | sylvain guintoli | ducati | 21 | 45.617 | 16 | 3 |
| 13 | 14 | 15 | alex de angelis | honda | 21 | 49.003 | 17 | 2 |
| 14 | 15 | 24 | toni elias | ducati | 21 | 59.139 | 19 | 1 |
| 15 | 16 | 33 | marco melandri | ducati | 21 | +1:03.328 | 14 | none |
| 16 | 17 | 9 | nobuatsu aoki | suzuki | 21 | +1:48.363 | 18 | none |
| 17 | ret | 48 | jorge lorenzo | yamaha | 12 | accident | 3 | none |
| 18 | ret | 52 | james toseland | yamaha | 2 | accident | 12 | none | | | | pos |
|---:|------:|
| 0 | 12 | | [
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select character where character = 'caz' 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 : character row 1 : caz | select character where character = 'caz' <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
& character \\
\midrule
0 & caz \\
\bottomrule
\end{tabular}
| select character where character = 'caz' <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>character</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>caz</td>
</tr>
</tbody>
</table> | select character where character = 'caz' <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 | | | | character |
|---:|:------------|
| 0 | caz | | [
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select # where office = 'public regulation commissioner' col : # | office | current officer row 1 : none | may succeed to governorship | none row 2 : none | governor of new mexico | susana martinez row 3 : 1 | lieutenant governor of new mexico | john sanchez row 4 : 2 | secretary of state of new mexico | dianna duran row 5 : 3 | president pro tempore of the senate | mary kay papen row 6 : 4 | speaker of the house of representatives | w. ken martinez row 7 : none | may serve as emergency interim successor | none row 8 : 4 | attorney general of new mexico | gary king row 9 : 5 | state auditor | hector balderas row 10 : 6 | state treasurer | james b. lewis row 11 : 7 | commissioner of public lands | ray powell row 12 : 8 | ,public regulation commission,, chair, | patrick lyons row 13 : 9 | public regulation commissioner | karen montoya row 14 : 10 | public regulation commissioner | valerie espinoza row 15 : 11 | public regulation commissioner | theresa becenti-aguilar row 16 : 12 | public regulation commissioner | ben hall | col : # row 1 : 9 row 2 : 10 row 3 : 11 row 4 : 12 | select # where office = 'public regulation commissioner' <table_name> : table \begin{tabular}{llll}
\toprule
& # & office & current officer \\
\midrule
0 & none & may succeed to governorship & none \\
1 & none & governor of new mexico & susana martinez \\
2 & 1 & lieutenant governor of new mexico & john sanchez \\
3 & 2 & secretary of state of new mexico & dianna duran \\
4 & 3 & president pro tempore of the senate & mary kay papen \\
5 & 4 & speaker of the house of representatives & w. ken martinez \\
6 & none & may serve as emergency interim successor & none \\
7 & 4 & attorney general of new mexico & gary king \\
8 & 5 & state auditor & hector balderas \\
9 & 6 & state treasurer & james b. lewis \\
10 & 7 & commissioner of public lands & ray powell \\
11 & 8 & ,public regulation commission,, chair, & patrick lyons \\
12 & 9 & public regulation commissioner & karen montoya \\
13 & 10 & public regulation commissioner & valerie espinoza \\
14 & 11 & public regulation commissioner & theresa becenti-aguilar \\
15 & 12 & public regulation commissioner & ben hall \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& # \\
\midrule
0 & 9 \\
1 & 10 \\
2 & 11 \\
3 & 12 \\
\bottomrule
\end{tabular}
| select # where office = 'public regulation commissioner' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>office</th>
<th>current officer</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>may succeed to governorship</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>governor of new mexico</td>
<td>susana martinez</td>
</tr>
<tr>
<th>2</th>
<td>1</td>
<td>lieutenant governor of new mexico</td>
<td>john sanchez</td>
</tr>
<tr>
<th>3</th>
<td>2</td>
<td>secretary of state of new mexico</td>
<td>dianna duran</td>
</tr>
<tr>
<th>4</th>
<td>3</td>
<td>president pro tempore of the senate</td>
<td>mary kay papen</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>speaker of the house of representatives</td>
<td>w. ken martinez</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
<td>may serve as emergency interim successor</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>4</td>
<td>attorney general of new mexico</td>
<td>gary king</td>
</tr>
<tr>
<th>8</th>
<td>5</td>
<td>state auditor</td>
<td>hector balderas</td>
</tr>
<tr>
<th>9</th>
<td>6</td>
<td>state treasurer</td>
<td>james b. lewis</td>
</tr>
<tr>
<th>10</th>
<td>7</td>
<td>commissioner of public lands</td>
<td>ray powell</td>
</tr>
<tr>
<th>11</th>
<td>8</td>
<td>,public regulation commission,, chair,</td>
<td>patrick lyons</td>
</tr>
<tr>
<th>12</th>
<td>9</td>
<td>public regulation commissioner</td>
<td>karen montoya</td>
</tr>
<tr>
<th>13</th>
<td>10</td>
<td>public regulation commissioner</td>
<td>valerie espinoza</td>
</tr>
<tr>
<th>14</th>
<td>11</td>
<td>public regulation commissioner</td>
<td>theresa becenti-aguilar</td>
</tr>
<tr>
<th>15</th>
<td>12</td>
<td>public regulation commissioner</td>
<td>ben hall</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
<tr>
<th>1</th>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>11</td>
</tr>
<tr>
<th>3</th>
<td>12</td>
</tr>
</tbody>
</table> | select # where office = 'public regulation commissioner' <table_name> : table | | # | office | current officer |
|---:|:-----|:-----------------------------------------|:------------------------|
| 0 | none | may succeed to governorship | none |
| 1 | none | governor of new mexico | susana martinez |
| 2 | 1 | lieutenant governor of new mexico | john sanchez |
| 3 | 2 | secretary of state of new mexico | dianna duran |
| 4 | 3 | president pro tempore of the senate | mary kay papen |
| 5 | 4 | speaker of the house of representatives | w. ken martinez |
| 6 | none | may serve as emergency interim successor | none |
| 7 | 4 | attorney general of new mexico | gary king |
| 8 | 5 | state auditor | hector balderas |
| 9 | 6 | state treasurer | james b. lewis |
| 10 | 7 | commissioner of public lands | ray powell |
| 11 | 8 | ,public regulation commission,, chair, | patrick lyons |
| 12 | 9 | public regulation commissioner | karen montoya |
| 13 | 10 | public regulation commissioner | valerie espinoza |
| 14 | 11 | public regulation commissioner | theresa becenti-aguilar |
| 15 | 12 | public regulation commissioner | ben hall | | | | # |
|---:|----:|
| 0 | 9 |
| 1 | 10 |
| 2 | 11 |
| 3 | 12 | | [
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] |
select rank where team = 'cofidis' col : rank | rider | team | points row 1 : 1 | robbie mcewen (aus) | davitamon-lotto | 288 row 2 : 2 | erik zabel (ger) | team milram | 199 row 3 : 3 | thor hushovd (nor) | credit agricole | 195 row 4 : 4 | bernhard eisel (aut) | francaise des jeux | 176 row 5 : 5 | luca paolini (ita) | liquigas | 174 row 6 : 6 | inaki isasi (esp) | euskaltel-euskadi | 130 row 7 : 7 | francisco ventoso (esp) | saunier duval-prodir | 128 row 8 : 8 | cristian moreni (ita) | cofidis | 116 row 9 : 9 | jimmy casper (fra) | cofidis | 98 row 10 : 10 | oscar pereiro (esp) | caisse d'epargne-illes balears | 88 | col : rank row 1 : 8 row 2 : 9 | select rank where team = 'cofidis' <table_name> : table \begin{tabular}{lllll}
\toprule
& rank & rider & team & points \\
\midrule
0 & 1 & robbie mcewen (aus) & davitamon-lotto & 288 \\
1 & 2 & erik zabel (ger) & team milram & 199 \\
2 & 3 & thor hushovd (nor) & credit agricole & 195 \\
3 & 4 & bernhard eisel (aut) & francaise des jeux & 176 \\
4 & 5 & luca paolini (ita) & liquigas & 174 \\
5 & 6 & inaki isasi (esp) & euskaltel-euskadi & 130 \\
6 & 7 & francisco ventoso (esp) & saunier duval-prodir & 128 \\
7 & 8 & cristian moreni (ita) & cofidis & 116 \\
8 & 9 & jimmy casper (fra) & cofidis & 98 \\
9 & 10 & oscar pereiro (esp) & caisse d'epargne-illes balears & 88 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& rank \\
\midrule
0 & 8 \\
1 & 9 \\
\bottomrule
\end{tabular}
| select rank where team = 'cofidis' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>rider</th>
<th>team</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>robbie mcewen (aus)</td>
<td>davitamon-lotto</td>
<td>288</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>erik zabel (ger)</td>
<td>team milram</td>
<td>199</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>thor hushovd (nor)</td>
<td>credit agricole</td>
<td>195</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>bernhard eisel (aut)</td>
<td>francaise des jeux</td>
<td>176</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>luca paolini (ita)</td>
<td>liquigas</td>
<td>174</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>inaki isasi (esp)</td>
<td>euskaltel-euskadi</td>
<td>130</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>francisco ventoso (esp)</td>
<td>saunier duval-prodir</td>
<td>128</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>cristian moreni (ita)</td>
<td>cofidis</td>
<td>116</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>jimmy casper (fra)</td>
<td>cofidis</td>
<td>98</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>oscar pereiro (esp)</td>
<td>caisse d'epargne-illes balears</td>
<td>88</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>8</td>
</tr>
<tr>
<th>1</th>
<td>9</td>
</tr>
</tbody>
</table> | select rank where team = 'cofidis' <table_name> : table | | rank | rider | team | points |
|---:|-------:|:------------------------|:-------------------------------|---------:|
| 0 | 1 | robbie mcewen (aus) | davitamon-lotto | 288 |
| 1 | 2 | erik zabel (ger) | team milram | 199 |
| 2 | 3 | thor hushovd (nor) | credit agricole | 195 |
| 3 | 4 | bernhard eisel (aut) | francaise des jeux | 176 |
| 4 | 5 | luca paolini (ita) | liquigas | 174 |
| 5 | 6 | inaki isasi (esp) | euskaltel-euskadi | 130 |
| 6 | 7 | francisco ventoso (esp) | saunier duval-prodir | 128 |
| 7 | 8 | cristian moreni (ita) | cofidis | 116 |
| 8 | 9 | jimmy casper (fra) | cofidis | 98 |
| 9 | 10 | oscar pereiro (esp) | caisse d'epargne-illes balears | 88 | | | | rank |
|---:|-------:|
| 0 | 8 |
| 1 | 9 | | [
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select count ( * ) where status = 1 col : ship | hull no. | status | years active | nvr page row 1 : henry j. kaiser | t-ao-187 | active-southern california duty oiler | 1986-present | ao187 row 2 : joshua humphreys | t-ao-188 | inactivated 1996, returned to service 2005 | 1987-1996; 2005-2006; 2010-present | ao188 row 3 : john lenthall | t-ao-189 | active | 1987-1996; 1998-present | ao189 row 4 : andrew j. higgins | t-ao-190 | inactivated may 1996. sold to the chilean navy may 2009. towed to atlantic marine alabama shipyard, mobile, alabama, september 2009 for three-month refit. commissioned in chilean navy on 10 february 2010 and renamed almirante montt | 1987-1996 (usa); 2010-present (chile) | ao190 row 5 : benjamin isherwood | t-ao-191 | cancelled when 95.3% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011 | launched 1988, christened 1991, never in service | ao191 row 6 : henry eckford | t-ao-192 | cancelled when 84% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011 | launched 1989, never in service | ao192 row 7 : walter s. diehl | t-ao-193 | active | 1988-present | ao193 row 8 : john ericsson | t-ao-194 | active | 1991-present | ao194 row 9 : leroy grumman | t-ao-195 | active | 1989-present | ao195 row 10 : kanawha | t-ao-196 | active | 1991-present | ao196 row 11 : pecos | t-ao-197 | active | 1990-present | ao197 row 12 : big horn | t-ao-198 | active | 1992-present | ao198 row 13 : tippecanoe | t-ao-199 | active | 1993-present | ao199 row 14 : guadalupe | t-ao-200 | active | 1992-present | ao200 row 15 : patuxent | t-ao-201 | active | 1995-present | ao201 row 16 : yukon | t-ao-202 | active | 1994-present | ao202 row 17 : laramie | t-ao-203 | active | 1996-present | ao203 row 18 : rappahannock | t-ao-204 | active | 1995-present | ao204 | col : count ( "*" ) row 1 : 0 | select count ( * ) where status = 1 <table_name> : table \begin{tabular}{llllll}
\toprule
& ship & hull no. & status & years active & nvr page \\
\midrule
0 & henry j. kaiser & t-ao-187 & active-southern california duty oiler & 1986-present & ao187 \\
1 & joshua humphreys & t-ao-188 & inactivated 1996, returned to service 2005 & 1987-1996; 2005-2006; 2010-present & ao188 \\
2 & john lenthall & t-ao-189 & active & 1987-1996; 1998-present & ao189 \\
3 & andrew j. higgins & t-ao-190 & inactivated may 1996. sold to the chilean navy may 2009. towed to atlantic marine alabama shipyard, mobile, alabama, september 2009 for three-month refit. commissioned in chilean navy on 10 february 2010 and renamed almirante montt & 1987-1996 (usa); 2010-present (chile) & ao190 \\
4 & benjamin isherwood & t-ao-191 & cancelled when 95.3% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011 & launched 1988, christened 1991, never in service & ao191 \\
5 & henry eckford & t-ao-192 & cancelled when 84% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011 & launched 1989, never in service & ao192 \\
6 & walter s. diehl & t-ao-193 & active & 1988-present & ao193 \\
7 & john ericsson & t-ao-194 & active & 1991-present & ao194 \\
8 & leroy grumman & t-ao-195 & active & 1989-present & ao195 \\
9 & kanawha & t-ao-196 & active & 1991-present & ao196 \\
10 & pecos & t-ao-197 & active & 1990-present & ao197 \\
11 & big horn & t-ao-198 & active & 1992-present & ao198 \\
12 & tippecanoe & t-ao-199 & active & 1993-present & ao199 \\
13 & guadalupe & t-ao-200 & active & 1992-present & ao200 \\
14 & patuxent & t-ao-201 & active & 1995-present & ao201 \\
15 & yukon & t-ao-202 & active & 1994-present & ao202 \\
16 & laramie & t-ao-203 & active & 1996-present & ao203 \\
17 & rappahannock & t-ao-204 & active & 1995-present & ao204 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where status = 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>ship</th>
<th>hull no.</th>
<th>status</th>
<th>years active</th>
<th>nvr page</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>henry j. kaiser</td>
<td>t-ao-187</td>
<td>active-southern california duty oiler</td>
<td>1986-present</td>
<td>ao187</td>
</tr>
<tr>
<th>1</th>
<td>joshua humphreys</td>
<td>t-ao-188</td>
<td>inactivated 1996, returned to service 2005</td>
<td>1987-1996; 2005-2006; 2010-present</td>
<td>ao188</td>
</tr>
<tr>
<th>2</th>
<td>john lenthall</td>
<td>t-ao-189</td>
<td>active</td>
<td>1987-1996; 1998-present</td>
<td>ao189</td>
</tr>
<tr>
<th>3</th>
<td>andrew j. higgins</td>
<td>t-ao-190</td>
<td>inactivated may 1996. sold to the chilean navy may 2009. towed to atlantic marine alabama shipyard, mobile, alabama, september 2009 for three-month refit. commissioned in chilean navy on 10 february 2010 and renamed almirante montt</td>
<td>1987-1996 (usa); 2010-present (chile)</td>
<td>ao190</td>
</tr>
<tr>
<th>4</th>
<td>benjamin isherwood</td>
<td>t-ao-191</td>
<td>cancelled when 95.3% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011</td>
<td>launched 1988, christened 1991, never in service</td>
<td>ao191</td>
</tr>
<tr>
<th>5</th>
<td>henry eckford</td>
<td>t-ao-192</td>
<td>cancelled when 84% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011</td>
<td>launched 1989, never in service</td>
<td>ao192</td>
</tr>
<tr>
<th>6</th>
<td>walter s. diehl</td>
<td>t-ao-193</td>
<td>active</td>
<td>1988-present</td>
<td>ao193</td>
</tr>
<tr>
<th>7</th>
<td>john ericsson</td>
<td>t-ao-194</td>
<td>active</td>
<td>1991-present</td>
<td>ao194</td>
</tr>
<tr>
<th>8</th>
<td>leroy grumman</td>
<td>t-ao-195</td>
<td>active</td>
<td>1989-present</td>
<td>ao195</td>
</tr>
<tr>
<th>9</th>
<td>kanawha</td>
<td>t-ao-196</td>
<td>active</td>
<td>1991-present</td>
<td>ao196</td>
</tr>
<tr>
<th>10</th>
<td>pecos</td>
<td>t-ao-197</td>
<td>active</td>
<td>1990-present</td>
<td>ao197</td>
</tr>
<tr>
<th>11</th>
<td>big horn</td>
<td>t-ao-198</td>
<td>active</td>
<td>1992-present</td>
<td>ao198</td>
</tr>
<tr>
<th>12</th>
<td>tippecanoe</td>
<td>t-ao-199</td>
<td>active</td>
<td>1993-present</td>
<td>ao199</td>
</tr>
<tr>
<th>13</th>
<td>guadalupe</td>
<td>t-ao-200</td>
<td>active</td>
<td>1992-present</td>
<td>ao200</td>
</tr>
<tr>
<th>14</th>
<td>patuxent</td>
<td>t-ao-201</td>
<td>active</td>
<td>1995-present</td>
<td>ao201</td>
</tr>
<tr>
<th>15</th>
<td>yukon</td>
<td>t-ao-202</td>
<td>active</td>
<td>1994-present</td>
<td>ao202</td>
</tr>
<tr>
<th>16</th>
<td>laramie</td>
<td>t-ao-203</td>
<td>active</td>
<td>1996-present</td>
<td>ao203</td>
</tr>
<tr>
<th>17</th>
<td>rappahannock</td>
<td>t-ao-204</td>
<td>active</td>
<td>1995-present</td>
<td>ao204</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 status = 1 <table_name> : table | | ship | hull no. | status | years active | nvr page |
|---:|:-------------------|:-----------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------|:-----------|
| 0 | henry j. kaiser | t-ao-187 | active-southern california duty oiler | 1986-present | ao187 |
| 1 | joshua humphreys | t-ao-188 | inactivated 1996, returned to service 2005 | 1987-1996; 2005-2006; 2010-present | ao188 |
| 2 | john lenthall | t-ao-189 | active | 1987-1996; 1998-present | ao189 |
| 3 | andrew j. higgins | t-ao-190 | inactivated may 1996. sold to the chilean navy may 2009. towed to atlantic marine alabama shipyard, mobile, alabama, september 2009 for three-month refit. commissioned in chilean navy on 10 february 2010 and renamed almirante montt | 1987-1996 (usa); 2010-present (chile) | ao190 |
| 4 | benjamin isherwood | t-ao-191 | cancelled when 95.3% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011 | launched 1988, christened 1991, never in service | ao191 |
| 5 | henry eckford | t-ao-192 | cancelled when 84% complete, transferred to the maritime administration, laid up in the james river reserve fleet, scrapped in 2011 | launched 1989, never in service | ao192 |
| 6 | walter s. diehl | t-ao-193 | active | 1988-present | ao193 |
| 7 | john ericsson | t-ao-194 | active | 1991-present | ao194 |
| 8 | leroy grumman | t-ao-195 | active | 1989-present | ao195 |
| 9 | kanawha | t-ao-196 | active | 1991-present | ao196 |
| 10 | pecos | t-ao-197 | active | 1990-present | ao197 |
| 11 | big horn | t-ao-198 | active | 1992-present | ao198 |
| 12 | tippecanoe | t-ao-199 | active | 1993-present | ao199 |
| 13 | guadalupe | t-ao-200 | active | 1992-present | ao200 |
| 14 | patuxent | t-ao-201 | active | 1995-present | ao201 |
| 15 | yukon | t-ao-202 | active | 1994-present | ao202 |
| 16 | laramie | t-ao-203 | active | 1996-present | ao203 |
| 17 | rappahannock | t-ao-204 | active | 1995-present | ao204 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select year where hungarians = '31.6%' col : year | total | romanians | hungarians | roma row 1 : 1850 | 4,541 | 69.3% | 23.9% | 6.5% row 2 : 1880 | 4,636 | 63.0% | 30.2% | none row 3 : 1890 | 5,499 | 62.7% | 31.6% | none row 4 : 1900 | 5,553 | 64.3% | 29.7% | none row 5 : 1910 | 6,234 | 64.6% | 30.4% | none row 6 : 1920 | 5,887 | 71.6% | 27.9% | none row 7 : 1930 | 6,456 | 70.5% | 22.8% | 2.6% row 8 : 1941 | 6,981 | 78.3% | 19.4% | none row 9 : 1956 | 6,649 | 74.7% | 19.0% | 6.0% row 10 : 1966 | 6,991 | 80.9% | 17.3% | 1.7% row 11 : 1977 | 7,089 | 78.1% | 16.9% | 4.9% row 12 : 1992 | 5,723 | 74.1% | 14.2% | 11.6% row 13 : 2002 | 5,506 | 74.4% | 12.0% | 13.6% row 14 : 2011 | 4,574 | 70.7% | 11.2% | 17.9% | col : year row 1 : 1890 | select year where hungarians = '31.6%' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & total & romanians & hungarians & roma \\
\midrule
0 & 1850 & 4,541 & 69.3% & 23.9% & 6.5% \\
1 & 1880 & 4,636 & 63.0% & 30.2% & none \\
2 & 1890 & 5,499 & 62.7% & 31.6% & none \\
3 & 1900 & 5,553 & 64.3% & 29.7% & none \\
4 & 1910 & 6,234 & 64.6% & 30.4% & none \\
5 & 1920 & 5,887 & 71.6% & 27.9% & none \\
6 & 1930 & 6,456 & 70.5% & 22.8% & 2.6% \\
7 & 1941 & 6,981 & 78.3% & 19.4% & none \\
8 & 1956 & 6,649 & 74.7% & 19.0% & 6.0% \\
9 & 1966 & 6,991 & 80.9% & 17.3% & 1.7% \\
10 & 1977 & 7,089 & 78.1% & 16.9% & 4.9% \\
11 & 1992 & 5,723 & 74.1% & 14.2% & 11.6% \\
12 & 2002 & 5,506 & 74.4% & 12.0% & 13.6% \\
13 & 2011 & 4,574 & 70.7% & 11.2% & 17.9% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1890 \\
\bottomrule
\end{tabular}
| select year where hungarians = '31.6%' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>total</th>
<th>romanians</th>
<th>hungarians</th>
<th>roma</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1850</td>
<td>4,541</td>
<td>69.3%</td>
<td>23.9%</td>
<td>6.5%</td>
</tr>
<tr>
<th>1</th>
<td>1880</td>
<td>4,636</td>
<td>63.0%</td>
<td>30.2%</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1890</td>
<td>5,499</td>
<td>62.7%</td>
<td>31.6%</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1900</td>
<td>5,553</td>
<td>64.3%</td>
<td>29.7%</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1910</td>
<td>6,234</td>
<td>64.6%</td>
<td>30.4%</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1920</td>
<td>5,887</td>
<td>71.6%</td>
<td>27.9%</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1930</td>
<td>6,456</td>
<td>70.5%</td>
<td>22.8%</td>
<td>2.6%</td>
</tr>
<tr>
<th>7</th>
<td>1941</td>
<td>6,981</td>
<td>78.3%</td>
<td>19.4%</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1956</td>
<td>6,649</td>
<td>74.7%</td>
<td>19.0%</td>
<td>6.0%</td>
</tr>
<tr>
<th>9</th>
<td>1966</td>
<td>6,991</td>
<td>80.9%</td>
<td>17.3%</td>
<td>1.7%</td>
</tr>
<tr>
<th>10</th>
<td>1977</td>
<td>7,089</td>
<td>78.1%</td>
<td>16.9%</td>
<td>4.9%</td>
</tr>
<tr>
<th>11</th>
<td>1992</td>
<td>5,723</td>
<td>74.1%</td>
<td>14.2%</td>
<td>11.6%</td>
</tr>
<tr>
<th>12</th>
<td>2002</td>
<td>5,506</td>
<td>74.4%</td>
<td>12.0%</td>
<td>13.6%</td>
</tr>
<tr>
<th>13</th>
<td>2011</td>
<td>4,574</td>
<td>70.7%</td>
<td>11.2%</td>
<td>17.9%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1890</td>
</tr>
</tbody>
</table> | select year where hungarians = '31.6%' <table_name> : table | | year | total | romanians | hungarians | roma |
|---:|-------:|:--------|:------------|:-------------|:-------|
| 0 | 1850 | 4,541 | 69.3% | 23.9% | 6.5% |
| 1 | 1880 | 4,636 | 63.0% | 30.2% | none |
| 2 | 1890 | 5,499 | 62.7% | 31.6% | none |
| 3 | 1900 | 5,553 | 64.3% | 29.7% | none |
| 4 | 1910 | 6,234 | 64.6% | 30.4% | none |
| 5 | 1920 | 5,887 | 71.6% | 27.9% | none |
| 6 | 1930 | 6,456 | 70.5% | 22.8% | 2.6% |
| 7 | 1941 | 6,981 | 78.3% | 19.4% | none |
| 8 | 1956 | 6,649 | 74.7% | 19.0% | 6.0% |
| 9 | 1966 | 6,991 | 80.9% | 17.3% | 1.7% |
| 10 | 1977 | 7,089 | 78.1% | 16.9% | 4.9% |
| 11 | 1992 | 5,723 | 74.1% | 14.2% | 11.6% |
| 12 | 2002 | 5,506 | 74.4% | 12.0% | 13.6% |
| 13 | 2011 | 4,574 | 70.7% | 11.2% | 17.9% | | | | year |
|---:|-------:|
| 0 | 1890 | | [
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select count ( result ) where record = '6-1' col : week | date | opponent | score | result | record row 1 : 1 | july 9 | vs. saskatchewan roughriders | 31-21 | win | 1-0 row 2 : 2 | july 16 | at montreal concordes | 36-0 | win | 2-0 row 3 : 3 | july 24 | vs. hamilton tiger-cats | 36-25 | loss | 2-1 row 4 : 4 | aug 1 | at edmonton eskimos | 32-26 | win | 3-1 row 5 : 5 | aug 8 | vs. bc lions | 29-16 | win | 4-1 row 6 : 6 | aug 20 | at calgary stampeders | 35-4 | win | 5-1 row 7 : 7 | aug 28 | vs. ottawa rough riders | 27-20 | win | 6-1 row 8 : 8 | sept 5 | at saskatchewan roughriders | 36-35 | win | 7-1 row 9 : 9 | sept 11 | vs. calgary stampeders | 15-11 | loss | 7-2 row 10 : 10 | sept 18 | at ottawa rough riders | 38-28 | loss | 7-3 row 11 : 11 | sept 25 | vs. montreal concordes | 19-16 | win | 8-3 row 12 : 12 | oct 2 | at bc lions | 29-19 | win | 9-3 row 13 : 13 | oct 11 | vs. toronto argonauts | 39-35 | win | 10-3 row 14 : 14 | oct 17 | at toronto argonauts | 29-16 | win | 11-3 row 15 : 15 | oct 23 | vs. edmonton eskimos | 33-17 | loss | 11-4 row 16 : 16 | nov 7 | at hamilton tiger-cats | 24-21 | loss | 11-5 | col : count ( "result" ) row 1 : 1 | select count ( result ) where record = '6-1' <table_name> : table \begin{tabular}{lllllll}
\toprule
& week & date & opponent & score & result & record \\
\midrule
0 & 1 & july 9 & vs. saskatchewan roughriders & 31-21 & win & 1-0 \\
1 & 2 & july 16 & at montreal concordes & 36-0 & win & 2-0 \\
2 & 3 & july 24 & vs. hamilton tiger-cats & 36-25 & loss & 2-1 \\
3 & 4 & aug 1 & at edmonton eskimos & 32-26 & win & 3-1 \\
4 & 5 & aug 8 & vs. bc lions & 29-16 & win & 4-1 \\
5 & 6 & aug 20 & at calgary stampeders & 35-4 & win & 5-1 \\
6 & 7 & aug 28 & vs. ottawa rough riders & 27-20 & win & 6-1 \\
7 & 8 & sept 5 & at saskatchewan roughriders & 36-35 & win & 7-1 \\
8 & 9 & sept 11 & vs. calgary stampeders & 15-11 & loss & 7-2 \\
9 & 10 & sept 18 & at ottawa rough riders & 38-28 & loss & 7-3 \\
10 & 11 & sept 25 & vs. montreal concordes & 19-16 & win & 8-3 \\
11 & 12 & oct 2 & at bc lions & 29-19 & win & 9-3 \\
12 & 13 & oct 11 & vs. toronto argonauts & 39-35 & win & 10-3 \\
13 & 14 & oct 17 & at toronto argonauts & 29-16 & win & 11-3 \\
14 & 15 & oct 23 & vs. edmonton eskimos & 33-17 & loss & 11-4 \\
15 & 16 & nov 7 & at hamilton tiger-cats & 24-21 & loss & 11-5 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "result" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( result ) where record = '6-1' <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>july 9</td>
<td>vs. saskatchewan roughriders</td>
<td>31-21</td>
<td>win</td>
<td>1-0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>july 16</td>
<td>at montreal concordes</td>
<td>36-0</td>
<td>win</td>
<td>2-0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>july 24</td>
<td>vs. hamilton tiger-cats</td>
<td>36-25</td>
<td>loss</td>
<td>2-1</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>aug 1</td>
<td>at edmonton eskimos</td>
<td>32-26</td>
<td>win</td>
<td>3-1</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>aug 8</td>
<td>vs. bc lions</td>
<td>29-16</td>
<td>win</td>
<td>4-1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>aug 20</td>
<td>at calgary stampeders</td>
<td>35-4</td>
<td>win</td>
<td>5-1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>aug 28</td>
<td>vs. ottawa rough riders</td>
<td>27-20</td>
<td>win</td>
<td>6-1</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>sept 5</td>
<td>at saskatchewan roughriders</td>
<td>36-35</td>
<td>win</td>
<td>7-1</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>sept 11</td>
<td>vs. calgary stampeders</td>
<td>15-11</td>
<td>loss</td>
<td>7-2</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>sept 18</td>
<td>at ottawa rough riders</td>
<td>38-28</td>
<td>loss</td>
<td>7-3</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>sept 25</td>
<td>vs. montreal concordes</td>
<td>19-16</td>
<td>win</td>
<td>8-3</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>oct 2</td>
<td>at bc lions</td>
<td>29-19</td>
<td>win</td>
<td>9-3</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>oct 11</td>
<td>vs. toronto argonauts</td>
<td>39-35</td>
<td>win</td>
<td>10-3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>oct 17</td>
<td>at toronto argonauts</td>
<td>29-16</td>
<td>win</td>
<td>11-3</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>oct 23</td>
<td>vs. edmonton eskimos</td>
<td>33-17</td>
<td>loss</td>
<td>11-4</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>nov 7</td>
<td>at hamilton tiger-cats</td>
<td>24-21</td>
<td>loss</td>
<td>11-5</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 record = '6-1' <table_name> : table | | week | date | opponent | score | result | record |
|---:|-------:|:--------|:-----------------------------|:--------|:---------|:---------|
| 0 | 1 | july 9 | vs. saskatchewan roughriders | 31-21 | win | 1-0 |
| 1 | 2 | july 16 | at montreal concordes | 36-0 | win | 2-0 |
| 2 | 3 | july 24 | vs. hamilton tiger-cats | 36-25 | loss | 2-1 |
| 3 | 4 | aug 1 | at edmonton eskimos | 32-26 | win | 3-1 |
| 4 | 5 | aug 8 | vs. bc lions | 29-16 | win | 4-1 |
| 5 | 6 | aug 20 | at calgary stampeders | 35-4 | win | 5-1 |
| 6 | 7 | aug 28 | vs. ottawa rough riders | 27-20 | win | 6-1 |
| 7 | 8 | sept 5 | at saskatchewan roughriders | 36-35 | win | 7-1 |
| 8 | 9 | sept 11 | vs. calgary stampeders | 15-11 | loss | 7-2 |
| 9 | 10 | sept 18 | at ottawa rough riders | 38-28 | loss | 7-3 |
| 10 | 11 | sept 25 | vs. montreal concordes | 19-16 | win | 8-3 |
| 11 | 12 | oct 2 | at bc lions | 29-19 | win | 9-3 |
| 12 | 13 | oct 11 | vs. toronto argonauts | 39-35 | win | 10-3 |
| 13 | 14 | oct 17 | at toronto argonauts | 29-16 | win | 11-3 |
| 14 | 15 | oct 23 | vs. edmonton eskimos | 33-17 | loss | 11-4 |
| 15 | 16 | nov 7 | at hamilton tiger-cats | 24-21 | loss | 11-5 | | | | count ( "result" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select count ( * ) where score = 1061 col : game | date | team | score | high points | high rebounds | high assists | location attendance | record row 1 : 1 | october 5 | @ portland | l 86-115 | chris kaman (14) | chris kaman, blake griffin (7) | randy foye (5) | rose garden 18,209 | 0-1 row 2 : 2 | october 7 | @ sacramento | w 120-88 | chris kaman (20) | blake griffin (13) | randy foye (8) | arco arena 10,284 | 1-1 row 3 : 3 | october 8 | @ golden state | l 87-127 | blake griffin (23) | blake griffin (9) | randy foye (6) | oracle arena 10,004 | 1-2 row 4 : 4 | october 12 | san antonio | l 99-100 | eric gordon (23) | blake griffin (17) | baron davis (7) | palacio de los deportes 18,674 | 1-3 row 5 : 5 | october 14 | denver | l 95-100 | blake griffin (24) | blake griffin (14) | baron davis (6) | staples center 10,572 | 1-4 row 6 : 6 | october 16 | utah | l 91-103 | eric gordon (23) | blake griffin (14) | baron davis (8) | staples center 18,997 | 1-5 row 7 : 7 | october 17 | denver | l 104-108 | brian cook (28) | al-farouq aminu (8) | baron davis, eric bledsoe (7) | staples center | 1-6 row 8 : 8 | october 19 | sacramento | l 94-96 | chris kaman (21) | chris kaman (10) | baron davis (8) | staples center 10,838 | 1-7 | col : count ( "*" ) row 1 : 0 | select count ( * ) where score = 1061 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& game & date & team & score & high points & high rebounds & high assists & location attendance & record \\
\midrule
0 & 1 & october 5 & @ portland & l 86-115 & chris kaman (14) & chris kaman, blake griffin (7) & randy foye (5) & rose garden 18,209 & 0-1 \\
1 & 2 & october 7 & @ sacramento & w 120-88 & chris kaman (20) & blake griffin (13) & randy foye (8) & arco arena 10,284 & 1-1 \\
2 & 3 & october 8 & @ golden state & l 87-127 & blake griffin (23) & blake griffin (9) & randy foye (6) & oracle arena 10,004 & 1-2 \\
3 & 4 & october 12 & san antonio & l 99-100 & eric gordon (23) & blake griffin (17) & baron davis (7) & palacio de los deportes 18,674 & 1-3 \\
4 & 5 & october 14 & denver & l 95-100 & blake griffin (24) & blake griffin (14) & baron davis (6) & staples center 10,572 & 1-4 \\
5 & 6 & october 16 & utah & l 91-103 & eric gordon (23) & blake griffin (14) & baron davis (8) & staples center 18,997 & 1-5 \\
6 & 7 & october 17 & denver & l 104-108 & brian cook (28) & al-farouq aminu (8) & baron davis, eric bledsoe (7) & staples center & 1-6 \\
7 & 8 & october 19 & sacramento & l 94-96 & chris kaman (21) & chris kaman (10) & baron davis (8) & staples center 10,838 & 1-7 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where score = 1061 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>date</th>
<th>team</th>
<th>score</th>
<th>high points</th>
<th>high rebounds</th>
<th>high assists</th>
<th>location attendance</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>october 5</td>
<td>@ portland</td>
<td>l 86-115</td>
<td>chris kaman (14)</td>
<td>chris kaman, blake griffin (7)</td>
<td>randy foye (5)</td>
<td>rose garden 18,209</td>
<td>0-1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>october 7</td>
<td>@ sacramento</td>
<td>w 120-88</td>
<td>chris kaman (20)</td>
<td>blake griffin (13)</td>
<td>randy foye (8)</td>
<td>arco arena 10,284</td>
<td>1-1</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>october 8</td>
<td>@ golden state</td>
<td>l 87-127</td>
<td>blake griffin (23)</td>
<td>blake griffin (9)</td>
<td>randy foye (6)</td>
<td>oracle arena 10,004</td>
<td>1-2</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>october 12</td>
<td>san antonio</td>
<td>l 99-100</td>
<td>eric gordon (23)</td>
<td>blake griffin (17)</td>
<td>baron davis (7)</td>
<td>palacio de los deportes 18,674</td>
<td>1-3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>october 14</td>
<td>denver</td>
<td>l 95-100</td>
<td>blake griffin (24)</td>
<td>blake griffin (14)</td>
<td>baron davis (6)</td>
<td>staples center 10,572</td>
<td>1-4</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>october 16</td>
<td>utah</td>
<td>l 91-103</td>
<td>eric gordon (23)</td>
<td>blake griffin (14)</td>
<td>baron davis (8)</td>
<td>staples center 18,997</td>
<td>1-5</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>october 17</td>
<td>denver</td>
<td>l 104-108</td>
<td>brian cook (28)</td>
<td>al-farouq aminu (8)</td>
<td>baron davis, eric bledsoe (7)</td>
<td>staples center</td>
<td>1-6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>october 19</td>
<td>sacramento</td>
<td>l 94-96</td>
<td>chris kaman (21)</td>
<td>chris kaman (10)</td>
<td>baron davis (8)</td>
<td>staples center 10,838</td>
<td>1-7</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 score = 1061 <table_name> : table | | game | date | team | score | high points | high rebounds | high assists | location attendance | record |
|---:|-------:|:-----------|:---------------|:----------|:-------------------|:-------------------------------|:------------------------------|:-------------------------------|:---------|
| 0 | 1 | october 5 | @ portland | l 86-115 | chris kaman (14) | chris kaman, blake griffin (7) | randy foye (5) | rose garden 18,209 | 0-1 |
| 1 | 2 | october 7 | @ sacramento | w 120-88 | chris kaman (20) | blake griffin (13) | randy foye (8) | arco arena 10,284 | 1-1 |
| 2 | 3 | october 8 | @ golden state | l 87-127 | blake griffin (23) | blake griffin (9) | randy foye (6) | oracle arena 10,004 | 1-2 |
| 3 | 4 | october 12 | san antonio | l 99-100 | eric gordon (23) | blake griffin (17) | baron davis (7) | palacio de los deportes 18,674 | 1-3 |
| 4 | 5 | october 14 | denver | l 95-100 | blake griffin (24) | blake griffin (14) | baron davis (6) | staples center 10,572 | 1-4 |
| 5 | 6 | october 16 | utah | l 91-103 | eric gordon (23) | blake griffin (14) | baron davis (8) | staples center 18,997 | 1-5 |
| 6 | 7 | october 17 | denver | l 104-108 | brian cook (28) | al-farouq aminu (8) | baron davis, eric bledsoe (7) | staples center | 1-6 |
| 7 | 8 | october 19 | sacramento | l 94-96 | chris kaman (21) | chris kaman (10) | baron davis (8) | staples center 10,838 | 1-7 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( dimensions ) where dimensions = '25 grams (0.88 oz)38 millimetres (1.5 in)' col : year | model | denomination | metal composition | dimensions row 1 : 1992 | re-establishment of kroon, 28 august 1992 | 100 krooni | .900 silver | 23 grams (0.81 oz)36 millimetres (1.4 in) row 2 : 1996 | atlanta olympics, 100th anniversary of modern olympiad | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) row 3 : 1998 | 80th anniversary of declaration of independence, 1918-1998 | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) row 4 : 1992 | re-establishment of krooni currency | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) row 5 : 1992 | barcelona olympics | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) row 6 : 1998 | 80th anniversary of declaration of independence, 1918-1998 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) row 7 : 2002 | 370th anniversary of the founding of tartu university | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) row 8 : 2004 | the flag of estonia - 2004 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) | col : count ( "dimensions" ) row 1 : 7 | select count ( dimensions ) where dimensions = '25 grams (0.88 oz)38 millimetres (1.5 in)' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & model & denomination & metal composition & dimensions \\
\midrule
0 & 1992 & re-establishment of kroon, 28 august 1992 & 100 krooni & .900 silver & 23 grams (0.81 oz)36 millimetres (1.4 in) \\
1 & 1996 & atlanta olympics, 100th anniversary of modern olympiad & 100 krooni & .925 silver & 25 grams (0.88 oz)38 millimetres (1.5 in) \\
2 & 1998 & 80th anniversary of declaration of independence, 1918-1998 & 100 krooni & .925 silver & 25 grams (0.88 oz)38 millimetres (1.5 in) \\
3 & 1992 & re-establishment of krooni currency & 10 krooni & .925 silver & 25 grams (0.88 oz)38 millimetres (1.5 in) \\
4 & 1992 & barcelona olympics & 10 krooni & .925 silver & 25 grams (0.88 oz)38 millimetres (1.5 in) \\
5 & 1998 & 80th anniversary of declaration of independence, 1918-1998 & 10 krooni & .925 silver & 25 grams (0.88 oz)38 millimetres (1.5 in) \\
6 & 2002 & 370th anniversary of the founding of tartu university & 10 krooni & .925 silver & 25 grams (0.88 oz)38 millimetres (1.5 in) \\
7 & 2004 & the flag of estonia - 2004 & 10 krooni & .925 silver & 25 grams (0.88 oz)38 millimetres (1.5 in) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "dimensions" ) \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select count ( dimensions ) where dimensions = '25 grams (0.88 oz)38 millimetres (1.5 in)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>model</th>
<th>denomination</th>
<th>metal composition</th>
<th>dimensions</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1992</td>
<td>re-establishment of kroon, 28 august 1992</td>
<td>100 krooni</td>
<td>.900 silver</td>
<td>23 grams (0.81 oz)36 millimetres (1.4 in)</td>
</tr>
<tr>
<th>1</th>
<td>1996</td>
<td>atlanta olympics, 100th anniversary of modern olympiad</td>
<td>100 krooni</td>
<td>.925 silver</td>
<td>25 grams (0.88 oz)38 millimetres (1.5 in)</td>
</tr>
<tr>
<th>2</th>
<td>1998</td>
<td>80th anniversary of declaration of independence, 1918-1998</td>
<td>100 krooni</td>
<td>.925 silver</td>
<td>25 grams (0.88 oz)38 millimetres (1.5 in)</td>
</tr>
<tr>
<th>3</th>
<td>1992</td>
<td>re-establishment of krooni currency</td>
<td>10 krooni</td>
<td>.925 silver</td>
<td>25 grams (0.88 oz)38 millimetres (1.5 in)</td>
</tr>
<tr>
<th>4</th>
<td>1992</td>
<td>barcelona olympics</td>
<td>10 krooni</td>
<td>.925 silver</td>
<td>25 grams (0.88 oz)38 millimetres (1.5 in)</td>
</tr>
<tr>
<th>5</th>
<td>1998</td>
<td>80th anniversary of declaration of independence, 1918-1998</td>
<td>10 krooni</td>
<td>.925 silver</td>
<td>25 grams (0.88 oz)38 millimetres (1.5 in)</td>
</tr>
<tr>
<th>6</th>
<td>2002</td>
<td>370th anniversary of the founding of tartu university</td>
<td>10 krooni</td>
<td>.925 silver</td>
<td>25 grams (0.88 oz)38 millimetres (1.5 in)</td>
</tr>
<tr>
<th>7</th>
<td>2004</td>
<td>the flag of estonia - 2004</td>
<td>10 krooni</td>
<td>.925 silver</td>
<td>25 grams (0.88 oz)38 millimetres (1.5 in)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "dimensions" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select count ( dimensions ) where dimensions = '25 grams (0.88 oz)38 millimetres (1.5 in)' <table_name> : table | | year | model | denomination | metal composition | dimensions |
|---:|-------:|:-----------------------------------------------------------|:---------------|:--------------------|:------------------------------------------|
| 0 | 1992 | re-establishment of kroon, 28 august 1992 | 100 krooni | .900 silver | 23 grams (0.81 oz)36 millimetres (1.4 in) |
| 1 | 1996 | atlanta olympics, 100th anniversary of modern olympiad | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) |
| 2 | 1998 | 80th anniversary of declaration of independence, 1918-1998 | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) |
| 3 | 1992 | re-establishment of krooni currency | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) |
| 4 | 1992 | barcelona olympics | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) |
| 5 | 1998 | 80th anniversary of declaration of independence, 1918-1998 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) |
| 6 | 2002 | 370th anniversary of the founding of tartu university | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) |
| 7 | 2004 | the flag of estonia - 2004 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) | | | | count ( "dimensions" ) |
|---:|-------------------------:|
| 0 | 7 | | [
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select hungarians where year = 1850 col : year | total | romanians | hungarians | roma row 1 : 1850 | 4,541 | 69.3% | 23.9% | 6.5% row 2 : 1880 | 4,636 | 63.0% | 30.2% | none row 3 : 1890 | 5,499 | 62.7% | 31.6% | none row 4 : 1900 | 5,553 | 64.3% | 29.7% | none row 5 : 1910 | 6,234 | 64.6% | 30.4% | none row 6 : 1920 | 5,887 | 71.6% | 27.9% | none row 7 : 1930 | 6,456 | 70.5% | 22.8% | 2.6% row 8 : 1941 | 6,981 | 78.3% | 19.4% | none row 9 : 1956 | 6,649 | 74.7% | 19.0% | 6.0% row 10 : 1966 | 6,991 | 80.9% | 17.3% | 1.7% row 11 : 1977 | 7,089 | 78.1% | 16.9% | 4.9% row 12 : 1992 | 5,723 | 74.1% | 14.2% | 11.6% row 13 : 2002 | 5,506 | 74.4% | 12.0% | 13.6% row 14 : 2011 | 4,574 | 70.7% | 11.2% | 17.9% | col : hungarians row 1 : 23.9% | select hungarians where year = 1850 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & total & romanians & hungarians & roma \\
\midrule
0 & 1850 & 4,541 & 69.3% & 23.9% & 6.5% \\
1 & 1880 & 4,636 & 63.0% & 30.2% & none \\
2 & 1890 & 5,499 & 62.7% & 31.6% & none \\
3 & 1900 & 5,553 & 64.3% & 29.7% & none \\
4 & 1910 & 6,234 & 64.6% & 30.4% & none \\
5 & 1920 & 5,887 & 71.6% & 27.9% & none \\
6 & 1930 & 6,456 & 70.5% & 22.8% & 2.6% \\
7 & 1941 & 6,981 & 78.3% & 19.4% & none \\
8 & 1956 & 6,649 & 74.7% & 19.0% & 6.0% \\
9 & 1966 & 6,991 & 80.9% & 17.3% & 1.7% \\
10 & 1977 & 7,089 & 78.1% & 16.9% & 4.9% \\
11 & 1992 & 5,723 & 74.1% & 14.2% & 11.6% \\
12 & 2002 & 5,506 & 74.4% & 12.0% & 13.6% \\
13 & 2011 & 4,574 & 70.7% & 11.2% & 17.9% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& hungarians \\
\midrule
0 & 23.9% \\
\bottomrule
\end{tabular}
| select hungarians where year = 1850 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>total</th>
<th>romanians</th>
<th>hungarians</th>
<th>roma</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1850</td>
<td>4,541</td>
<td>69.3%</td>
<td>23.9%</td>
<td>6.5%</td>
</tr>
<tr>
<th>1</th>
<td>1880</td>
<td>4,636</td>
<td>63.0%</td>
<td>30.2%</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1890</td>
<td>5,499</td>
<td>62.7%</td>
<td>31.6%</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1900</td>
<td>5,553</td>
<td>64.3%</td>
<td>29.7%</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1910</td>
<td>6,234</td>
<td>64.6%</td>
<td>30.4%</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1920</td>
<td>5,887</td>
<td>71.6%</td>
<td>27.9%</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1930</td>
<td>6,456</td>
<td>70.5%</td>
<td>22.8%</td>
<td>2.6%</td>
</tr>
<tr>
<th>7</th>
<td>1941</td>
<td>6,981</td>
<td>78.3%</td>
<td>19.4%</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1956</td>
<td>6,649</td>
<td>74.7%</td>
<td>19.0%</td>
<td>6.0%</td>
</tr>
<tr>
<th>9</th>
<td>1966</td>
<td>6,991</td>
<td>80.9%</td>
<td>17.3%</td>
<td>1.7%</td>
</tr>
<tr>
<th>10</th>
<td>1977</td>
<td>7,089</td>
<td>78.1%</td>
<td>16.9%</td>
<td>4.9%</td>
</tr>
<tr>
<th>11</th>
<td>1992</td>
<td>5,723</td>
<td>74.1%</td>
<td>14.2%</td>
<td>11.6%</td>
</tr>
<tr>
<th>12</th>
<td>2002</td>
<td>5,506</td>
<td>74.4%</td>
<td>12.0%</td>
<td>13.6%</td>
</tr>
<tr>
<th>13</th>
<td>2011</td>
<td>4,574</td>
<td>70.7%</td>
<td>11.2%</td>
<td>17.9%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>hungarians</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>23.9%</td>
</tr>
</tbody>
</table> | select hungarians where year = 1850 <table_name> : table | | year | total | romanians | hungarians | roma |
|---:|-------:|:--------|:------------|:-------------|:-------|
| 0 | 1850 | 4,541 | 69.3% | 23.9% | 6.5% |
| 1 | 1880 | 4,636 | 63.0% | 30.2% | none |
| 2 | 1890 | 5,499 | 62.7% | 31.6% | none |
| 3 | 1900 | 5,553 | 64.3% | 29.7% | none |
| 4 | 1910 | 6,234 | 64.6% | 30.4% | none |
| 5 | 1920 | 5,887 | 71.6% | 27.9% | none |
| 6 | 1930 | 6,456 | 70.5% | 22.8% | 2.6% |
| 7 | 1941 | 6,981 | 78.3% | 19.4% | none |
| 8 | 1956 | 6,649 | 74.7% | 19.0% | 6.0% |
| 9 | 1966 | 6,991 | 80.9% | 17.3% | 1.7% |
| 10 | 1977 | 7,089 | 78.1% | 16.9% | 4.9% |
| 11 | 1992 | 5,723 | 74.1% | 14.2% | 11.6% |
| 12 | 2002 | 5,506 | 74.4% | 12.0% | 13.6% |
| 13 | 2011 | 4,574 | 70.7% | 11.2% | 17.9% | | | | hungarians |
|---:|:-------------|
| 0 | 23.9% | | [
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] |
select name where position = 'mf' col : place | position | number | name | nasl | playoffs | cfu club championship | concacaf champions league | total row 1 : 1 | fw | 11 | nicholas addlery | 9 | 0 | 0 | 1 | 10 row 2 : 2 | fw | 9 | jonathan fana | 4 | 0 | 4 | 0 | 8 row 3 : 3 | fw | 7 | david foley | 6 | 1 | 0 | 0 | 7 row 4 : 3 | fw | 24 | hector ramos | 3 | 0 | 2 | 2 | 7 row 5 : 5 | df | 33 | jay needham | 3 | 0 | 0 | 0 | 3 row 6 : 5 | fw | 22 | gregory richardson | 1 | 0 | 1 | 1 | 3 row 7 : 7 | mf | 20 | josh hansen | 0 | 0 | 2 | 0 | 2 row 8 : 7 | none | none | own goal | 0 | 0 | 2 | 0 | 2 row 9 : 9 | df | 3 | richard martinez | 1 | 0 | 0 | 0 | 1 row 10 : 9 | df | 16 | anthony vazquez | 1 | 0 | 0 | 0 | 1 row 11 : 9 | df | 5 | noah delgado | 1 | 0 | 0 | 0 | 1 row 12 : 9 | mf | 14 | jarad van schaik | 1 | 0 | 0 | 0 | 1 row 13 : 9 | mf | 17 | tyler wilson | 1 | 0 | 0 | 0 | 1 row 14 : 9 | mf | 24 | justin fojo | 1 | 0 | 0 | 0 | 1 row 15 : none | none | none | totals | 32 | 1 | 11 | 4 | 48 | col : name row 1 : josh hansen row 2 : jarad van schaik row 3 : tyler wilson row 4 : justin fojo | select name where position = 'mf' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& place & position & number & name & nasl & playoffs & cfu club championship & concacaf champions league & total \\
\midrule
0 & 1 & fw & 11 & nicholas addlery & 9 & 0 & 0 & 1 & 10 \\
1 & 2 & fw & 9 & jonathan fana & 4 & 0 & 4 & 0 & 8 \\
2 & 3 & fw & 7 & david foley & 6 & 1 & 0 & 0 & 7 \\
3 & 3 & fw & 24 & hector ramos & 3 & 0 & 2 & 2 & 7 \\
4 & 5 & df & 33 & jay needham & 3 & 0 & 0 & 0 & 3 \\
5 & 5 & fw & 22 & gregory richardson & 1 & 0 & 1 & 1 & 3 \\
6 & 7 & mf & 20 & josh hansen & 0 & 0 & 2 & 0 & 2 \\
7 & 7 & none & none & own goal & 0 & 0 & 2 & 0 & 2 \\
8 & 9 & df & 3 & richard martinez & 1 & 0 & 0 & 0 & 1 \\
9 & 9 & df & 16 & anthony vazquez & 1 & 0 & 0 & 0 & 1 \\
10 & 9 & df & 5 & noah delgado & 1 & 0 & 0 & 0 & 1 \\
11 & 9 & mf & 14 & jarad van schaik & 1 & 0 & 0 & 0 & 1 \\
12 & 9 & mf & 17 & tyler wilson & 1 & 0 & 0 & 0 & 1 \\
13 & 9 & mf & 24 & justin fojo & 1 & 0 & 0 & 0 & 1 \\
14 & none & none & none & totals & 32 & 1 & 11 & 4 & 48 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & josh hansen \\
1 & jarad van schaik \\
2 & tyler wilson \\
3 & justin fojo \\
\bottomrule
\end{tabular}
| select name where position = 'mf' <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>nasl</th>
<th>playoffs</th>
<th>cfu club championship</th>
<th>concacaf champions league</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>fw</td>
<td>11</td>
<td>nicholas addlery</td>
<td>9</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>fw</td>
<td>9</td>
<td>jonathan fana</td>
<td>4</td>
<td>0</td>
<td>4</td>
<td>0</td>
<td>8</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>fw</td>
<td>7</td>
<td>david foley</td>
<td>6</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>7</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>fw</td>
<td>24</td>
<td>hector ramos</td>
<td>3</td>
<td>0</td>
<td>2</td>
<td>2</td>
<td>7</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>df</td>
<td>33</td>
<td>jay needham</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>3</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>fw</td>
<td>22</td>
<td>gregory richardson</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>mf</td>
<td>20</td>
<td>josh hansen</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>none</td>
<td>none</td>
<td>own goal</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>df</td>
<td>3</td>
<td>richard martinez</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>df</td>
<td>16</td>
<td>anthony vazquez</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>9</td>
<td>df</td>
<td>5</td>
<td>noah delgado</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>9</td>
<td>mf</td>
<td>14</td>
<td>jarad van schaik</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>9</td>
<td>mf</td>
<td>17</td>
<td>tyler wilson</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>9</td>
<td>mf</td>
<td>24</td>
<td>justin fojo</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>none</td>
<td>none</td>
<td>none</td>
<td>totals</td>
<td>32</td>
<td>1</td>
<td>11</td>
<td>4</td>
<td>48</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>josh hansen</td>
</tr>
<tr>
<th>1</th>
<td>jarad van schaik</td>
</tr>
<tr>
<th>2</th>
<td>tyler wilson</td>
</tr>
<tr>
<th>3</th>
<td>justin fojo</td>
</tr>
</tbody>
</table> | select name where position = 'mf' <table_name> : table | | place | position | number | name | nasl | playoffs | cfu club championship | concacaf champions league | total |
|---:|:--------|:-----------|:---------|:-------------------|-------:|-----------:|------------------------:|----------------------------:|--------:|
| 0 | 1 | fw | 11 | nicholas addlery | 9 | 0 | 0 | 1 | 10 |
| 1 | 2 | fw | 9 | jonathan fana | 4 | 0 | 4 | 0 | 8 |
| 2 | 3 | fw | 7 | david foley | 6 | 1 | 0 | 0 | 7 |
| 3 | 3 | fw | 24 | hector ramos | 3 | 0 | 2 | 2 | 7 |
| 4 | 5 | df | 33 | jay needham | 3 | 0 | 0 | 0 | 3 |
| 5 | 5 | fw | 22 | gregory richardson | 1 | 0 | 1 | 1 | 3 |
| 6 | 7 | mf | 20 | josh hansen | 0 | 0 | 2 | 0 | 2 |
| 7 | 7 | none | none | own goal | 0 | 0 | 2 | 0 | 2 |
| 8 | 9 | df | 3 | richard martinez | 1 | 0 | 0 | 0 | 1 |
| 9 | 9 | df | 16 | anthony vazquez | 1 | 0 | 0 | 0 | 1 |
| 10 | 9 | df | 5 | noah delgado | 1 | 0 | 0 | 0 | 1 |
| 11 | 9 | mf | 14 | jarad van schaik | 1 | 0 | 0 | 0 | 1 |
| 12 | 9 | mf | 17 | tyler wilson | 1 | 0 | 0 | 0 | 1 |
| 13 | 9 | mf | 24 | justin fojo | 1 | 0 | 0 | 0 | 1 |
| 14 | none | none | none | totals | 32 | 1 | 11 | 4 | 48 | | | | name |
|---:|:-----------------|
| 0 | josh hansen |
| 1 | jarad van schaik |
| 2 | tyler wilson |
| 3 | justin fojo | | [
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select bowling center where city = 'encino, california' order by city asc limit 736 col : event | bowling center | city | dates | winner row 1 : eastern open | edison lanes | edison, new jersey | dec 2-6 | dennis chapis (2) row 2 : charlotte open | freedom lanes | charlotte, north carolina | dec 9-13 | gene rhoda (3) row 3 : western open | saratoga lanes | san jose, california | jan 4-8 | jim godman (1) row 4 : denver open | broadway bowl | denver, colorado | jan 11-15 | dick weber (16) row 5 : hialeah-miami open | hialeah lanes | hialeah, florida | feb 1-5 | les schissler (3) row 6 : mobile-sertoma open | florida lanes | mobile, alabama | feb 8-12 | mike limongello (2) row 7 : fresno open | sunnyside bowl | fresno, california | feb 15-19 | dick weber (17) row 8 : las vegas open | showboat lanes | las vegas, nevada | feb 22-26 | skee foremsky (1) row 9 : miller high life open | bowlero lanes | milwaukee, wisconsin | mar 1-5 | bill lillard (1) row 10 : st. paul open | all-star bowl | st. paul, minnesota | mar 8-12 | gene rhoda (4) row 11 : buckeye open | imperial lanes | toledo, ohio | mar 15-19 | pete tountas (2) row 12 : greater buffalo open | fairlanes | depew, new york | mar 22-26 | bobby jacks (1) row 13 : firestone tournament of champions | riviera lanes | akron, ohio | mar 29 - apr 2 | wayne zahn (4) row 14 : seattle open | ballinger bowl | seattle, washington | jun 9-12 | wayne zahn (5) row 15 : portland open | valley lanes | portland, oregon | jun 16-19 | don johnson (2) row 16 : fresno open | cedar lanes | fresno, california | jun 22-26 | les schissler (4) row 17 : tucson squirt open | cactus bowl | tucson, arizona | jul 1-4 | johnny guenther (2) row 18 : southern california open | encino bowl | encino, california | jul 7-10 | barry asher (1) row 19 : fort worth open | meadowbrook lanes | fort worth, texas | jul 14-17 | dick ritger (1) row 20 : reading open | hiester lanes | reading, pennsylvania | jul 28-31 | dick ritger (2) row 21 : u.s. coast guard open | starlite lanes | grand haven, michigan | aug 2-5 | george howard (4) row 22 : brockton open | westgate lanes | brockton, massachusetts | aug 11-14 | bobby jacks (2) row 23 : waukegan open | bertrand bowl | waukegan, illinois | aug 18-21 | bobby jacks (3) row 24 : fort smith open | midland bowl | fort smith, arkansas | aug 25-28 | johnny petraglia (1) row 25 : labor day classic | hart bowl | dallas, texas | sep 2-5 | bud horn (1) row 26 : crescent city open | mardi gras bowl | new orleans, louisiana | sep 8-12 | barry asher (2) row 27 : seventh annual pba national championship | garden city bowl | garden city, new york | nov 1-6 | wayne zahn (6) row 28 : camden pba open | camden lanes | camden, new jersey | nov 9-12 | ralph engan (1) row 29 : baltimore open | fair lanes-colt | baltimore, maryland | nov 17-20 | jim stefanich (1) | col : bowling center row 1 : encino bowl | select bowling center where city = 'encino, california' order by city asc limit 736 <table_name> : table \begin{tabular}{llllll}
\toprule
& event & bowling center & city & dates & winner \\
\midrule
0 & eastern open & edison lanes & edison, new jersey & dec 2-6 & dennis chapis (2) \\
1 & charlotte open & freedom lanes & charlotte, north carolina & dec 9-13 & gene rhoda (3) \\
2 & western open & saratoga lanes & san jose, california & jan 4-8 & jim godman (1) \\
3 & denver open & broadway bowl & denver, colorado & jan 11-15 & dick weber (16) \\
4 & hialeah-miami open & hialeah lanes & hialeah, florida & feb 1-5 & les schissler (3) \\
5 & mobile-sertoma open & florida lanes & mobile, alabama & feb 8-12 & mike limongello (2) \\
6 & fresno open & sunnyside bowl & fresno, california & feb 15-19 & dick weber (17) \\
7 & las vegas open & showboat lanes & las vegas, nevada & feb 22-26 & skee foremsky (1) \\
8 & miller high life open & bowlero lanes & milwaukee, wisconsin & mar 1-5 & bill lillard (1) \\
9 & st. paul open & all-star bowl & st. paul, minnesota & mar 8-12 & gene rhoda (4) \\
10 & buckeye open & imperial lanes & toledo, ohio & mar 15-19 & pete tountas (2) \\
11 & greater buffalo open & fairlanes & depew, new york & mar 22-26 & bobby jacks (1) \\
12 & firestone tournament of champions & riviera lanes & akron, ohio & mar 29 - apr 2 & wayne zahn (4) \\
13 & seattle open & ballinger bowl & seattle, washington & jun 9-12 & wayne zahn (5) \\
14 & portland open & valley lanes & portland, oregon & jun 16-19 & don johnson (2) \\
15 & fresno open & cedar lanes & fresno, california & jun 22-26 & les schissler (4) \\
16 & tucson squirt open & cactus bowl & tucson, arizona & jul 1-4 & johnny guenther (2) \\
17 & southern california open & encino bowl & encino, california & jul 7-10 & barry asher (1) \\
18 & fort worth open & meadowbrook lanes & fort worth, texas & jul 14-17 & dick ritger (1) \\
19 & reading open & hiester lanes & reading, pennsylvania & jul 28-31 & dick ritger (2) \\
20 & u.s. coast guard open & starlite lanes & grand haven, michigan & aug 2-5 & george howard (4) \\
21 & brockton open & westgate lanes & brockton, massachusetts & aug 11-14 & bobby jacks (2) \\
22 & waukegan open & bertrand bowl & waukegan, illinois & aug 18-21 & bobby jacks (3) \\
23 & fort smith open & midland bowl & fort smith, arkansas & aug 25-28 & johnny petraglia (1) \\
24 & labor day classic & hart bowl & dallas, texas & sep 2-5 & bud horn (1) \\
25 & crescent city open & mardi gras bowl & new orleans, louisiana & sep 8-12 & barry asher (2) \\
26 & seventh annual pba national championship & garden city bowl & garden city, new york & nov 1-6 & wayne zahn (6) \\
27 & camden pba open & camden lanes & camden, new jersey & nov 9-12 & ralph engan (1) \\
28 & baltimore open & fair lanes-colt & baltimore, maryland & nov 17-20 & jim stefanich (1) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& bowling center \\
\midrule
0 & encino bowl \\
\bottomrule
\end{tabular}
| select bowling center where city = 'encino, california' order by city asc limit 736 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>event</th>
<th>bowling center</th>
<th>city</th>
<th>dates</th>
<th>winner</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>eastern open</td>
<td>edison lanes</td>
<td>edison, new jersey</td>
<td>dec 2-6</td>
<td>dennis chapis (2)</td>
</tr>
<tr>
<th>1</th>
<td>charlotte open</td>
<td>freedom lanes</td>
<td>charlotte, north carolina</td>
<td>dec 9-13</td>
<td>gene rhoda (3)</td>
</tr>
<tr>
<th>2</th>
<td>western open</td>
<td>saratoga lanes</td>
<td>san jose, california</td>
<td>jan 4-8</td>
<td>jim godman (1)</td>
</tr>
<tr>
<th>3</th>
<td>denver open</td>
<td>broadway bowl</td>
<td>denver, colorado</td>
<td>jan 11-15</td>
<td>dick weber (16)</td>
</tr>
<tr>
<th>4</th>
<td>hialeah-miami open</td>
<td>hialeah lanes</td>
<td>hialeah, florida</td>
<td>feb 1-5</td>
<td>les schissler (3)</td>
</tr>
<tr>
<th>5</th>
<td>mobile-sertoma open</td>
<td>florida lanes</td>
<td>mobile, alabama</td>
<td>feb 8-12</td>
<td>mike limongello (2)</td>
</tr>
<tr>
<th>6</th>
<td>fresno open</td>
<td>sunnyside bowl</td>
<td>fresno, california</td>
<td>feb 15-19</td>
<td>dick weber (17)</td>
</tr>
<tr>
<th>7</th>
<td>las vegas open</td>
<td>showboat lanes</td>
<td>las vegas, nevada</td>
<td>feb 22-26</td>
<td>skee foremsky (1)</td>
</tr>
<tr>
<th>8</th>
<td>miller high life open</td>
<td>bowlero lanes</td>
<td>milwaukee, wisconsin</td>
<td>mar 1-5</td>
<td>bill lillard (1)</td>
</tr>
<tr>
<th>9</th>
<td>st. paul open</td>
<td>all-star bowl</td>
<td>st. paul, minnesota</td>
<td>mar 8-12</td>
<td>gene rhoda (4)</td>
</tr>
<tr>
<th>10</th>
<td>buckeye open</td>
<td>imperial lanes</td>
<td>toledo, ohio</td>
<td>mar 15-19</td>
<td>pete tountas (2)</td>
</tr>
<tr>
<th>11</th>
<td>greater buffalo open</td>
<td>fairlanes</td>
<td>depew, new york</td>
<td>mar 22-26</td>
<td>bobby jacks (1)</td>
</tr>
<tr>
<th>12</th>
<td>firestone tournament of champions</td>
<td>riviera lanes</td>
<td>akron, ohio</td>
<td>mar 29 - apr 2</td>
<td>wayne zahn (4)</td>
</tr>
<tr>
<th>13</th>
<td>seattle open</td>
<td>ballinger bowl</td>
<td>seattle, washington</td>
<td>jun 9-12</td>
<td>wayne zahn (5)</td>
</tr>
<tr>
<th>14</th>
<td>portland open</td>
<td>valley lanes</td>
<td>portland, oregon</td>
<td>jun 16-19</td>
<td>don johnson (2)</td>
</tr>
<tr>
<th>15</th>
<td>fresno open</td>
<td>cedar lanes</td>
<td>fresno, california</td>
<td>jun 22-26</td>
<td>les schissler (4)</td>
</tr>
<tr>
<th>16</th>
<td>tucson squirt open</td>
<td>cactus bowl</td>
<td>tucson, arizona</td>
<td>jul 1-4</td>
<td>johnny guenther (2)</td>
</tr>
<tr>
<th>17</th>
<td>southern california open</td>
<td>encino bowl</td>
<td>encino, california</td>
<td>jul 7-10</td>
<td>barry asher (1)</td>
</tr>
<tr>
<th>18</th>
<td>fort worth open</td>
<td>meadowbrook lanes</td>
<td>fort worth, texas</td>
<td>jul 14-17</td>
<td>dick ritger (1)</td>
</tr>
<tr>
<th>19</th>
<td>reading open</td>
<td>hiester lanes</td>
<td>reading, pennsylvania</td>
<td>jul 28-31</td>
<td>dick ritger (2)</td>
</tr>
<tr>
<th>20</th>
<td>u.s. coast guard open</td>
<td>starlite lanes</td>
<td>grand haven, michigan</td>
<td>aug 2-5</td>
<td>george howard (4)</td>
</tr>
<tr>
<th>21</th>
<td>brockton open</td>
<td>westgate lanes</td>
<td>brockton, massachusetts</td>
<td>aug 11-14</td>
<td>bobby jacks (2)</td>
</tr>
<tr>
<th>22</th>
<td>waukegan open</td>
<td>bertrand bowl</td>
<td>waukegan, illinois</td>
<td>aug 18-21</td>
<td>bobby jacks (3)</td>
</tr>
<tr>
<th>23</th>
<td>fort smith open</td>
<td>midland bowl</td>
<td>fort smith, arkansas</td>
<td>aug 25-28</td>
<td>johnny petraglia (1)</td>
</tr>
<tr>
<th>24</th>
<td>labor day classic</td>
<td>hart bowl</td>
<td>dallas, texas</td>
<td>sep 2-5</td>
<td>bud horn (1)</td>
</tr>
<tr>
<th>25</th>
<td>crescent city open</td>
<td>mardi gras bowl</td>
<td>new orleans, louisiana</td>
<td>sep 8-12</td>
<td>barry asher (2)</td>
</tr>
<tr>
<th>26</th>
<td>seventh annual pba national championship</td>
<td>garden city bowl</td>
<td>garden city, new york</td>
<td>nov 1-6</td>
<td>wayne zahn (6)</td>
</tr>
<tr>
<th>27</th>
<td>camden pba open</td>
<td>camden lanes</td>
<td>camden, new jersey</td>
<td>nov 9-12</td>
<td>ralph engan (1)</td>
</tr>
<tr>
<th>28</th>
<td>baltimore open</td>
<td>fair lanes-colt</td>
<td>baltimore, maryland</td>
<td>nov 17-20</td>
<td>jim stefanich (1)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>bowling center</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>encino bowl</td>
</tr>
</tbody>
</table> | select bowling center where city = 'encino, california' order by city asc limit 736 <table_name> : table | | event | bowling center | city | dates | winner |
|---:|:-----------------------------------------|:------------------|:--------------------------|:---------------|:---------------------|
| 0 | eastern open | edison lanes | edison, new jersey | dec 2-6 | dennis chapis (2) |
| 1 | charlotte open | freedom lanes | charlotte, north carolina | dec 9-13 | gene rhoda (3) |
| 2 | western open | saratoga lanes | san jose, california | jan 4-8 | jim godman (1) |
| 3 | denver open | broadway bowl | denver, colorado | jan 11-15 | dick weber (16) |
| 4 | hialeah-miami open | hialeah lanes | hialeah, florida | feb 1-5 | les schissler (3) |
| 5 | mobile-sertoma open | florida lanes | mobile, alabama | feb 8-12 | mike limongello (2) |
| 6 | fresno open | sunnyside bowl | fresno, california | feb 15-19 | dick weber (17) |
| 7 | las vegas open | showboat lanes | las vegas, nevada | feb 22-26 | skee foremsky (1) |
| 8 | miller high life open | bowlero lanes | milwaukee, wisconsin | mar 1-5 | bill lillard (1) |
| 9 | st. paul open | all-star bowl | st. paul, minnesota | mar 8-12 | gene rhoda (4) |
| 10 | buckeye open | imperial lanes | toledo, ohio | mar 15-19 | pete tountas (2) |
| 11 | greater buffalo open | fairlanes | depew, new york | mar 22-26 | bobby jacks (1) |
| 12 | firestone tournament of champions | riviera lanes | akron, ohio | mar 29 - apr 2 | wayne zahn (4) |
| 13 | seattle open | ballinger bowl | seattle, washington | jun 9-12 | wayne zahn (5) |
| 14 | portland open | valley lanes | portland, oregon | jun 16-19 | don johnson (2) |
| 15 | fresno open | cedar lanes | fresno, california | jun 22-26 | les schissler (4) |
| 16 | tucson squirt open | cactus bowl | tucson, arizona | jul 1-4 | johnny guenther (2) |
| 17 | southern california open | encino bowl | encino, california | jul 7-10 | barry asher (1) |
| 18 | fort worth open | meadowbrook lanes | fort worth, texas | jul 14-17 | dick ritger (1) |
| 19 | reading open | hiester lanes | reading, pennsylvania | jul 28-31 | dick ritger (2) |
| 20 | u.s. coast guard open | starlite lanes | grand haven, michigan | aug 2-5 | george howard (4) |
| 21 | brockton open | westgate lanes | brockton, massachusetts | aug 11-14 | bobby jacks (2) |
| 22 | waukegan open | bertrand bowl | waukegan, illinois | aug 18-21 | bobby jacks (3) |
| 23 | fort smith open | midland bowl | fort smith, arkansas | aug 25-28 | johnny petraglia (1) |
| 24 | labor day classic | hart bowl | dallas, texas | sep 2-5 | bud horn (1) |
| 25 | crescent city open | mardi gras bowl | new orleans, louisiana | sep 8-12 | barry asher (2) |
| 26 | seventh annual pba national championship | garden city bowl | garden city, new york | nov 1-6 | wayne zahn (6) |
| 27 | camden pba open | camden lanes | camden, new jersey | nov 9-12 | ralph engan (1) |
| 28 | baltimore open | fair lanes-colt | baltimore, maryland | nov 17-20 | jim stefanich (1) | | | | bowling center |
|---:|:-----------------|
| 0 | encino bowl | | [
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select number of stars where notes = 'added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006' col : national team | title(s) represented | first worn | number of stars | notes row 1 : brazil | world cup | 1971 | 5 | third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968 row 2 : italy | world cup | 1982 | 4 | added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006 row 3 : germany | world cup | 1996 | 3 | 1954, 1974, third win was in 1990 row 4 : uruguay | world cup and olympics | 1930 | 4 | represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships row 5 : argentina | world cup | 2003 | 2 | 1978, second win was in 1986 row 6 : england | world cup | 2003 | 1 | title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve row 7 : france | world cup | 1998 | 1 | title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000 row 8 : spain | world cup | 2010 | 1 | title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony | col : number of stars row 1 : 4 | select number of stars where notes = 'added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006' <table_name> : table \begin{tabular}{llllll}
\toprule
& national team & title(s) represented & first worn & number of stars & notes \\
\midrule
0 & brazil & world cup & 1971 & 5 & third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968 \\
1 & italy & world cup & 1982 & 4 & added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006 \\
2 & germany & world cup & 1996 & 3 & 1954, 1974, third win was in 1990 \\
3 & uruguay & world cup and olympics & 1930 & 4 & represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships \\
4 & argentina & world cup & 2003 & 2 & 1978, second win was in 1986 \\
5 & england & world cup & 2003 & 1 & title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve \\
6 & france & world cup & 1998 & 1 & title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000 \\
7 & spain & world cup & 2010 & 1 & title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& number of stars \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select number of stars where notes = 'added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>national team</th>
<th>title(s) represented</th>
<th>first worn</th>
<th>number of stars</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>brazil</td>
<td>world cup</td>
<td>1971</td>
<td>5</td>
<td>third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968</td>
</tr>
<tr>
<th>1</th>
<td>italy</td>
<td>world cup</td>
<td>1982</td>
<td>4</td>
<td>added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006</td>
</tr>
<tr>
<th>2</th>
<td>germany</td>
<td>world cup</td>
<td>1996</td>
<td>3</td>
<td>1954, 1974, third win was in 1990</td>
</tr>
<tr>
<th>3</th>
<td>uruguay</td>
<td>world cup and olympics</td>
<td>1930</td>
<td>4</td>
<td>represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships</td>
</tr>
<tr>
<th>4</th>
<td>argentina</td>
<td>world cup</td>
<td>2003</td>
<td>2</td>
<td>1978, second win was in 1986</td>
</tr>
<tr>
<th>5</th>
<td>england</td>
<td>world cup</td>
<td>2003</td>
<td>1</td>
<td>title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve</td>
</tr>
<tr>
<th>6</th>
<td>france</td>
<td>world cup</td>
<td>1998</td>
<td>1</td>
<td>title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000</td>
</tr>
<tr>
<th>7</th>
<td>spain</td>
<td>world cup</td>
<td>2010</td>
<td>1</td>
<td>title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>number of stars</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select number of stars where notes = 'added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006' <table_name> : table | | national team | title(s) represented | first worn | number of stars | notes |
|---:|:----------------|:-----------------------|-------------:|------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | brazil | world cup | 1971 | 5 | third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968 |
| 1 | italy | world cup | 1982 | 4 | added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006 |
| 2 | germany | world cup | 1996 | 3 | 1954, 1974, third win was in 1990 |
| 3 | uruguay | world cup and olympics | 1930 | 4 | represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships |
| 4 | argentina | world cup | 2003 | 2 | 1978, second win was in 1986 |
| 5 | england | world cup | 2003 | 1 | title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve |
| 6 | france | world cup | 1998 | 1 | title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000 |
| 7 | spain | world cup | 2010 | 1 | title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony | | | | number of stars |
|---:|------------------:|
| 0 | 4 | | [
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select time behind where nation = 'greece' col : rank | lane | nation | swimmers | time | time behind | notes row 1 : none | 4 | united states | michael phelps (1:46.49) ryan lochte (1:47.52) peter vanderkaay (1:47.79) klete keller (1:45.53) | 7:07.33 | none | am row 2 : none | 5 | australia | grant hackett (1:47.50) michael klim (1:47.62) nicholas sprenger (1:48.16) ian thorpe (1:44.18) | 7:07.46 | 0.13 | none row 3 : none | 7 | italy | emiliano brembilla (1:48.16) massimiliano rosolino (1:46.24) simone cercato (1:49.85) filippo magnini (1:47.58) | 7:11.83 | 4.5 | none row 4 : 4 | 6 | great britain | simon burnett (1:47.90) gavin meadows (1:48.46) david o'brien (1:49.05) ross davenport (1:47.19) | 7:12.60 | 5.27 | none row 5 : 5 | 2 | canada | brent hayden (1:49.08) brian johns (1:49.15) andrew hurd (1:48.09) rick say (1:47.01) | 7:13.33 | 6 | none row 6 : 6 | 3 | germany | jens schreiber (1:49.08) heiko hell (1:49.15) lars conrad (1:48.23) christian keller (1:50.05) | 7:16.51 | 9.18 | none row 7 : 7 | 8 | france | amaury leveaux (1:48.57) fabien horth (1:48.67) nicolas kintz (1:50.01) nicolas rostoucher (1:50.18) | 7:17.43 | 10.1 | none row 8 : 8 | 1 | greece | apostolos antonopoulos (1:50.34) dimitrios manganas (1:51.33) andreas zisimos (1:50.26) nikolaos xylouris (1:51.09) | 7:23.02 | 15.67 | none | col : time behind row 1 : 15.67 | select time behind where nation = 'greece' <table_name> : table \begin{tabular}{llllllll}
\toprule
& rank & lane & nation & swimmers & time & time behind & notes \\
\midrule
0 & none & 4 & united states & michael phelps (1:46.49) ryan lochte (1:47.52) peter vanderkaay (1:47.79) klete keller (1:45.53) & 7:07.33 & none & am \\
1 & none & 5 & australia & grant hackett (1:47.50) michael klim (1:47.62) nicholas sprenger (1:48.16) ian thorpe (1:44.18) & 7:07.46 & 0.13 & none \\
2 & none & 7 & italy & emiliano brembilla (1:48.16) massimiliano rosolino (1:46.24) simone cercato (1:49.85) filippo magnini (1:47.58) & 7:11.83 & 4.5 & none \\
3 & 4 & 6 & great britain & simon burnett (1:47.90) gavin meadows (1:48.46) david o'brien (1:49.05) ross davenport (1:47.19) & 7:12.60 & 5.27 & none \\
4 & 5 & 2 & canada & brent hayden (1:49.08) brian johns (1:49.15) andrew hurd (1:48.09) rick say (1:47.01) & 7:13.33 & 6 & none \\
5 & 6 & 3 & germany & jens schreiber (1:49.08) heiko hell (1:49.15) lars conrad (1:48.23) christian keller (1:50.05) & 7:16.51 & 9.18 & none \\
6 & 7 & 8 & france & amaury leveaux (1:48.57) fabien horth (1:48.67) nicolas kintz (1:50.01) nicolas rostoucher (1:50.18) & 7:17.43 & 10.1 & none \\
7 & 8 & 1 & greece & apostolos antonopoulos (1:50.34) dimitrios manganas (1:51.33) andreas zisimos (1:50.26) nikolaos xylouris (1:51.09) & 7:23.02 & 15.67 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& time behind \\
\midrule
0 & 15.67 \\
\bottomrule
\end{tabular}
| select time behind where nation = 'greece' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>lane</th>
<th>nation</th>
<th>swimmers</th>
<th>time</th>
<th>time behind</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>4</td>
<td>united states</td>
<td>michael phelps (1:46.49) ryan lochte (1:47.52) peter vanderkaay (1:47.79) klete keller (1:45.53)</td>
<td>7:07.33</td>
<td>none</td>
<td>am</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>5</td>
<td>australia</td>
<td>grant hackett (1:47.50) michael klim (1:47.62) nicholas sprenger (1:48.16) ian thorpe (1:44.18)</td>
<td>7:07.46</td>
<td>0.13</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>7</td>
<td>italy</td>
<td>emiliano brembilla (1:48.16) massimiliano rosolino (1:46.24) simone cercato (1:49.85) filippo magnini (1:47.58)</td>
<td>7:11.83</td>
<td>4.5</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>6</td>
<td>great britain</td>
<td>simon burnett (1:47.90) gavin meadows (1:48.46) david o'brien (1:49.05) ross davenport (1:47.19)</td>
<td>7:12.60</td>
<td>5.27</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2</td>
<td>canada</td>
<td>brent hayden (1:49.08) brian johns (1:49.15) andrew hurd (1:48.09) rick say (1:47.01)</td>
<td>7:13.33</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>3</td>
<td>germany</td>
<td>jens schreiber (1:49.08) heiko hell (1:49.15) lars conrad (1:48.23) christian keller (1:50.05)</td>
<td>7:16.51</td>
<td>9.18</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>8</td>
<td>france</td>
<td>amaury leveaux (1:48.57) fabien horth (1:48.67) nicolas kintz (1:50.01) nicolas rostoucher (1:50.18)</td>
<td>7:17.43</td>
<td>10.1</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>1</td>
<td>greece</td>
<td>apostolos antonopoulos (1:50.34) dimitrios manganas (1:51.33) andreas zisimos (1:50.26) nikolaos xylouris (1:51.09)</td>
<td>7:23.02</td>
<td>15.67</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>time behind</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>15.67</td>
</tr>
</tbody>
</table> | select time behind where nation = 'greece' <table_name> : table | | rank | lane | nation | swimmers | time | time behind | notes |
|---:|:-------|-------:|:--------------|:--------------------------------------------------------------------------------------------------------------------|:--------|:--------------|:--------|
| 0 | none | 4 | united states | michael phelps (1:46.49) ryan lochte (1:47.52) peter vanderkaay (1:47.79) klete keller (1:45.53) | 7:07.33 | none | am |
| 1 | none | 5 | australia | grant hackett (1:47.50) michael klim (1:47.62) nicholas sprenger (1:48.16) ian thorpe (1:44.18) | 7:07.46 | 0.13 | none |
| 2 | none | 7 | italy | emiliano brembilla (1:48.16) massimiliano rosolino (1:46.24) simone cercato (1:49.85) filippo magnini (1:47.58) | 7:11.83 | 4.5 | none |
| 3 | 4 | 6 | great britain | simon burnett (1:47.90) gavin meadows (1:48.46) david o'brien (1:49.05) ross davenport (1:47.19) | 7:12.60 | 5.27 | none |
| 4 | 5 | 2 | canada | brent hayden (1:49.08) brian johns (1:49.15) andrew hurd (1:48.09) rick say (1:47.01) | 7:13.33 | 6 | none |
| 5 | 6 | 3 | germany | jens schreiber (1:49.08) heiko hell (1:49.15) lars conrad (1:48.23) christian keller (1:50.05) | 7:16.51 | 9.18 | none |
| 6 | 7 | 8 | france | amaury leveaux (1:48.57) fabien horth (1:48.67) nicolas kintz (1:50.01) nicolas rostoucher (1:50.18) | 7:17.43 | 10.1 | none |
| 7 | 8 | 1 | greece | apostolos antonopoulos (1:50.34) dimitrios manganas (1:51.33) andreas zisimos (1:50.26) nikolaos xylouris (1:51.09) | 7:23.02 | 15.67 | none | | | | time behind |
|---:|--------------:|
| 0 | 15.67 | | [
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] |
select count ( * ) where fate = 'changed call to 7rn in 1991' col : callsign | area served | frequency | band | fate | freq currently | purpose row 1 : 7cae | hobart | 92.1 | fm | changed call to 7the ca. 1980 | 7the | community row 2 : 7dy | derby | none | am | moved to scottsdale and changed call to 7sd in 1954 | 7sd | commercial row 3 : 7ex | launceston | 1008 | am | moved to fm in 2008 as 7exx | silent | commercial row 4 : 7ho | hobart | 864 | am | moved to fm in 1990 as 7hho | 7rph | commercial row 5 : 7ht | hobart | 1080 | am | moved to fm in 1998 as 7xxx | 7tab (hpon) | commercial row 6 : 7la | launceston | 1098 | am | moved to fm in 2008 as 7laa | silent | commercial row 7 : 7nt | launceston | 711 | am | moved to fm in 2006, retained call | silent | national row 8 : 7qn | queenstown | 630 | am | moved to fm in 1991, retained call | 7rn | national row 9 : 7qt | queenstown | 837 | am | changed call to 7xs in 1988 | 7xs | commercial row 10 : 7uv | ulverstone | none | am | moved to devonport and changed call to 7ad in 1940 | 7ad | commercial row 11 : 7zl | hobart | 603 | am | changed call to 7rn in 1991 | 7rn | national | col : count ( "*" ) row 1 : 1 | select count ( * ) where fate = 'changed call to 7rn in 1991' <table_name> : table \begin{tabular}{llllllll}
\toprule
& callsign & area served & frequency & band & fate & freq currently & purpose \\
\midrule
0 & 7cae & hobart & 92.1 & fm & changed call to 7the ca. 1980 & 7the & community \\
1 & 7dy & derby & none & am & moved to scottsdale and changed call to 7sd in 1954 & 7sd & commercial \\
2 & 7ex & launceston & 1008 & am & moved to fm in 2008 as 7exx & silent & commercial \\
3 & 7ho & hobart & 864 & am & moved to fm in 1990 as 7hho & 7rph & commercial \\
4 & 7ht & hobart & 1080 & am & moved to fm in 1998 as 7xxx & 7tab (hpon) & commercial \\
5 & 7la & launceston & 1098 & am & moved to fm in 2008 as 7laa & silent & commercial \\
6 & 7nt & launceston & 711 & am & moved to fm in 2006, retained call & silent & national \\
7 & 7qn & queenstown & 630 & am & moved to fm in 1991, retained call & 7rn & national \\
8 & 7qt & queenstown & 837 & am & changed call to 7xs in 1988 & 7xs & commercial \\
9 & 7uv & ulverstone & none & am & moved to devonport and changed call to 7ad in 1940 & 7ad & commercial \\
10 & 7zl & hobart & 603 & am & changed call to 7rn in 1991 & 7rn & national \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where fate = 'changed call to 7rn in 1991' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>callsign</th>
<th>area served</th>
<th>frequency</th>
<th>band</th>
<th>fate</th>
<th>freq currently</th>
<th>purpose</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7cae</td>
<td>hobart</td>
<td>92.1</td>
<td>fm</td>
<td>changed call to 7the ca. 1980</td>
<td>7the</td>
<td>community</td>
</tr>
<tr>
<th>1</th>
<td>7dy</td>
<td>derby</td>
<td>none</td>
<td>am</td>
<td>moved to scottsdale and changed call to 7sd in 1954</td>
<td>7sd</td>
<td>commercial</td>
</tr>
<tr>
<th>2</th>
<td>7ex</td>
<td>launceston</td>
<td>1008</td>
<td>am</td>
<td>moved to fm in 2008 as 7exx</td>
<td>silent</td>
<td>commercial</td>
</tr>
<tr>
<th>3</th>
<td>7ho</td>
<td>hobart</td>
<td>864</td>
<td>am</td>
<td>moved to fm in 1990 as 7hho</td>
<td>7rph</td>
<td>commercial</td>
</tr>
<tr>
<th>4</th>
<td>7ht</td>
<td>hobart</td>
<td>1080</td>
<td>am</td>
<td>moved to fm in 1998 as 7xxx</td>
<td>7tab (hpon)</td>
<td>commercial</td>
</tr>
<tr>
<th>5</th>
<td>7la</td>
<td>launceston</td>
<td>1098</td>
<td>am</td>
<td>moved to fm in 2008 as 7laa</td>
<td>silent</td>
<td>commercial</td>
</tr>
<tr>
<th>6</th>
<td>7nt</td>
<td>launceston</td>
<td>711</td>
<td>am</td>
<td>moved to fm in 2006, retained call</td>
<td>silent</td>
<td>national</td>
</tr>
<tr>
<th>7</th>
<td>7qn</td>
<td>queenstown</td>
<td>630</td>
<td>am</td>
<td>moved to fm in 1991, retained call</td>
<td>7rn</td>
<td>national</td>
</tr>
<tr>
<th>8</th>
<td>7qt</td>
<td>queenstown</td>
<td>837</td>
<td>am</td>
<td>changed call to 7xs in 1988</td>
<td>7xs</td>
<td>commercial</td>
</tr>
<tr>
<th>9</th>
<td>7uv</td>
<td>ulverstone</td>
<td>none</td>
<td>am</td>
<td>moved to devonport and changed call to 7ad in 1940</td>
<td>7ad</td>
<td>commercial</td>
</tr>
<tr>
<th>10</th>
<td>7zl</td>
<td>hobart</td>
<td>603</td>
<td>am</td>
<td>changed call to 7rn in 1991</td>
<td>7rn</td>
<td>national</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 fate = 'changed call to 7rn in 1991' <table_name> : table | | callsign | area served | frequency | band | fate | freq currently | purpose |
|---:|:-----------|:--------------|:------------|:-------|:----------------------------------------------------|:-----------------|:-----------|
| 0 | 7cae | hobart | 92.1 | fm | changed call to 7the ca. 1980 | 7the | community |
| 1 | 7dy | derby | none | am | moved to scottsdale and changed call to 7sd in 1954 | 7sd | commercial |
| 2 | 7ex | launceston | 1008 | am | moved to fm in 2008 as 7exx | silent | commercial |
| 3 | 7ho | hobart | 864 | am | moved to fm in 1990 as 7hho | 7rph | commercial |
| 4 | 7ht | hobart | 1080 | am | moved to fm in 1998 as 7xxx | 7tab (hpon) | commercial |
| 5 | 7la | launceston | 1098 | am | moved to fm in 2008 as 7laa | silent | commercial |
| 6 | 7nt | launceston | 711 | am | moved to fm in 2006, retained call | silent | national |
| 7 | 7qn | queenstown | 630 | am | moved to fm in 1991, retained call | 7rn | national |
| 8 | 7qt | queenstown | 837 | am | changed call to 7xs in 1988 | 7xs | commercial |
| 9 | 7uv | ulverstone | none | am | moved to devonport and changed call to 7ad in 1940 | 7ad | commercial |
| 10 | 7zl | hobart | 603 | am | changed call to 7rn in 1991 | 7rn | national | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select county where tally = ( select tally where county = 'kilkenny' ) + 1 col : rank | player | county | tally | total | opposition row 1 : 1 | nicky english | tipperary | 2-12 | 18 | antrim row 2 : 2 | mark corrigan | offaly | 3-7 | 16 | kilkenny row 3 : 3 | joe hennessy | kerry | 3-5 | 14 | limerick row 4 : 3 | finbarr delaney | cork | 1-11 | 14 | waterford row 5 : 5 | nicky english | tipperary | 0-13 | 13 | waterford row 6 : 5 | adrian ronan | kilkenny | 1-10 | 13 | westmeath row 7 : 7 | nicky english | tipperary | 2-5 | 11 | limerick row 8 : 7 | danny mcnaughton | antrim | 2-5 | 11 | down row 9 : 9 | m. j. ryan | dublin | 1-7 | 10 | laois row 10 : 10 | gary kirby | limerick | 1-6 | 9 | kerry row 11 : 10 | pat murphy | waterford | 3-0 | 9 | cork | col : count ( "county" ) row 1 : 0 | select county where tally = ( select tally where county = 'kilkenny' ) + 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & player & county & tally & total & opposition \\
\midrule
0 & 1 & nicky english & tipperary & 2-12 & 18 & antrim \\
1 & 2 & mark corrigan & offaly & 3-7 & 16 & kilkenny \\
2 & 3 & joe hennessy & kerry & 3-5 & 14 & limerick \\
3 & 3 & finbarr delaney & cork & 1-11 & 14 & waterford \\
4 & 5 & nicky english & tipperary & 0-13 & 13 & waterford \\
5 & 5 & adrian ronan & kilkenny & 1-10 & 13 & westmeath \\
6 & 7 & nicky english & tipperary & 2-5 & 11 & limerick \\
7 & 7 & danny mcnaughton & antrim & 2-5 & 11 & down \\
8 & 9 & m. j. ryan & dublin & 1-7 & 10 & laois \\
9 & 10 & gary kirby & limerick & 1-6 & 9 & kerry \\
10 & 10 & pat murphy & waterford & 3-0 & 9 & cork \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "county" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select county where tally = ( select tally where county = 'kilkenny' ) + 1 <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>nicky english</td>
<td>tipperary</td>
<td>2-12</td>
<td>18</td>
<td>antrim</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>mark corrigan</td>
<td>offaly</td>
<td>3-7</td>
<td>16</td>
<td>kilkenny</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>joe hennessy</td>
<td>kerry</td>
<td>3-5</td>
<td>14</td>
<td>limerick</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>finbarr delaney</td>
<td>cork</td>
<td>1-11</td>
<td>14</td>
<td>waterford</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>nicky english</td>
<td>tipperary</td>
<td>0-13</td>
<td>13</td>
<td>waterford</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>adrian ronan</td>
<td>kilkenny</td>
<td>1-10</td>
<td>13</td>
<td>westmeath</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>nicky english</td>
<td>tipperary</td>
<td>2-5</td>
<td>11</td>
<td>limerick</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>danny mcnaughton</td>
<td>antrim</td>
<td>2-5</td>
<td>11</td>
<td>down</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>m. j. ryan</td>
<td>dublin</td>
<td>1-7</td>
<td>10</td>
<td>laois</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>gary kirby</td>
<td>limerick</td>
<td>1-6</td>
<td>9</td>
<td>kerry</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>pat murphy</td>
<td>waterford</td>
<td>3-0</td>
<td>9</td>
<td>cork</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>0</td>
</tr>
</tbody>
</table> | select county where tally = ( select tally where county = 'kilkenny' ) + 1 <table_name> : table | | rank | player | county | tally | total | opposition |
|---:|-------:|:-----------------|:----------|:--------|--------:|:-------------|
| 0 | 1 | nicky english | tipperary | 2-12 | 18 | antrim |
| 1 | 2 | mark corrigan | offaly | 3-7 | 16 | kilkenny |
| 2 | 3 | joe hennessy | kerry | 3-5 | 14 | limerick |
| 3 | 3 | finbarr delaney | cork | 1-11 | 14 | waterford |
| 4 | 5 | nicky english | tipperary | 0-13 | 13 | waterford |
| 5 | 5 | adrian ronan | kilkenny | 1-10 | 13 | westmeath |
| 6 | 7 | nicky english | tipperary | 2-5 | 11 | limerick |
| 7 | 7 | danny mcnaughton | antrim | 2-5 | 11 | down |
| 8 | 9 | m. j. ryan | dublin | 1-7 | 10 | laois |
| 9 | 10 | gary kirby | limerick | 1-6 | 9 | kerry |
| 10 | 10 | pat murphy | waterford | 3-0 | 9 | cork | | | | count ( "county" ) |
|---:|---------------------:|
| 0 | 0 | | [
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select grid where laps = 86 col : pos | no | driver | team | laps | time/retired | grid | points row 1 : 1 | 32 | patrick carpentier | team player's | 87 | 1:48:11.023 | 1 | 22 row 2 : 2 | 1 | bruno junqueira | newman/haas racing | 87 | +0.8 secs | 2 | 17 row 3 : 3 | 3 | paul tracy | team player's | 87 | +28.6 secs | 3 | 14 row 4 : 4 | 9 | michel jourdain, jr | team rahal | 87 | +40.8 secs | 13 | 12 row 5 : 5 | 34 | mario haberfeld | mi-jack conquest racing | 87 | +42.1 secs | 6 | 10 row 6 : 6 | 20 | oriol servia | patrick racing | 87 | +1:00.2 | 10 | 8 row 7 : 7 | 51 | adrian fernandez | fernandez racing | 87 | +1:01.4 | 5 | 6 row 8 : 8 | 12 | jimmy vasser | american spirit team johansson | 87 | +1:01.8 | 8 | 5 row 9 : 9 | 7 | tiago monteiro | fittipaldi-dingman racing | 86 | + 1 lap | 15 | 4 row 10 : 10 | 55 | mario dominguez | herdez competition | 86 | + 1 lap | 11 | 3 row 11 : 11 | 27 | bryan herta | pk racing | 86 | + 1 lap | 12 | 2 row 12 : 12 | 31 | ryan hunter-reay | american spirit team johansson | 86 | + 1 lap | 17 | 1 row 13 : 13 | 19 | joel camathias | dale coyne racing | 85 | + 2 laps | 18 | 0 row 14 : 14 | 33 | alex tagliani | rocketsports racing | 85 | + 2 laps | 14 | 0 row 15 : 15 | 4 | roberto moreno | herdez competition | 85 | + 2 laps | 9 | 0 row 16 : 16 | 11 | geoff boss | dale coyne racing | 83 | mechanical | 19 | 0 row 17 : 17 | 2 | sebastien bourdais | newman/haas racing | 77 | mechanical | 4 | 0 row 18 : 18 | 15 | darren manning | walker racing | 12 | mechanical | 7 | 0 row 19 : 19 | 5 | rodolfo lavin | walker racing | 10 | mechanical | 16 | 0 | col : grid row 1 : 15 row 2 : 11 row 3 : 12 row 4 : 17 | select grid where laps = 86 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & team & laps & time/retired & grid & points \\
\midrule
0 & 1 & 32 & patrick carpentier & team player's & 87 & 1:48:11.023 & 1 & 22 \\
1 & 2 & 1 & bruno junqueira & newman/haas racing & 87 & +0.8 secs & 2 & 17 \\
2 & 3 & 3 & paul tracy & team player's & 87 & +28.6 secs & 3 & 14 \\
3 & 4 & 9 & michel jourdain, jr & team rahal & 87 & +40.8 secs & 13 & 12 \\
4 & 5 & 34 & mario haberfeld & mi-jack conquest racing & 87 & +42.1 secs & 6 & 10 \\
5 & 6 & 20 & oriol servia & patrick racing & 87 & +1:00.2 & 10 & 8 \\
6 & 7 & 51 & adrian fernandez & fernandez racing & 87 & +1:01.4 & 5 & 6 \\
7 & 8 & 12 & jimmy vasser & american spirit team johansson & 87 & +1:01.8 & 8 & 5 \\
8 & 9 & 7 & tiago monteiro & fittipaldi-dingman racing & 86 & + 1 lap & 15 & 4 \\
9 & 10 & 55 & mario dominguez & herdez competition & 86 & + 1 lap & 11 & 3 \\
10 & 11 & 27 & bryan herta & pk racing & 86 & + 1 lap & 12 & 2 \\
11 & 12 & 31 & ryan hunter-reay & american spirit team johansson & 86 & + 1 lap & 17 & 1 \\
12 & 13 & 19 & joel camathias & dale coyne racing & 85 & + 2 laps & 18 & 0 \\
13 & 14 & 33 & alex tagliani & rocketsports racing & 85 & + 2 laps & 14 & 0 \\
14 & 15 & 4 & roberto moreno & herdez competition & 85 & + 2 laps & 9 & 0 \\
15 & 16 & 11 & geoff boss & dale coyne racing & 83 & mechanical & 19 & 0 \\
16 & 17 & 2 & sebastien bourdais & newman/haas racing & 77 & mechanical & 4 & 0 \\
17 & 18 & 15 & darren manning & walker racing & 12 & mechanical & 7 & 0 \\
18 & 19 & 5 & rodolfo lavin & walker racing & 10 & mechanical & 16 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& grid \\
\midrule
0 & 15 \\
1 & 11 \\
2 & 12 \\
3 & 17 \\
\bottomrule
\end{tabular}
| select grid where laps = 86 <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>32</td>
<td>patrick carpentier</td>
<td>team player's</td>
<td>87</td>
<td>1:48:11.023</td>
<td>1</td>
<td>22</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1</td>
<td>bruno junqueira</td>
<td>newman/haas racing</td>
<td>87</td>
<td>+0.8 secs</td>
<td>2</td>
<td>17</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>3</td>
<td>paul tracy</td>
<td>team player's</td>
<td>87</td>
<td>+28.6 secs</td>
<td>3</td>
<td>14</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>9</td>
<td>michel jourdain, jr</td>
<td>team rahal</td>
<td>87</td>
<td>+40.8 secs</td>
<td>13</td>
<td>12</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>34</td>
<td>mario haberfeld</td>
<td>mi-jack conquest racing</td>
<td>87</td>
<td>+42.1 secs</td>
<td>6</td>
<td>10</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>20</td>
<td>oriol servia</td>
<td>patrick racing</td>
<td>87</td>
<td>+1:00.2</td>
<td>10</td>
<td>8</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>51</td>
<td>adrian fernandez</td>
<td>fernandez racing</td>
<td>87</td>
<td>+1:01.4</td>
<td>5</td>
<td>6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>12</td>
<td>jimmy vasser</td>
<td>american spirit team johansson</td>
<td>87</td>
<td>+1:01.8</td>
<td>8</td>
<td>5</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>7</td>
<td>tiago monteiro</td>
<td>fittipaldi-dingman racing</td>
<td>86</td>
<td>+ 1 lap</td>
<td>15</td>
<td>4</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>55</td>
<td>mario dominguez</td>
<td>herdez competition</td>
<td>86</td>
<td>+ 1 lap</td>
<td>11</td>
<td>3</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>27</td>
<td>bryan herta</td>
<td>pk racing</td>
<td>86</td>
<td>+ 1 lap</td>
<td>12</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>31</td>
<td>ryan hunter-reay</td>
<td>american spirit team johansson</td>
<td>86</td>
<td>+ 1 lap</td>
<td>17</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>19</td>
<td>joel camathias</td>
<td>dale coyne racing</td>
<td>85</td>
<td>+ 2 laps</td>
<td>18</td>
<td>0</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>33</td>
<td>alex tagliani</td>
<td>rocketsports racing</td>
<td>85</td>
<td>+ 2 laps</td>
<td>14</td>
<td>0</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>4</td>
<td>roberto moreno</td>
<td>herdez competition</td>
<td>85</td>
<td>+ 2 laps</td>
<td>9</td>
<td>0</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>11</td>
<td>geoff boss</td>
<td>dale coyne racing</td>
<td>83</td>
<td>mechanical</td>
<td>19</td>
<td>0</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>2</td>
<td>sebastien bourdais</td>
<td>newman/haas racing</td>
<td>77</td>
<td>mechanical</td>
<td>4</td>
<td>0</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>15</td>
<td>darren manning</td>
<td>walker racing</td>
<td>12</td>
<td>mechanical</td>
<td>7</td>
<td>0</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>5</td>
<td>rodolfo lavin</td>
<td>walker racing</td>
<td>10</td>
<td>mechanical</td>
<td>16</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>grid</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>15</td>
</tr>
<tr>
<th>1</th>
<td>11</td>
</tr>
<tr>
<th>2</th>
<td>12</td>
</tr>
<tr>
<th>3</th>
<td>17</td>
</tr>
</tbody>
</table> | select grid where laps = 86 <table_name> : table | | pos | no | driver | team | laps | time/retired | grid | points |
|---:|------:|-----:|:--------------------|:-------------------------------|-------:|:---------------|-------:|---------:|
| 0 | 1 | 32 | patrick carpentier | team player's | 87 | 1:48:11.023 | 1 | 22 |
| 1 | 2 | 1 | bruno junqueira | newman/haas racing | 87 | +0.8 secs | 2 | 17 |
| 2 | 3 | 3 | paul tracy | team player's | 87 | +28.6 secs | 3 | 14 |
| 3 | 4 | 9 | michel jourdain, jr | team rahal | 87 | +40.8 secs | 13 | 12 |
| 4 | 5 | 34 | mario haberfeld | mi-jack conquest racing | 87 | +42.1 secs | 6 | 10 |
| 5 | 6 | 20 | oriol servia | patrick racing | 87 | +1:00.2 | 10 | 8 |
| 6 | 7 | 51 | adrian fernandez | fernandez racing | 87 | +1:01.4 | 5 | 6 |
| 7 | 8 | 12 | jimmy vasser | american spirit team johansson | 87 | +1:01.8 | 8 | 5 |
| 8 | 9 | 7 | tiago monteiro | fittipaldi-dingman racing | 86 | + 1 lap | 15 | 4 |
| 9 | 10 | 55 | mario dominguez | herdez competition | 86 | + 1 lap | 11 | 3 |
| 10 | 11 | 27 | bryan herta | pk racing | 86 | + 1 lap | 12 | 2 |
| 11 | 12 | 31 | ryan hunter-reay | american spirit team johansson | 86 | + 1 lap | 17 | 1 |
| 12 | 13 | 19 | joel camathias | dale coyne racing | 85 | + 2 laps | 18 | 0 |
| 13 | 14 | 33 | alex tagliani | rocketsports racing | 85 | + 2 laps | 14 | 0 |
| 14 | 15 | 4 | roberto moreno | herdez competition | 85 | + 2 laps | 9 | 0 |
| 15 | 16 | 11 | geoff boss | dale coyne racing | 83 | mechanical | 19 | 0 |
| 16 | 17 | 2 | sebastien bourdais | newman/haas racing | 77 | mechanical | 4 | 0 |
| 17 | 18 | 15 | darren manning | walker racing | 12 | mechanical | 7 | 0 |
| 18 | 19 | 5 | rodolfo lavin | walker racing | 10 | mechanical | 16 | 0 | | | | grid |
|---:|-------:|
| 0 | 15 |
| 1 | 11 |
| 2 | 12 |
| 3 | 17 | | [
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select count ( * ) where song = 2 col : year | song | album | position | chart row 1 : 1987 | "summergirls" | 24/7 | 50 | billboard hot 100 row 2 : 1989 | "24/7" | 24/7 | 42 | billboard hot 100 row 3 : 1989 | "24/7" | 24/7 | 12 | hot r&b/hip-hop songs row 4 : 1989 | "i like it" | 24/7 | 7 | billboard hot 100 row 5 : 1989 | "i like it" | 24/7 | 3 | hot dance club play row 6 : 1989 | "sunshine" | 24/7 | 23 | billboard hot 100 row 7 : 1990 | "never 2 much of u" | 24/7 | 61 | billboard hot 100 row 8 : 1990 | "romeo" | swingin' | 6 | billboard hot 100 row 9 : 1991 | "gentle" | swingin' | 31 | billboard hot 100 row 10 : 1993 | "ooh child" | the way i am | 27 | billboard hot 100 row 11 : 1993 | "endlessly" | the way i am | none | billboard hot 100 | col : count ( "*" ) row 1 : 0 | select count ( * ) where song = 2 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & song & album & position & chart \\
\midrule
0 & 1987 & "summergirls" & 24/7 & 50 & billboard hot 100 \\
1 & 1989 & "24/7" & 24/7 & 42 & billboard hot 100 \\
2 & 1989 & "24/7" & 24/7 & 12 & hot r&b/hip-hop songs \\
3 & 1989 & "i like it" & 24/7 & 7 & billboard hot 100 \\
4 & 1989 & "i like it" & 24/7 & 3 & hot dance club play \\
5 & 1989 & "sunshine" & 24/7 & 23 & billboard hot 100 \\
6 & 1990 & "never 2 much of u" & 24/7 & 61 & billboard hot 100 \\
7 & 1990 & "romeo" & swingin' & 6 & billboard hot 100 \\
8 & 1991 & "gentle" & swingin' & 31 & billboard hot 100 \\
9 & 1993 & "ooh child" & the way i am & 27 & billboard hot 100 \\
10 & 1993 & "endlessly" & the way i am & none & billboard hot 100 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where song = 2 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>song</th>
<th>album</th>
<th>position</th>
<th>chart</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1987</td>
<td>"summergirls"</td>
<td>24/7</td>
<td>50</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>1</th>
<td>1989</td>
<td>"24/7"</td>
<td>24/7</td>
<td>42</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>2</th>
<td>1989</td>
<td>"24/7"</td>
<td>24/7</td>
<td>12</td>
<td>hot r&b/hip-hop songs</td>
</tr>
<tr>
<th>3</th>
<td>1989</td>
<td>"i like it"</td>
<td>24/7</td>
<td>7</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>4</th>
<td>1989</td>
<td>"i like it"</td>
<td>24/7</td>
<td>3</td>
<td>hot dance club play</td>
</tr>
<tr>
<th>5</th>
<td>1989</td>
<td>"sunshine"</td>
<td>24/7</td>
<td>23</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>6</th>
<td>1990</td>
<td>"never 2 much of u"</td>
<td>24/7</td>
<td>61</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>7</th>
<td>1990</td>
<td>"romeo"</td>
<td>swingin'</td>
<td>6</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>8</th>
<td>1991</td>
<td>"gentle"</td>
<td>swingin'</td>
<td>31</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>9</th>
<td>1993</td>
<td>"ooh child"</td>
<td>the way i am</td>
<td>27</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>10</th>
<td>1993</td>
<td>"endlessly"</td>
<td>the way i am</td>
<td>none</td>
<td>billboard hot 100</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 song = 2 <table_name> : table | | year | song | album | position | chart |
|---:|-------:|:--------------------|:-------------|:-----------|:----------------------|
| 0 | 1987 | "summergirls" | 24/7 | 50 | billboard hot 100 |
| 1 | 1989 | "24/7" | 24/7 | 42 | billboard hot 100 |
| 2 | 1989 | "24/7" | 24/7 | 12 | hot r&b/hip-hop songs |
| 3 | 1989 | "i like it" | 24/7 | 7 | billboard hot 100 |
| 4 | 1989 | "i like it" | 24/7 | 3 | hot dance club play |
| 5 | 1989 | "sunshine" | 24/7 | 23 | billboard hot 100 |
| 6 | 1990 | "never 2 much of u" | 24/7 | 61 | billboard hot 100 |
| 7 | 1990 | "romeo" | swingin' | 6 | billboard hot 100 |
| 8 | 1991 | "gentle" | swingin' | 31 | billboard hot 100 |
| 9 | 1993 | "ooh child" | the way i am | 27 | billboard hot 100 |
| 10 | 1993 | "endlessly" | the way i am | none | billboard hot 100 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select min ( year ) where year > 10 col : year | film | role | language | notes row 1 : 2009 | toss: a flip of destiny | sherry | hindi | none row 2 : 2009 | aa okkadu | dr. pavitra | telugu | none row 3 : 2010 | mouna ragam | sandhya | telugu | none row 4 : 2010 | saradaga kasepu | manimala | telugu | none row 5 : 2010 | orange | madhu | telugu | special appearance row 6 : 2012 | kamaal dhamaal malamaal | maria | hindi | none row 7 : 2013 | mahankali | tanisha | telugu | none row 8 : 2013 | shadow | none | telugu | none row 9 : 2013 | eepeeko | none | tamil | filming row 10 : 2013 | black coffee | none | malayalam | filming row 11 : 2014 | koothara | shaista | malayalam | filming row 12 : 2014 | kotha janta | none | telugu | filming row 13 : 2013 | serndhu polama | none | tamil | filming | col : min ( "year" ) row 1 : 2009 | select min ( year ) where year > 10 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & film & role & language & notes \\
\midrule
0 & 2009 & toss: a flip of destiny & sherry & hindi & none \\
1 & 2009 & aa okkadu & dr. pavitra & telugu & none \\
2 & 2010 & mouna ragam & sandhya & telugu & none \\
3 & 2010 & saradaga kasepu & manimala & telugu & none \\
4 & 2010 & orange & madhu & telugu & special appearance \\
5 & 2012 & kamaal dhamaal malamaal & maria & hindi & none \\
6 & 2013 & mahankali & tanisha & telugu & none \\
7 & 2013 & shadow & none & telugu & none \\
8 & 2013 & eepeeko & none & tamil & filming \\
9 & 2013 & black coffee & none & malayalam & filming \\
10 & 2014 & koothara & shaista & malayalam & filming \\
11 & 2014 & kotha janta & none & telugu & filming \\
12 & 2013 & serndhu polama & none & tamil & filming \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& min ( "year" ) \\
\midrule
0 & 2009 \\
\bottomrule
\end{tabular}
| select min ( year ) where year > 10 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>film</th>
<th>role</th>
<th>language</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2009</td>
<td>toss: a flip of destiny</td>
<td>sherry</td>
<td>hindi</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2009</td>
<td>aa okkadu</td>
<td>dr. pavitra</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2010</td>
<td>mouna ragam</td>
<td>sandhya</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2010</td>
<td>saradaga kasepu</td>
<td>manimala</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2010</td>
<td>orange</td>
<td>madhu</td>
<td>telugu</td>
<td>special appearance</td>
</tr>
<tr>
<th>5</th>
<td>2012</td>
<td>kamaal dhamaal malamaal</td>
<td>maria</td>
<td>hindi</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2013</td>
<td>mahankali</td>
<td>tanisha</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>2013</td>
<td>shadow</td>
<td>none</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2013</td>
<td>eepeeko</td>
<td>none</td>
<td>tamil</td>
<td>filming</td>
</tr>
<tr>
<th>9</th>
<td>2013</td>
<td>black coffee</td>
<td>none</td>
<td>malayalam</td>
<td>filming</td>
</tr>
<tr>
<th>10</th>
<td>2014</td>
<td>koothara</td>
<td>shaista</td>
<td>malayalam</td>
<td>filming</td>
</tr>
<tr>
<th>11</th>
<td>2014</td>
<td>kotha janta</td>
<td>none</td>
<td>telugu</td>
<td>filming</td>
</tr>
<tr>
<th>12</th>
<td>2013</td>
<td>serndhu polama</td>
<td>none</td>
<td>tamil</td>
<td>filming</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>min ( "year" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2009</td>
</tr>
</tbody>
</table> | select min ( year ) where year > 10 <table_name> : table | | year | film | role | language | notes |
|---:|-------:|:------------------------|:------------|:-----------|:-------------------|
| 0 | 2009 | toss: a flip of destiny | sherry | hindi | none |
| 1 | 2009 | aa okkadu | dr. pavitra | telugu | none |
| 2 | 2010 | mouna ragam | sandhya | telugu | none |
| 3 | 2010 | saradaga kasepu | manimala | telugu | none |
| 4 | 2010 | orange | madhu | telugu | special appearance |
| 5 | 2012 | kamaal dhamaal malamaal | maria | hindi | none |
| 6 | 2013 | mahankali | tanisha | telugu | none |
| 7 | 2013 | shadow | none | telugu | none |
| 8 | 2013 | eepeeko | none | tamil | filming |
| 9 | 2013 | black coffee | none | malayalam | filming |
| 10 | 2014 | koothara | shaista | malayalam | filming |
| 11 | 2014 | kotha janta | none | telugu | filming |
| 12 | 2013 | serndhu polama | none | tamil | filming | | | | min ( "year" ) |
|---:|-----------------:|
| 0 | 2009 | | [
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] |
select count ( pos ) where time = 'did not start' col : pos | no | rider | bike | laps | time | grid | points row 1 : 1 | 93 | marc marquez | derbi | 22 | 40:46.315 | 1 | 25 row 2 : 2 | 38 | bradley smith | aprilia | 22 | 4.638 | 3 | 20 row 3 : 3 | 44 | pol espargaro | derbi | 22 | 4.996 | 2 | 16 row 4 : 4 | 11 | sandro cortese | derbi | 22 | 45.366 | 5 | 13 row 5 : 5 | 7 | efren vazquez | derbi | 22 | 45.433 | 8 | 11 row 6 : 6 | 71 | tomoyoshi koyama | aprilia | 22 | 49.685 | 6 | 10 row 7 : 7 | 35 | randy krummenacher | aprilia | 22 | 49.735 | 14 | 9 row 8 : 8 | 14 | johann zarco | aprilia | 22 | 49.743 | 10 | 8 row 9 : 9 | 94 | jonas folger | aprilia | 22 | 49.775 | 12 | 7 row 10 : 10 | 99 | danny webb | aprilia | 22 | 53.115 | 16 | 6 row 11 : 11 | 26 | adrian martin | aprilia | 22 | 58.669 | 19 | 5 row 12 : 12 | 15 | simone grotzkyj | aprilia | 22 | 58.8 | 11 | 4 row 13 : 13 | 23 | alberto moncayo | aprilia | 22 | +1:02.050 | 13 | 3 row 14 : 14 | 78 | marcel schrotter | honda | 22 | +1:15.497 | 23 | 2 row 15 : 15 | 63 | zulfahmi khairuddin | aprilia | 22 | +1:16.029 | 18 | 1 row 16 : 16 | 84 | jakub kornfeil | aprilia | 22 | +1:26.441 | 28 | none row 17 : 17 | 69 | louis rossi | aprilia | 22 | +1:33.613 | 24 | none row 18 : 18 | 87 | luca marconi | aprilia | 22 | +1:36.186 | 25 | none row 19 : 19 | 58 | joan perello | honda | 22 | +1:36.223 | 26 | none row 20 : 20 | 60 | michael van der mark | lambretta | 22 | +1:36.340 | 27 | none row 21 : 21 | 59 | johnny rosell | honda | 22 | +1:43.804 | 22 | none row 22 : 22 | 72 | marco ravaioli | lambretta | 22 | +1:55.331 | 30 | none row 23 : 23 | 56 | peter sebestyen | aprilia | 21 | +1 lap | 32 | none row 24 : ret | 40 | nicolas terol | aprilia | 21 | accident | 4 | none row 25 : ret | 39 | luis salom | aprilia | 14 | retirement | 15 | none row 26 : ret | 17 | eduard lopez | aprilia | 11 | retirement | 31 | none row 27 : ret | 55 | isaac vinales | aprilia | 10 | accident | 21 | none row 28 : ret | 50 | sturla fagerhaug | aprilia | 7 | accident | 17 | none row 29 : ret | 5 | alexis masbou | aprilia | 5 | accident | 9 | none row 30 : ret | 12 | esteve rabat | aprilia | 0 | accident | 7 | none row 31 : ret | 53 | jasper iwema | aprilia | 0 | accident | 20 | none row 32 : dns | 32 | lorenzo savadori | aprilia | none | did not start | 29 | none | col : count ( "pos" ) row 1 : 1 | select count ( pos ) where time = 'did not start' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & rider & bike & laps & time & grid & points \\
\midrule
0 & 1 & 93 & marc marquez & derbi & 22 & 40:46.315 & 1 & 25 \\
1 & 2 & 38 & bradley smith & aprilia & 22 & 4.638 & 3 & 20 \\
2 & 3 & 44 & pol espargaro & derbi & 22 & 4.996 & 2 & 16 \\
3 & 4 & 11 & sandro cortese & derbi & 22 & 45.366 & 5 & 13 \\
4 & 5 & 7 & efren vazquez & derbi & 22 & 45.433 & 8 & 11 \\
5 & 6 & 71 & tomoyoshi koyama & aprilia & 22 & 49.685 & 6 & 10 \\
6 & 7 & 35 & randy krummenacher & aprilia & 22 & 49.735 & 14 & 9 \\
7 & 8 & 14 & johann zarco & aprilia & 22 & 49.743 & 10 & 8 \\
8 & 9 & 94 & jonas folger & aprilia & 22 & 49.775 & 12 & 7 \\
9 & 10 & 99 & danny webb & aprilia & 22 & 53.115 & 16 & 6 \\
10 & 11 & 26 & adrian martin & aprilia & 22 & 58.669 & 19 & 5 \\
11 & 12 & 15 & simone grotzkyj & aprilia & 22 & 58.8 & 11 & 4 \\
12 & 13 & 23 & alberto moncayo & aprilia & 22 & +1:02.050 & 13 & 3 \\
13 & 14 & 78 & marcel schrotter & honda & 22 & +1:15.497 & 23 & 2 \\
14 & 15 & 63 & zulfahmi khairuddin & aprilia & 22 & +1:16.029 & 18 & 1 \\
15 & 16 & 84 & jakub kornfeil & aprilia & 22 & +1:26.441 & 28 & none \\
16 & 17 & 69 & louis rossi & aprilia & 22 & +1:33.613 & 24 & none \\
17 & 18 & 87 & luca marconi & aprilia & 22 & +1:36.186 & 25 & none \\
18 & 19 & 58 & joan perello & honda & 22 & +1:36.223 & 26 & none \\
19 & 20 & 60 & michael van der mark & lambretta & 22 & +1:36.340 & 27 & none \\
20 & 21 & 59 & johnny rosell & honda & 22 & +1:43.804 & 22 & none \\
21 & 22 & 72 & marco ravaioli & lambretta & 22 & +1:55.331 & 30 & none \\
22 & 23 & 56 & peter sebestyen & aprilia & 21 & +1 lap & 32 & none \\
23 & ret & 40 & nicolas terol & aprilia & 21 & accident & 4 & none \\
24 & ret & 39 & luis salom & aprilia & 14 & retirement & 15 & none \\
25 & ret & 17 & eduard lopez & aprilia & 11 & retirement & 31 & none \\
26 & ret & 55 & isaac vinales & aprilia & 10 & accident & 21 & none \\
27 & ret & 50 & sturla fagerhaug & aprilia & 7 & accident & 17 & none \\
28 & ret & 5 & alexis masbou & aprilia & 5 & accident & 9 & none \\
29 & ret & 12 & esteve rabat & aprilia & 0 & accident & 7 & none \\
30 & ret & 53 & jasper iwema & aprilia & 0 & accident & 20 & none \\
31 & dns & 32 & lorenzo savadori & aprilia & none & did not start & 29 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "pos" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( pos ) where time = 'did not start' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>rider</th>
<th>bike</th>
<th>laps</th>
<th>time</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>93</td>
<td>marc marquez</td>
<td>derbi</td>
<td>22</td>
<td>40:46.315</td>
<td>1</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>38</td>
<td>bradley smith</td>
<td>aprilia</td>
<td>22</td>
<td>4.638</td>
<td>3</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>44</td>
<td>pol espargaro</td>
<td>derbi</td>
<td>22</td>
<td>4.996</td>
<td>2</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>11</td>
<td>sandro cortese</td>
<td>derbi</td>
<td>22</td>
<td>45.366</td>
<td>5</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>7</td>
<td>efren vazquez</td>
<td>derbi</td>
<td>22</td>
<td>45.433</td>
<td>8</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>71</td>
<td>tomoyoshi koyama</td>
<td>aprilia</td>
<td>22</td>
<td>49.685</td>
<td>6</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>35</td>
<td>randy krummenacher</td>
<td>aprilia</td>
<td>22</td>
<td>49.735</td>
<td>14</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>14</td>
<td>johann zarco</td>
<td>aprilia</td>
<td>22</td>
<td>49.743</td>
<td>10</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>94</td>
<td>jonas folger</td>
<td>aprilia</td>
<td>22</td>
<td>49.775</td>
<td>12</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>99</td>
<td>danny webb</td>
<td>aprilia</td>
<td>22</td>
<td>53.115</td>
<td>16</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>26</td>
<td>adrian martin</td>
<td>aprilia</td>
<td>22</td>
<td>58.669</td>
<td>19</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>15</td>
<td>simone grotzkyj</td>
<td>aprilia</td>
<td>22</td>
<td>58.8</td>
<td>11</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>23</td>
<td>alberto moncayo</td>
<td>aprilia</td>
<td>22</td>
<td>+1:02.050</td>
<td>13</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>78</td>
<td>marcel schrotter</td>
<td>honda</td>
<td>22</td>
<td>+1:15.497</td>
<td>23</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>63</td>
<td>zulfahmi khairuddin</td>
<td>aprilia</td>
<td>22</td>
<td>+1:16.029</td>
<td>18</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>84</td>
<td>jakub kornfeil</td>
<td>aprilia</td>
<td>22</td>
<td>+1:26.441</td>
<td>28</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>69</td>
<td>louis rossi</td>
<td>aprilia</td>
<td>22</td>
<td>+1:33.613</td>
<td>24</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>87</td>
<td>luca marconi</td>
<td>aprilia</td>
<td>22</td>
<td>+1:36.186</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>58</td>
<td>joan perello</td>
<td>honda</td>
<td>22</td>
<td>+1:36.223</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>60</td>
<td>michael van der mark</td>
<td>lambretta</td>
<td>22</td>
<td>+1:36.340</td>
<td>27</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>59</td>
<td>johnny rosell</td>
<td>honda</td>
<td>22</td>
<td>+1:43.804</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>72</td>
<td>marco ravaioli</td>
<td>lambretta</td>
<td>22</td>
<td>+1:55.331</td>
<td>30</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>56</td>
<td>peter sebestyen</td>
<td>aprilia</td>
<td>21</td>
<td>+1 lap</td>
<td>32</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>ret</td>
<td>40</td>
<td>nicolas terol</td>
<td>aprilia</td>
<td>21</td>
<td>accident</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>39</td>
<td>luis salom</td>
<td>aprilia</td>
<td>14</td>
<td>retirement</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>17</td>
<td>eduard lopez</td>
<td>aprilia</td>
<td>11</td>
<td>retirement</td>
<td>31</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>ret</td>
<td>55</td>
<td>isaac vinales</td>
<td>aprilia</td>
<td>10</td>
<td>accident</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>ret</td>
<td>50</td>
<td>sturla fagerhaug</td>
<td>aprilia</td>
<td>7</td>
<td>accident</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>ret</td>
<td>5</td>
<td>alexis masbou</td>
<td>aprilia</td>
<td>5</td>
<td>accident</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>ret</td>
<td>12</td>
<td>esteve rabat</td>
<td>aprilia</td>
<td>0</td>
<td>accident</td>
<td>7</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>ret</td>
<td>53</td>
<td>jasper iwema</td>
<td>aprilia</td>
<td>0</td>
<td>accident</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>dns</td>
<td>32</td>
<td>lorenzo savadori</td>
<td>aprilia</td>
<td>none</td>
<td>did not start</td>
<td>29</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "pos" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( pos ) where time = 'did not start' <table_name> : table | | pos | no | rider | bike | laps | time | grid | points |
|---:|:------|-----:|:---------------------|:----------|:-------|:--------------|-------:|:---------|
| 0 | 1 | 93 | marc marquez | derbi | 22 | 40:46.315 | 1 | 25 |
| 1 | 2 | 38 | bradley smith | aprilia | 22 | 4.638 | 3 | 20 |
| 2 | 3 | 44 | pol espargaro | derbi | 22 | 4.996 | 2 | 16 |
| 3 | 4 | 11 | sandro cortese | derbi | 22 | 45.366 | 5 | 13 |
| 4 | 5 | 7 | efren vazquez | derbi | 22 | 45.433 | 8 | 11 |
| 5 | 6 | 71 | tomoyoshi koyama | aprilia | 22 | 49.685 | 6 | 10 |
| 6 | 7 | 35 | randy krummenacher | aprilia | 22 | 49.735 | 14 | 9 |
| 7 | 8 | 14 | johann zarco | aprilia | 22 | 49.743 | 10 | 8 |
| 8 | 9 | 94 | jonas folger | aprilia | 22 | 49.775 | 12 | 7 |
| 9 | 10 | 99 | danny webb | aprilia | 22 | 53.115 | 16 | 6 |
| 10 | 11 | 26 | adrian martin | aprilia | 22 | 58.669 | 19 | 5 |
| 11 | 12 | 15 | simone grotzkyj | aprilia | 22 | 58.8 | 11 | 4 |
| 12 | 13 | 23 | alberto moncayo | aprilia | 22 | +1:02.050 | 13 | 3 |
| 13 | 14 | 78 | marcel schrotter | honda | 22 | +1:15.497 | 23 | 2 |
| 14 | 15 | 63 | zulfahmi khairuddin | aprilia | 22 | +1:16.029 | 18 | 1 |
| 15 | 16 | 84 | jakub kornfeil | aprilia | 22 | +1:26.441 | 28 | none |
| 16 | 17 | 69 | louis rossi | aprilia | 22 | +1:33.613 | 24 | none |
| 17 | 18 | 87 | luca marconi | aprilia | 22 | +1:36.186 | 25 | none |
| 18 | 19 | 58 | joan perello | honda | 22 | +1:36.223 | 26 | none |
| 19 | 20 | 60 | michael van der mark | lambretta | 22 | +1:36.340 | 27 | none |
| 20 | 21 | 59 | johnny rosell | honda | 22 | +1:43.804 | 22 | none |
| 21 | 22 | 72 | marco ravaioli | lambretta | 22 | +1:55.331 | 30 | none |
| 22 | 23 | 56 | peter sebestyen | aprilia | 21 | +1 lap | 32 | none |
| 23 | ret | 40 | nicolas terol | aprilia | 21 | accident | 4 | none |
| 24 | ret | 39 | luis salom | aprilia | 14 | retirement | 15 | none |
| 25 | ret | 17 | eduard lopez | aprilia | 11 | retirement | 31 | none |
| 26 | ret | 55 | isaac vinales | aprilia | 10 | accident | 21 | none |
| 27 | ret | 50 | sturla fagerhaug | aprilia | 7 | accident | 17 | none |
| 28 | ret | 5 | alexis masbou | aprilia | 5 | accident | 9 | none |
| 29 | ret | 12 | esteve rabat | aprilia | 0 | accident | 7 | none |
| 30 | ret | 53 | jasper iwema | aprilia | 0 | accident | 20 | none |
| 31 | dns | 32 | lorenzo savadori | aprilia | none | did not start | 29 | none | | | | count ( "pos" ) |
|---:|------------------:|
| 0 | 1 | | [
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select venue where # = 6 col : # | date | venue | opponent | score | result | competition row 1 : 1 | 2011-02-08 00:00:00 | stade georges pompidou, valence, france | mali | 1-0 | 1-0 | friendly row 2 : 2 | 2011-05-11 00:00:00 | stade felix houphouet-boigny, abidjan, cote d'ivoire | namibia | 4-1 | 5-1 | friendly row 3 : 3 | 2011-06-05 00:00:00 | stade de l'amitie, cotonou, benin | benin | 0-1 | 2-6 | 2012 africa cup of nations qualification - group h row 4 : 4 | 2011-08-10 00:00:00 | stade de geneve, geneve, switzerland | israel | 1-0 | 4-3 | friendly row 5 : 5 | 2011-09-03 00:00:00 | stade amahoro, kigali, rwanda | rwanda | 0-4 | 0-5 | 2012 africa cup of nations qualification - group h row 6 : 6 | 2012-11-14 00:00:00 | linzer stadion, linz, austria | austria | 0-1 | 0-3 | friendly row 7 : 7 | 2013-01-14 00:00:00 | al nahyan stadium, abu dhabi, united arab emirates | egypt | 4-2 | 4-2 | friendly row 8 : 8 | 2013-01-26 00:00:00 | royal bafokeng stadium, rustenburg, south africa | tunisia | 3-0 | 3-0 | 2013 africa cup of nations | col : venue row 1 : linzer stadion, linz, austria | select venue where # = 6 <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & date & venue & opponent & score & result & competition \\
\midrule
0 & 1 & 2011-02-08 00:00:00 & stade georges pompidou, valence, france & mali & 1-0 & 1-0 & friendly \\
1 & 2 & 2011-05-11 00:00:00 & stade felix houphouet-boigny, abidjan, cote d'ivoire & namibia & 4-1 & 5-1 & friendly \\
2 & 3 & 2011-06-05 00:00:00 & stade de l'amitie, cotonou, benin & benin & 0-1 & 2-6 & 2012 africa cup of nations qualification - group h \\
3 & 4 & 2011-08-10 00:00:00 & stade de geneve, geneve, switzerland & israel & 1-0 & 4-3 & friendly \\
4 & 5 & 2011-09-03 00:00:00 & stade amahoro, kigali, rwanda & rwanda & 0-4 & 0-5 & 2012 africa cup of nations qualification - group h \\
5 & 6 & 2012-11-14 00:00:00 & linzer stadion, linz, austria & austria & 0-1 & 0-3 & friendly \\
6 & 7 & 2013-01-14 00:00:00 & al nahyan stadium, abu dhabi, united arab emirates & egypt & 4-2 & 4-2 & friendly \\
7 & 8 & 2013-01-26 00:00:00 & royal bafokeng stadium, rustenburg, south africa & tunisia & 3-0 & 3-0 & 2013 africa cup of nations \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& venue \\
\midrule
0 & linzer stadion, linz, austria \\
\bottomrule
\end{tabular}
| select venue where # = 6 <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>2011-02-08 00:00:00</td>
<td>stade georges pompidou, valence, france</td>
<td>mali</td>
<td>1-0</td>
<td>1-0</td>
<td>friendly</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2011-05-11 00:00:00</td>
<td>stade felix houphouet-boigny, abidjan, cote d'ivoire</td>
<td>namibia</td>
<td>4-1</td>
<td>5-1</td>
<td>friendly</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2011-06-05 00:00:00</td>
<td>stade de l'amitie, cotonou, benin</td>
<td>benin</td>
<td>0-1</td>
<td>2-6</td>
<td>2012 africa cup of nations qualification - group h</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2011-08-10 00:00:00</td>
<td>stade de geneve, geneve, switzerland</td>
<td>israel</td>
<td>1-0</td>
<td>4-3</td>
<td>friendly</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2011-09-03 00:00:00</td>
<td>stade amahoro, kigali, rwanda</td>
<td>rwanda</td>
<td>0-4</td>
<td>0-5</td>
<td>2012 africa cup of nations qualification - group h</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2012-11-14 00:00:00</td>
<td>linzer stadion, linz, austria</td>
<td>austria</td>
<td>0-1</td>
<td>0-3</td>
<td>friendly</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2013-01-14 00:00:00</td>
<td>al nahyan stadium, abu dhabi, united arab emirates</td>
<td>egypt</td>
<td>4-2</td>
<td>4-2</td>
<td>friendly</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2013-01-26 00:00:00</td>
<td>royal bafokeng stadium, rustenburg, south africa</td>
<td>tunisia</td>
<td>3-0</td>
<td>3-0</td>
<td>2013 africa cup of nations</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>venue</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>linzer stadion, linz, austria</td>
</tr>
</tbody>
</table> | select venue where # = 6 <table_name> : table | | # | date | venue | opponent | score | result | competition |
|---:|----:|:--------------------|:-----------------------------------------------------|:-----------|:--------|:---------|:---------------------------------------------------|
| 0 | 1 | 2011-02-08 00:00:00 | stade georges pompidou, valence, france | mali | 1-0 | 1-0 | friendly |
| 1 | 2 | 2011-05-11 00:00:00 | stade felix houphouet-boigny, abidjan, cote d'ivoire | namibia | 4-1 | 5-1 | friendly |
| 2 | 3 | 2011-06-05 00:00:00 | stade de l'amitie, cotonou, benin | benin | 0-1 | 2-6 | 2012 africa cup of nations qualification - group h |
| 3 | 4 | 2011-08-10 00:00:00 | stade de geneve, geneve, switzerland | israel | 1-0 | 4-3 | friendly |
| 4 | 5 | 2011-09-03 00:00:00 | stade amahoro, kigali, rwanda | rwanda | 0-4 | 0-5 | 2012 africa cup of nations qualification - group h |
| 5 | 6 | 2012-11-14 00:00:00 | linzer stadion, linz, austria | austria | 0-1 | 0-3 | friendly |
| 6 | 7 | 2013-01-14 00:00:00 | al nahyan stadium, abu dhabi, united arab emirates | egypt | 4-2 | 4-2 | friendly |
| 7 | 8 | 2013-01-26 00:00:00 | royal bafokeng stadium, rustenburg, south africa | tunisia | 3-0 | 3-0 | 2013 africa cup of nations | | | | venue |
|---:|:------------------------------|
| 0 | linzer stadion, linz, austria | | [
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select termini where year opened = 1928 col : line | year opened | termini -1 | termini -2 row 1 : j church | 1917 | embarcadero station | balboa park station row 2 : k ingleside | 1918 | embarcadero station | balboa park station row 3 : l taraval | 1919 | embarcadero station | 46th avenue and wawona san francisco zoo row 4 : m ocean view | 1925 | embarcadero station | san jose and geneva balboa park station row 5 : n judah | 1928 | 4th and king station caltrain depot | judah and la playa ocean beach row 6 : t third street | 2007 | west portal station | sunnydale station row 7 : s castro shuttle (peak hours & game days) | none | embarcadero station 4th and king station (game days) | castro station west portal station (game days) | col : min ( "termini" ) row 1 : judah and la playa ocean beach | select termini where year opened = 1928 <table_name> : table \begin{tabular}{lllll}
\toprule
& line & year opened & termini -1 & termini -2 \\
\midrule
0 & j church & 1917 & embarcadero station & balboa park station \\
1 & k ingleside & 1918 & embarcadero station & balboa park station \\
2 & l taraval & 1919 & embarcadero station & 46th avenue and wawona san francisco zoo \\
3 & m ocean view & 1925 & embarcadero station & san jose and geneva balboa park station \\
4 & n judah & 1928 & 4th and king station caltrain depot & judah and la playa ocean beach \\
5 & t third street & 2007 & west portal station & sunnydale station \\
6 & s castro shuttle (peak hours & game days) & none & embarcadero station 4th and king station (game days) & castro station west portal station (game days) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& min ( "termini" ) \\
\midrule
0 & judah and la playa ocean beach \\
\bottomrule
\end{tabular}
| select termini where year opened = 1928 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>line</th>
<th>year opened</th>
<th>termini -1</th>
<th>termini -2</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>j church</td>
<td>1917</td>
<td>embarcadero station</td>
<td>balboa park station</td>
</tr>
<tr>
<th>1</th>
<td>k ingleside</td>
<td>1918</td>
<td>embarcadero station</td>
<td>balboa park station</td>
</tr>
<tr>
<th>2</th>
<td>l taraval</td>
<td>1919</td>
<td>embarcadero station</td>
<td>46th avenue and wawona san francisco zoo</td>
</tr>
<tr>
<th>3</th>
<td>m ocean view</td>
<td>1925</td>
<td>embarcadero station</td>
<td>san jose and geneva balboa park station</td>
</tr>
<tr>
<th>4</th>
<td>n judah</td>
<td>1928</td>
<td>4th and king station caltrain depot</td>
<td>judah and la playa ocean beach</td>
</tr>
<tr>
<th>5</th>
<td>t third street</td>
<td>2007</td>
<td>west portal station</td>
<td>sunnydale station</td>
</tr>
<tr>
<th>6</th>
<td>s castro shuttle (peak hours & game days)</td>
<td>none</td>
<td>embarcadero station 4th and king station (game days)</td>
<td>castro station west portal station (game days)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>min ( "termini" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>judah and la playa ocean beach</td>
</tr>
</tbody>
</table> | select termini where year opened = 1928 <table_name> : table | | line | year opened | termini -1 | termini -2 |
|---:|:------------------------------------------|:--------------|:-----------------------------------------------------|:-----------------------------------------------|
| 0 | j church | 1917 | embarcadero station | balboa park station |
| 1 | k ingleside | 1918 | embarcadero station | balboa park station |
| 2 | l taraval | 1919 | embarcadero station | 46th avenue and wawona san francisco zoo |
| 3 | m ocean view | 1925 | embarcadero station | san jose and geneva balboa park station |
| 4 | n judah | 1928 | 4th and king station caltrain depot | judah and la playa ocean beach |
| 5 | t third street | 2007 | west portal station | sunnydale station |
| 6 | s castro shuttle (peak hours & game days) | none | embarcadero station 4th and king station (game days) | castro station west portal station (game days) | | | | min ( "termini" ) |
|---:|:-------------------------------|
| 0 | judah and la playa ocean beach | | [
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select grid where driver = 'cliff allison' col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 7 | jo bonnier | brm | 75 | 2:05:26.8 | 1 | 8 row 2 : 2 | 8 | jack brabham | cooper-climax | 75 | + 14.2 | 2 | 6 row 3 : 3 | 9 | masten gregory | cooper-climax | 75 | + 1:23.0 | 7 | 4 row 4 : 4 | 12 | innes ireland | lotus-climax | 74 | + 1 lap | 9 | 3 row 5 : 5 | 1 | jean behra | ferrari | 74 | + 1 lap | 4 | 2 row 6 : 6 | 3 | phil hill | ferrari | 73 | + 2 laps | 12 | none row 7 : 7 | 14 | graham hill | lotus-climax | 73 | + 2 laps | 5 | none row 8 : 8 | 10 | maurice trintignant | cooper-climax | 73 | + 2 laps | 11 | none row 9 : 9 | 16 | cliff allison | ferrari | 71 | + 4 laps | 15 | none row 10 : 10 | 15 | carel godin de beaufort | porsche | 68 | + 7 laps | 14 | none row 11 : ret | 11 | stirling moss | cooper-climax | 62 | gearbox | 3 | 1 row 12 : ret | 6 | harry schell | brm | 46 | gearbox | 6 | none row 13 : ret | 2 | tony brooks | ferrari | 42 | oil leak | 8 | none row 14 : ret | 5 | carroll shelby | aston martin | 25 | engine | 10 | none row 15 : ret | 4 | roy salvadori | aston martin | 3 | engine | 13 | none | col : grid row 1 : 15 | select grid where driver = 'cliff allison' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 7 & jo bonnier & brm & 75 & 2:05:26.8 & 1 & 8 \\
1 & 2 & 8 & jack brabham & cooper-climax & 75 & + 14.2 & 2 & 6 \\
2 & 3 & 9 & masten gregory & cooper-climax & 75 & + 1:23.0 & 7 & 4 \\
3 & 4 & 12 & innes ireland & lotus-climax & 74 & + 1 lap & 9 & 3 \\
4 & 5 & 1 & jean behra & ferrari & 74 & + 1 lap & 4 & 2 \\
5 & 6 & 3 & phil hill & ferrari & 73 & + 2 laps & 12 & none \\
6 & 7 & 14 & graham hill & lotus-climax & 73 & + 2 laps & 5 & none \\
7 & 8 & 10 & maurice trintignant & cooper-climax & 73 & + 2 laps & 11 & none \\
8 & 9 & 16 & cliff allison & ferrari & 71 & + 4 laps & 15 & none \\
9 & 10 & 15 & carel godin de beaufort & porsche & 68 & + 7 laps & 14 & none \\
10 & ret & 11 & stirling moss & cooper-climax & 62 & gearbox & 3 & 1 \\
11 & ret & 6 & harry schell & brm & 46 & gearbox & 6 & none \\
12 & ret & 2 & tony brooks & ferrari & 42 & oil leak & 8 & none \\
13 & ret & 5 & carroll shelby & aston martin & 25 & engine & 10 & none \\
14 & ret & 4 & roy salvadori & aston martin & 3 & engine & 13 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& grid \\
\midrule
0 & 15 \\
\bottomrule
\end{tabular}
| select grid where driver = 'cliff allison' <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>7</td>
<td>jo bonnier</td>
<td>brm</td>
<td>75</td>
<td>2:05:26.8</td>
<td>1</td>
<td>8</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>8</td>
<td>jack brabham</td>
<td>cooper-climax</td>
<td>75</td>
<td>+ 14.2</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>9</td>
<td>masten gregory</td>
<td>cooper-climax</td>
<td>75</td>
<td>+ 1:23.0</td>
<td>7</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>12</td>
<td>innes ireland</td>
<td>lotus-climax</td>
<td>74</td>
<td>+ 1 lap</td>
<td>9</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1</td>
<td>jean behra</td>
<td>ferrari</td>
<td>74</td>
<td>+ 1 lap</td>
<td>4</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>3</td>
<td>phil hill</td>
<td>ferrari</td>
<td>73</td>
<td>+ 2 laps</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>14</td>
<td>graham hill</td>
<td>lotus-climax</td>
<td>73</td>
<td>+ 2 laps</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>10</td>
<td>maurice trintignant</td>
<td>cooper-climax</td>
<td>73</td>
<td>+ 2 laps</td>
<td>11</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>16</td>
<td>cliff allison</td>
<td>ferrari</td>
<td>71</td>
<td>+ 4 laps</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>15</td>
<td>carel godin de beaufort</td>
<td>porsche</td>
<td>68</td>
<td>+ 7 laps</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>ret</td>
<td>11</td>
<td>stirling moss</td>
<td>cooper-climax</td>
<td>62</td>
<td>gearbox</td>
<td>3</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>ret</td>
<td>6</td>
<td>harry schell</td>
<td>brm</td>
<td>46</td>
<td>gearbox</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>ret</td>
<td>2</td>
<td>tony brooks</td>
<td>ferrari</td>
<td>42</td>
<td>oil leak</td>
<td>8</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>ret</td>
<td>5</td>
<td>carroll shelby</td>
<td>aston martin</td>
<td>25</td>
<td>engine</td>
<td>10</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>ret</td>
<td>4</td>
<td>roy salvadori</td>
<td>aston martin</td>
<td>3</td>
<td>engine</td>
<td>13</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>grid</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>15</td>
</tr>
</tbody>
</table> | select grid where driver = 'cliff allison' <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:------------------------|:--------------|-------:|:---------------|-------:|:---------|
| 0 | 1 | 7 | jo bonnier | brm | 75 | 2:05:26.8 | 1 | 8 |
| 1 | 2 | 8 | jack brabham | cooper-climax | 75 | + 14.2 | 2 | 6 |
| 2 | 3 | 9 | masten gregory | cooper-climax | 75 | + 1:23.0 | 7 | 4 |
| 3 | 4 | 12 | innes ireland | lotus-climax | 74 | + 1 lap | 9 | 3 |
| 4 | 5 | 1 | jean behra | ferrari | 74 | + 1 lap | 4 | 2 |
| 5 | 6 | 3 | phil hill | ferrari | 73 | + 2 laps | 12 | none |
| 6 | 7 | 14 | graham hill | lotus-climax | 73 | + 2 laps | 5 | none |
| 7 | 8 | 10 | maurice trintignant | cooper-climax | 73 | + 2 laps | 11 | none |
| 8 | 9 | 16 | cliff allison | ferrari | 71 | + 4 laps | 15 | none |
| 9 | 10 | 15 | carel godin de beaufort | porsche | 68 | + 7 laps | 14 | none |
| 10 | ret | 11 | stirling moss | cooper-climax | 62 | gearbox | 3 | 1 |
| 11 | ret | 6 | harry schell | brm | 46 | gearbox | 6 | none |
| 12 | ret | 2 | tony brooks | ferrari | 42 | oil leak | 8 | none |
| 13 | ret | 5 | carroll shelby | aston martin | 25 | engine | 10 | none |
| 14 | ret | 4 | roy salvadori | aston martin | 3 | engine | 13 | none | | | | grid |
|---:|-------:|
| 0 | 15 | | [
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select count ( * ) where title = 'the velvet touch' col : year | title | role | notes row 1 : 1941 | the maltese falcon | kasper gutman | nominated - academy award for best supporting actor row 2 : 1941 | they died with their boots on | lt. gen. winfield scott | none row 3 : 1942 | across the pacific | dr. lorenz | none row 4 : 1942 | casablanca | signor ferrari | none row 5 : 1943 | background to danger | col. robinson | none row 6 : 1944 | passage to marseille | major duval | none row 7 : 1944 | between two worlds | rev. tim thompson | none row 8 : 1944 | the mask of dimitrios | mr. peters | none row 9 : 1944 | the conspirators | ricardo quintanilla | none row 10 : 1944 | hollywood canteen | himself | none row 11 : 1945 | pillow to post | col. michael otley | none row 12 : 1945 | conflict | dr. mark hamilton | none row 13 : 1945 | christmas in connecticut | alexander yardley | none row 14 : 1946 | three strangers | jerome k. arbutny | none row 15 : 1946 | devotion | william makepeace thackeray | none row 16 : 1946 | the verdict | supt. george edward grodman | none row 17 : 1947 | that way with women | james p. alden | none row 18 : 1947 | the hucksters | evan llewellyn evans | none row 19 : 1948 | the velvet touch | capt. danbury | none row 20 : 1948 | ruthless | buck mansfield | none row 21 : 1948 | the woman in white | count alessandro fosco | none row 22 : 1949 | flamingo road | sheriff titus semple | none row 23 : 1949 | malaya | the dutchman | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where title = 'the velvet touch' <table_name> : table \begin{tabular}{lllll}
\toprule
& year & title & role & notes \\
\midrule
0 & 1941 & the maltese falcon & kasper gutman & nominated - academy award for best supporting actor \\
1 & 1941 & they died with their boots on & lt. gen. winfield scott & none \\
2 & 1942 & across the pacific & dr. lorenz & none \\
3 & 1942 & casablanca & signor ferrari & none \\
4 & 1943 & background to danger & col. robinson & none \\
5 & 1944 & passage to marseille & major duval & none \\
6 & 1944 & between two worlds & rev. tim thompson & none \\
7 & 1944 & the mask of dimitrios & mr. peters & none \\
8 & 1944 & the conspirators & ricardo quintanilla & none \\
9 & 1944 & hollywood canteen & himself & none \\
10 & 1945 & pillow to post & col. michael otley & none \\
11 & 1945 & conflict & dr. mark hamilton & none \\
12 & 1945 & christmas in connecticut & alexander yardley & none \\
13 & 1946 & three strangers & jerome k. arbutny & none \\
14 & 1946 & devotion & william makepeace thackeray & none \\
15 & 1946 & the verdict & supt. george edward grodman & none \\
16 & 1947 & that way with women & james p. alden & none \\
17 & 1947 & the hucksters & evan llewellyn evans & none \\
18 & 1948 & the velvet touch & capt. danbury & none \\
19 & 1948 & ruthless & buck mansfield & none \\
20 & 1948 & the woman in white & count alessandro fosco & none \\
21 & 1949 & flamingo road & sheriff titus semple & none \\
22 & 1949 & malaya & the dutchman & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where title = 'the velvet touch' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>role</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1941</td>
<td>the maltese falcon</td>
<td>kasper gutman</td>
<td>nominated - academy award for best supporting actor</td>
</tr>
<tr>
<th>1</th>
<td>1941</td>
<td>they died with their boots on</td>
<td>lt. gen. winfield scott</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1942</td>
<td>across the pacific</td>
<td>dr. lorenz</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1942</td>
<td>casablanca</td>
<td>signor ferrari</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1943</td>
<td>background to danger</td>
<td>col. robinson</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1944</td>
<td>passage to marseille</td>
<td>major duval</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1944</td>
<td>between two worlds</td>
<td>rev. tim thompson</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1944</td>
<td>the mask of dimitrios</td>
<td>mr. peters</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1944</td>
<td>the conspirators</td>
<td>ricardo quintanilla</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1944</td>
<td>hollywood canteen</td>
<td>himself</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>1945</td>
<td>pillow to post</td>
<td>col. michael otley</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>1945</td>
<td>conflict</td>
<td>dr. mark hamilton</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>1945</td>
<td>christmas in connecticut</td>
<td>alexander yardley</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1946</td>
<td>three strangers</td>
<td>jerome k. arbutny</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>1946</td>
<td>devotion</td>
<td>william makepeace thackeray</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>1946</td>
<td>the verdict</td>
<td>supt. george edward grodman</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>1947</td>
<td>that way with women</td>
<td>james p. alden</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>1947</td>
<td>the hucksters</td>
<td>evan llewellyn evans</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>1948</td>
<td>the velvet touch</td>
<td>capt. danbury</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>1948</td>
<td>ruthless</td>
<td>buck mansfield</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>1948</td>
<td>the woman in white</td>
<td>count alessandro fosco</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>1949</td>
<td>flamingo road</td>
<td>sheriff titus semple</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>1949</td>
<td>malaya</td>
<td>the dutchman</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 title = 'the velvet touch' <table_name> : table | | year | title | role | notes |
|---:|-------:|:------------------------------|:----------------------------|:----------------------------------------------------|
| 0 | 1941 | the maltese falcon | kasper gutman | nominated - academy award for best supporting actor |
| 1 | 1941 | they died with their boots on | lt. gen. winfield scott | none |
| 2 | 1942 | across the pacific | dr. lorenz | none |
| 3 | 1942 | casablanca | signor ferrari | none |
| 4 | 1943 | background to danger | col. robinson | none |
| 5 | 1944 | passage to marseille | major duval | none |
| 6 | 1944 | between two worlds | rev. tim thompson | none |
| 7 | 1944 | the mask of dimitrios | mr. peters | none |
| 8 | 1944 | the conspirators | ricardo quintanilla | none |
| 9 | 1944 | hollywood canteen | himself | none |
| 10 | 1945 | pillow to post | col. michael otley | none |
| 11 | 1945 | conflict | dr. mark hamilton | none |
| 12 | 1945 | christmas in connecticut | alexander yardley | none |
| 13 | 1946 | three strangers | jerome k. arbutny | none |
| 14 | 1946 | devotion | william makepeace thackeray | none |
| 15 | 1946 | the verdict | supt. george edward grodman | none |
| 16 | 1947 | that way with women | james p. alden | none |
| 17 | 1947 | the hucksters | evan llewellyn evans | none |
| 18 | 1948 | the velvet touch | capt. danbury | none |
| 19 | 1948 | ruthless | buck mansfield | none |
| 20 | 1948 | the woman in white | count alessandro fosco | none |
| 21 | 1949 | flamingo road | sheriff titus semple | none |
| 22 | 1949 | malaya | the dutchman | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( score ) where # < 15 col : # | date | opponent | score | win | loss | save | crowd | record row 1 : 1 | apr 3 | @min | w 8-1 | morris | williams | none | 34381 | 1-0 row 2 : 2 | apr 5 | @min | w 7-3 | petry | viola | none | 8373 | 2-0 row 3 : 3 | apr 6 | @chw | w 3-2 | wilcox | dotson | hernandez | 42692 | 3-0 row 4 : 4 | apr 7 | @chw | w 4-0 | morris | bannister | none | 24616 | 4-0 row 5 : 5 | apr 8 | @chw | w 7-3 | lopez | seaver | none | 20478 | 5-0 row 6 : 6 | apr 10 | tex | w 5-1 | petry | stewart | none | 51238 | 6-0 row 7 : 7 | apr 12 | tex | w 9-4 | morris | tanana | none | 19154 | 7-0 row 8 : 8 | apr 13 | @bos | w 13-9 | bair | hurst | none | 35179 | 8-0 row 9 : 9 | apr 18 | kcr | w 4-3 (10) | hernandez | beckwith | none | 12310 | 9-0 row 10 : 10 | apr 19 | kcr | l 2-5 | saberhagen | petry | quisenberry | 12100 | 9-1 row 11 : 11 | apr 20 | chw | w 3-2 | lopez | reed | none | 33554 | 10-1 row 12 : 12 | apr 21 | chw | w 4-1 | rozema | hoyt | bair | 34395 | 11-1 row 13 : 13 | apr 22 | chw | w 9-1 | berenguer | brennan | none | 10603 | 12-1 row 14 : 14 | apr 24 | min | w 6-5 | morris | davis | none | none | 13-1 row 15 : 15 | apr 24 | min | w 4-3 | abbott | viola | lopez | 20315 | 14-1 row 16 : 16 | apr 25 | @tex | w 9-4 | wilcox | stewart | hernandez | 25883 | 15-1 row 17 : 17 | apr 26 | @tex | w 7-5 | bair | tanana | lopez | 13559 | 16-1 row 18 : 18 | apr 27 | cle | l 4-8 (19) | aponte | abbott | none | 34112 | 16-2 row 19 : 19 | apr 28 | cle | w 6-2 | morris | behenna | none | 28253 | 17-2 row 20 : 20 | apr 29 | cle | w 6-1 | petry | spillner | none | 24853 | 18-2 | col : count ( "score" ) row 1 : 6 | select count ( score ) where # < 15 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& # & date & opponent & score & win & loss & save & crowd & record \\
\midrule
0 & 1 & apr 3 & @min & w 8-1 & morris & williams & none & 34381 & 1-0 \\
1 & 2 & apr 5 & @min & w 7-3 & petry & viola & none & 8373 & 2-0 \\
2 & 3 & apr 6 & @chw & w 3-2 & wilcox & dotson & hernandez & 42692 & 3-0 \\
3 & 4 & apr 7 & @chw & w 4-0 & morris & bannister & none & 24616 & 4-0 \\
4 & 5 & apr 8 & @chw & w 7-3 & lopez & seaver & none & 20478 & 5-0 \\
5 & 6 & apr 10 & tex & w 5-1 & petry & stewart & none & 51238 & 6-0 \\
6 & 7 & apr 12 & tex & w 9-4 & morris & tanana & none & 19154 & 7-0 \\
7 & 8 & apr 13 & @bos & w 13-9 & bair & hurst & none & 35179 & 8-0 \\
8 & 9 & apr 18 & kcr & w 4-3 (10) & hernandez & beckwith & none & 12310 & 9-0 \\
9 & 10 & apr 19 & kcr & l 2-5 & saberhagen & petry & quisenberry & 12100 & 9-1 \\
10 & 11 & apr 20 & chw & w 3-2 & lopez & reed & none & 33554 & 10-1 \\
11 & 12 & apr 21 & chw & w 4-1 & rozema & hoyt & bair & 34395 & 11-1 \\
12 & 13 & apr 22 & chw & w 9-1 & berenguer & brennan & none & 10603 & 12-1 \\
13 & 14 & apr 24 & min & w 6-5 & morris & davis & none & none & 13-1 \\
14 & 15 & apr 24 & min & w 4-3 & abbott & viola & lopez & 20315 & 14-1 \\
15 & 16 & apr 25 & @tex & w 9-4 & wilcox & stewart & hernandez & 25883 & 15-1 \\
16 & 17 & apr 26 & @tex & w 7-5 & bair & tanana & lopez & 13559 & 16-1 \\
17 & 18 & apr 27 & cle & l 4-8 (19) & aponte & abbott & none & 34112 & 16-2 \\
18 & 19 & apr 28 & cle & w 6-2 & morris & behenna & none & 28253 & 17-2 \\
19 & 20 & apr 29 & cle & w 6-1 & petry & spillner & none & 24853 & 18-2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "score" ) \\
\midrule
0 & 6 \\
\bottomrule
\end{tabular}
| select count ( score ) where # < 15 <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>win</th>
<th>loss</th>
<th>save</th>
<th>crowd</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>apr 3</td>
<td>@min</td>
<td>w 8-1</td>
<td>morris</td>
<td>williams</td>
<td>none</td>
<td>34381</td>
<td>1-0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>apr 5</td>
<td>@min</td>
<td>w 7-3</td>
<td>petry</td>
<td>viola</td>
<td>none</td>
<td>8373</td>
<td>2-0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>apr 6</td>
<td>@chw</td>
<td>w 3-2</td>
<td>wilcox</td>
<td>dotson</td>
<td>hernandez</td>
<td>42692</td>
<td>3-0</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>apr 7</td>
<td>@chw</td>
<td>w 4-0</td>
<td>morris</td>
<td>bannister</td>
<td>none</td>
<td>24616</td>
<td>4-0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>apr 8</td>
<td>@chw</td>
<td>w 7-3</td>
<td>lopez</td>
<td>seaver</td>
<td>none</td>
<td>20478</td>
<td>5-0</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>apr 10</td>
<td>tex</td>
<td>w 5-1</td>
<td>petry</td>
<td>stewart</td>
<td>none</td>
<td>51238</td>
<td>6-0</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>apr 12</td>
<td>tex</td>
<td>w 9-4</td>
<td>morris</td>
<td>tanana</td>
<td>none</td>
<td>19154</td>
<td>7-0</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>apr 13</td>
<td>@bos</td>
<td>w 13-9</td>
<td>bair</td>
<td>hurst</td>
<td>none</td>
<td>35179</td>
<td>8-0</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>apr 18</td>
<td>kcr</td>
<td>w 4-3 (10)</td>
<td>hernandez</td>
<td>beckwith</td>
<td>none</td>
<td>12310</td>
<td>9-0</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>apr 19</td>
<td>kcr</td>
<td>l 2-5</td>
<td>saberhagen</td>
<td>petry</td>
<td>quisenberry</td>
<td>12100</td>
<td>9-1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>apr 20</td>
<td>chw</td>
<td>w 3-2</td>
<td>lopez</td>
<td>reed</td>
<td>none</td>
<td>33554</td>
<td>10-1</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>apr 21</td>
<td>chw</td>
<td>w 4-1</td>
<td>rozema</td>
<td>hoyt</td>
<td>bair</td>
<td>34395</td>
<td>11-1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>apr 22</td>
<td>chw</td>
<td>w 9-1</td>
<td>berenguer</td>
<td>brennan</td>
<td>none</td>
<td>10603</td>
<td>12-1</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>apr 24</td>
<td>min</td>
<td>w 6-5</td>
<td>morris</td>
<td>davis</td>
<td>none</td>
<td>none</td>
<td>13-1</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>apr 24</td>
<td>min</td>
<td>w 4-3</td>
<td>abbott</td>
<td>viola</td>
<td>lopez</td>
<td>20315</td>
<td>14-1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>apr 25</td>
<td>@tex</td>
<td>w 9-4</td>
<td>wilcox</td>
<td>stewart</td>
<td>hernandez</td>
<td>25883</td>
<td>15-1</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>apr 26</td>
<td>@tex</td>
<td>w 7-5</td>
<td>bair</td>
<td>tanana</td>
<td>lopez</td>
<td>13559</td>
<td>16-1</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>apr 27</td>
<td>cle</td>
<td>l 4-8 (19)</td>
<td>aponte</td>
<td>abbott</td>
<td>none</td>
<td>34112</td>
<td>16-2</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>apr 28</td>
<td>cle</td>
<td>w 6-2</td>
<td>morris</td>
<td>behenna</td>
<td>none</td>
<td>28253</td>
<td>17-2</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>apr 29</td>
<td>cle</td>
<td>w 6-1</td>
<td>petry</td>
<td>spillner</td>
<td>none</td>
<td>24853</td>
<td>18-2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "score" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>6</td>
</tr>
</tbody>
</table> | select count ( score ) where # < 15 <table_name> : table | | # | date | opponent | score | win | loss | save | crowd | record |
|---:|----:|:-------|:-----------|:-----------|:-----------|:----------|:------------|:--------|:---------|
| 0 | 1 | apr 3 | @min | w 8-1 | morris | williams | none | 34381 | 1-0 |
| 1 | 2 | apr 5 | @min | w 7-3 | petry | viola | none | 8373 | 2-0 |
| 2 | 3 | apr 6 | @chw | w 3-2 | wilcox | dotson | hernandez | 42692 | 3-0 |
| 3 | 4 | apr 7 | @chw | w 4-0 | morris | bannister | none | 24616 | 4-0 |
| 4 | 5 | apr 8 | @chw | w 7-3 | lopez | seaver | none | 20478 | 5-0 |
| 5 | 6 | apr 10 | tex | w 5-1 | petry | stewart | none | 51238 | 6-0 |
| 6 | 7 | apr 12 | tex | w 9-4 | morris | tanana | none | 19154 | 7-0 |
| 7 | 8 | apr 13 | @bos | w 13-9 | bair | hurst | none | 35179 | 8-0 |
| 8 | 9 | apr 18 | kcr | w 4-3 (10) | hernandez | beckwith | none | 12310 | 9-0 |
| 9 | 10 | apr 19 | kcr | l 2-5 | saberhagen | petry | quisenberry | 12100 | 9-1 |
| 10 | 11 | apr 20 | chw | w 3-2 | lopez | reed | none | 33554 | 10-1 |
| 11 | 12 | apr 21 | chw | w 4-1 | rozema | hoyt | bair | 34395 | 11-1 |
| 12 | 13 | apr 22 | chw | w 9-1 | berenguer | brennan | none | 10603 | 12-1 |
| 13 | 14 | apr 24 | min | w 6-5 | morris | davis | none | none | 13-1 |
| 14 | 15 | apr 24 | min | w 4-3 | abbott | viola | lopez | 20315 | 14-1 |
| 15 | 16 | apr 25 | @tex | w 9-4 | wilcox | stewart | hernandez | 25883 | 15-1 |
| 16 | 17 | apr 26 | @tex | w 7-5 | bair | tanana | lopez | 13559 | 16-1 |
| 17 | 18 | apr 27 | cle | l 4-8 (19) | aponte | abbott | none | 34112 | 16-2 |
| 18 | 19 | apr 28 | cle | w 6-2 | morris | behenna | none | 28253 | 17-2 |
| 19 | 20 | apr 29 | cle | w 6-1 | petry | spillner | none | 24853 | 18-2 | | | | count ( "score" ) |
|---:|--------------------:|
| 0 | 6 | | [
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select airline where airline = 'alaska airlines' col : rank | city | passengers | ranking | airline row 1 : 1 | united states, los angeles | 14749 | none | alaska airlines row 2 : 2 | united states, houston | 5465 | none | united express row 3 : 3 | canada, calgary | 3761 | none | air transat, westjet row 4 : 4 | canada, saskatoon | 2282 | 4 | none row 5 : 5 | canada, vancouver | 2103 | none | air transat row 6 : 6 | united states, phoenix | 1829 | 1 | us airways row 7 : 7 | canada, toronto | 1202 | 1 | air transat, canjet row 8 : 8 | canada, edmonton | 110 | none | none row 9 : 9 | united states, oakland | 107 | none | none | col : airline row 1 : alaska airlines | select airline where airline = 'alaska airlines' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & city & passengers & ranking & airline \\
\midrule
0 & 1 & united states, los angeles & 14749 & none & alaska airlines \\
1 & 2 & united states, houston & 5465 & none & united express \\
2 & 3 & canada, calgary & 3761 & none & air transat, westjet \\
3 & 4 & canada, saskatoon & 2282 & 4 & none \\
4 & 5 & canada, vancouver & 2103 & none & air transat \\
5 & 6 & united states, phoenix & 1829 & 1 & us airways \\
6 & 7 & canada, toronto & 1202 & 1 & air transat, canjet \\
7 & 8 & canada, edmonton & 110 & none & none \\
8 & 9 & united states, oakland & 107 & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& airline \\
\midrule
0 & alaska airlines \\
\bottomrule
\end{tabular}
| select airline where airline = 'alaska airlines' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>city</th>
<th>passengers</th>
<th>ranking</th>
<th>airline</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>united states, los angeles</td>
<td>14749</td>
<td>none</td>
<td>alaska airlines</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>united states, houston</td>
<td>5465</td>
<td>none</td>
<td>united express</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>canada, calgary</td>
<td>3761</td>
<td>none</td>
<td>air transat, westjet</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>canada, saskatoon</td>
<td>2282</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>canada, vancouver</td>
<td>2103</td>
<td>none</td>
<td>air transat</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>united states, phoenix</td>
<td>1829</td>
<td>1</td>
<td>us airways</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>canada, toronto</td>
<td>1202</td>
<td>1</td>
<td>air transat, canjet</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>canada, edmonton</td>
<td>110</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>united states, oakland</td>
<td>107</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>airline</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>alaska airlines</td>
</tr>
</tbody>
</table> | select airline where airline = 'alaska airlines' <table_name> : table | | rank | city | passengers | ranking | airline |
|---:|-------:|:---------------------------|-------------:|:----------|:---------------------|
| 0 | 1 | united states, los angeles | 14749 | none | alaska airlines |
| 1 | 2 | united states, houston | 5465 | none | united express |
| 2 | 3 | canada, calgary | 3761 | none | air transat, westjet |
| 3 | 4 | canada, saskatoon | 2282 | 4 | none |
| 4 | 5 | canada, vancouver | 2103 | none | air transat |
| 5 | 6 | united states, phoenix | 1829 | 1 | us airways |
| 6 | 7 | canada, toronto | 1202 | 1 | air transat, canjet |
| 7 | 8 | canada, edmonton | 110 | none | none |
| 8 | 9 | united states, oakland | 107 | none | none | | | | airline |
|---:|:----------------|
| 0 | alaska airlines | | [
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select nation where gold = 16 col : rank | nation | gold | silver | bronze | total row 1 : 1 | france | 28 | 28 | 24 | 80 row 2 : 2 | romania | 16 | 3 | 5 | 24 row 3 : 3 | canada | 14 | 10 | 15 | 39 row 4 : 4 | quebec | 8 | 4 | 16 | 28 row 5 : 5 | morocco | 6 | 11 | 7 | 24 row 6 : 6 | tunisia | 4 | 7 | 1 | 12 row 7 : 7 | egypt | 2 | 5 | 4 | 11 row 8 : 8 | switzerland | 2 | 1 | 5 | 8 row 9 : 9 | senegal | 2 | 1 | 3 | 6 row 10 : 10 | french community of belgium | 1 | 3 | 6 | 10 row 11 : 11 | madagascar | 1 | 2 | 3 | 6 row 12 : 12 | burkina faso | 1 | none | 2 | 3 row 13 : 13 | togo | 1 | none | 1 | 2 row 14 : 14 | guinea | 1 | none | none | 1 row 15 : 15 | lebanon | 1 | none | none | 1 row 16 : 16 | ivory coast | none | 3 | 3 | 6 row 17 : 17 | republic of the congo | none | 3 | 2 | 5 row 18 : 18 | new brunswick | none | 1 | 2 | 3 row 19 : 19 | central african republic | none | 1 | none | 1 row 20 : 20 | dominica | none | 1 | none | 1 row 21 : 21 | gabon | none | 1 | none | 1 row 22 : 22 | mali | none | 1 | none | 1 row 23 : 23 | cambodia | none | none | 2 | 2 row 24 : 24 | luxembourg | none | none | 2 | 2 row 25 : 25 | mauritius | none | none | 2 | 2 row 26 : 26 | burundi | none | none | 1 | 1 row 27 : 27 | djibouti | none | none | 1 | 1 row 28 : 28 | vietnam | none | none | 1 | 1 | col : nation row 1 : romania | select nation where gold = 16 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & france & 28 & 28 & 24 & 80 \\
1 & 2 & romania & 16 & 3 & 5 & 24 \\
2 & 3 & canada & 14 & 10 & 15 & 39 \\
3 & 4 & quebec & 8 & 4 & 16 & 28 \\
4 & 5 & morocco & 6 & 11 & 7 & 24 \\
5 & 6 & tunisia & 4 & 7 & 1 & 12 \\
6 & 7 & egypt & 2 & 5 & 4 & 11 \\
7 & 8 & switzerland & 2 & 1 & 5 & 8 \\
8 & 9 & senegal & 2 & 1 & 3 & 6 \\
9 & 10 & french community of belgium & 1 & 3 & 6 & 10 \\
10 & 11 & madagascar & 1 & 2 & 3 & 6 \\
11 & 12 & burkina faso & 1 & none & 2 & 3 \\
12 & 13 & togo & 1 & none & 1 & 2 \\
13 & 14 & guinea & 1 & none & none & 1 \\
14 & 15 & lebanon & 1 & none & none & 1 \\
15 & 16 & ivory coast & none & 3 & 3 & 6 \\
16 & 17 & republic of the congo & none & 3 & 2 & 5 \\
17 & 18 & new brunswick & none & 1 & 2 & 3 \\
18 & 19 & central african republic & none & 1 & none & 1 \\
19 & 20 & dominica & none & 1 & none & 1 \\
20 & 21 & gabon & none & 1 & none & 1 \\
21 & 22 & mali & none & 1 & none & 1 \\
22 & 23 & cambodia & none & none & 2 & 2 \\
23 & 24 & luxembourg & none & none & 2 & 2 \\
24 & 25 & mauritius & none & none & 2 & 2 \\
25 & 26 & burundi & none & none & 1 & 1 \\
26 & 27 & djibouti & none & none & 1 & 1 \\
27 & 28 & vietnam & none & none & 1 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & romania \\
\bottomrule
\end{tabular}
| select nation where gold = 16 <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>france</td>
<td>28</td>
<td>28</td>
<td>24</td>
<td>80</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>romania</td>
<td>16</td>
<td>3</td>
<td>5</td>
<td>24</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>canada</td>
<td>14</td>
<td>10</td>
<td>15</td>
<td>39</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>quebec</td>
<td>8</td>
<td>4</td>
<td>16</td>
<td>28</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>morocco</td>
<td>6</td>
<td>11</td>
<td>7</td>
<td>24</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>tunisia</td>
<td>4</td>
<td>7</td>
<td>1</td>
<td>12</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>egypt</td>
<td>2</td>
<td>5</td>
<td>4</td>
<td>11</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>switzerland</td>
<td>2</td>
<td>1</td>
<td>5</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>senegal</td>
<td>2</td>
<td>1</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>french community of belgium</td>
<td>1</td>
<td>3</td>
<td>6</td>
<td>10</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>madagascar</td>
<td>1</td>
<td>2</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>burkina faso</td>
<td>1</td>
<td>none</td>
<td>2</td>
<td>3</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>togo</td>
<td>1</td>
<td>none</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>guinea</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>lebanon</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>ivory coast</td>
<td>none</td>
<td>3</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>republic of the congo</td>
<td>none</td>
<td>3</td>
<td>2</td>
<td>5</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>new brunswick</td>
<td>none</td>
<td>1</td>
<td>2</td>
<td>3</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>central african republic</td>
<td>none</td>
<td>1</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>dominica</td>
<td>none</td>
<td>1</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>gabon</td>
<td>none</td>
<td>1</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>mali</td>
<td>none</td>
<td>1</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>cambodia</td>
<td>none</td>
<td>none</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>luxembourg</td>
<td>none</td>
<td>none</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>mauritius</td>
<td>none</td>
<td>none</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>burundi</td>
<td>none</td>
<td>none</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>djibouti</td>
<td>none</td>
<td>none</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>27</th>
<td>28</td>
<td>vietnam</td>
<td>none</td>
<td>none</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>romania</td>
</tr>
</tbody>
</table> | select nation where gold = 16 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|-------:|:----------------------------|:-------|:---------|:---------|--------:|
| 0 | 1 | france | 28 | 28 | 24 | 80 |
| 1 | 2 | romania | 16 | 3 | 5 | 24 |
| 2 | 3 | canada | 14 | 10 | 15 | 39 |
| 3 | 4 | quebec | 8 | 4 | 16 | 28 |
| 4 | 5 | morocco | 6 | 11 | 7 | 24 |
| 5 | 6 | tunisia | 4 | 7 | 1 | 12 |
| 6 | 7 | egypt | 2 | 5 | 4 | 11 |
| 7 | 8 | switzerland | 2 | 1 | 5 | 8 |
| 8 | 9 | senegal | 2 | 1 | 3 | 6 |
| 9 | 10 | french community of belgium | 1 | 3 | 6 | 10 |
| 10 | 11 | madagascar | 1 | 2 | 3 | 6 |
| 11 | 12 | burkina faso | 1 | none | 2 | 3 |
| 12 | 13 | togo | 1 | none | 1 | 2 |
| 13 | 14 | guinea | 1 | none | none | 1 |
| 14 | 15 | lebanon | 1 | none | none | 1 |
| 15 | 16 | ivory coast | none | 3 | 3 | 6 |
| 16 | 17 | republic of the congo | none | 3 | 2 | 5 |
| 17 | 18 | new brunswick | none | 1 | 2 | 3 |
| 18 | 19 | central african republic | none | 1 | none | 1 |
| 19 | 20 | dominica | none | 1 | none | 1 |
| 20 | 21 | gabon | none | 1 | none | 1 |
| 21 | 22 | mali | none | 1 | none | 1 |
| 22 | 23 | cambodia | none | none | 2 | 2 |
| 23 | 24 | luxembourg | none | none | 2 | 2 |
| 24 | 25 | mauritius | none | none | 2 | 2 |
| 25 | 26 | burundi | none | none | 1 | 1 |
| 26 | 27 | djibouti | none | none | 1 | 1 |
| 27 | 28 | vietnam | none | none | 1 | 1 | | | | nation |
|---:|:---------|
| 0 | romania | | [
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select overall record where win = 'white (13-3)' 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 : overall record row 1 : 44-30 | select overall record where win = 'white (13-3)' <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
& overall record \\
\midrule
0 & 44-30 \\
\bottomrule
\end{tabular}
| select overall record where win = 'white (13-3)' <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>overall record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>44-30</td>
</tr>
</tbody>
</table> | select overall record where win = 'white (13-3)' <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 | | | | overall record |
|---:|:-----------------|
| 0 | 44-30 | | [
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select count ( event ) where venue = 'athens, greece' col : year | competition | venue | position | event | notes row 1 : 2001 | beijing marathon | beijing, pr china | 7th | marathon | 2:10:46 row 2 : 2002 | beijing marathon | beijing, pr china | 1st | marathon | 2:13:09 row 3 : 2004 | olympic games | athens, greece | 31st | marathon | 2:19:26 row 4 : 2007 | xiamen international marathon | xiamen, pr china | 1st | marathon | 2:13:17 row 5 : 2007 | world championships | osaka, japan | 43rd | marathon | 2:32:44 row 6 : 2008 | olympic games | beijing, pr china | 51st | marathon | 2:24:08 | col : count ( "event" ) row 1 : 1 | select count ( event ) where venue = 'athens, greece' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & competition & venue & position & event & notes \\
\midrule
0 & 2001 & beijing marathon & beijing, pr china & 7th & marathon & 2:10:46 \\
1 & 2002 & beijing marathon & beijing, pr china & 1st & marathon & 2:13:09 \\
2 & 2004 & olympic games & athens, greece & 31st & marathon & 2:19:26 \\
3 & 2007 & xiamen international marathon & xiamen, pr china & 1st & marathon & 2:13:17 \\
4 & 2007 & world championships & osaka, japan & 43rd & marathon & 2:32:44 \\
5 & 2008 & olympic games & beijing, pr china & 51st & marathon & 2:24:08 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "event" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( event ) where venue = 'athens, greece' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>competition</th>
<th>venue</th>
<th>position</th>
<th>event</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2001</td>
<td>beijing marathon</td>
<td>beijing, pr china</td>
<td>7th</td>
<td>marathon</td>
<td>2:10:46</td>
</tr>
<tr>
<th>1</th>
<td>2002</td>
<td>beijing marathon</td>
<td>beijing, pr china</td>
<td>1st</td>
<td>marathon</td>
<td>2:13:09</td>
</tr>
<tr>
<th>2</th>
<td>2004</td>
<td>olympic games</td>
<td>athens, greece</td>
<td>31st</td>
<td>marathon</td>
<td>2:19:26</td>
</tr>
<tr>
<th>3</th>
<td>2007</td>
<td>xiamen international marathon</td>
<td>xiamen, pr china</td>
<td>1st</td>
<td>marathon</td>
<td>2:13:17</td>
</tr>
<tr>
<th>4</th>
<td>2007</td>
<td>world championships</td>
<td>osaka, japan</td>
<td>43rd</td>
<td>marathon</td>
<td>2:32:44</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>olympic games</td>
<td>beijing, pr china</td>
<td>51st</td>
<td>marathon</td>
<td>2:24:08</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "event" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( event ) where venue = 'athens, greece' <table_name> : table | | year | competition | venue | position | event | notes |
|---:|-------:|:------------------------------|:------------------|:-----------|:---------|:--------|
| 0 | 2001 | beijing marathon | beijing, pr china | 7th | marathon | 2:10:46 |
| 1 | 2002 | beijing marathon | beijing, pr china | 1st | marathon | 2:13:09 |
| 2 | 2004 | olympic games | athens, greece | 31st | marathon | 2:19:26 |
| 3 | 2007 | xiamen international marathon | xiamen, pr china | 1st | marathon | 2:13:17 |
| 4 | 2007 | world championships | osaka, japan | 43rd | marathon | 2:32:44 |
| 5 | 2008 | olympic games | beijing, pr china | 51st | marathon | 2:24:08 | | | | count ( "event" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select # where artist = 'mary mcgregor' col : # | title | artist | highest pos. reached | weeks at no. 1 row 1 : 1 | "don't cry for me argentina" | julie covington | 1 | 7 row 2 : 2 | "the way you that you do it" | pussyfoot | 1 | 7 row 3 : 3 | "i just want to be your everything" | andy gibb | 1 | 7 row 4 : 4 | "that's rock and roll" | shaun cassidy | 2 | none row 5 : 5 | "living next door to alice" | smokie | 2 | none row 6 : 6 | "i go to rio" | peter allen | 1 | 5 row 7 : 7 | "torn between two lovers" | mary mcgregor | 1 | 4 row 8 : 8 | "walk right in" | dr hook | 1 | 5 row 9 : 9 | "you're moving out today" | carole bayer sager | 1 | 4 row 10 : 10 | "if you leave me now" | chicago | 1 | 5 (pkd #1 in 76 & 77) row 11 : 11 | "don't give up on us" | david soul | 1 | 3 row 12 : 12 | "lido shuffle" / "what can i say" | boz scaggs | 2 | none row 13 : 13 | "you and me" | alice cooper | 2 | none row 14 : 14 | "dance little lady dance" | tina charles | 4 | none row 15 : 15 | "when i need you" | leo sayer | 8 | none row 16 : 16 | "don't fall in love" | ferrets | 2 | none row 17 : 17 | "i feel love" | donna summer | 1 | 1 row 18 : 18 | "help is on its way" | little river band | 1 | 1 row 19 : 19 | "you gotta get up and dance" | supercharge | 3 | none row 20 : 20 | "mull of kintyre" | wings | 1 | 11 (pkd #1 in 77 & 78) row 21 : 21 | "don't leave me this way" | thelma houston | 6 | none row 22 : 22 | "ain't gonna bump no more with no big fat woman" | joe tex | 2 | none row 23 : 23 | "you're in my heart" | rod stewart | 1 | 1 row 24 : 24 | "ma baker" | boney m | 5 | none row 25 : 25 | "lucille" | kenny rogers | 7 | none | col : # row 1 : 7 | select # where artist = 'mary mcgregor' <table_name> : table \begin{tabular}{llllll}
\toprule
& # & title & artist & highest pos. reached & weeks at no. 1 \\
\midrule
0 & 1 & "don't cry for me argentina" & julie covington & 1 & 7 \\
1 & 2 & "the way you that you do it" & pussyfoot & 1 & 7 \\
2 & 3 & "i just want to be your everything" & andy gibb & 1 & 7 \\
3 & 4 & "that's rock and roll" & shaun cassidy & 2 & none \\
4 & 5 & "living next door to alice" & smokie & 2 & none \\
5 & 6 & "i go to rio" & peter allen & 1 & 5 \\
6 & 7 & "torn between two lovers" & mary mcgregor & 1 & 4 \\
7 & 8 & "walk right in" & dr hook & 1 & 5 \\
8 & 9 & "you're moving out today" & carole bayer sager & 1 & 4 \\
9 & 10 & "if you leave me now" & chicago & 1 & 5 (pkd #1 in 76 & 77) \\
10 & 11 & "don't give up on us" & david soul & 1 & 3 \\
11 & 12 & "lido shuffle" / "what can i say" & boz scaggs & 2 & none \\
12 & 13 & "you and me" & alice cooper & 2 & none \\
13 & 14 & "dance little lady dance" & tina charles & 4 & none \\
14 & 15 & "when i need you" & leo sayer & 8 & none \\
15 & 16 & "don't fall in love" & ferrets & 2 & none \\
16 & 17 & "i feel love" & donna summer & 1 & 1 \\
17 & 18 & "help is on its way" & little river band & 1 & 1 \\
18 & 19 & "you gotta get up and dance" & supercharge & 3 & none \\
19 & 20 & "mull of kintyre" & wings & 1 & 11 (pkd #1 in 77 & 78) \\
20 & 21 & "don't leave me this way" & thelma houston & 6 & none \\
21 & 22 & "ain't gonna bump no more with no big fat woman" & joe tex & 2 & none \\
22 & 23 & "you're in my heart" & rod stewart & 1 & 1 \\
23 & 24 & "ma baker" & boney m & 5 & none \\
24 & 25 & "lucille" & kenny rogers & 7 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& # \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select # where artist = 'mary mcgregor' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>title</th>
<th>artist</th>
<th>highest pos. reached</th>
<th>weeks at no. 1</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>"don't cry for me argentina"</td>
<td>julie covington</td>
<td>1</td>
<td>7</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>"the way you that you do it"</td>
<td>pussyfoot</td>
<td>1</td>
<td>7</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>"i just want to be your everything"</td>
<td>andy gibb</td>
<td>1</td>
<td>7</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>"that's rock and roll"</td>
<td>shaun cassidy</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>"living next door to alice"</td>
<td>smokie</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>"i go to rio"</td>
<td>peter allen</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>"torn between two lovers"</td>
<td>mary mcgregor</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>"walk right in"</td>
<td>dr hook</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>"you're moving out today"</td>
<td>carole bayer sager</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>"if you leave me now"</td>
<td>chicago</td>
<td>1</td>
<td>5 (pkd #1 in 76 & 77)</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>"don't give up on us"</td>
<td>david soul</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>"lido shuffle" / "what can i say"</td>
<td>boz scaggs</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>"you and me"</td>
<td>alice cooper</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>"dance little lady dance"</td>
<td>tina charles</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>"when i need you"</td>
<td>leo sayer</td>
<td>8</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>"don't fall in love"</td>
<td>ferrets</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>"i feel love"</td>
<td>donna summer</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>"help is on its way"</td>
<td>little river band</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>"you gotta get up and dance"</td>
<td>supercharge</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>"mull of kintyre"</td>
<td>wings</td>
<td>1</td>
<td>11 (pkd #1 in 77 & 78)</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>"don't leave me this way"</td>
<td>thelma houston</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>"ain't gonna bump no more with no big fat woman"</td>
<td>joe tex</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>"you're in my heart"</td>
<td>rod stewart</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>"ma baker"</td>
<td>boney m</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>"lucille"</td>
<td>kenny rogers</td>
<td>7</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select # where artist = 'mary mcgregor' <table_name> : table | | # | title | artist | highest pos. reached | weeks at no. 1 |
|---:|----:|:-------------------------------------------------|:-------------------|-----------------------:|:-----------------------|
| 0 | 1 | "don't cry for me argentina" | julie covington | 1 | 7 |
| 1 | 2 | "the way you that you do it" | pussyfoot | 1 | 7 |
| 2 | 3 | "i just want to be your everything" | andy gibb | 1 | 7 |
| 3 | 4 | "that's rock and roll" | shaun cassidy | 2 | none |
| 4 | 5 | "living next door to alice" | smokie | 2 | none |
| 5 | 6 | "i go to rio" | peter allen | 1 | 5 |
| 6 | 7 | "torn between two lovers" | mary mcgregor | 1 | 4 |
| 7 | 8 | "walk right in" | dr hook | 1 | 5 |
| 8 | 9 | "you're moving out today" | carole bayer sager | 1 | 4 |
| 9 | 10 | "if you leave me now" | chicago | 1 | 5 (pkd #1 in 76 & 77) |
| 10 | 11 | "don't give up on us" | david soul | 1 | 3 |
| 11 | 12 | "lido shuffle" / "what can i say" | boz scaggs | 2 | none |
| 12 | 13 | "you and me" | alice cooper | 2 | none |
| 13 | 14 | "dance little lady dance" | tina charles | 4 | none |
| 14 | 15 | "when i need you" | leo sayer | 8 | none |
| 15 | 16 | "don't fall in love" | ferrets | 2 | none |
| 16 | 17 | "i feel love" | donna summer | 1 | 1 |
| 17 | 18 | "help is on its way" | little river band | 1 | 1 |
| 18 | 19 | "you gotta get up and dance" | supercharge | 3 | none |
| 19 | 20 | "mull of kintyre" | wings | 1 | 11 (pkd #1 in 77 & 78) |
| 20 | 21 | "don't leave me this way" | thelma houston | 6 | none |
| 21 | 22 | "ain't gonna bump no more with no big fat woman" | joe tex | 2 | none |
| 22 | 23 | "you're in my heart" | rod stewart | 1 | 1 |
| 23 | 24 | "ma baker" | boney m | 5 | none |
| 24 | 25 | "lucille" | kenny rogers | 7 | none | | | | # |
|---:|----:|
| 0 | 7 | | [
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] |
select constructor where driver = 'erik comas' 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 : constructor row 1 : ligier-renault | select constructor where driver = 'erik comas' <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
& constructor \\
\midrule
0 & ligier-renault \\
\bottomrule
\end{tabular}
| select constructor where driver = 'erik comas' <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>constructor</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>ligier-renault</td>
</tr>
</tbody>
</table> | select constructor where driver = 'erik comas' <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 | | | | constructor |
|---:|:---------------|
| 0 | ligier-renault | | [
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select max ( title ) where composer = 'jacques brel' col : track | title | translation | composer | recorded row 1 : 1 | "demain l'on se marie (la chanson des fiances)" | tomor | | row 2 : we'll marry (the song of the fiances) | jacques brel | 1958-03-14 | | row 3 : 2 | "au printemps" | in the spring | jacques brel | 1958-04-01 row 4 : 3 | "je ne sais pas" | i don't know | jacques brel | 1958-04-01 row 5 : 4 | "le colonel" | the colonel | jacques brel, gaby wagenheim | 1958-04-01 row 6 : 5 | "dors ma mie, bonsoir" | sleep my love, good night | jacques brel, francois rauber | 1958-03-12 row 7 : 6 | "la lumiere jaillira" | the light will shine | jacques brel, francois rauber | 1958-04-01 row 8 : 7 | "dites, si c'etait vrai" (poeme) | say, if it were true (poem) | jacques brel | 1958-04-01 row 9 : 8 | "l'homme dans la cite" | the man in the city | jacques brel, francois rauber | 1958-04-01 row 10 : 9 | "litanies pour un retour" | litanies for a return | jacques brel, francois rauber | 1958-04-01 row 11 : 10 | "voici" | here | jacques brel, francois rauber | 1958-04-01 row 12 : 11 | "voir" | see | jacques brel | 1958-10-07 row 13 : 12 | "l'aventure" | the adventure | jacques brel | 1958-10-21 row 14 : 13 | "dites, si c'etait vrai" (poeme) | say, if it were true (poem) | jacques brel | 1956-09-19 | col : max ( "title" ) row 1 : "voir" | select max ( title ) where composer = 'jacques brel' <table_name> : table \begin{tabular}{llllll}
\toprule
& track & title & translation & composer & recorded \\
\midrule
0 & 1 & "demain l'on se marie (la chanson des fiances)" & tomor & & \\
1 & we'll marry (the song of the fiances) & jacques brel & 1958-03-14 & & \\
2 & 2 & "au printemps" & in the spring & jacques brel & 1958-04-01 \\
3 & 3 & "je ne sais pas" & i don't know & jacques brel & 1958-04-01 \\
4 & 4 & "le colonel" & the colonel & jacques brel, gaby wagenheim & 1958-04-01 \\
5 & 5 & "dors ma mie, bonsoir" & sleep my love, good night & jacques brel, francois rauber & 1958-03-12 \\
6 & 6 & "la lumiere jaillira" & the light will shine & jacques brel, francois rauber & 1958-04-01 \\
7 & 7 & "dites, si c'etait vrai" (poeme) & say, if it were true (poem) & jacques brel & 1958-04-01 \\
8 & 8 & "l'homme dans la cite" & the man in the city & jacques brel, francois rauber & 1958-04-01 \\
9 & 9 & "litanies pour un retour" & litanies for a return & jacques brel, francois rauber & 1958-04-01 \\
10 & 10 & "voici" & here & jacques brel, francois rauber & 1958-04-01 \\
11 & 11 & "voir" & see & jacques brel & 1958-10-07 \\
12 & 12 & "l'aventure" & the adventure & jacques brel & 1958-10-21 \\
13 & 13 & "dites, si c'etait vrai" (poeme) & say, if it were true (poem) & jacques brel & 1956-09-19 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& max ( "title" ) \\
\midrule
0 & "voir" \\
\bottomrule
\end{tabular}
| select max ( title ) where composer = 'jacques brel' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>track</th>
<th>title</th>
<th>translation</th>
<th>composer</th>
<th>recorded</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>"demain l'on se marie (la chanson des fiances)"</td>
<td>tomor</td>
<td></td>
<td></td>
</tr>
<tr>
<th>1</th>
<td>we'll marry (the song of the fiances)</td>
<td>jacques brel</td>
<td>1958-03-14</td>
<td></td>
<td></td>
</tr>
<tr>
<th>2</th>
<td>2</td>
<td>"au printemps"</td>
<td>in the spring</td>
<td>jacques brel</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>"je ne sais pas"</td>
<td>i don't know</td>
<td>jacques brel</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>"le colonel"</td>
<td>the colonel</td>
<td>jacques brel, gaby wagenheim</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>"dors ma mie, bonsoir"</td>
<td>sleep my love, good night</td>
<td>jacques brel, francois rauber</td>
<td>1958-03-12</td>
</tr>
<tr>
<th>6</th>
<td>6</td>
<td>"la lumiere jaillira"</td>
<td>the light will shine</td>
<td>jacques brel, francois rauber</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>"dites, si c'etait vrai" (poeme)</td>
<td>say, if it were true (poem)</td>
<td>jacques brel</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>"l'homme dans la cite"</td>
<td>the man in the city</td>
<td>jacques brel, francois rauber</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>"litanies pour un retour"</td>
<td>litanies for a return</td>
<td>jacques brel, francois rauber</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>"voici"</td>
<td>here</td>
<td>jacques brel, francois rauber</td>
<td>1958-04-01</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>"voir"</td>
<td>see</td>
<td>jacques brel</td>
<td>1958-10-07</td>
</tr>
<tr>
<th>12</th>
<td>12</td>
<td>"l'aventure"</td>
<td>the adventure</td>
<td>jacques brel</td>
<td>1958-10-21</td>
</tr>
<tr>
<th>13</th>
<td>13</td>
<td>"dites, si c'etait vrai" (poeme)</td>
<td>say, if it were true (poem)</td>
<td>jacques brel</td>
<td>1956-09-19</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>max ( "title" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>"voir"</td>
</tr>
</tbody>
</table> | select max ( title ) where composer = 'jacques brel' <table_name> : table | | track | title | translation | composer | recorded |
|---:|:--------------------------------------|:------------------------------------------------|:----------------------------|:------------------------------|:-----------|
| 0 | 1 | "demain l'on se marie (la chanson des fiances)" | tomor | | |
| 1 | we'll marry (the song of the fiances) | jacques brel | 1958-03-14 | | |
| 2 | 2 | "au printemps" | in the spring | jacques brel | 1958-04-01 |
| 3 | 3 | "je ne sais pas" | i don't know | jacques brel | 1958-04-01 |
| 4 | 4 | "le colonel" | the colonel | jacques brel, gaby wagenheim | 1958-04-01 |
| 5 | 5 | "dors ma mie, bonsoir" | sleep my love, good night | jacques brel, francois rauber | 1958-03-12 |
| 6 | 6 | "la lumiere jaillira" | the light will shine | jacques brel, francois rauber | 1958-04-01 |
| 7 | 7 | "dites, si c'etait vrai" (poeme) | say, if it were true (poem) | jacques brel | 1958-04-01 |
| 8 | 8 | "l'homme dans la cite" | the man in the city | jacques brel, francois rauber | 1958-04-01 |
| 9 | 9 | "litanies pour un retour" | litanies for a return | jacques brel, francois rauber | 1958-04-01 |
| 10 | 10 | "voici" | here | jacques brel, francois rauber | 1958-04-01 |
| 11 | 11 | "voir" | see | jacques brel | 1958-10-07 |
| 12 | 12 | "l'aventure" | the adventure | jacques brel | 1958-10-21 |
| 13 | 13 | "dites, si c'etait vrai" (poeme) | say, if it were true (poem) | jacques brel | 1956-09-19 | | | | max ( "title" ) |
|---:|:------------------|
| 0 | "voir" | | [
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select no where constructor = 'arrows' col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 3 | michael schumacher | ferrari | 71 | 1:34:45.026 | 2 | 10 row 2 : 2 | 4 | eddie irvine | ferrari | 71 | 19.575 | 4 | 6 row 3 : 3 | 8 | mika hakkinen | mclaren-mercedes | 71 | 19.747 | 1 | 4 row 4 : 4 | 1 | jacques villeneuve | williams-mecachrome | 71 | +1:06.965 | 5 | 3 row 5 : 5 | 6 | alexander wurz | benetton-playlife | 70 | +1 lap | 10 | 2 row 6 : 6 | 7 | david coulthard | mclaren-mercedes | 70 | +1 lap | 3 | 1 row 7 : 7 | 14 | jean alesi | sauber-petronas | 70 | +1 lap | 11 | none row 8 : 8 | 15 | johnny herbert | sauber-petronas | 70 | +1 lap | 13 | none row 9 : 9 | 5 | giancarlo fisichella | benetton-playlife | 70 | +1 lap | 9 | none row 10 : 10 | 18 | rubens barrichello | stewart-ford | 69 | +2 laps | 14 | none row 11 : 11 | 11 | olivier panis | prost-peugeot | 69 | +2 laps | 16 | none row 12 : 12 | 19 | jos verstappen | stewart-ford | 69 | +2 laps | 15 | none row 13 : 13 | 17 | mika salo | arrows | 69 | +2 laps | 19 | none row 14 : 14 | 16 | pedro diniz | arrows | 69 | +2 laps | 17 | none row 15 : 15 | 2 | heinz-harald frentzen | williams-mecachrome | 68 | suspension | 8 | none row 16 : 16 | 10 | ralf schumacher | jordan-mugen-honda | 68 | +3 laps | 6 | none row 17 : 17 | 22 | shinji nakano | minardi-ford | 65 | engine | 21 | none row 18 : ret | 21 | toranosuke takagi | tyrrell-ford | 60 | engine | 20 | none row 19 : ret | 12 | jarno trulli | prost-peugeot | 55 | spun off | 12 | none row 20 : ret | 23 | esteban tuero | minardi-ford | 41 | gearbox | 22 | none row 21 : ret | 9 | damon hill | jordan-mugen-honda | 19 | hydraulics | 7 | none row 22 : ret | 20 | ricardo rosset | tyrrell-ford | 16 | hydraulics | 18 | none | col : no row 1 : 17 row 2 : 16 | select no where constructor = 'arrows' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 3 & michael schumacher & ferrari & 71 & 1:34:45.026 & 2 & 10 \\
1 & 2 & 4 & eddie irvine & ferrari & 71 & 19.575 & 4 & 6 \\
2 & 3 & 8 & mika hakkinen & mclaren-mercedes & 71 & 19.747 & 1 & 4 \\
3 & 4 & 1 & jacques villeneuve & williams-mecachrome & 71 & +1:06.965 & 5 & 3 \\
4 & 5 & 6 & alexander wurz & benetton-playlife & 70 & +1 lap & 10 & 2 \\
5 & 6 & 7 & david coulthard & mclaren-mercedes & 70 & +1 lap & 3 & 1 \\
6 & 7 & 14 & jean alesi & sauber-petronas & 70 & +1 lap & 11 & none \\
7 & 8 & 15 & johnny herbert & sauber-petronas & 70 & +1 lap & 13 & none \\
8 & 9 & 5 & giancarlo fisichella & benetton-playlife & 70 & +1 lap & 9 & none \\
9 & 10 & 18 & rubens barrichello & stewart-ford & 69 & +2 laps & 14 & none \\
10 & 11 & 11 & olivier panis & prost-peugeot & 69 & +2 laps & 16 & none \\
11 & 12 & 19 & jos verstappen & stewart-ford & 69 & +2 laps & 15 & none \\
12 & 13 & 17 & mika salo & arrows & 69 & +2 laps & 19 & none \\
13 & 14 & 16 & pedro diniz & arrows & 69 & +2 laps & 17 & none \\
14 & 15 & 2 & heinz-harald frentzen & williams-mecachrome & 68 & suspension & 8 & none \\
15 & 16 & 10 & ralf schumacher & jordan-mugen-honda & 68 & +3 laps & 6 & none \\
16 & 17 & 22 & shinji nakano & minardi-ford & 65 & engine & 21 & none \\
17 & ret & 21 & toranosuke takagi & tyrrell-ford & 60 & engine & 20 & none \\
18 & ret & 12 & jarno trulli & prost-peugeot & 55 & spun off & 12 & none \\
19 & ret & 23 & esteban tuero & minardi-ford & 41 & gearbox & 22 & none \\
20 & ret & 9 & damon hill & jordan-mugen-honda & 19 & hydraulics & 7 & none \\
21 & ret & 20 & ricardo rosset & tyrrell-ford & 16 & hydraulics & 18 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& no \\
\midrule
0 & 17 \\
1 & 16 \\
\bottomrule
\end{tabular}
| select no where constructor = 'arrows' <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>3</td>
<td>michael schumacher</td>
<td>ferrari</td>
<td>71</td>
<td>1:34:45.026</td>
<td>2</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>4</td>
<td>eddie irvine</td>
<td>ferrari</td>
<td>71</td>
<td>19.575</td>
<td>4</td>
<td>6</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>8</td>
<td>mika hakkinen</td>
<td>mclaren-mercedes</td>
<td>71</td>
<td>19.747</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1</td>
<td>jacques villeneuve</td>
<td>williams-mecachrome</td>
<td>71</td>
<td>+1:06.965</td>
<td>5</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>6</td>
<td>alexander wurz</td>
<td>benetton-playlife</td>
<td>70</td>
<td>+1 lap</td>
<td>10</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>7</td>
<td>david coulthard</td>
<td>mclaren-mercedes</td>
<td>70</td>
<td>+1 lap</td>
<td>3</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>14</td>
<td>jean alesi</td>
<td>sauber-petronas</td>
<td>70</td>
<td>+1 lap</td>
<td>11</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>15</td>
<td>johnny herbert</td>
<td>sauber-petronas</td>
<td>70</td>
<td>+1 lap</td>
<td>13</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>5</td>
<td>giancarlo fisichella</td>
<td>benetton-playlife</td>
<td>70</td>
<td>+1 lap</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>18</td>
<td>rubens barrichello</td>
<td>stewart-ford</td>
<td>69</td>
<td>+2 laps</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>11</td>
<td>olivier panis</td>
<td>prost-peugeot</td>
<td>69</td>
<td>+2 laps</td>
<td>16</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>19</td>
<td>jos verstappen</td>
<td>stewart-ford</td>
<td>69</td>
<td>+2 laps</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>17</td>
<td>mika salo</td>
<td>arrows</td>
<td>69</td>
<td>+2 laps</td>
<td>19</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>16</td>
<td>pedro diniz</td>
<td>arrows</td>
<td>69</td>
<td>+2 laps</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>2</td>
<td>heinz-harald frentzen</td>
<td>williams-mecachrome</td>
<td>68</td>
<td>suspension</td>
<td>8</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>10</td>
<td>ralf schumacher</td>
<td>jordan-mugen-honda</td>
<td>68</td>
<td>+3 laps</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>22</td>
<td>shinji nakano</td>
<td>minardi-ford</td>
<td>65</td>
<td>engine</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>21</td>
<td>toranosuke takagi</td>
<td>tyrrell-ford</td>
<td>60</td>
<td>engine</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>12</td>
<td>jarno trulli</td>
<td>prost-peugeot</td>
<td>55</td>
<td>spun off</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>23</td>
<td>esteban tuero</td>
<td>minardi-ford</td>
<td>41</td>
<td>gearbox</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>9</td>
<td>damon hill</td>
<td>jordan-mugen-honda</td>
<td>19</td>
<td>hydraulics</td>
<td>7</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>ret</td>
<td>20</td>
<td>ricardo rosset</td>
<td>tyrrell-ford</td>
<td>16</td>
<td>hydraulics</td>
<td>18</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>17</td>
</tr>
<tr>
<th>1</th>
<td>16</td>
</tr>
</tbody>
</table> | select no where constructor = 'arrows' <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:----------------------|:--------------------|-------:|:---------------|-------:|:---------|
| 0 | 1 | 3 | michael schumacher | ferrari | 71 | 1:34:45.026 | 2 | 10 |
| 1 | 2 | 4 | eddie irvine | ferrari | 71 | 19.575 | 4 | 6 |
| 2 | 3 | 8 | mika hakkinen | mclaren-mercedes | 71 | 19.747 | 1 | 4 |
| 3 | 4 | 1 | jacques villeneuve | williams-mecachrome | 71 | +1:06.965 | 5 | 3 |
| 4 | 5 | 6 | alexander wurz | benetton-playlife | 70 | +1 lap | 10 | 2 |
| 5 | 6 | 7 | david coulthard | mclaren-mercedes | 70 | +1 lap | 3 | 1 |
| 6 | 7 | 14 | jean alesi | sauber-petronas | 70 | +1 lap | 11 | none |
| 7 | 8 | 15 | johnny herbert | sauber-petronas | 70 | +1 lap | 13 | none |
| 8 | 9 | 5 | giancarlo fisichella | benetton-playlife | 70 | +1 lap | 9 | none |
| 9 | 10 | 18 | rubens barrichello | stewart-ford | 69 | +2 laps | 14 | none |
| 10 | 11 | 11 | olivier panis | prost-peugeot | 69 | +2 laps | 16 | none |
| 11 | 12 | 19 | jos verstappen | stewart-ford | 69 | +2 laps | 15 | none |
| 12 | 13 | 17 | mika salo | arrows | 69 | +2 laps | 19 | none |
| 13 | 14 | 16 | pedro diniz | arrows | 69 | +2 laps | 17 | none |
| 14 | 15 | 2 | heinz-harald frentzen | williams-mecachrome | 68 | suspension | 8 | none |
| 15 | 16 | 10 | ralf schumacher | jordan-mugen-honda | 68 | +3 laps | 6 | none |
| 16 | 17 | 22 | shinji nakano | minardi-ford | 65 | engine | 21 | none |
| 17 | ret | 21 | toranosuke takagi | tyrrell-ford | 60 | engine | 20 | none |
| 18 | ret | 12 | jarno trulli | prost-peugeot | 55 | spun off | 12 | none |
| 19 | ret | 23 | esteban tuero | minardi-ford | 41 | gearbox | 22 | none |
| 20 | ret | 9 | damon hill | jordan-mugen-honda | 19 | hydraulics | 7 | none |
| 21 | ret | 20 | ricardo rosset | tyrrell-ford | 16 | hydraulics | 18 | none | | | | no |
|---:|-----:|
| 0 | 17 |
| 1 | 16 | | [
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select bronze where nation = 'west germany (frg)' col : rank | nation | gold | silver | bronze | total row 1 : 1 | soviet union (urs) | 4 | 1 | 6 | 11 row 2 : 2 | yugoslavia (yug) | 2 | 0 | 1 | 3 row 3 : 3 | west germany (frg) | 1 | 1 | 1 | 3 row 4 : 4 | bulgaria (bul) | 1 | 1 | 0 | 2 row 5 : 4 | czechoslovakia (tch) | 1 | 1 | 0 | 2 row 6 : 4 | east germany (gdr) | 1 | 1 | 0 | 2 row 7 : 4 | great britain (gbr) | 1 | 1 | 0 | 2 row 8 : 8 | norway (nor) | 1 | 0 | 0 | 1 row 9 : 8 | romania (rou) | 1 | 0 | 0 | 1 row 10 : 10 | china (chn) | 0 | 1 | 1 | 2 row 11 : 11 | chile (chi) | 0 | 1 | 0 | 1 row 12 : 11 | france (fra) | 0 | 1 | 0 | 1 row 13 : 11 | japan (jpn) | 0 | 1 | 0 | 1 row 14 : 11 | south korea (kor) | 0 | 1 | 0 | 1 row 15 : 11 | sweden (swe) | 0 | 1 | 0 | 1 row 16 : 11 | united states (usa) | 0 | 1 | 0 | 1 row 17 : 17 | hungary (hun) | 0 | 0 | 2 | 2 row 18 : 18 | belgium (bel) | 0 | 0 | 1 | 1 row 19 : 18 | spain (esp) | 0 | 0 | 1 | 1 row 20 : total | total | 13 | 13 | 13 | 39 | col : bronze row 1 : 1 | select bronze where nation = 'west germany (frg)' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & soviet union (urs) & 4 & 1 & 6 & 11 \\
1 & 2 & yugoslavia (yug) & 2 & 0 & 1 & 3 \\
2 & 3 & west germany (frg) & 1 & 1 & 1 & 3 \\
3 & 4 & bulgaria (bul) & 1 & 1 & 0 & 2 \\
4 & 4 & czechoslovakia (tch) & 1 & 1 & 0 & 2 \\
5 & 4 & east germany (gdr) & 1 & 1 & 0 & 2 \\
6 & 4 & great britain (gbr) & 1 & 1 & 0 & 2 \\
7 & 8 & norway (nor) & 1 & 0 & 0 & 1 \\
8 & 8 & romania (rou) & 1 & 0 & 0 & 1 \\
9 & 10 & china (chn) & 0 & 1 & 1 & 2 \\
10 & 11 & chile (chi) & 0 & 1 & 0 & 1 \\
11 & 11 & france (fra) & 0 & 1 & 0 & 1 \\
12 & 11 & japan (jpn) & 0 & 1 & 0 & 1 \\
13 & 11 & south korea (kor) & 0 & 1 & 0 & 1 \\
14 & 11 & sweden (swe) & 0 & 1 & 0 & 1 \\
15 & 11 & united states (usa) & 0 & 1 & 0 & 1 \\
16 & 17 & hungary (hun) & 0 & 0 & 2 & 2 \\
17 & 18 & belgium (bel) & 0 & 0 & 1 & 1 \\
18 & 18 & spain (esp) & 0 & 0 & 1 & 1 \\
19 & total & total & 13 & 13 & 13 & 39 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& bronze \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select bronze where nation = 'west germany (frg)' <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>soviet union (urs)</td>
<td>4</td>
<td>1</td>
<td>6</td>
<td>11</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>yugoslavia (yug)</td>
<td>2</td>
<td>0</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>west germany (frg)</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>bulgaria (bul)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>czechoslovakia (tch)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>east germany (gdr)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>great britain (gbr)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>norway (nor)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>romania (rou)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>china (chn)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>chile (chi)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>france (fra)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>11</td>
<td>japan (jpn)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>11</td>
<td>south korea (kor)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>11</td>
<td>sweden (swe)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>11</td>
<td>united states (usa)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>hungary (hun)</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>belgium (bel)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>18</td>
<td>spain (esp)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>total</td>
<td>total</td>
<td>13</td>
<td>13</td>
<td>13</td>
<td>39</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>bronze</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select bronze where nation = 'west germany (frg)' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | soviet union (urs) | 4 | 1 | 6 | 11 |
| 1 | 2 | yugoslavia (yug) | 2 | 0 | 1 | 3 |
| 2 | 3 | west germany (frg) | 1 | 1 | 1 | 3 |
| 3 | 4 | bulgaria (bul) | 1 | 1 | 0 | 2 |
| 4 | 4 | czechoslovakia (tch) | 1 | 1 | 0 | 2 |
| 5 | 4 | east germany (gdr) | 1 | 1 | 0 | 2 |
| 6 | 4 | great britain (gbr) | 1 | 1 | 0 | 2 |
| 7 | 8 | norway (nor) | 1 | 0 | 0 | 1 |
| 8 | 8 | romania (rou) | 1 | 0 | 0 | 1 |
| 9 | 10 | china (chn) | 0 | 1 | 1 | 2 |
| 10 | 11 | chile (chi) | 0 | 1 | 0 | 1 |
| 11 | 11 | france (fra) | 0 | 1 | 0 | 1 |
| 12 | 11 | japan (jpn) | 0 | 1 | 0 | 1 |
| 13 | 11 | south korea (kor) | 0 | 1 | 0 | 1 |
| 14 | 11 | sweden (swe) | 0 | 1 | 0 | 1 |
| 15 | 11 | united states (usa) | 0 | 1 | 0 | 1 |
| 16 | 17 | hungary (hun) | 0 | 0 | 2 | 2 |
| 17 | 18 | belgium (bel) | 0 | 0 | 1 | 1 |
| 18 | 18 | spain (esp) | 0 | 0 | 1 | 1 |
| 19 | total | total | 13 | 13 | 13 | 39 | | | | bronze |
|---:|---------:|
| 0 | 1 | | [
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select count ( * ) where dutch = 'een beetje' col : afrikaans | ipa | dutch | english | german row 1 : hallo! hoe gaan dit? | [ɦaləu ɦu xaˑn dət] | hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het? | hello! how is it going? (hello! how are you?) | hallo! wie geht's? (hallo! wie geht's dir/ihnen?) row 2 : baie goed, dankie | [bajə xuˑt daŋki] | heel goed, dank je | very well, thank you | sehr gut, danke row 3 : praat jy afrikaans? | [prɑˑt jəi afrikɑˑs] | spreek/praat je/jij afrikaans? | do you speak afrikaans? | sprichst du afrikaans? row 4 : praat jy engels? | [prɑˑt jəi ɛŋəls] | spreek/praat je/jij engels? | do you speak english? | sprichst du englisch? row 5 : ja | [jɑˑ] | ja | yes | ja row 6 : nee | [neˑə] | nee | no | nein row 7 : 'n bietjie | [ə biki] | een beetje | a bit | ein bisschen row 8 : wat is jou naam? | [vat əs jəu nɑˑm] | hoe heet je? / wat is jouw naam? | what is your name? | wie heißt du? / wie ist dein name? row 9 : die kinders praat afrikaans | [di kənərs prɑˑt afrikɑˑns] | de kinderen spreken/praten afrikaans | the children speak afrikaans | die kinder sprechen afrikaans row 10 : ek is lief vir jou. less common: ek het jou lief | [æk əs lif vɯr jəʊ] | ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief | i love you | ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation) | col : count ( "*" ) row 1 : 1 | select count ( * ) where dutch = 'een beetje' <table_name> : table \begin{tabular}{llllll}
\toprule
& afrikaans & ipa & dutch & english & german \\
\midrule
0 & hallo! hoe gaan dit? & [ɦaləu ɦu xaˑn dət] & hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het? & hello! how is it going? (hello! how are you?) & hallo! wie geht's? (hallo! wie geht's dir/ihnen?) \\
1 & baie goed, dankie & [bajə xuˑt daŋki] & heel goed, dank je & very well, thank you & sehr gut, danke \\
2 & praat jy afrikaans? & [prɑˑt jəi afrikɑˑs] & spreek/praat je/jij afrikaans? & do you speak afrikaans? & sprichst du afrikaans? \\
3 & praat jy engels? & [prɑˑt jəi ɛŋəls] & spreek/praat je/jij engels? & do you speak english? & sprichst du englisch? \\
4 & ja & [jɑˑ] & ja & yes & ja \\
5 & nee & [neˑə] & nee & no & nein \\
6 & 'n bietjie & [ə biki] & een beetje & a bit & ein bisschen \\
7 & wat is jou naam? & [vat əs jəu nɑˑm] & hoe heet je? / wat is jouw naam? & what is your name? & wie heißt du? / wie ist dein name? \\
8 & die kinders praat afrikaans & [di kənərs prɑˑt afrikɑˑns] & de kinderen spreken/praten afrikaans & the children speak afrikaans & die kinder sprechen afrikaans \\
9 & ek is lief vir jou. less common: ek het jou lief & [æk əs lif vɯr jəʊ] & ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief & i love you & ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where dutch = 'een beetje' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>afrikaans</th>
<th>ipa</th>
<th>dutch</th>
<th>english</th>
<th>german</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>hallo! hoe gaan dit?</td>
<td>[ɦaləu ɦu xaˑn dət]</td>
<td>hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het?</td>
<td>hello! how is it going? (hello! how are you?)</td>
<td>hallo! wie geht's? (hallo! wie geht's dir/ihnen?)</td>
</tr>
<tr>
<th>1</th>
<td>baie goed, dankie</td>
<td>[bajə xuˑt daŋki]</td>
<td>heel goed, dank je</td>
<td>very well, thank you</td>
<td>sehr gut, danke</td>
</tr>
<tr>
<th>2</th>
<td>praat jy afrikaans?</td>
<td>[prɑˑt jəi afrikɑˑs]</td>
<td>spreek/praat je/jij afrikaans?</td>
<td>do you speak afrikaans?</td>
<td>sprichst du afrikaans?</td>
</tr>
<tr>
<th>3</th>
<td>praat jy engels?</td>
<td>[prɑˑt jəi ɛŋəls]</td>
<td>spreek/praat je/jij engels?</td>
<td>do you speak english?</td>
<td>sprichst du englisch?</td>
</tr>
<tr>
<th>4</th>
<td>ja</td>
<td>[jɑˑ]</td>
<td>ja</td>
<td>yes</td>
<td>ja</td>
</tr>
<tr>
<th>5</th>
<td>nee</td>
<td>[neˑə]</td>
<td>nee</td>
<td>no</td>
<td>nein</td>
</tr>
<tr>
<th>6</th>
<td>'n bietjie</td>
<td>[ə biki]</td>
<td>een beetje</td>
<td>a bit</td>
<td>ein bisschen</td>
</tr>
<tr>
<th>7</th>
<td>wat is jou naam?</td>
<td>[vat əs jəu nɑˑm]</td>
<td>hoe heet je? / wat is jouw naam?</td>
<td>what is your name?</td>
<td>wie heißt du? / wie ist dein name?</td>
</tr>
<tr>
<th>8</th>
<td>die kinders praat afrikaans</td>
<td>[di kənərs prɑˑt afrikɑˑns]</td>
<td>de kinderen spreken/praten afrikaans</td>
<td>the children speak afrikaans</td>
<td>die kinder sprechen afrikaans</td>
</tr>
<tr>
<th>9</th>
<td>ek is lief vir jou. less common: ek het jou lief</td>
<td>[æk əs lif vɯr jəʊ]</td>
<td>ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief</td>
<td>i love you</td>
<td>ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation)</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 dutch = 'een beetje' <table_name> : table | | afrikaans | ipa | dutch | english | german |
|---:|:-------------------------------------------------|:----------------------------|:------------------------------------------------------------------|:----------------------------------------------|:------------------------------------------------------------------------------------------|
| 0 | hallo! hoe gaan dit? | [ɦaləu ɦu xaˑn dət] | hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het? | hello! how is it going? (hello! how are you?) | hallo! wie geht's? (hallo! wie geht's dir/ihnen?) |
| 1 | baie goed, dankie | [bajə xuˑt daŋki] | heel goed, dank je | very well, thank you | sehr gut, danke |
| 2 | praat jy afrikaans? | [prɑˑt jəi afrikɑˑs] | spreek/praat je/jij afrikaans? | do you speak afrikaans? | sprichst du afrikaans? |
| 3 | praat jy engels? | [prɑˑt jəi ɛŋəls] | spreek/praat je/jij engels? | do you speak english? | sprichst du englisch? |
| 4 | ja | [jɑˑ] | ja | yes | ja |
| 5 | nee | [neˑə] | nee | no | nein |
| 6 | 'n bietjie | [ə biki] | een beetje | a bit | ein bisschen |
| 7 | wat is jou naam? | [vat əs jəu nɑˑm] | hoe heet je? / wat is jouw naam? | what is your name? | wie heißt du? / wie ist dein name? |
| 8 | die kinders praat afrikaans | [di kənərs prɑˑt afrikɑˑns] | de kinderen spreken/praten afrikaans | the children speak afrikaans | die kinder sprechen afrikaans |
| 9 | ek is lief vir jou. less common: ek het jou lief | [æk əs lif vɯr jəʊ] | ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief | i love you | ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation) | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select model where last of whiteness = '12 months' col : model | availability | introduced | length of use | last of whiteness row 1 : crest whitestrips classic previously crest whitestrips | discontinued | may 2001 | 14 days | 12 months row 2 : crest whitestrips professional | discontinued | 2001 | 10 days | 12 months row 3 : crest whitestrips supreme | dentist and online | september 2003 | 21 days | 18 months row 4 : crest whitestrips premium | discontinued | january 2004 | 7 days | 12 months row 5 : crest whitestrips pro previously crest whitestrips premium plus | discontinued | april 2005 | 10 days | 18 months row 6 : crest whitestrips renewal | discontinued | january 2006 | 10 days | 18 months row 7 : crest whitestrips daily multicare | discontinued | march 2007 | daily | white after using system row 8 : crest whitestrips advanced seal | discontinued | february 2009 | 14 days | 18 months row 9 : crest whitestrips 3d vivid | instore and online | 2009 | 10 days | 12 months row 10 : crest whitestrips 3d advanced vivid | instore and online | march 2010 | 14 days | 12 months row 11 : crest whitestrips 3d professional effects | instore and online | march 2010 | 20 days | 12 months row 12 : crest 3d white 2 hour express | instore and online | 2010 | 2 hours | 3 months row 13 : crest 3d intensive professional effects | instore and online | 2011 | 7 days | 12 months | col : model row 1 : crest whitestrips classic previously crest whitestrips row 2 : crest whitestrips professional row 3 : crest whitestrips premium row 4 : crest whitestrips 3d vivid row 5 : crest whitestrips 3d advanced vivid row 6 : crest whitestrips 3d professional effects row 7 : crest 3d intensive professional effects | select model where last of whiteness = '12 months' <table_name> : table \begin{tabular}{llllll}
\toprule
& model & availability & introduced & length of use & last of whiteness \\
\midrule
0 & crest whitestrips classic previously crest whitestrips & discontinued & may 2001 & 14 days & 12 months \\
1 & crest whitestrips professional & discontinued & 2001 & 10 days & 12 months \\
2 & crest whitestrips supreme & dentist and online & september 2003 & 21 days & 18 months \\
3 & crest whitestrips premium & discontinued & january 2004 & 7 days & 12 months \\
4 & crest whitestrips pro previously crest whitestrips premium plus & discontinued & april 2005 & 10 days & 18 months \\
5 & crest whitestrips renewal & discontinued & january 2006 & 10 days & 18 months \\
6 & crest whitestrips daily multicare & discontinued & march 2007 & daily & white after using system \\
7 & crest whitestrips advanced seal & discontinued & february 2009 & 14 days & 18 months \\
8 & crest whitestrips 3d vivid & instore and online & 2009 & 10 days & 12 months \\
9 & crest whitestrips 3d advanced vivid & instore and online & march 2010 & 14 days & 12 months \\
10 & crest whitestrips 3d professional effects & instore and online & march 2010 & 20 days & 12 months \\
11 & crest 3d white 2 hour express & instore and online & 2010 & 2 hours & 3 months \\
12 & crest 3d intensive professional effects & instore and online & 2011 & 7 days & 12 months \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& model \\
\midrule
0 & crest whitestrips classic previously crest whitestrips \\
1 & crest whitestrips professional \\
2 & crest whitestrips premium \\
3 & crest whitestrips 3d vivid \\
4 & crest whitestrips 3d advanced vivid \\
5 & crest whitestrips 3d professional effects \\
6 & crest 3d intensive professional effects \\
\bottomrule
\end{tabular}
| select model where last of whiteness = '12 months' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>model</th>
<th>availability</th>
<th>introduced</th>
<th>length of use</th>
<th>last of whiteness</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>crest whitestrips classic previously crest whitestrips</td>
<td>discontinued</td>
<td>may 2001</td>
<td>14 days</td>
<td>12 months</td>
</tr>
<tr>
<th>1</th>
<td>crest whitestrips professional</td>
<td>discontinued</td>
<td>2001</td>
<td>10 days</td>
<td>12 months</td>
</tr>
<tr>
<th>2</th>
<td>crest whitestrips supreme</td>
<td>dentist and online</td>
<td>september 2003</td>
<td>21 days</td>
<td>18 months</td>
</tr>
<tr>
<th>3</th>
<td>crest whitestrips premium</td>
<td>discontinued</td>
<td>january 2004</td>
<td>7 days</td>
<td>12 months</td>
</tr>
<tr>
<th>4</th>
<td>crest whitestrips pro previously crest whitestrips premium plus</td>
<td>discontinued</td>
<td>april 2005</td>
<td>10 days</td>
<td>18 months</td>
</tr>
<tr>
<th>5</th>
<td>crest whitestrips renewal</td>
<td>discontinued</td>
<td>january 2006</td>
<td>10 days</td>
<td>18 months</td>
</tr>
<tr>
<th>6</th>
<td>crest whitestrips daily multicare</td>
<td>discontinued</td>
<td>march 2007</td>
<td>daily</td>
<td>white after using system</td>
</tr>
<tr>
<th>7</th>
<td>crest whitestrips advanced seal</td>
<td>discontinued</td>
<td>february 2009</td>
<td>14 days</td>
<td>18 months</td>
</tr>
<tr>
<th>8</th>
<td>crest whitestrips 3d vivid</td>
<td>instore and online</td>
<td>2009</td>
<td>10 days</td>
<td>12 months</td>
</tr>
<tr>
<th>9</th>
<td>crest whitestrips 3d advanced vivid</td>
<td>instore and online</td>
<td>march 2010</td>
<td>14 days</td>
<td>12 months</td>
</tr>
<tr>
<th>10</th>
<td>crest whitestrips 3d professional effects</td>
<td>instore and online</td>
<td>march 2010</td>
<td>20 days</td>
<td>12 months</td>
</tr>
<tr>
<th>11</th>
<td>crest 3d white 2 hour express</td>
<td>instore and online</td>
<td>2010</td>
<td>2 hours</td>
<td>3 months</td>
</tr>
<tr>
<th>12</th>
<td>crest 3d intensive professional effects</td>
<td>instore and online</td>
<td>2011</td>
<td>7 days</td>
<td>12 months</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>model</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>crest whitestrips classic previously crest whitestrips</td>
</tr>
<tr>
<th>1</th>
<td>crest whitestrips professional</td>
</tr>
<tr>
<th>2</th>
<td>crest whitestrips premium</td>
</tr>
<tr>
<th>3</th>
<td>crest whitestrips 3d vivid</td>
</tr>
<tr>
<th>4</th>
<td>crest whitestrips 3d advanced vivid</td>
</tr>
<tr>
<th>5</th>
<td>crest whitestrips 3d professional effects</td>
</tr>
<tr>
<th>6</th>
<td>crest 3d intensive professional effects</td>
</tr>
</tbody>
</table> | select model where last of whiteness = '12 months' <table_name> : table | | model | availability | introduced | length of use | last of whiteness |
|---:|:----------------------------------------------------------------|:-------------------|:---------------|:----------------|:-------------------------|
| 0 | crest whitestrips classic previously crest whitestrips | discontinued | may 2001 | 14 days | 12 months |
| 1 | crest whitestrips professional | discontinued | 2001 | 10 days | 12 months |
| 2 | crest whitestrips supreme | dentist and online | september 2003 | 21 days | 18 months |
| 3 | crest whitestrips premium | discontinued | january 2004 | 7 days | 12 months |
| 4 | crest whitestrips pro previously crest whitestrips premium plus | discontinued | april 2005 | 10 days | 18 months |
| 5 | crest whitestrips renewal | discontinued | january 2006 | 10 days | 18 months |
| 6 | crest whitestrips daily multicare | discontinued | march 2007 | daily | white after using system |
| 7 | crest whitestrips advanced seal | discontinued | february 2009 | 14 days | 18 months |
| 8 | crest whitestrips 3d vivid | instore and online | 2009 | 10 days | 12 months |
| 9 | crest whitestrips 3d advanced vivid | instore and online | march 2010 | 14 days | 12 months |
| 10 | crest whitestrips 3d professional effects | instore and online | march 2010 | 20 days | 12 months |
| 11 | crest 3d white 2 hour express | instore and online | 2010 | 2 hours | 3 months |
| 12 | crest 3d intensive professional effects | instore and online | 2011 | 7 days | 12 months | | | | model |
|---:|:-------------------------------------------------------|
| 0 | crest whitestrips classic previously crest whitestrips |
| 1 | crest whitestrips professional |
| 2 | crest whitestrips premium |
| 3 | crest whitestrips 3d vivid |
| 4 | crest whitestrips 3d advanced vivid |
| 5 | crest whitestrips 3d professional effects |
| 6 | crest 3d intensive professional effects | | [
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