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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a8878aaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import scipy\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "88fa1f3d",
   "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>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>container_id</th>\n",
       "      <th>last_collection</th>\n",
       "      <th>pre_height</th>\n",
       "      <th>post_height</th>\n",
       "      <th>sensor_mean_temperature</th>\n",
       "      <th>sensor_max_temperature</th>\n",
       "      <th>sensor_min_temperature</th>\n",
       "      <th>...</th>\n",
       "      <th>weather_mean_moisture</th>\n",
       "      <th>weather_max_moisture</th>\n",
       "      <th>weather_min_moisture</th>\n",
       "      <th>holiday_percentage</th>\n",
       "      <th>Lockdown</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>weekday</th>\n",
       "      <th>collection_intervall</th>\n",
       "      <th>number_collections</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2020-05-22 18:51:01.742945</td>\n",
       "      <td>70B3D500700016DA</td>\n",
       "      <td>-14 days +06:00:58.208000</td>\n",
       "      <td>136</td>\n",
       "      <td>16</td>\n",
       "      <td>15.251029</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.121212</td>\n",
       "      <td>95.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.360606</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2020-06-05 14:49:42.681218</td>\n",
       "      <td>70B3D500700016DA</td>\n",
       "      <td>-14 days +04:01:19.058000</td>\n",
       "      <td>120</td>\n",
       "      <td>14</td>\n",
       "      <td>16.410714</td>\n",
       "      <td>44</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>53.888554</td>\n",
       "      <td>93.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.361446</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2020-06-29 13:47:52.050553</td>\n",
       "      <td>70B3D500700016DA</td>\n",
       "      <td>-24 days +01:01:50.633000</td>\n",
       "      <td>136</td>\n",
       "      <td>14</td>\n",
       "      <td>18.255446</td>\n",
       "      <td>43</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>65.890435</td>\n",
       "      <td>97.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.375652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2020-07-17 13:46:18.287249</td>\n",
       "      <td>70B3D500700016DA</td>\n",
       "      <td>-18 days +00:01:33.806000</td>\n",
       "      <td>128</td>\n",
       "      <td>12</td>\n",
       "      <td>19.053476</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>58.773148</td>\n",
       "      <td>96.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-08-07 09:44:36.149679</td>\n",
       "      <td>70B3D500700016DA</td>\n",
       "      <td>-21 days +04:01:42.126000</td>\n",
       "      <td>118</td>\n",
       "      <td>14</td>\n",
       "      <td>21.981524</td>\n",
       "      <td>47</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>49.794000</td>\n",
       "      <td>95.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.288000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>1</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>4381</td>\n",
       "      <td>4381</td>\n",
       "      <td>2020-08-08 15:42:32.866709</td>\n",
       "      <td>70B3D50070001786</td>\n",
       "      <td>-2 days +21:00:01.687000</td>\n",
       "      <td>64</td>\n",
       "      <td>28</td>\n",
       "      <td>33.296296</td>\n",
       "      <td>59</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>40.925926</td>\n",
       "      <td>64.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.592593</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628</th>\n",
       "      <td>4382</td>\n",
       "      <td>4382</td>\n",
       "      <td>2020-08-09 15:42:30.118122</td>\n",
       "      <td>70B3D50070001786</td>\n",
       "      <td>-1 days +00:00:02.748000</td>\n",
       "      <td>60</td>\n",
       "      <td>24</td>\n",
       "      <td>32.217391</td>\n",
       "      <td>60</td>\n",
       "      <td>15</td>\n",
       "      <td>...</td>\n",
       "      <td>44.416667</td>\n",
       "      <td>75.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>4383</td>\n",
       "      <td>4383</td>\n",
       "      <td>2020-08-11 12:42:24.962069</td>\n",
       "      <td>70B3D50070001786</td>\n",
       "      <td>-2 days +03:00:05.138000</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "      <td>28.121951</td>\n",
       "      <td>60</td>\n",
       "      <td>15</td>\n",
       "      <td>...</td>\n",
       "      <td>47.222222</td>\n",
       "      <td>69.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.177778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>630</th>\n",
       "      <td>4384</td>\n",
       "      <td>4384</td>\n",
       "      <td>2020-09-07 13:40:11.695782</td>\n",
       "      <td>70B3D50070001786</td>\n",
       "      <td>-28 days +23:02:13.362000</td>\n",
       "      <td>62</td>\n",
       "      <td>30</td>\n",
       "      <td>20.341463</td>\n",
       "      <td>55</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>67.885978</td>\n",
       "      <td>98.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.295840</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>4385</td>\n",
       "      <td>4385</td>\n",
       "      <td>2020-09-14 15:39:33.709211</td>\n",
       "      <td>70B3D50070001786</td>\n",
       "      <td>-8 days +22:00:37.993000</td>\n",
       "      <td>64</td>\n",
       "      <td>28</td>\n",
       "      <td>20.869281</td>\n",
       "      <td>44</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>58.441176</td>\n",
       "      <td>94.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.282353</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>632 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0  Unnamed: 0.1                   timestamp      container_id  \\\n",
       "0             0             0  2020-05-22 18:51:01.742945  70B3D500700016DA   \n",
       "1             1             1  2020-06-05 14:49:42.681218  70B3D500700016DA   \n",
       "2             2             2  2020-06-29 13:47:52.050553  70B3D500700016DA   \n",
       "3             3             3  2020-07-17 13:46:18.287249  70B3D500700016DA   \n",
       "4             4             4  2020-08-07 09:44:36.149679  70B3D500700016DA   \n",
       "..          ...           ...                         ...               ...   \n",
       "627        4381          4381  2020-08-08 15:42:32.866709  70B3D50070001786   \n",
       "628        4382          4382  2020-08-09 15:42:30.118122  70B3D50070001786   \n",
       "629        4383          4383  2020-08-11 12:42:24.962069  70B3D50070001786   \n",
       "630        4384          4384  2020-09-07 13:40:11.695782  70B3D50070001786   \n",
       "631        4385          4385  2020-09-14 15:39:33.709211  70B3D50070001786   \n",
       "\n",
       "               last_collection  pre_height  post_height  \\\n",
       "0    -14 days +06:00:58.208000         136           16   \n",
       "1    -14 days +04:01:19.058000         120           14   \n",
       "2    -24 days +01:01:50.633000         136           14   \n",
       "3    -18 days +00:01:33.806000         128           12   \n",
       "4    -21 days +04:01:42.126000         118           14   \n",
       "..                         ...         ...          ...   \n",
       "627   -2 days +21:00:01.687000          64           28   \n",
       "628   -1 days +00:00:02.748000          60           24   \n",
       "629   -2 days +03:00:05.138000          70           30   \n",
       "630  -28 days +23:02:13.362000          62           30   \n",
       "631   -8 days +22:00:37.993000          64           28   \n",
       "\n",
       "     sensor_mean_temperature  sensor_max_temperature  sensor_min_temperature  \\\n",
       "0                  15.251029                      47                       0   \n",
       "1                  16.410714                      44                       4   \n",
       "2                  18.255446                      43                       4   \n",
       "3                  19.053476                      45                       7   \n",
       "4                  21.981524                      47                       6   \n",
       "..                       ...                     ...                     ...   \n",
       "627                33.296296                      59                      16   \n",
       "628                32.217391                      60                      15   \n",
       "629                28.121951                      60                      15   \n",
       "630                20.341463                      55                       7   \n",
       "631                20.869281                      44                       6   \n",
       "\n",
       "     ...  weather_mean_moisture  weather_max_moisture  weather_min_moisture  \\\n",
       "0    ...              58.121212                  95.0                  25.0   \n",
       "1    ...              53.888554                  93.0                  19.0   \n",
       "2    ...              65.890435                  97.0                  25.0   \n",
       "3    ...              58.773148                  96.0                  22.0   \n",
       "4    ...              49.794000                  95.0                  20.0   \n",
       "..   ...                    ...                   ...                   ...   \n",
       "627  ...              40.925926                  64.0                  23.0   \n",
       "628  ...              44.416667                  75.0                  21.0   \n",
       "629  ...              47.222222                  69.0                  23.0   \n",
       "630  ...              67.885978                  98.0                  28.0   \n",
       "631  ...              58.441176                  94.0                  26.0   \n",
       "\n",
       "     holiday_percentage  Lockdown  year  month  weekday  collection_intervall  \\\n",
       "0              0.360606       0.0  2020      5        4                    14   \n",
       "1              0.361446       0.0  2020      6        4                    14   \n",
       "2              0.375652       0.0  2020      6        0                    24   \n",
       "3              0.222222       0.0  2020      7        4                    18   \n",
       "4              0.288000       0.0  2020      8        4                    21   \n",
       "..                  ...       ...   ...    ...      ...                   ...   \n",
       "627            0.592593       0.0  2020      8        5                     2   \n",
       "628            1.000000       0.0  2020      8        6                     1   \n",
       "629            0.177778       0.0  2020      8        1                     2   \n",
       "630            0.295840       0.0  2020      9        0                    28   \n",
       "631            0.282353       0.0  2020      9        0                     8   \n",
       "\n",
       "     number_collections  \n",
       "0                     1  \n",
       "1                     1  \n",
       "2                     1  \n",
       "3                     1  \n",
       "4                     1  \n",
       "..                  ...  \n",
       "627                   1  \n",
       "628                   1  \n",
       "629                   1  \n",
       "630                   1  \n",
       "631                   1  \n",
       "\n",
       "[632 rows x 26 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file=os.getcwd()\n",
    "file_m=file[0:(len(file)-9)]\n",
    "file_dz='data\\\\modeling\\\\train'\n",
    "file_data=file_m+file_dz\n",
    "data_name=os.listdir(file_data)\n",
    "data='train_data'\n",
    "file_number=file_m+file_dz+'\\\\'+data+'.txt' \n",
    "df = pd.read_csv(file_number)\n",
    "df[\"collection_intervall\"] = list(map(lambda st: str(st)[0:int(st.index(\"d\"))],df[\"last_collection\"]))\n",
    "df[\"collection_intervall\"]=df[\"collection_intervall\"].astype(int)\n",
    "df[\"collection_intervall\"]= list(map(lambda z: z*(-1),df[\"collection_intervall\"]))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9aada1d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train=pd.DataFrame({'pre_height':df['pre_height'],'post_height':df['post_height'],\n",
    "                      'collection_intervall':df['collection_intervall'],'sensor_mean_temperature':df['sensor_mean_temperature'],\n",
    "                     'weather_mean_temperature':df['weather_mean_temperature'],'weather_mean_rain':df['weather_mean_rain'],\n",
    "                     'weather_mean_moisture':df['weather_mean_moisture'],'holiday_percentage':df['holiday_percentage'],\n",
    "                     'lockdown':df['Lockdown']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d24d8bb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "colormap = plt.cm.YlGn\n",
    "plt.figure(figsize=(12,12))\n",
    "plt.title('Pearson Correlation of Features', y=1.05, size=15)\n",
    "sns.heatmap(X_train.astype(float).corr(),linewidths=0.1,vmax=1.0, square=True, cmap=colormap, linecolor='white', annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae1ed94d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}