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trend_prediction_app

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ryanrahmadifa commited on Aug 12, 2024

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8010b21

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1 Parent(s): 220ae8f

Added more features.

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Files changed (3) hide show

modules/__pycache__/data_preparation.cpython-39.pyc +0 -0
modules/data_preparation.py +10 -3
test.ipynb +316 -1

modules/__pycache__/data_preparation.cpython-39.pyc CHANGED Viewed

Binary files a/modules/__pycache__/data_preparation.cpython-39.pyc and b/modules/__pycache__/data_preparation.cpython-39.pyc differ

modules/data_preparation.py CHANGED Viewed

@@ -3,6 +3,8 @@ import plotly.express as px
 import datetime
 import plotly.graph_objects as go
 import numpy as np
 def clean_text(text):
     new_text = text
@@ -32,10 +34,15 @@ def prepare_df(df, categories, date_filter):
         # insert column using insert(position,column_name,first_column) function
         news_data.insert(0, 'headline', first_column)
-        news_data['updatedDate'] = news_data['updatedDate'].apply(lambda x: datetime.datetime.strptime(x, '%y/%m/%d %H:%M:%S'))
-        news_data = news_data[(news_data['updatedDate'] >= date_filter[0]) & (news_data['updatedDate'] <= date_filter[1])]
     except Exception as E:
         print(E)

 import datetime
 import plotly.graph_objects as go
 import numpy as np
+import pandas as pd
+import datetime
 def clean_text(text):
     new_text = text
         # insert column using insert(position,column_name,first_column) function
         news_data.insert(0, 'headline', first_column)
+        news_data['updatedDate'] = pd.to_datetime(news_data['updatedDate'], format='%Y-%m-%d %H:%M:%S%z')
+        dates = []
+        dates.append(datetime.datetime.strftime(date_filter[0], '%Y-%m-%d %H:%M:%S%z'))
+        dates.append(datetime.datetime.strftime(date_filter[1], '%Y-%m-%d %H:%M:%S%z'))
+        news_data = news_data[(news_data['updatedDate'] >= dates[0]) & (news_data['updatedDate'] <= dates[1])]
     except Exception as E:
         print(E)

test.ipynb CHANGED Viewed

@@ -871,12 +871,327 @@
     "print(f'Bearish prediction {test.negative_score.mean()}\\n Neutral prediction {test.neutral_score.mean()}\\n Bullish prediction {test.positive_score.mean()}')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

     "print(f'Bearish prediction {test.negative_score.mean()}\\n Neutral prediction {test.neutral_score.mean()}\\n Bullish prediction {test.positive_score.mean()}')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>body</th>\n",
+       "      <th>headline</th>\n",
+       "      <th>updatedDate</th>\n",
+       "      <th>topic_prediction</th>\n",
+       "      <th>topic_verification</th>\n",
+       "      <th>negative_score</th>\n",
+       "      <th>neutral_score</th>\n",
+       "      <th>positive_score</th>\n",
+       "      <th>trend_prediction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Spanish crude import volumes increased 11% ye...</td>\n",
+       "      <td>SPAIN DATA: H1 crude imports rise 11% to 1.4 m...</td>\n",
+       "      <td>2024-08-08 12:11:55+00:00</td>\n",
+       "      <td>Crude Oil</td>\n",
+       "      <td>Crude Oil</td>\n",
+       "      <td>0.991473</td>\n",
+       "      <td>0.005524</td>\n",
+       "      <td>0.519264</td>\n",
+       "      <td>Bearish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>A number of refineries in China have resumed ...</td>\n",
+       "      <td>REFINERY NEWS: Host of Chinese units back from...</td>\n",
+       "      <td>2024-08-08 11:51:12+00:00</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>0.417054</td>\n",
+       "      <td>0.845595</td>\n",
+       "      <td>0.180685</td>\n",
+       "      <td>Neutral</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Some refineries in the Asia-Pacific region in...</td>\n",
+       "      <td>REFINERY NEWS ROUNDUP: Mixed runs in Asia-Pacific</td>\n",
+       "      <td>2024-08-08 11:50:48+00:00</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>0.268708</td>\n",
+       "      <td>0.044504</td>\n",
+       "      <td>0.992063</td>\n",
+       "      <td>Bullish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>The physical low sulfur (1%S) fuel oil Med-No...</td>\n",
+       "      <td>Physical 1%S fuel oil Med-North spread hits re...</td>\n",
+       "      <td>2024-08-08 11:28:20+00:00</td>\n",
+       "      <td>Middle Distillates</td>\n",
+       "      <td>Middle Distillates</td>\n",
+       "      <td>0.951985</td>\n",
+       "      <td>0.009613</td>\n",
+       "      <td>0.822905</td>\n",
+       "      <td>Bearish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Bunkering activity in India has experienced s...</td>\n",
+       "      <td>Indian ports see Jan-July bunker, STS calls up...</td>\n",
+       "      <td>2024-08-08 11:27:15+00:00</td>\n",
+       "      <td>Heavy Distillates</td>\n",
+       "      <td>Heavy Distillates</td>\n",
+       "      <td>0.098844</td>\n",
+       "      <td>0.059348</td>\n",
+       "      <td>0.997325</td>\n",
+       "      <td>Bullish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>136</th>\n",
+       "      <td>Saudi Aramco maintained or raised the Asia-bo...</td>\n",
+       "      <td>Saudi Aramco maintains or raises Asia-bound Se...</td>\n",
+       "      <td>2024-08-05 01:59:16+00:00</td>\n",
+       "      <td>Crude Oil</td>\n",
+       "      <td>Crude Oil</td>\n",
+       "      <td>0.154642</td>\n",
+       "      <td>0.032633</td>\n",
+       "      <td>0.997273</td>\n",
+       "      <td>Bullish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>137</th>\n",
+       "      <td>The combined open interest for front-month Si...</td>\n",
+       "      <td>ICE front-month Singapore HSFO open interest r...</td>\n",
+       "      <td>2024-08-05 01:26:07+00:00</td>\n",
+       "      <td>Heavy Distillates</td>\n",
+       "      <td>Heavy Distillates</td>\n",
+       "      <td>0.368089</td>\n",
+       "      <td>0.017483</td>\n",
+       "      <td>0.994805</td>\n",
+       "      <td>Bullish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>138</th>\n",
+       "      <td>Production will be increasing “in the near fu...</td>\n",
+       "      <td>REFINERY NEWS: Fort Energy at Fujairah ‘remain...</td>\n",
+       "      <td>2024-08-05 00:45:56+00:00</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>0.775953</td>\n",
+       "      <td>0.520116</td>\n",
+       "      <td>0.177664</td>\n",
+       "      <td>Bearish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>139</th>\n",
+       "      <td>Container ship Groton was attacked 125 nautic...</td>\n",
+       "      <td>Container ship Groton attacked near Yemen amid...</td>\n",
+       "      <td>2024-08-04 12:25:30+00:00</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>0.245594</td>\n",
+       "      <td>0.044671</td>\n",
+       "      <td>0.994086</td>\n",
+       "      <td>Bullish</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>140</th>\n",
+       "      <td>A drone strike on an oil depot in Russia’s Be...</td>\n",
+       "      <td>Oil depot in Russia’s Belgorod region hit by d...</td>\n",
+       "      <td>2024-08-04 10:14:50+00:00</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>Macroeconomic &amp; Geopolitics</td>\n",
+       "      <td>0.243901</td>\n",
+       "      <td>0.951199</td>\n",
+       "      <td>0.129076</td>\n",
+       "      <td>Neutral</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>141 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                  body  \\\n",
+       "0     Spanish crude import volumes increased 11% ye...   \n",
+       "1     A number of refineries in China have resumed ...   \n",
+       "2     Some refineries in the Asia-Pacific region in...   \n",
+       "3     The physical low sulfur (1%S) fuel oil Med-No...   \n",
+       "4     Bunkering activity in India has experienced s...   \n",
+       "..                                                 ...   \n",
+       "136   Saudi Aramco maintained or raised the Asia-bo...   \n",
+       "137   The combined open interest for front-month Si...   \n",
+       "138   Production will be increasing “in the near fu...   \n",
+       "139   Container ship Groton was attacked 125 nautic...   \n",
+       "140   A drone strike on an oil depot in Russia’s Be...   \n",
+       "\n",
+       "                                              headline  \\\n",
+       "0    SPAIN DATA: H1 crude imports rise 11% to 1.4 m...   \n",
+       "1    REFINERY NEWS: Host of Chinese units back from...   \n",
+       "2    REFINERY NEWS ROUNDUP: Mixed runs in Asia-Pacific   \n",
+       "3    Physical 1%S fuel oil Med-North spread hits re...   \n",
+       "4    Indian ports see Jan-July bunker, STS calls up...   \n",
+       "..                                                 ...   \n",
+       "136  Saudi Aramco maintains or raises Asia-bound Se...   \n",
+       "137  ICE front-month Singapore HSFO open interest r...   \n",
+       "138  REFINERY NEWS: Fort Energy at Fujairah ‘remain...   \n",
+       "139  Container ship Groton attacked near Yemen amid...   \n",
+       "140  Oil depot in Russia’s Belgorod region hit by d...   \n",
+       "\n",
+       "                   updatedDate             topic_prediction  \\\n",
+       "0    2024-08-08 12:11:55+00:00                    Crude Oil   \n",
+       "1    2024-08-08 11:51:12+00:00  Macroeconomic & Geopolitics   \n",
+       "2    2024-08-08 11:50:48+00:00  Macroeconomic & Geopolitics   \n",
+       "3    2024-08-08 11:28:20+00:00           Middle Distillates   \n",
+       "4    2024-08-08 11:27:15+00:00            Heavy Distillates   \n",
+       "..                         ...                          ...   \n",
+       "136  2024-08-05 01:59:16+00:00                    Crude Oil   \n",
+       "137  2024-08-05 01:26:07+00:00            Heavy Distillates   \n",
+       "138  2024-08-05 00:45:56+00:00  Macroeconomic & Geopolitics   \n",
+       "139  2024-08-04 12:25:30+00:00  Macroeconomic & Geopolitics   \n",
+       "140  2024-08-04 10:14:50+00:00  Macroeconomic & Geopolitics   \n",
+       "\n",
+       "              topic_verification  negative_score  neutral_score  \\\n",
+       "0                      Crude Oil        0.991473       0.005524   \n",
+       "1    Macroeconomic & Geopolitics        0.417054       0.845595   \n",
+       "2    Macroeconomic & Geopolitics        0.268708       0.044504   \n",
+       "3             Middle Distillates        0.951985       0.009613   \n",
+       "4              Heavy Distillates        0.098844       0.059348   \n",
+       "..                           ...             ...            ...   \n",
+       "136                    Crude Oil        0.154642       0.032633   \n",
+       "137            Heavy Distillates        0.368089       0.017483   \n",
+       "138  Macroeconomic & Geopolitics        0.775953       0.520116   \n",
+       "139  Macroeconomic & Geopolitics        0.245594       0.044671   \n",
+       "140  Macroeconomic & Geopolitics        0.243901       0.951199   \n",
+       "\n",
+       "     positive_score trend_prediction  \n",
+       "0          0.519264          Bearish  \n",
+       "1          0.180685          Neutral  \n",
+       "2          0.992063          Bullish  \n",
+       "3          0.822905          Bearish  \n",
+       "4          0.997325          Bullish  \n",
+       "..              ...              ...  \n",
+       "136        0.997273          Bullish  \n",
+       "137        0.994805          Bullish  \n",
+       "138        0.177664          Bearish  \n",
+       "139        0.994086          Bullish  \n",
+       "140        0.129076          Neutral  \n",
+       "\n",
+       "[141 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import os\n",
+    "\n",
+    "test = pd.read_excel('evaluation.xlsx').drop(columns=['Unnamed: 0']).iloc[:, :9]\n",
+    "\n",
+    "test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test['updatedDate'] = pd.to_datetime(test['updatedDate'], format='%Y-%m-%d %H:%M:%S%z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 141 entries, 0 to 140\n",
+      "Data columns (total 9 columns):\n",
+      " #   Column              Non-Null Count  Dtype              \n",
+      "---  ------              --------------  -----              \n",
+      " 0   body                141 non-null    object             \n",
+      " 1   headline            141 non-null    object             \n",
+      " 2   updatedDate         141 non-null    datetime64[ns, UTC]\n",
+      " 3   topic_prediction    141 non-null    object             \n",
+      " 4   topic_verification  141 non-null    object             \n",
+      " 5   negative_score      141 non-null    float64            \n",
+      " 6   neutral_score       141 non-null    float64            \n",
+      " 7   positive_score      141 non-null    float64            \n",
+      " 8   trend_prediction    141 non-null    object             \n",
+      "dtypes: datetime64[ns, UTC](1), float64(3), object(5)\n",
+      "memory usage: 10.0+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "test.info()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "from datetime import datetime\n",
+    "import numpy as np\n",
+    "\n",
+    "test[test['updatedDate']>= datetime.strptime('2024-08-07 00:00:00+00:00', '%Y-%m-%d %H:%M:%S%z')]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import datetime\n",
+    "\n",
+    "test_date = datetime(2024, 8, 4)"
+   ]
   }
  ],
  "metadata": {