smart-home-s-temperature-processing-tf-keras.ipynb

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     "start_time": "2022-07-24T15:35:16.817143",
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    "tags": []
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   "source": [
    "# Smart Home's Temperature - Time Series Forecasting\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "96284db6",
   "metadata": {
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   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import gc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "578ed664",
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     "start_time": "2022-07-24T15:35:16.882635",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d5bbf506",
   "metadata": {
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     "status": "completed"
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   "outputs": [
    {
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      "text/plain": [
       "((2764, 19), (1373, 18))"
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     "execution_count": 2,
     "metadata": {},
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   ],
   "source": [
    "train=pd.read_csv('../input/smart-homes-temperature-time-series-forecasting/train.csv')\n",
    "test=pd.read_csv('../input/smart-homes-temperature-time-series-forecasting/test.csv')\n",
    "\n",
    "train.shape, test.shape"
   ]
  },
  {
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     "status": "completed"
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    "tags": []
   },
   "source": [
    "# Understanding Data "
   ]
  },
  {
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   "execution_count": 3,
   "id": "cba71030",
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     "status": "completed"
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   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>CO2_(dinning-room)</th>\n",
       "      <th>CO2_room</th>\n",
       "      <th>Relative_humidity_(dinning-room)</th>\n",
       "      <th>Relative_humidity_room</th>\n",
       "      <th>Lighting_(dinning-room)</th>\n",
       "      <th>Lighting_room</th>\n",
       "      <th>Meteo_Rain</th>\n",
       "      <th>Meteo_Sun_dusk</th>\n",
       "      <th>Meteo_Wind</th>\n",
       "      <th>Meteo_Sun_light_in_west_facade</th>\n",
       "      <th>Meteo_Sun_light_in_east_facade</th>\n",
       "      <th>Meteo_Sun_light_in_south_facade</th>\n",
       "      <th>Meteo_Sun_irradiance</th>\n",
       "      <th>Outdoor_relative_humidity_Sensor</th>\n",
       "      <th>Day_of_the_week</th>\n",
       "      <th>Indoor_temperature_room</th>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>13/03/2012</td>\n",
       "      <td>11:45</td>\n",
       "      <td>216.560</td>\n",
       "      <td>221.920</td>\n",
       "      <td>39.9125</td>\n",
       "      <td>42.4150</td>\n",
       "      <td>81.6650</td>\n",
       "      <td>113.520</td>\n",
       "      <td>0.0</td>\n",
       "      <td>623.360</td>\n",
       "      <td>1.42625</td>\n",
       "      <td>9690.24</td>\n",
       "      <td>12604.20</td>\n",
       "      <td>95436.8</td>\n",
       "      <td>758.880</td>\n",
       "      <td>48.3750</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.8275</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>13/03/2012</td>\n",
       "      <td>12:00</td>\n",
       "      <td>219.947</td>\n",
       "      <td>220.363</td>\n",
       "      <td>39.9267</td>\n",
       "      <td>42.2453</td>\n",
       "      <td>81.7413</td>\n",
       "      <td>113.605</td>\n",
       "      <td>0.0</td>\n",
       "      <td>623.211</td>\n",
       "      <td>1.59200</td>\n",
       "      <td>11022.00</td>\n",
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       "      <td>95436.8</td>\n",
       "      <td>762.069</td>\n",
       "      <td>47.8080</td>\n",
       "      <td>2.0</td>\n",
       "      <td>18.1207</td>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>13/03/2012</td>\n",
       "      <td>12:15</td>\n",
       "      <td>219.403</td>\n",
       "      <td>218.933</td>\n",
       "      <td>39.7720</td>\n",
       "      <td>42.2267</td>\n",
       "      <td>81.4240</td>\n",
       "      <td>113.600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>622.656</td>\n",
       "      <td>1.89133</td>\n",
       "      <td>13960.50</td>\n",
       "      <td>9669.63</td>\n",
       "      <td>95398.6</td>\n",
       "      <td>766.251</td>\n",
       "      <td>47.4320</td>\n",
       "      <td>2.0</td>\n",
       "      <td>18.4367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>13/03/2012</td>\n",
       "      <td>12:30</td>\n",
       "      <td>218.613</td>\n",
       "      <td>217.045</td>\n",
       "      <td>39.7760</td>\n",
       "      <td>42.0987</td>\n",
       "      <td>81.5013</td>\n",
       "      <td>113.344</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.82800</td>\n",
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       "      <td>95360.3</td>\n",
       "      <td>766.037</td>\n",
       "      <td>47.0240</td>\n",
       "      <td>2.0</td>\n",
       "      <td>18.7513</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>13/03/2012</td>\n",
       "      <td>12:45</td>\n",
       "      <td>217.714</td>\n",
       "      <td>216.080</td>\n",
       "      <td>39.7757</td>\n",
       "      <td>42.0686</td>\n",
       "      <td>81.4657</td>\n",
       "      <td>113.034</td>\n",
       "      <td>0.0</td>\n",
       "      <td>622.400</td>\n",
       "      <td>2.36071</td>\n",
       "      <td>26349.00</td>\n",
       "      <td>9208.32</td>\n",
       "      <td>95354.9</td>\n",
       "      <td>762.743</td>\n",
       "      <td>45.4743</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.0414</td>\n",
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       "   Id        Date   Time  CO2_(dinning-room)  CO2_room  \\\n",
       "0   0  13/03/2012  11:45             216.560   221.920   \n",
       "1   1  13/03/2012  12:00             219.947   220.363   \n",
       "2   2  13/03/2012  12:15             219.403   218.933   \n",
       "3   3  13/03/2012  12:30             218.613   217.045   \n",
       "4   4  13/03/2012  12:45             217.714   216.080   \n",
       "\n",
       "   Relative_humidity_(dinning-room)  Relative_humidity_room  \\\n",
       "0                           39.9125                 42.4150   \n",
       "1                           39.9267                 42.2453   \n",
       "2                           39.7720                 42.2267   \n",
       "3                           39.7760                 42.0987   \n",
       "4                           39.7757                 42.0686   \n",
       "\n",
       "   Lighting_(dinning-room)  Lighting_room  Meteo_Rain  Meteo_Sun_dusk  \\\n",
       "0                  81.6650        113.520         0.0         623.360   \n",
       "1                  81.7413        113.605         0.0         623.211   \n",
       "2                  81.4240        113.600         0.0         622.656   \n",
       "3                  81.5013        113.344         0.0         622.571   \n",
       "4                  81.4657        113.034         0.0         622.400   \n",
       "\n",
       "   Meteo_Wind  Meteo_Sun_light_in_west_facade  Meteo_Sun_light_in_east_facade  \\\n",
       "0     1.42625                         9690.24                        12604.20   \n",
       "1     1.59200                        11022.00                        10787.20   \n",
       "2     1.89133                        13960.50                         9669.63   \n",
       "3     1.82800                        18511.20                         9648.13   \n",
       "4     2.36071                        26349.00                         9208.32   \n",
       "\n",
       "   Meteo_Sun_light_in_south_facade  Meteo_Sun_irradiance  \\\n",
       "0                          95436.8               758.880   \n",
       "1                          95436.8               762.069   \n",
       "2                          95398.6               766.251   \n",
       "3                          95360.3               766.037   \n",
       "4                          95354.9               762.743   \n",
       "\n",
       "   Outdoor_relative_humidity_Sensor  Day_of_the_week  Indoor_temperature_room  \n",
       "0                           48.3750              2.0                  17.8275  \n",
       "1                           47.8080              2.0                  18.1207  \n",
       "2                           47.4320              2.0                  18.4367  \n",
       "3                           47.0240              2.0                  18.7513  \n",
       "4                           45.4743              2.0                  19.0414  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
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       "      <th>CO2_(dinning-room)</th>\n",
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       "      <th>Meteo_Wind</th>\n",
       "      <th>Meteo_Sun_light_in_west_facade</th>\n",
       "      <th>Meteo_Sun_light_in_east_facade</th>\n",
       "      <th>Meteo_Sun_light_in_south_facade</th>\n",
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       "      <th>0</th>\n",
       "      <td>2764</td>\n",
       "      <td>18/04/2012</td>\n",
       "      <td>00:00</td>\n",
       "      <td>207.840</td>\n",
       "      <td>206.560</td>\n",
       "      <td>31.5800</td>\n",
       "      <td>30.1600</td>\n",
       "      <td>11.7200</td>\n",
       "      <td>14.1600</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>1</th>\n",
       "      <td>2765</td>\n",
       "      <td>18/04/2012</td>\n",
       "      <td>00:15</td>\n",
       "      <td>207.499</td>\n",
       "      <td>206.101</td>\n",
       "      <td>31.6240</td>\n",
       "      <td>30.0613</td>\n",
       "      <td>11.5240</td>\n",
       "      <td>14.7600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.80800</td>\n",
       "      <td>38.9680</td>\n",
       "      <td>3.0</td>\n",
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       "      <th>2</th>\n",
       "      <td>2766</td>\n",
       "      <td>18/04/2012</td>\n",
       "      <td>00:30</td>\n",
       "      <td>207.360</td>\n",
       "      <td>206.805</td>\n",
       "      <td>31.6507</td>\n",
       "      <td>30.1773</td>\n",
       "      <td>11.6220</td>\n",
       "      <td>14.9547</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.088000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.96400</td>\n",
       "      <td>38.9467</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2767</td>\n",
       "      <td>18/04/2012</td>\n",
       "      <td>00:45</td>\n",
       "      <td>207.445</td>\n",
       "      <td>206.325</td>\n",
       "      <td>31.6987</td>\n",
       "      <td>30.2560</td>\n",
       "      <td>11.7847</td>\n",
       "      <td>15.0520</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.127333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.02933</td>\n",
       "      <td>39.0760</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2768</td>\n",
       "      <td>18/04/2012</td>\n",
       "      <td>01:00</td>\n",
       "      <td>207.840</td>\n",
       "      <td>205.952</td>\n",
       "      <td>31.7707</td>\n",
       "      <td>30.3840</td>\n",
       "      <td>11.5887</td>\n",
       "      <td>15.2147</td>\n",
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       "      <td>0.65</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.88600</td>\n",
       "      <td>40.0413</td>\n",
       "      <td>3.0</td>\n",
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       "     Id        Date   Time  CO2_(dinning-room)  CO2_room  \\\n",
       "0  2764  18/04/2012  00:00             207.840   206.560   \n",
       "1  2765  18/04/2012  00:15             207.499   206.101   \n",
       "2  2766  18/04/2012  00:30             207.360   206.805   \n",
       "3  2767  18/04/2012  00:45             207.445   206.325   \n",
       "4  2768  18/04/2012  01:00             207.840   205.952   \n",
       "\n",
       "   Relative_humidity_(dinning-room)  Relative_humidity_room  \\\n",
       "0                           31.5800                 30.1600   \n",
       "1                           31.6240                 30.0613   \n",
       "2                           31.6507                 30.1773   \n",
       "3                           31.6987                 30.2560   \n",
       "4                           31.7707                 30.3840   \n",
       "\n",
       "   Lighting_(dinning-room)  Lighting_room  Meteo_Rain  Meteo_Sun_dusk  \\\n",
       "0                  11.7200        14.1600         0.0            0.65   \n",
       "1                  11.5240        14.7600         0.0            0.65   \n",
       "2                  11.6220        14.9547         0.0            0.65   \n",
       "3                  11.7847        15.0520         0.0            0.65   \n",
       "4                  11.5887        15.2147         0.0            0.65   \n",
       "\n",
       "   Meteo_Wind  Meteo_Sun_light_in_west_facade  Meteo_Sun_light_in_east_facade  \\\n",
       "0    0.000000                             0.0                             0.0   \n",
       "1    0.000000                             0.0                             0.0   \n",
       "2    0.088000                             0.0                             0.0   \n",
       "3    0.127333                             0.0                             0.0   \n",
       "4    0.000000                             0.0                             0.0   \n",
       "\n",
       "   Meteo_Sun_light_in_south_facade  Meteo_Sun_irradiance  \\\n",
       "0                              0.0              -3.12000   \n",
       "1                              0.0              -2.80800   \n",
       "2                              0.0              -2.96400   \n",
       "3                              0.0              -3.02933   \n",
       "4                              0.0              -2.88600   \n",
       "\n",
       "   Outdoor_relative_humidity_Sensor  Day_of_the_week  \n",
       "0                           39.0800              3.0  \n",
       "1                           38.9680              3.0  \n",
       "2                           38.9467              3.0  \n",
       "3                           39.0760              3.0  \n",
       "4                           40.0413              3.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9ae4a83",
   "metadata": {
    "papermill": {
     "duration": 0.012388,
     "end_time": "2022-07-24T15:35:17.124901",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.112513",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Checking missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "13230f9e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:17.151813Z",
     "iopub.status.busy": "2022-07-24T15:35:17.151414Z",
     "iopub.status.idle": "2022-07-24T15:35:17.162696Z",
     "shell.execute_reply": "2022-07-24T15:35:17.161930Z"
    },
    "papermill": {
     "duration": 0.027106,
     "end_time": "2022-07-24T15:35:17.164618",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.137512",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(False, False)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.isna().sum().any(), test.isna().sum().any()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "954304d9",
   "metadata": {
    "papermill": {
     "duration": 0.012443,
     "end_time": "2022-07-24T15:35:17.189898",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.177455",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Checking columns dtypes and data memories size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "631494b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:17.217582Z",
     "iopub.status.busy": "2022-07-24T15:35:17.217188Z",
     "iopub.status.idle": "2022-07-24T15:35:17.243046Z",
     "shell.execute_reply": "2022-07-24T15:35:17.242112Z"
    },
    "papermill": {
     "duration": 0.042639,
     "end_time": "2022-07-24T15:35:17.245381",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.202742",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2764 entries, 0 to 2763\n",
      "Data columns (total 19 columns):\n",
      " #   Column                            Non-Null Count  Dtype  \n",
      "---  ------                            --------------  -----  \n",
      " 0   Id                                2764 non-null   int64  \n",
      " 1   Date                              2764 non-null   object \n",
      " 2   Time                              2764 non-null   object \n",
      " 3   CO2_(dinning-room)                2764 non-null   float64\n",
      " 4   CO2_room                          2764 non-null   float64\n",
      " 5   Relative_humidity_(dinning-room)  2764 non-null   float64\n",
      " 6   Relative_humidity_room            2764 non-null   float64\n",
      " 7   Lighting_(dinning-room)           2764 non-null   float64\n",
      " 8   Lighting_room                     2764 non-null   float64\n",
      " 9   Meteo_Rain                        2764 non-null   float64\n",
      " 10  Meteo_Sun_dusk                    2764 non-null   float64\n",
      " 11  Meteo_Wind                        2764 non-null   float64\n",
      " 12  Meteo_Sun_light_in_west_facade    2764 non-null   float64\n",
      " 13  Meteo_Sun_light_in_east_facade    2764 non-null   float64\n",
      " 14  Meteo_Sun_light_in_south_facade   2764 non-null   float64\n",
      " 15  Meteo_Sun_irradiance              2764 non-null   float64\n",
      " 16  Outdoor_relative_humidity_Sensor  2764 non-null   float64\n",
      " 17  Day_of_the_week                   2764 non-null   float64\n",
      " 18  Indoor_temperature_room           2764 non-null   float64\n",
      "dtypes: float64(16), int64(1), object(2)\n",
      "memory usage: 410.4+ KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "89bc7f9b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:17.273483Z",
     "iopub.status.busy": "2022-07-24T15:35:17.272803Z",
     "iopub.status.idle": "2022-07-24T15:35:17.286273Z",
     "shell.execute_reply": "2022-07-24T15:35:17.284765Z"
    },
    "papermill": {
     "duration": 0.031605,
     "end_time": "2022-07-24T15:35:17.289925",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.258320",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1373 entries, 0 to 1372\n",
      "Data columns (total 18 columns):\n",
      " #   Column                            Non-Null Count  Dtype  \n",
      "---  ------                            --------------  -----  \n",
      " 0   Id                                1373 non-null   int64  \n",
      " 1   Date                              1373 non-null   object \n",
      " 2   Time                              1373 non-null   object \n",
      " 3   CO2_(dinning-room)                1373 non-null   float64\n",
      " 4   CO2_room                          1373 non-null   float64\n",
      " 5   Relative_humidity_(dinning-room)  1373 non-null   float64\n",
      " 6   Relative_humidity_room            1373 non-null   float64\n",
      " 7   Lighting_(dinning-room)           1373 non-null   float64\n",
      " 8   Lighting_room                     1373 non-null   float64\n",
      " 9   Meteo_Rain                        1373 non-null   float64\n",
      " 10  Meteo_Sun_dusk                    1373 non-null   float64\n",
      " 11  Meteo_Wind                        1373 non-null   float64\n",
      " 12  Meteo_Sun_light_in_west_facade    1373 non-null   float64\n",
      " 13  Meteo_Sun_light_in_east_facade    1373 non-null   float64\n",
      " 14  Meteo_Sun_light_in_south_facade   1373 non-null   float64\n",
      " 15  Meteo_Sun_irradiance              1373 non-null   float64\n",
      " 16  Outdoor_relative_humidity_Sensor  1373 non-null   float64\n",
      " 17  Day_of_the_week                   1373 non-null   float64\n",
      "dtypes: float64(15), int64(1), object(2)\n",
      "memory usage: 193.2+ KB\n"
     ]
    }
   ],
   "source": [
    "test.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "505117bf",
   "metadata": {
    "papermill": {
     "duration": 0.012827,
     "end_time": "2022-07-24T15:35:17.317214",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.304387",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Dropping duplicates instances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6627829c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:17.345683Z",
     "iopub.status.busy": "2022-07-24T15:35:17.345267Z",
     "iopub.status.idle": "2022-07-24T15:35:17.359833Z",
     "shell.execute_reply": "2022-07-24T15:35:17.358686Z"
    },
    "papermill": {
     "duration": 0.031979,
     "end_time": "2022-07-24T15:35:17.362309",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.330330",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2764, 19)\n",
      "(2764, 19)\n"
     ]
    }
   ],
   "source": [
    "print(train.shape)\n",
    "train = train.drop_duplicates()\n",
    "print(train.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e93eaef",
   "metadata": {
    "papermill": {
     "duration": 0.013309,
     "end_time": "2022-07-24T15:35:17.389340",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.376031",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Describe data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7f29c189",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:17.418478Z",
     "iopub.status.busy": "2022-07-24T15:35:17.418063Z",
     "iopub.status.idle": "2022-07-24T15:35:17.479540Z",
     "shell.execute_reply": "2022-07-24T15:35:17.478395Z"
    },
    "papermill": {
     "duration": 0.078798,
     "end_time": "2022-07-24T15:35:17.481998",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.403200",
     "status": "completed"
    },
    "tags": []
   },
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>1381.500000</td>\n",
       "      <td>798.042397</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>690.750000</td>\n",
       "      <td>1381.50000</td>\n",
       "      <td>2072.250000</td>\n",
       "      <td>2763.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO2_(dinning-room)</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>208.479123</td>\n",
       "      <td>27.032686</td>\n",
       "      <td>187.339000</td>\n",
       "      <td>200.893250</td>\n",
       "      <td>207.04550</td>\n",
       "      <td>211.245500</td>\n",
       "      <td>594.38900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO2_room</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>211.065844</td>\n",
       "      <td>28.469144</td>\n",
       "      <td>188.907000</td>\n",
       "      <td>202.682750</td>\n",
       "      <td>209.40800</td>\n",
       "      <td>213.218750</td>\n",
       "      <td>609.23700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Relative_humidity_(dinning-room)</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>44.878420</td>\n",
       "      <td>6.587440</td>\n",
       "      <td>27.084000</td>\n",
       "      <td>40.351975</td>\n",
       "      <td>45.43465</td>\n",
       "      <td>49.352675</td>\n",
       "      <td>60.95730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Relative_humidity_room</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>47.321220</td>\n",
       "      <td>7.557795</td>\n",
       "      <td>29.594700</td>\n",
       "      <td>42.531325</td>\n",
       "      <td>47.53470</td>\n",
       "      <td>52.685975</td>\n",
       "      <td>62.59470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lighting_(dinning-room)</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>26.745381</td>\n",
       "      <td>23.298441</td>\n",
       "      <td>10.740000</td>\n",
       "      <td>11.588700</td>\n",
       "      <td>11.80130</td>\n",
       "      <td>31.224000</td>\n",
       "      <td>110.69300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lighting_room</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>40.732571</td>\n",
       "      <td>42.326087</td>\n",
       "      <td>11.328000</td>\n",
       "      <td>13.265300</td>\n",
       "      <td>17.69000</td>\n",
       "      <td>52.057350</td>\n",
       "      <td>162.96500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Rain</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>0.047033</td>\n",
       "      <td>0.206705</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_dusk</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>325.369289</td>\n",
       "      <td>305.062614</td>\n",
       "      <td>0.606667</td>\n",
       "      <td>0.650000</td>\n",
       "      <td>611.79700</td>\n",
       "      <td>619.210750</td>\n",
       "      <td>624.96000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Wind</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>1.108531</td>\n",
       "      <td>1.161283</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.094833</td>\n",
       "      <td>0.65900</td>\n",
       "      <td>1.971497</td>\n",
       "      <td>6.32133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_light_in_west_facade</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>14936.617682</td>\n",
       "      <td>25964.049455</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>15088.000000</td>\n",
       "      <td>95278.40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_light_in_east_facade</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>12248.000148</td>\n",
       "      <td>21758.550527</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>11131.275000</td>\n",
       "      <td>85535.40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_light_in_south_facade</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>22047.525813</td>\n",
       "      <td>32709.387051</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>38736.575000</td>\n",
       "      <td>95704.40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_irradiance</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>215.010017</td>\n",
       "      <td>297.234046</td>\n",
       "      <td>-4.164670</td>\n",
       "      <td>-3.381330</td>\n",
       "      <td>3.92200</td>\n",
       "      <td>435.434500</td>\n",
       "      <td>1028.27000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outdoor_relative_humidity_Sensor</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>55.981988</td>\n",
       "      <td>13.019610</td>\n",
       "      <td>22.260700</td>\n",
       "      <td>46.430675</td>\n",
       "      <td>57.47735</td>\n",
       "      <td>65.649325</td>\n",
       "      <td>83.80530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day_of_the_week</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>3.954438</td>\n",
       "      <td>1.991799</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.00000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>7.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indoor_temperature_room</th>\n",
       "      <td>2764.0</td>\n",
       "      <td>18.824852</td>\n",
       "      <td>2.821178</td>\n",
       "      <td>11.076000</td>\n",
       "      <td>17.060350</td>\n",
       "      <td>19.02100</td>\n",
       "      <td>20.828700</td>\n",
       "      <td>24.94400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   count          mean           std  \\\n",
       "Id                                2764.0   1381.500000    798.042397   \n",
       "CO2_(dinning-room)                2764.0    208.479123     27.032686   \n",
       "CO2_room                          2764.0    211.065844     28.469144   \n",
       "Relative_humidity_(dinning-room)  2764.0     44.878420      6.587440   \n",
       "Relative_humidity_room            2764.0     47.321220      7.557795   \n",
       "Lighting_(dinning-room)           2764.0     26.745381     23.298441   \n",
       "Lighting_room                     2764.0     40.732571     42.326087   \n",
       "Meteo_Rain                        2764.0      0.047033      0.206705   \n",
       "Meteo_Sun_dusk                    2764.0    325.369289    305.062614   \n",
       "Meteo_Wind                        2764.0      1.108531      1.161283   \n",
       "Meteo_Sun_light_in_west_facade    2764.0  14936.617682  25964.049455   \n",
       "Meteo_Sun_light_in_east_facade    2764.0  12248.000148  21758.550527   \n",
       "Meteo_Sun_light_in_south_facade   2764.0  22047.525813  32709.387051   \n",
       "Meteo_Sun_irradiance              2764.0    215.010017    297.234046   \n",
       "Outdoor_relative_humidity_Sensor  2764.0     55.981988     13.019610   \n",
       "Day_of_the_week                   2764.0      3.954438      1.991799   \n",
       "Indoor_temperature_room           2764.0     18.824852      2.821178   \n",
       "\n",
       "                                         min         25%         50%  \\\n",
       "Id                                  0.000000  690.750000  1381.50000   \n",
       "CO2_(dinning-room)                187.339000  200.893250   207.04550   \n",
       "CO2_room                          188.907000  202.682750   209.40800   \n",
       "Relative_humidity_(dinning-room)   27.084000   40.351975    45.43465   \n",
       "Relative_humidity_room             29.594700   42.531325    47.53470   \n",
       "Lighting_(dinning-room)            10.740000   11.588700    11.80130   \n",
       "Lighting_room                      11.328000   13.265300    17.69000   \n",
       "Meteo_Rain                          0.000000    0.000000     0.00000   \n",
       "Meteo_Sun_dusk                      0.606667    0.650000   611.79700   \n",
       "Meteo_Wind                          0.000000    0.094833     0.65900   \n",
       "Meteo_Sun_light_in_west_facade      0.000000    0.000000     0.00000   \n",
       "Meteo_Sun_light_in_east_facade      0.000000    0.000000     0.00000   \n",
       "Meteo_Sun_light_in_south_facade     0.000000    0.000000     0.00000   \n",
       "Meteo_Sun_irradiance               -4.164670   -3.381330     3.92200   \n",
       "Outdoor_relative_humidity_Sensor   22.260700   46.430675    57.47735   \n",
       "Day_of_the_week                     1.000000    2.000000     4.00000   \n",
       "Indoor_temperature_room            11.076000   17.060350    19.02100   \n",
       "\n",
       "                                           75%          max  \n",
       "Id                                 2072.250000   2763.00000  \n",
       "CO2_(dinning-room)                  211.245500    594.38900  \n",
       "CO2_room                            213.218750    609.23700  \n",
       "Relative_humidity_(dinning-room)     49.352675     60.95730  \n",
       "Relative_humidity_room               52.685975     62.59470  \n",
       "Lighting_(dinning-room)              31.224000    110.69300  \n",
       "Lighting_room                        52.057350    162.96500  \n",
       "Meteo_Rain                            0.000000      1.00000  \n",
       "Meteo_Sun_dusk                      619.210750    624.96000  \n",
       "Meteo_Wind                            1.971497      6.32133  \n",
       "Meteo_Sun_light_in_west_facade    15088.000000  95278.40000  \n",
       "Meteo_Sun_light_in_east_facade    11131.275000  85535.40000  \n",
       "Meteo_Sun_light_in_south_facade   38736.575000  95704.40000  \n",
       "Meteo_Sun_irradiance                435.434500   1028.27000  \n",
       "Outdoor_relative_humidity_Sensor     65.649325     83.80530  \n",
       "Day_of_the_week                       6.000000      7.00000  \n",
       "Indoor_temperature_room              20.828700     24.94400  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "37d72f66",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:17.511648Z",
     "iopub.status.busy": "2022-07-24T15:35:17.511255Z",
     "iopub.status.idle": "2022-07-24T15:35:17.568590Z",
     "shell.execute_reply": "2022-07-24T15:35:17.567403Z"
    },
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     "duration": 0.074979,
     "end_time": "2022-07-24T15:35:17.570982",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.496003",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>3450.000000</td>\n",
       "      <td>396.495271</td>\n",
       "      <td>2764.000000</td>\n",
       "      <td>3107.000000</td>\n",
       "      <td>3450.00000</td>\n",
       "      <td>3793.0000</td>\n",
       "      <td>4136.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO2_(dinning-room)</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>202.816621</td>\n",
       "      <td>8.303086</td>\n",
       "      <td>189.195000</td>\n",
       "      <td>197.867000</td>\n",
       "      <td>203.11500</td>\n",
       "      <td>206.2190</td>\n",
       "      <td>278.6450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO2_room</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>206.684117</td>\n",
       "      <td>10.862867</td>\n",
       "      <td>192.107000</td>\n",
       "      <td>199.541000</td>\n",
       "      <td>207.92500</td>\n",
       "      <td>210.7310</td>\n",
       "      <td>313.2160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Relative_humidity_(dinning-room)</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>37.380174</td>\n",
       "      <td>5.653677</td>\n",
       "      <td>26.173300</td>\n",
       "      <td>32.484000</td>\n",
       "      <td>35.84130</td>\n",
       "      <td>42.9253</td>\n",
       "      <td>52.5893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Relative_humidity_room</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>38.959385</td>\n",
       "      <td>6.765015</td>\n",
       "      <td>27.256000</td>\n",
       "      <td>32.569300</td>\n",
       "      <td>38.81200</td>\n",
       "      <td>44.7013</td>\n",
       "      <td>52.6240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lighting_(dinning-room)</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>33.449148</td>\n",
       "      <td>29.418966</td>\n",
       "      <td>10.838000</td>\n",
       "      <td>11.540700</td>\n",
       "      <td>20.82330</td>\n",
       "      <td>51.5733</td>\n",
       "      <td>111.7970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lighting_room</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>45.562360</td>\n",
       "      <td>42.988297</td>\n",
       "      <td>13.509300</td>\n",
       "      <td>14.906700</td>\n",
       "      <td>24.41600</td>\n",
       "      <td>67.5200</td>\n",
       "      <td>157.1570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Rain</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>0.022093</td>\n",
       "      <td>0.138203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_dusk</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>354.671855</td>\n",
       "      <td>302.567396</td>\n",
       "      <td>0.606667</td>\n",
       "      <td>0.650000</td>\n",
       "      <td>615.36000</td>\n",
       "      <td>620.4370</td>\n",
       "      <td>625.0030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Wind</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>1.699378</td>\n",
       "      <td>1.251345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.614667</td>\n",
       "      <td>1.57267</td>\n",
       "      <td>2.7160</td>\n",
       "      <td>5.3540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_light_in_west_facade</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>14371.755460</td>\n",
       "      <td>23932.658023</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2802.69000</td>\n",
       "      <td>13545.5000</td>\n",
       "      <td>93121.2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_light_in_east_facade</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>16220.137264</td>\n",
       "      <td>25966.803138</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3024.90000</td>\n",
       "      <td>17013.4000</td>\n",
       "      <td>92367.5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_light_in_south_facade</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>15447.785256</td>\n",
       "      <td>20945.850541</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2609.15000</td>\n",
       "      <td>26637.7000</td>\n",
       "      <td>77359.8000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Meteo_Sun_irradiance</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>266.816322</td>\n",
       "      <td>338.532417</td>\n",
       "      <td>-3.708000</td>\n",
       "      <td>-3.042000</td>\n",
       "      <td>35.81600</td>\n",
       "      <td>566.2930</td>\n",
       "      <td>1094.6600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outdoor_relative_humidity_Sensor</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>47.755124</td>\n",
       "      <td>12.794045</td>\n",
       "      <td>22.246700</td>\n",
       "      <td>37.338700</td>\n",
       "      <td>46.84530</td>\n",
       "      <td>57.8720</td>\n",
       "      <td>75.8907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day_of_the_week</th>\n",
       "      <td>1373.0</td>\n",
       "      <td>3.978878</td>\n",
       "      <td>1.983746</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.00000</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>7.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   count          mean           std  \\\n",
       "Id                                1373.0   3450.000000    396.495271   \n",
       "CO2_(dinning-room)                1373.0    202.816621      8.303086   \n",
       "CO2_room                          1373.0    206.684117     10.862867   \n",
       "Relative_humidity_(dinning-room)  1373.0     37.380174      5.653677   \n",
       "Relative_humidity_room            1373.0     38.959385      6.765015   \n",
       "Lighting_(dinning-room)           1373.0     33.449148     29.418966   \n",
       "Lighting_room                     1373.0     45.562360     42.988297   \n",
       "Meteo_Rain                        1373.0      0.022093      0.138203   \n",
       "Meteo_Sun_dusk                    1373.0    354.671855    302.567396   \n",
       "Meteo_Wind                        1373.0      1.699378      1.251345   \n",
       "Meteo_Sun_light_in_west_facade    1373.0  14371.755460  23932.658023   \n",
       "Meteo_Sun_light_in_east_facade    1373.0  16220.137264  25966.803138   \n",
       "Meteo_Sun_light_in_south_facade   1373.0  15447.785256  20945.850541   \n",
       "Meteo_Sun_irradiance              1373.0    266.816322    338.532417   \n",
       "Outdoor_relative_humidity_Sensor  1373.0     47.755124     12.794045   \n",
       "Day_of_the_week                   1373.0      3.978878      1.983746   \n",
       "\n",
       "                                          min          25%         50%  \\\n",
       "Id                                2764.000000  3107.000000  3450.00000   \n",
       "CO2_(dinning-room)                 189.195000   197.867000   203.11500   \n",
       "CO2_room                           192.107000   199.541000   207.92500   \n",
       "Relative_humidity_(dinning-room)    26.173300    32.484000    35.84130   \n",
       "Relative_humidity_room              27.256000    32.569300    38.81200   \n",
       "Lighting_(dinning-room)             10.838000    11.540700    20.82330   \n",
       "Lighting_room                       13.509300    14.906700    24.41600   \n",
       "Meteo_Rain                           0.000000     0.000000     0.00000   \n",
       "Meteo_Sun_dusk                       0.606667     0.650000   615.36000   \n",
       "Meteo_Wind                           0.000000     0.614667     1.57267   \n",
       "Meteo_Sun_light_in_west_facade       0.000000     0.000000  2802.69000   \n",
       "Meteo_Sun_light_in_east_facade       0.000000     0.000000  3024.90000   \n",
       "Meteo_Sun_light_in_south_facade      0.000000     0.000000  2609.15000   \n",
       "Meteo_Sun_irradiance                -3.708000    -3.042000    35.81600   \n",
       "Outdoor_relative_humidity_Sensor    22.246700    37.338700    46.84530   \n",
       "Day_of_the_week                      1.000000     2.000000     4.00000   \n",
       "\n",
       "                                         75%         max  \n",
       "Id                                 3793.0000   4136.0000  \n",
       "CO2_(dinning-room)                  206.2190    278.6450  \n",
       "CO2_room                            210.7310    313.2160  \n",
       "Relative_humidity_(dinning-room)     42.9253     52.5893  \n",
       "Relative_humidity_room               44.7013     52.6240  \n",
       "Lighting_(dinning-room)              51.5733    111.7970  \n",
       "Lighting_room                        67.5200    157.1570  \n",
       "Meteo_Rain                            0.0000      1.0000  \n",
       "Meteo_Sun_dusk                      620.4370    625.0030  \n",
       "Meteo_Wind                            2.7160      5.3540  \n",
       "Meteo_Sun_light_in_west_facade    13545.5000  93121.2000  \n",
       "Meteo_Sun_light_in_east_facade    17013.4000  92367.5000  \n",
       "Meteo_Sun_light_in_south_facade   26637.7000  77359.8000  \n",
       "Meteo_Sun_irradiance                566.2930   1094.6600  \n",
       "Outdoor_relative_humidity_Sensor     57.8720     75.8907  \n",
       "Day_of_the_week                       6.0000      7.0000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0305b868",
   "metadata": {
    "papermill": {
     "duration": 0.014886,
     "end_time": "2022-07-24T15:35:17.600462",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.585576",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8a29dfc2",
   "metadata": {
    "papermill": {
     "duration": 0.01491,
     "end_time": "2022-07-24T15:35:17.629892",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.614982",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84b52c13",
   "metadata": {
    "papermill": {
     "duration": 0.014979,
     "end_time": "2022-07-24T15:35:17.659505",
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     "start_time": "2022-07-24T15:35:17.644526",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Converting `Date` and `Time` columns to DateTime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3ae90dc9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:17.690598Z",
     "iopub.status.busy": "2022-07-24T15:35:17.690225Z",
     "iopub.status.idle": "2022-07-24T15:35:17.986632Z",
     "shell.execute_reply": "2022-07-24T15:35:17.985446Z"
    },
    "papermill": {
     "duration": 0.31516,
     "end_time": "2022-07-24T15:35:17.989071",
     "exception": false,
     "start_time": "2022-07-24T15:35:17.673911",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2012-03-13 11:45:00\n",
       "1   2012-03-13 12:00:00\n",
       "2   2012-03-13 12:15:00\n",
       "3   2012-03-13 12:30:00\n",
       "4   2012-03-13 12:45:00\n",
       "Name: DateTime, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[\"DateTime\"] = pd.to_datetime(train[\"Date\"] + ' ' + train[\"Time\"])\n",
    "\n",
    "train[\"DateTime\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a669c695",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.019743Z",
     "iopub.status.busy": "2022-07-24T15:35:18.019380Z",
     "iopub.status.idle": "2022-07-24T15:35:18.169866Z",
     "shell.execute_reply": "2022-07-24T15:35:18.168742Z"
    },
    "papermill": {
     "duration": 0.168422,
     "end_time": "2022-07-24T15:35:18.172206",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.003784",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2012-04-18 00:00:00\n",
       "1   2012-04-18 00:15:00\n",
       "2   2012-04-18 00:30:00\n",
       "3   2012-04-18 00:45:00\n",
       "4   2012-04-18 01:00:00\n",
       "Name: DateTime, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test[\"DateTime\"] = pd.to_datetime(test[\"Date\"] + ' ' + test[\"Time\"])\n",
    "\n",
    "test[\"DateTime\"].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0eef5cee",
   "metadata": {
    "papermill": {
     "duration": 0.014194,
     "end_time": "2022-07-24T15:35:18.201000",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.186806",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Removing `Date` and `Time` columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a8aca4f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.231776Z",
     "iopub.status.busy": "2022-07-24T15:35:18.231417Z",
     "iopub.status.idle": "2022-07-24T15:35:18.339970Z",
     "shell.execute_reply": "2022-07-24T15:35:18.338600Z"
    },
    "papermill": {
     "duration": 0.127516,
     "end_time": "2022-07-24T15:35:18.343029",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.215513",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before : (2764, 20) (1373, 19)\n",
      "After : (2764, 17) (1373, 16)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "126"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "remove_col = ['Id','Date','Time']\n",
    "\n",
    "print(\"Before :\", train.shape, test.shape)\n",
    "\n",
    "train = train.drop(remove_col,axis=1)\n",
    "test = test.drop(remove_col,axis=1)\n",
    "\n",
    "print(\"After :\", train.shape, test.shape)\n",
    "\n",
    "# Free memories\n",
    "gc.collect()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92d6a26e",
   "metadata": {
    "papermill": {
     "duration": 0.0144,
     "end_time": "2022-07-24T15:35:18.372786",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.358386",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Features Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a845410",
   "metadata": {
    "papermill": {
     "duration": 0.014302,
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     "start_time": "2022-07-24T15:35:18.387487",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Features Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a9710c51",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.432535Z",
     "iopub.status.busy": "2022-07-24T15:35:18.432158Z",
     "iopub.status.idle": "2022-07-24T15:35:18.441974Z",
     "shell.execute_reply": "2022-07-24T15:35:18.440852Z"
    },
    "papermill": {
     "duration": 0.027939,
     "end_time": "2022-07-24T15:35:18.444154",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.416215",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Thanks : https://www.kaggle.com/code/iamleonie/intro-to-time-series-forecasting/notebook\n",
    "\n",
    "def extrac_features(df=pd.DataFrame(), col='DateTime', prefix='DateTime'):\n",
    "    \n",
    "    #df[f'{prefix}_year']         = pd.DatetimeIndex(df[col]).year\n",
    "    df[f'{prefix}_month']        = pd.DatetimeIndex(df[col]).month\n",
    "    df[f'{prefix}_day']          = pd.DatetimeIndex(df[col]).day\n",
    "    df[f'{prefix}_day_of_year']  = pd.DatetimeIndex(df[col]).dayofyear\n",
    "    df[f'{prefix}_day_of_week']  = pd.DatetimeIndex(df[col]).dayofweek\n",
    "    df[f'{prefix}_week_of_year'] = pd.DatetimeIndex(df[col]).weekofyear\n",
    "    df[f'{prefix}_quarter']      = pd.DatetimeIndex(df[col]).quarter\n",
    "    \n",
    "    #df[f'{prefix}_is_month_start']  = pd.DatetimeIndex(df[col]).is_month_start\n",
    "    df[f'{prefix}_is_month_end']    = pd.DatetimeIndex(df[col]).is_month_end\n",
    "    \n",
    "    df[f'{prefix}_hour']         = pd.DatetimeIndex(df[col]).hour\n",
    "    df[f'{prefix}_minute']       = pd.DatetimeIndex(df[col]).minute\n",
    "    \n",
    "    df[f'{prefix}_season']       = df[f'{prefix}_month']%12 // 3 + 1\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0c4247d7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.476294Z",
     "iopub.status.busy": "2022-07-24T15:35:18.475644Z",
     "iopub.status.idle": "2022-07-24T15:35:18.520320Z",
     "shell.execute_reply": "2022-07-24T15:35:18.518805Z"
    },
    "papermill": {
     "duration": 0.063656,
     "end_time": "2022-07-24T15:35:18.522798",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.459142",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New data dimensions : (2764, 27) (1373, 26) \n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:10: FutureWarning: weekofyear and week have been deprecated, please use DatetimeIndex.isocalendar().week instead, which returns a Series.  To exactly reproduce the behavior of week and weekofyear and return an Index, you may call pd.Int64Index(idx.isocalendar().week)\n",
      "  # Remove the CWD from sys.path while we load stuff.\n"
     ]
    },
    {
     "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>CO2_(dinning-room)</th>\n",
       "      <th>CO2_room</th>\n",
       "      <th>Relative_humidity_(dinning-room)</th>\n",
       "      <th>Relative_humidity_room</th>\n",
       "      <th>Lighting_(dinning-room)</th>\n",
       "      <th>Lighting_room</th>\n",
       "      <th>Meteo_Rain</th>\n",
       "      <th>Meteo_Sun_dusk</th>\n",
       "      <th>Meteo_Wind</th>\n",
       "      <th>Meteo_Sun_light_in_west_facade</th>\n",
       "      <th>...</th>\n",
       "      <th>DateTime_month</th>\n",
       "      <th>DateTime_day</th>\n",
       "      <th>DateTime_day_of_year</th>\n",
       "      <th>DateTime_day_of_week</th>\n",
       "      <th>DateTime_week_of_year</th>\n",
       "      <th>DateTime_quarter</th>\n",
       "      <th>DateTime_is_month_end</th>\n",
       "      <th>DateTime_hour</th>\n",
       "      <th>DateTime_minute</th>\n",
       "      <th>DateTime_season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>216.560</td>\n",
       "      <td>221.920</td>\n",
       "      <td>39.9125</td>\n",
       "      <td>42.4150</td>\n",
       "      <td>81.6650</td>\n",
       "      <td>113.520</td>\n",
       "      <td>0.0</td>\n",
       "      <td>623.360</td>\n",
       "      <td>1.42625</td>\n",
       "      <td>9690.24</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>219.947</td>\n",
       "      <td>220.363</td>\n",
       "      <td>39.9267</td>\n",
       "      <td>42.2453</td>\n",
       "      <td>81.7413</td>\n",
       "      <td>113.605</td>\n",
       "      <td>0.0</td>\n",
       "      <td>623.211</td>\n",
       "      <td>1.59200</td>\n",
       "      <td>11022.00</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>219.403</td>\n",
       "      <td>218.933</td>\n",
       "      <td>39.7720</td>\n",
       "      <td>42.2267</td>\n",
       "      <td>81.4240</td>\n",
       "      <td>113.600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>622.656</td>\n",
       "      <td>1.89133</td>\n",
       "      <td>13960.50</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   CO2_(dinning-room)  CO2_room  Relative_humidity_(dinning-room)  \\\n",
       "0             216.560   221.920                           39.9125   \n",
       "1             219.947   220.363                           39.9267   \n",
       "2             219.403   218.933                           39.7720   \n",
       "\n",
       "   Relative_humidity_room  Lighting_(dinning-room)  Lighting_room  Meteo_Rain  \\\n",
       "0                 42.4150                  81.6650        113.520         0.0   \n",
       "1                 42.2453                  81.7413        113.605         0.0   \n",
       "2                 42.2267                  81.4240        113.600         0.0   \n",
       "\n",
       "   Meteo_Sun_dusk  Meteo_Wind  Meteo_Sun_light_in_west_facade  ...  \\\n",
       "0         623.360     1.42625                         9690.24  ...   \n",
       "1         623.211     1.59200                        11022.00  ...   \n",
       "2         622.656     1.89133                        13960.50  ...   \n",
       "\n",
       "   DateTime_month  DateTime_day  DateTime_day_of_year  DateTime_day_of_week  \\\n",
       "0               3            13                    73                     1   \n",
       "1               3            13                    73                     1   \n",
       "2               3            13                    73                     1   \n",
       "\n",
       "   DateTime_week_of_year  DateTime_quarter DateTime_is_month_end  \\\n",
       "0                     11                 1                 False   \n",
       "1                     11                 1                 False   \n",
       "2                     11                 1                 False   \n",
       "\n",
       "   DateTime_hour  DateTime_minute  DateTime_season  \n",
       "0             11               45                2  \n",
       "1             12                0                2  \n",
       "2             12               15                2  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_fe = extrac_features(train.copy(), 'DateTime')\n",
    "test_fe = extrac_features(test.copy(), 'DateTime')\n",
    "\n",
    "print(\"New data dimensions :\", train_fe.shape, test_fe.shape, '\\n')\n",
    "train_fe.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9f8dd44",
   "metadata": {
    "papermill": {
     "duration": 0.015269,
     "end_time": "2022-07-24T15:35:18.553701",
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     "start_time": "2022-07-24T15:35:18.538432",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Checking Correlation matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fd80c166",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.588281Z",
     "iopub.status.busy": "2022-07-24T15:35:18.587259Z",
     "iopub.status.idle": "2022-07-24T15:35:18.755593Z",
     "shell.execute_reply": "2022-07-24T15:35:18.754680Z"
    },
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     "duration": 0.188937,
     "end_time": "2022-07-24T15:35:18.759188",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.570251",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
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       "}\n",
       "#T_97135_row0_col25, #T_97135_row6_col12, #T_97135_row13_col19, #T_97135_row14_col1, #T_97135_row17_col3 {\n",
       "  background-color: #5d7ce6;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col0 {\n",
       "  background-color: #ca3b37;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col2, #T_97135_row2_col1, #T_97135_row7_col6, #T_97135_row11_col22, #T_97135_row13_col1, #T_97135_row13_col18, #T_97135_row13_col20, #T_97135_row18_col10, #T_97135_row20_col10, #T_97135_row22_col13, #T_97135_row24_col0 {\n",
       "  background-color: #7da0f9;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col3, #T_97135_row17_col9, #T_97135_row18_col2, #T_97135_row18_col13, #T_97135_row20_col2, #T_97135_row20_col13, #T_97135_row25_col9 {\n",
       "  background-color: #97b8ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row1_col4, #T_97135_row1_col11, #T_97135_row5_col21, #T_97135_row19_col22 {\n",
       "  background-color: #b9d0f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row1_col5, #T_97135_row9_col0 {\n",
       "  background-color: #a6c4fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row1_col7, #T_97135_row8_col10, #T_97135_row21_col9 {\n",
       "  background-color: #92b4fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row1_col9, #T_97135_row1_col13, #T_97135_row2_col18, #T_97135_row9_col16 {\n",
       "  background-color: #afcafc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row1_col12, #T_97135_row3_col16, #T_97135_row6_col17, #T_97135_row15_col22 {\n",
       "  background-color: #bad0f8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row1_col14, #T_97135_row8_col19 {\n",
       "  background-color: #536edd;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col16, #T_97135_row7_col2, #T_97135_row12_col13, #T_97135_row14_col25, #T_97135_row16_col7, #T_97135_row17_col7, #T_97135_row18_col7, #T_97135_row20_col7, #T_97135_row21_col7, #T_97135_row22_col6, #T_97135_row25_col4, #T_97135_row25_col7, #T_97135_row25_col17 {\n",
       "  background-color: #7295f4;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col17 {\n",
       "  background-color: #e3d9d3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row1_col18, #T_97135_row5_col23, #T_97135_row9_col6, #T_97135_row11_col23, #T_97135_row16_col14 {\n",
       "  background-color: #5e7de7;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col19, #T_97135_row3_col4, #T_97135_row3_col15, #T_97135_row23_col10 {\n",
       "  background-color: #5470de;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col20, #T_97135_row5_col6, #T_97135_row18_col14 {\n",
       "  background-color: #5f7fe8;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col23, #T_97135_row4_col23, #T_97135_row6_col2, #T_97135_row7_col19, #T_97135_row12_col19, #T_97135_row18_col5, #T_97135_row20_col5, #T_97135_row21_col4, #T_97135_row25_col5 {\n",
       "  background-color: #6a8bef;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row1_col25, #T_97135_row14_col0, #T_97135_row16_col19, #T_97135_row18_col19, #T_97135_row25_col14 {\n",
       "  background-color: #5875e1;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col0, #T_97135_row3_col19, #T_97135_row5_col2, #T_97135_row9_col3, #T_97135_row10_col2, #T_97135_row11_col3, #T_97135_row12_col22, #T_97135_row16_col10, #T_97135_row17_col6, #T_97135_row22_col0, #T_97135_row24_col6, #T_97135_row25_col10 {\n",
       "  background-color: #7b9ff9;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col3 {\n",
       "  background-color: #c53334;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col4, #T_97135_row2_col6, #T_97135_row4_col19, #T_97135_row6_col0, #T_97135_row8_col14, #T_97135_row19_col1, #T_97135_row21_col5, #T_97135_row25_col11 {\n",
       "  background-color: #6788ee;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col5, #T_97135_row2_col14, #T_97135_row9_col2, #T_97135_row18_col17, #T_97135_row19_col25, #T_97135_row20_col17, #T_97135_row22_col5, #T_97135_row22_col23, #T_97135_row24_col23 {\n",
       "  background-color: #6687ed;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col9, #T_97135_row6_col22, #T_97135_row6_col23, #T_97135_row24_col4 {\n",
       "  background-color: #779af7;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col10, #T_97135_row3_col1, #T_97135_row10_col19, #T_97135_row14_col5, #T_97135_row15_col14, #T_97135_row22_col12 {\n",
       "  background-color: #7a9df8;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col13 {\n",
       "  background-color: #ed8366;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col15, #T_97135_row4_col2, #T_97135_row6_col9, #T_97135_row13_col25, #T_97135_row15_col11, #T_97135_row17_col19, #T_97135_row23_col14 {\n",
       "  background-color: #7396f5;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col16, #T_97135_row9_col5 {\n",
       "  background-color: #c6d6f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row2_col19, #T_97135_row5_col22, #T_97135_row12_col3, #T_97135_row14_col13, #T_97135_row17_col13 {\n",
       "  background-color: #7ea1fa;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col20, #T_97135_row10_col9, #T_97135_row13_col21, #T_97135_row21_col3 {\n",
       "  background-color: #aec9fc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row2_col21 {\n",
       "  background-color: #d3dbe7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row2_col22, #T_97135_row18_col1 {\n",
       "  background-color: #4055c8;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col24, #T_97135_row3_col24, #T_97135_row8_col24, #T_97135_row13_col23, #T_97135_row14_col24, #T_97135_row15_col24, #T_97135_row16_col24, #T_97135_row18_col24, #T_97135_row19_col24, #T_97135_row20_col24, #T_97135_row21_col24, #T_97135_row22_col24, #T_97135_row25_col24 {\n",
       "  background-color: #3c4ec2;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row2_col25, #T_97135_row16_col8, #T_97135_row21_col13 {\n",
       "  background-color: #a2c1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row3_col0, #T_97135_row9_col22, #T_97135_row10_col15, #T_97135_row12_col2, #T_97135_row13_col0, #T_97135_row14_col7, #T_97135_row17_col5, #T_97135_row19_col11, #T_97135_row22_col7, #T_97135_row24_col11, #T_97135_row25_col22 {\n",
       "  background-color: #7597f6;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col2, #T_97135_row5_col12 {\n",
       "  background-color: #c73635;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col7, #T_97135_row3_col8, #T_97135_row3_col23, #T_97135_row19_col23, #T_97135_row20_col14, #T_97135_row21_col11, #T_97135_row25_col23 {\n",
       "  background-color: #5b7ae5;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col9, #T_97135_row5_col19, #T_97135_row6_col7, #T_97135_row11_col2, #T_97135_row14_col2, #T_97135_row21_col6, #T_97135_row24_col7, #T_97135_row25_col6 {\n",
       "  background-color: #7093f3;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col10, #T_97135_row16_col4, #T_97135_row17_col8, #T_97135_row22_col11, #T_97135_row23_col11, #T_97135_row24_col5, #T_97135_row24_col19 {\n",
       "  background-color: #6c8ff1;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col11, #T_97135_row16_col17, #T_97135_row20_col19 {\n",
       "  background-color: #4f69d9;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col12, #T_97135_row6_col10, #T_97135_row9_col19 {\n",
       "  background-color: #6282ea;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col13 {\n",
       "  background-color: #dd5f4b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col14 {\n",
       "  background-color: #5a78e4;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col18, #T_97135_row3_col20, #T_97135_row7_col0, #T_97135_row9_col1, #T_97135_row12_col18, #T_97135_row12_col20, #T_97135_row16_col13 {\n",
       "  background-color: #9fbfff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row3_col21 {\n",
       "  background-color: #cad8ef;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row3_col22, #T_97135_row6_col19, #T_97135_row6_col24, #T_97135_row7_col24, #T_97135_row9_col24, #T_97135_row10_col23, #T_97135_row13_col4, #T_97135_row13_col5, #T_97135_row13_col7, #T_97135_row13_col8, #T_97135_row13_col9, #T_97135_row13_col11, #T_97135_row13_col12, #T_97135_row13_col14, #T_97135_row13_col15, #T_97135_row15_col2, #T_97135_row15_col3, #T_97135_row15_col6, #T_97135_row15_col10, #T_97135_row15_col13, #T_97135_row17_col16, #T_97135_row17_col18, #T_97135_row17_col20, #T_97135_row17_col21, #T_97135_row17_col25, #T_97135_row21_col0, #T_97135_row21_col1, #T_97135_row21_col17 {\n",
       "  background-color: #3b4cc0;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row3_col25, #T_97135_row14_col12, #T_97135_row15_col1, #T_97135_row19_col2, #T_97135_row22_col18, #T_97135_row24_col9 {\n",
       "  background-color: #90b2fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col0, #T_97135_row5_col17, #T_97135_row11_col0, #T_97135_row25_col15 {\n",
       "  background-color: #c3d5f4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col1, #T_97135_row11_col1 {\n",
       "  background-color: #c1d4f4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col5, #T_97135_row21_col18, #T_97135_row21_col20 {\n",
       "  background-color: #c43032;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row4_col6, #T_97135_row9_col13, #T_97135_row10_col6, #T_97135_row16_col11, #T_97135_row19_col0 {\n",
       "  background-color: #6180e9;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row4_col7, #T_97135_row7_col4 {\n",
       "  background-color: #f7ad90;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col8, #T_97135_row7_col8 {\n",
       "  background-color: #f6bea4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col9 {\n",
       "  background-color: #efcfbf;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col10, #T_97135_row9_col4 {\n",
       "  background-color: #e4d9d2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col11, #T_97135_row4_col12, #T_97135_row5_col4, #T_97135_row11_col4, #T_97135_row11_col12, #T_97135_row12_col4, #T_97135_row12_col11 {\n",
       "  background-color: #c32e31;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row4_col14, #T_97135_row10_col0, #T_97135_row10_col1, #T_97135_row11_col25, #T_97135_row21_col12, #T_97135_row22_col1, #T_97135_row23_col1, #T_97135_row23_col2, #T_97135_row23_col22, #T_97135_row24_col8, #T_97135_row24_col22 {\n",
       "  background-color: #84a7fc;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row4_col15, #T_97135_row7_col15, #T_97135_row9_col17, #T_97135_row12_col17, #T_97135_row19_col17 {\n",
       "  background-color: #c0d4f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col16, #T_97135_row8_col23, #T_97135_row22_col19, #T_97135_row22_col21 {\n",
       "  background-color: #a7c5fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col17, #T_97135_row8_col16 {\n",
       "  background-color: #c5d6f2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col21, #T_97135_row8_col20, #T_97135_row14_col15 {\n",
       "  background-color: #b5cdfa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row4_col22, #T_97135_row7_col14, #T_97135_row18_col22, #T_97135_row21_col10, #T_97135_row23_col4 {\n",
       "  background-color: #799cf8;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row4_col24 {\n",
       "  background-color: #3f53c6;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row4_col25, #T_97135_row6_col20, #T_97135_row10_col14, #T_97135_row15_col0, #T_97135_row17_col15 {\n",
       "  background-color: #8db0fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col1, #T_97135_row15_col20 {\n",
       "  background-color: #b6cefa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col7, #T_97135_row11_col10 {\n",
       "  background-color: #f7af91;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col8, #T_97135_row11_col8 {\n",
       "  background-color: #f1ccb8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col9, #T_97135_row8_col15, #T_97135_row15_col23 {\n",
       "  background-color: #dcdddd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col10 {\n",
       "  background-color: #f7ba9f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col11, #T_97135_row11_col5 {\n",
       "  background-color: #be242e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row5_col13, #T_97135_row7_col3, #T_97135_row15_col4, #T_97135_row17_col12, #T_97135_row19_col9, #T_97135_row25_col12 {\n",
       "  background-color: #88abfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col15, #T_97135_row6_col21, #T_97135_row14_col21 {\n",
       "  background-color: #b2ccfb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col18, #T_97135_row5_col20, #T_97135_row7_col18, #T_97135_row7_col20, #T_97135_row14_col16, #T_97135_row22_col16, #T_97135_row24_col18, #T_97135_row24_col20 {\n",
       "  background-color: #9abbff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row5_col24, #T_97135_row10_col24, #T_97135_row16_col0, #T_97135_row17_col2, #T_97135_row22_col2 {\n",
       "  background-color: #3e51c5;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row5_col25, #T_97135_row7_col25, #T_97135_row17_col10, #T_97135_row17_col11, #T_97135_row17_col14, #T_97135_row22_col20, #T_97135_row23_col6, #T_97135_row23_col13, #T_97135_row23_col18, #T_97135_row23_col20, #T_97135_row24_col25 {\n",
       "  background-color: #8fb1fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row6_col3, #T_97135_row19_col3 {\n",
       "  background-color: #a9c6fd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row6_col4, #T_97135_row22_col3 {\n",
       "  background-color: #5673e0;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row6_col5, #T_97135_row8_col2 {\n",
       "  background-color: #4c66d6;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row6_col8 {\n",
       "  background-color: #c4d5f3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row6_col11 {\n",
       "  background-color: #4e68d8;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row6_col13 {\n",
       "  background-color: #e8d6cc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row6_col14, #T_97135_row25_col1 {\n",
       "  background-color: #485fd1;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row6_col16, #T_97135_row16_col2, #T_97135_row18_col3, #T_97135_row18_col8, #T_97135_row20_col3, #T_97135_row20_col8, #T_97135_row25_col8 {\n",
       "  background-color: #a1c0ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row7_col1, #T_97135_row9_col10, #T_97135_row9_col18, #T_97135_row9_col20, #T_97135_row11_col16, #T_97135_row15_col19, #T_97135_row25_col3 {\n",
       "  background-color: #9ebeff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row7_col5 {\n",
       "  background-color: #f7b194;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row7_col9 {\n",
       "  background-color: #f7b599;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row7_col10 {\n",
       "  background-color: #f6bfa6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row7_col11 {\n",
       "  background-color: #f7a688;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row7_col12 {\n",
       "  background-color: #f18f71;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row7_col13, #T_97135_row11_col13, #T_97135_row14_col4, #T_97135_row22_col25, #T_97135_row23_col0, #T_97135_row24_col2, #T_97135_row24_col10 {\n",
       "  background-color: #81a4fb;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row7_col16, #T_97135_row19_col21, #T_97135_row22_col14, #T_97135_row24_col16 {\n",
       "  background-color: #adc9fd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row7_col17, #T_97135_row7_col21, #T_97135_row12_col0, #T_97135_row24_col21 {\n",
       "  background-color: #bbd1f8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col4 {\n",
       "  background-color: #f5c4ac;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col5 {\n",
       "  background-color: #ead4c8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col7, #T_97135_row10_col7, #T_97135_row23_col15 {\n",
       "  background-color: #f4c5ad;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col9 {\n",
       "  background-color: #f6a586;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col11, #T_97135_row22_col17 {\n",
       "  background-color: #edd2c3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col12 {\n",
       "  background-color: #f7ac8e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col13, #T_97135_row8_col22, #T_97135_row11_col19, #T_97135_row12_col23, #T_97135_row13_col10, #T_97135_row16_col6, #T_97135_row18_col4, #T_97135_row19_col7, #T_97135_row20_col4, #T_97135_row20_col6, #T_97135_row22_col8 {\n",
       "  background-color: #6f92f3;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row8_col18, #T_97135_row23_col21 {\n",
       "  background-color: #b3cdfb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row8_col21, #T_97135_row19_col15, #T_97135_row21_col15 {\n",
       "  background-color: #d2dbe8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row9_col7 {\n",
       "  background-color: #f5c1a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row9_col8, #T_97135_row12_col8 {\n",
       "  background-color: #f7aa8c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row9_col11 {\n",
       "  background-color: #e2dad5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row9_col12 {\n",
       "  background-color: #f7b093;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row9_col15, #T_97135_row11_col9 {\n",
       "  background-color: #edd1c2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row9_col23, #T_97135_row13_col16, #T_97135_row14_col9, #T_97135_row15_col17, #T_97135_row19_col16 {\n",
       "  background-color: #9bbcff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row9_col25, #T_97135_row12_col25, #T_97135_row16_col9, #T_97135_row18_col9, #T_97135_row25_col2 {\n",
       "  background-color: #94b6ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col4 {\n",
       "  background-color: #e0dbd8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col5 {\n",
       "  background-color: #f5c2aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col11 {\n",
       "  background-color: #f7b497;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col12 {\n",
       "  background-color: #f2cab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col13, #T_97135_row15_col25, #T_97135_row21_col2, #T_97135_row23_col16 {\n",
       "  background-color: #a3c2fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col17 {\n",
       "  background-color: #c7d7f0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col18, #T_97135_row10_col20, #T_97135_row25_col13 {\n",
       "  background-color: #98b9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row10_col22 {\n",
       "  background-color: #8badfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row11_col6, #T_97135_row12_col6, #T_97135_row16_col23, #T_97135_row18_col23, #T_97135_row20_col23, #T_97135_row21_col19, #T_97135_row21_col23 {\n",
       "  background-color: #5977e3;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row11_col7 {\n",
       "  background-color: #f7a889;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row11_col14 {\n",
       "  background-color: #89acfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row11_col15, #T_97135_row12_col16, #T_97135_row24_col13, #T_97135_row24_col15 {\n",
       "  background-color: #b1cbfc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row11_col17 {\n",
       "  background-color: #cdd9ec;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row12_col7, #T_97135_row13_col2 {\n",
       "  background-color: #f39475;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row12_col9 {\n",
       "  background-color: #f7a98b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row12_col10, #T_97135_row14_col19 {\n",
       "  background-color: #f2cbb7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row12_col15 {\n",
       "  background-color: #cbd8ee;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row13_col3 {\n",
       "  background-color: #e0654f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row13_col6, #T_97135_row14_col17, #T_97135_row16_col15 {\n",
       "  background-color: #ccd9ed;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row13_col22 {\n",
       "  background-color: #465ecf;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row15_col9 {\n",
       "  background-color: #dfdbd9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row15_col12, #T_97135_row19_col13, #T_97135_row21_col8 {\n",
       "  background-color: #a5c3fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row15_col16, #T_97135_row18_col15, #T_97135_row20_col15 {\n",
       "  background-color: #c9d7f0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row15_col21 {\n",
       "  background-color: #d9dce1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row16_col18, #T_97135_row16_col20, #T_97135_row18_col16, #T_97135_row20_col16 {\n",
       "  background-color: #b50927;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row16_col21, #T_97135_row21_col16, #T_97135_row25_col20 {\n",
       "  background-color: #bb1b2c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row16_col22, #T_97135_row18_col6, #T_97135_row19_col4, #T_97135_row19_col5 {\n",
       "  background-color: #6e90f2;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row16_col25, #T_97135_row18_col21, #T_97135_row20_col21 {\n",
       "  background-color: #c12b30;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row17_col22 {\n",
       "  background-color: #d1dae9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row18_col0, #T_97135_row25_col19 {\n",
       "  background-color: #4358cb;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row18_col25, #T_97135_row20_col25, #T_97135_row25_col18 {\n",
       "  background-color: #bd1f2d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row19_col6 {\n",
       "  background-color: #4b64d5;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row19_col14 {\n",
       "  background-color: #f3c8b2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row20_col0 {\n",
       "  background-color: #445acc;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row20_col1 {\n",
       "  background-color: #4257c9;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row21_col25 {\n",
       "  background-color: #d75445;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row22_col15 {\n",
       "  background-color: #d8dce2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row23_col3 {\n",
       "  background-color: #93b5fe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row24_col3 {\n",
       "  background-color: #9dbdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_97135_row25_col0 {\n",
       "  background-color: #4961d2;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row25_col16 {\n",
       "  background-color: #c0282f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_97135_row25_col21 {\n",
       "  background-color: #d1493f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_97135_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >CO2_(dinning-room)</th>\n",
       "      <th class=\"col_heading level0 col1\" >CO2_room</th>\n",
       "      <th class=\"col_heading level0 col2\" >Relative_humidity_(dinning-room)</th>\n",
       "      <th class=\"col_heading level0 col3\" >Relative_humidity_room</th>\n",
       "      <th class=\"col_heading level0 col4\" >Lighting_(dinning-room)</th>\n",
       "      <th class=\"col_heading level0 col5\" >Lighting_room</th>\n",
       "      <th class=\"col_heading level0 col6\" >Meteo_Rain</th>\n",
       "      <th class=\"col_heading level0 col7\" >Meteo_Sun_dusk</th>\n",
       "      <th class=\"col_heading level0 col8\" >Meteo_Wind</th>\n",
       "      <th class=\"col_heading level0 col9\" >Meteo_Sun_light_in_west_facade</th>\n",
       "      <th class=\"col_heading level0 col10\" >Meteo_Sun_light_in_east_facade</th>\n",
       "      <th class=\"col_heading level0 col11\" >Meteo_Sun_light_in_south_facade</th>\n",
       "      <th class=\"col_heading level0 col12\" >Meteo_Sun_irradiance</th>\n",
       "      <th class=\"col_heading level0 col13\" >Outdoor_relative_humidity_Sensor</th>\n",
       "      <th class=\"col_heading level0 col14\" >Day_of_the_week</th>\n",
       "      <th class=\"col_heading level0 col15\" >Indoor_temperature_room</th>\n",
       "      <th class=\"col_heading level0 col16\" >DateTime_month</th>\n",
       "      <th class=\"col_heading level0 col17\" >DateTime_day</th>\n",
       "      <th class=\"col_heading level0 col18\" >DateTime_day_of_year</th>\n",
       "      <th class=\"col_heading level0 col19\" >DateTime_day_of_week</th>\n",
       "      <th class=\"col_heading level0 col20\" >DateTime_week_of_year</th>\n",
       "      <th class=\"col_heading level0 col21\" >DateTime_quarter</th>\n",
       "      <th class=\"col_heading level0 col22\" >DateTime_is_month_end</th>\n",
       "      <th class=\"col_heading level0 col23\" >DateTime_hour</th>\n",
       "      <th class=\"col_heading level0 col24\" >DateTime_minute</th>\n",
       "      <th class=\"col_heading level0 col25\" >DateTime_season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row0\" class=\"row_heading level0 row0\" >CO2_(dinning-room)</th>\n",
       "      <td id=\"T_97135_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
       "      <td id=\"T_97135_row0_col1\" class=\"data row0 col1\" >0.925522</td>\n",
       "      <td id=\"T_97135_row0_col2\" class=\"data row0 col2\" >-0.004698</td>\n",
       "      <td id=\"T_97135_row0_col3\" class=\"data row0 col3\" >-0.027170</td>\n",
       "      <td id=\"T_97135_row0_col4\" class=\"data row0 col4\" >0.255059</td>\n",
       "      <td id=\"T_97135_row0_col5\" class=\"data row0 col5\" >0.214517</td>\n",
       "      <td id=\"T_97135_row0_col6\" class=\"data row0 col6\" >-0.078120</td>\n",
       "      <td id=\"T_97135_row0_col7\" class=\"data row0 col7\" >0.121910</td>\n",
       "      <td id=\"T_97135_row0_col8\" class=\"data row0 col8\" >0.029190</td>\n",
       "      <td id=\"T_97135_row0_col9\" class=\"data row0 col9\" >0.146489</td>\n",
       "      <td id=\"T_97135_row0_col10\" class=\"data row0 col10\" >0.023633</td>\n",
       "      <td id=\"T_97135_row0_col11\" class=\"data row0 col11\" >0.256665</td>\n",
       "      <td id=\"T_97135_row0_col12\" class=\"data row0 col12\" >0.226493</td>\n",
       "      <td id=\"T_97135_row0_col13\" class=\"data row0 col13\" >-0.028235</td>\n",
       "      <td id=\"T_97135_row0_col14\" class=\"data row0 col14\" >-0.135281</td>\n",
       "      <td id=\"T_97135_row0_col15\" class=\"data row0 col15\" >0.061361</td>\n",
       "      <td id=\"T_97135_row0_col16\" class=\"data row0 col16\" >-0.240092</td>\n",
       "      <td id=\"T_97135_row0_col17\" class=\"data row0 col17\" >0.240166</td>\n",
       "      <td id=\"T_97135_row0_col18\" class=\"data row0 col18\" >-0.220575</td>\n",
       "      <td id=\"T_97135_row0_col19\" class=\"data row0 col19\" >-0.102890</td>\n",
       "      <td id=\"T_97135_row0_col20\" class=\"data row0 col20\" >-0.216872</td>\n",
       "      <td id=\"T_97135_row0_col21\" class=\"data row0 col21\" >-0.256514</td>\n",
       "      <td id=\"T_97135_row0_col22\" class=\"data row0 col22\" >-0.004804</td>\n",
       "      <td id=\"T_97135_row0_col23\" class=\"data row0 col23\" >0.017826</td>\n",
       "      <td id=\"T_97135_row0_col24\" class=\"data row0 col24\" >0.000972</td>\n",
       "      <td id=\"T_97135_row0_col25\" class=\"data row0 col25\" >-0.195800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row1\" class=\"row_heading level0 row1\" >CO2_room</th>\n",
       "      <td id=\"T_97135_row1_col0\" class=\"data row1 col0\" >0.925522</td>\n",
       "      <td id=\"T_97135_row1_col1\" class=\"data row1 col1\" >1.000000</td>\n",
       "      <td id=\"T_97135_row1_col2\" class=\"data row1 col2\" >-0.013242</td>\n",
       "      <td id=\"T_97135_row1_col3\" class=\"data row1 col3\" >-0.022244</td>\n",
       "      <td id=\"T_97135_row1_col4\" class=\"data row1 col4\" >0.241727</td>\n",
       "      <td id=\"T_97135_row1_col5\" class=\"data row1 col5\" >0.196714</td>\n",
       "      <td id=\"T_97135_row1_col6\" class=\"data row1 col6\" >-0.077395</td>\n",
       "      <td id=\"T_97135_row1_col7\" class=\"data row1 col7\" >0.108002</td>\n",
       "      <td id=\"T_97135_row1_col8\" class=\"data row1 col8\" >0.009194</td>\n",
       "      <td id=\"T_97135_row1_col9\" class=\"data row1 col9\" >0.115046</td>\n",
       "      <td id=\"T_97135_row1_col10\" class=\"data row1 col10\" >0.012565</td>\n",
       "      <td id=\"T_97135_row1_col11\" class=\"data row1 col11\" >0.242475</td>\n",
       "      <td id=\"T_97135_row1_col12\" class=\"data row1 col12\" >0.204212</td>\n",
       "      <td id=\"T_97135_row1_col13\" class=\"data row1 col13\" >-0.009462</td>\n",
       "      <td id=\"T_97135_row1_col14\" class=\"data row1 col14\" >-0.129085</td>\n",
       "      <td id=\"T_97135_row1_col15\" class=\"data row1 col15\" >0.056195</td>\n",
       "      <td id=\"T_97135_row1_col16\" class=\"data row1 col16\" >-0.259032</td>\n",
       "      <td id=\"T_97135_row1_col17\" class=\"data row1 col17\" >0.228068</td>\n",
       "      <td id=\"T_97135_row1_col18\" class=\"data row1 col18\" >-0.242740</td>\n",
       "      <td id=\"T_97135_row1_col19\" class=\"data row1 col19\" >-0.091499</td>\n",
       "      <td id=\"T_97135_row1_col20\" class=\"data row1 col20\" >-0.239317</td>\n",
       "      <td id=\"T_97135_row1_col21\" class=\"data row1 col21\" >-0.272055</td>\n",
       "      <td id=\"T_97135_row1_col22\" class=\"data row1 col22\" >0.011424</td>\n",
       "      <td id=\"T_97135_row1_col23\" class=\"data row1 col23\" >0.014045</td>\n",
       "      <td id=\"T_97135_row1_col24\" class=\"data row1 col24\" >0.000976</td>\n",
       "      <td id=\"T_97135_row1_col25\" class=\"data row1 col25\" >-0.216379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row2\" class=\"row_heading level0 row2\" >Relative_humidity_(dinning-room)</th>\n",
       "      <td id=\"T_97135_row2_col0\" class=\"data row2 col0\" >-0.004698</td>\n",
       "      <td id=\"T_97135_row2_col1\" class=\"data row2 col1\" >-0.013242</td>\n",
       "      <td id=\"T_97135_row2_col2\" class=\"data row2 col2\" >1.000000</td>\n",
       "      <td id=\"T_97135_row2_col3\" class=\"data row2 col3\" >0.931267</td>\n",
       "      <td id=\"T_97135_row2_col4\" class=\"data row2 col4\" >-0.046600</td>\n",
       "      <td id=\"T_97135_row2_col5\" class=\"data row2 col5\" >-0.017654</td>\n",
       "      <td id=\"T_97135_row2_col6\" class=\"data row2 col6\" >-0.081597</td>\n",
       "      <td id=\"T_97135_row2_col7\" class=\"data row2 col7\" >-0.052456</td>\n",
       "      <td id=\"T_97135_row2_col8\" class=\"data row2 col8\" >-0.197537</td>\n",
       "      <td id=\"T_97135_row2_col9\" class=\"data row2 col9\" >-0.100505</td>\n",
       "      <td id=\"T_97135_row2_col10\" class=\"data row2 col10\" >-0.016503</td>\n",
       "      <td id=\"T_97135_row2_col11\" class=\"data row2 col11\" >-0.057019</td>\n",
       "      <td id=\"T_97135_row2_col12\" class=\"data row2 col12\" >-0.045240</td>\n",
       "      <td id=\"T_97135_row2_col13\" class=\"data row2 col13\" >0.696973</td>\n",
       "      <td id=\"T_97135_row2_col14\" class=\"data row2 col14\" >-0.058968</td>\n",
       "      <td id=\"T_97135_row2_col15\" class=\"data row2 col15\" >-0.275193</td>\n",
       "      <td id=\"T_97135_row2_col16\" class=\"data row2 col16\" >0.115456</td>\n",
       "      <td id=\"T_97135_row2_col17\" class=\"data row2 col17\" >-0.258226</td>\n",
       "      <td id=\"T_97135_row2_col18\" class=\"data row2 col18\" >0.083177</td>\n",
       "      <td id=\"T_97135_row2_col19\" class=\"data row2 col19\" >0.057002</td>\n",
       "      <td id=\"T_97135_row2_col20\" class=\"data row2 col20\" >0.081235</td>\n",
       "      <td id=\"T_97135_row2_col21\" class=\"data row2 col21\" >0.126092</td>\n",
       "      <td id=\"T_97135_row2_col22\" class=\"data row2 col22\" >-0.259382</td>\n",
       "      <td id=\"T_97135_row2_col23\" class=\"data row2 col23\" >0.011194</td>\n",
       "      <td id=\"T_97135_row2_col24\" class=\"data row2 col24\" >-0.000469</td>\n",
       "      <td id=\"T_97135_row2_col25\" class=\"data row2 col25\" >0.073273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row3\" class=\"row_heading level0 row3\" >Relative_humidity_room</th>\n",
       "      <td id=\"T_97135_row3_col0\" class=\"data row3 col0\" >-0.027170</td>\n",
       "      <td id=\"T_97135_row3_col1\" class=\"data row3 col1\" >-0.022244</td>\n",
       "      <td id=\"T_97135_row3_col2\" class=\"data row3 col2\" >0.931267</td>\n",
       "      <td id=\"T_97135_row3_col3\" class=\"data row3 col3\" >1.000000</td>\n",
       "      <td id=\"T_97135_row3_col4\" class=\"data row3 col4\" >-0.116434</td>\n",
       "      <td id=\"T_97135_row3_col5\" class=\"data row3 col5\" >-0.092876</td>\n",
       "      <td id=\"T_97135_row3_col6\" class=\"data row3 col6\" >0.051322</td>\n",
       "      <td id=\"T_97135_row3_col7\" class=\"data row3 col7\" >-0.083595</td>\n",
       "      <td id=\"T_97135_row3_col8\" class=\"data row3 col8\" >-0.153276</td>\n",
       "      <td id=\"T_97135_row3_col9\" class=\"data row3 col9\" >-0.130920</td>\n",
       "      <td id=\"T_97135_row3_col10\" class=\"data row3 col10\" >-0.067384</td>\n",
       "      <td id=\"T_97135_row3_col11\" class=\"data row3 col11\" >-0.133493</td>\n",
       "      <td id=\"T_97135_row3_col12\" class=\"data row3 col12\" >-0.120310</td>\n",
       "      <td id=\"T_97135_row3_col13\" class=\"data row3 col13\" >0.809993</td>\n",
       "      <td id=\"T_97135_row3_col14\" class=\"data row3 col14\" >-0.103301</td>\n",
       "      <td id=\"T_97135_row3_col15\" class=\"data row3 col15\" >-0.417901</td>\n",
       "      <td id=\"T_97135_row3_col16\" class=\"data row3 col16\" >0.055625</td>\n",
       "      <td id=\"T_97135_row3_col17\" class=\"data row3 col17\" >-0.260071</td>\n",
       "      <td id=\"T_97135_row3_col18\" class=\"data row3 col18\" >0.018974</td>\n",
       "      <td id=\"T_97135_row3_col19\" class=\"data row3 col19\" >0.050301</td>\n",
       "      <td id=\"T_97135_row3_col20\" class=\"data row3 col20\" >0.017413</td>\n",
       "      <td id=\"T_97135_row3_col21\" class=\"data row3 col21\" >0.073061</td>\n",
       "      <td id=\"T_97135_row3_col22\" class=\"data row3 col22\" >-0.289126</td>\n",
       "      <td id=\"T_97135_row3_col23\" class=\"data row3 col23\" >-0.038387</td>\n",
       "      <td id=\"T_97135_row3_col24\" class=\"data row3 col24\" >-0.000602</td>\n",
       "      <td id=\"T_97135_row3_col25\" class=\"data row3 col25\" >0.006435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row4\" class=\"row_heading level0 row4\" >Lighting_(dinning-room)</th>\n",
       "      <td id=\"T_97135_row4_col0\" class=\"data row4 col0\" >0.255059</td>\n",
       "      <td id=\"T_97135_row4_col1\" class=\"data row4 col1\" >0.241727</td>\n",
       "      <td id=\"T_97135_row4_col2\" class=\"data row4 col2\" >-0.046600</td>\n",
       "      <td id=\"T_97135_row4_col3\" class=\"data row4 col3\" >-0.116434</td>\n",
       "      <td id=\"T_97135_row4_col4\" class=\"data row4 col4\" >1.000000</td>\n",
       "      <td id=\"T_97135_row4_col5\" class=\"data row4 col5\" >0.948650</td>\n",
       "      <td id=\"T_97135_row4_col6\" class=\"data row4 col6\" >-0.108220</td>\n",
       "      <td id=\"T_97135_row4_col7\" class=\"data row4 col7\" >0.631730</td>\n",
       "      <td id=\"T_97135_row4_col8\" class=\"data row4 col8\" >0.545034</td>\n",
       "      <td id=\"T_97135_row4_col9\" class=\"data row4 col9\" >0.426375</td>\n",
       "      <td id=\"T_97135_row4_col10\" class=\"data row4 col10\" >0.404444</td>\n",
       "      <td id=\"T_97135_row4_col11\" class=\"data row4 col11\" >0.949340</td>\n",
       "      <td id=\"T_97135_row4_col12\" class=\"data row4 col12\" >0.948145</td>\n",
       "      <td id=\"T_97135_row4_col13\" class=\"data row4 col13\" >-0.220635</td>\n",
       "      <td id=\"T_97135_row4_col14\" class=\"data row4 col14\" >0.045991</td>\n",
       "      <td id=\"T_97135_row4_col15\" class=\"data row4 col15\" >0.069264</td>\n",
       "      <td id=\"T_97135_row4_col16\" class=\"data row4 col16\" >-0.025871</td>\n",
       "      <td id=\"T_97135_row4_col17\" class=\"data row4 col17\" >0.049451</td>\n",
       "      <td id=\"T_97135_row4_col18\" class=\"data row4 col18\" >-0.020278</td>\n",
       "      <td id=\"T_97135_row4_col19\" class=\"data row4 col19\" >-0.021075</td>\n",
       "      <td id=\"T_97135_row4_col20\" class=\"data row4 col20\" >-0.019589</td>\n",
       "      <td id=\"T_97135_row4_col21\" class=\"data row4 col21\" >-0.037866</td>\n",
       "      <td id=\"T_97135_row4_col22\" class=\"data row4 col22\" >-0.040400</td>\n",
       "      <td id=\"T_97135_row4_col23\" class=\"data row4 col23\" >0.014259</td>\n",
       "      <td id=\"T_97135_row4_col24\" class=\"data row4 col24\" >0.008701</td>\n",
       "      <td id=\"T_97135_row4_col25\" class=\"data row4 col25\" >-0.006951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row5\" class=\"row_heading level0 row5\" >Lighting_room</th>\n",
       "      <td id=\"T_97135_row5_col0\" class=\"data row5 col0\" >0.214517</td>\n",
       "      <td id=\"T_97135_row5_col1\" class=\"data row5 col1\" >0.196714</td>\n",
       "      <td id=\"T_97135_row5_col2\" class=\"data row5 col2\" >-0.017654</td>\n",
       "      <td id=\"T_97135_row5_col3\" class=\"data row5 col3\" >-0.092876</td>\n",
       "      <td id=\"T_97135_row5_col4\" class=\"data row5 col4\" >0.948650</td>\n",
       "      <td id=\"T_97135_row5_col5\" class=\"data row5 col5\" >1.000000</td>\n",
       "      <td id=\"T_97135_row5_col6\" class=\"data row5 col6\" >-0.112234</td>\n",
       "      <td id=\"T_97135_row5_col7\" class=\"data row5 col7\" >0.629562</td>\n",
       "      <td id=\"T_97135_row5_col8\" class=\"data row5 col8\" >0.475906</td>\n",
       "      <td id=\"T_97135_row5_col9\" class=\"data row5 col9\" >0.315060</td>\n",
       "      <td id=\"T_97135_row5_col10\" class=\"data row5 col10\" >0.565679</td>\n",
       "      <td id=\"T_97135_row5_col11\" class=\"data row5 col11\" >0.965505</td>\n",
       "      <td id=\"T_97135_row5_col12\" class=\"data row5 col12\" >0.932237</td>\n",
       "      <td id=\"T_97135_row5_col13\" class=\"data row5 col13\" >-0.182360</td>\n",
       "      <td id=\"T_97135_row5_col14\" class=\"data row5 col14\" >0.051008</td>\n",
       "      <td id=\"T_97135_row5_col15\" class=\"data row5 col15\" >0.002253</td>\n",
       "      <td id=\"T_97135_row5_col16\" class=\"data row5 col16\" >-0.008809</td>\n",
       "      <td id=\"T_97135_row5_col17\" class=\"data row5 col17\" >0.032314</td>\n",
       "      <td id=\"T_97135_row5_col18\" class=\"data row5 col18\" >-0.004483</td>\n",
       "      <td id=\"T_97135_row5_col19\" class=\"data row5 col19\" >0.009603</td>\n",
       "      <td id=\"T_97135_row5_col20\" class=\"data row5 col20\" >-0.004759</td>\n",
       "      <td id=\"T_97135_row5_col21\" class=\"data row5 col21\" >-0.014375</td>\n",
       "      <td id=\"T_97135_row5_col22\" class=\"data row5 col22\" >-0.017395</td>\n",
       "      <td id=\"T_97135_row5_col23\" class=\"data row5 col23\" >-0.025948</td>\n",
       "      <td id=\"T_97135_row5_col24\" class=\"data row5 col24\" >0.004786</td>\n",
       "      <td id=\"T_97135_row5_col25\" class=\"data row5 col25\" >-0.002783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row6\" class=\"row_heading level0 row6\" >Meteo_Rain</th>\n",
       "      <td id=\"T_97135_row6_col0\" class=\"data row6 col0\" >-0.078120</td>\n",
       "      <td id=\"T_97135_row6_col1\" class=\"data row6 col1\" >-0.077395</td>\n",
       "      <td id=\"T_97135_row6_col2\" class=\"data row6 col2\" >-0.081597</td>\n",
       "      <td id=\"T_97135_row6_col3\" class=\"data row6 col3\" >0.051322</td>\n",
       "      <td id=\"T_97135_row6_col4\" class=\"data row6 col4\" >-0.108220</td>\n",
       "      <td id=\"T_97135_row6_col5\" class=\"data row6 col5\" >-0.112234</td>\n",
       "      <td id=\"T_97135_row6_col6\" class=\"data row6 col6\" >1.000000</td>\n",
       "      <td id=\"T_97135_row6_col7\" class=\"data row6 col7\" >-0.005661</td>\n",
       "      <td id=\"T_97135_row6_col8\" class=\"data row6 col8\" >0.239575</td>\n",
       "      <td id=\"T_97135_row6_col9\" class=\"data row6 col9\" >-0.116674</td>\n",
       "      <td id=\"T_97135_row6_col10\" class=\"data row6 col10\" >-0.105728</td>\n",
       "      <td id=\"T_97135_row6_col11\" class=\"data row6 col11\" >-0.137075</td>\n",
       "      <td id=\"T_97135_row6_col12\" class=\"data row6 col12\" >-0.139149</td>\n",
       "      <td id=\"T_97135_row6_col13\" class=\"data row6 col13\" >0.294056</td>\n",
       "      <td id=\"T_97135_row6_col14\" class=\"data row6 col14\" >-0.172599</td>\n",
       "      <td id=\"T_97135_row6_col15\" class=\"data row6 col15\" >-0.262621</td>\n",
       "      <td id=\"T_97135_row6_col16\" class=\"data row6 col16\" >-0.053974</td>\n",
       "      <td id=\"T_97135_row6_col17\" class=\"data row6 col17\" >-0.009263</td>\n",
       "      <td id=\"T_97135_row6_col18\" class=\"data row6 col18\" >-0.059673</td>\n",
       "      <td id=\"T_97135_row6_col19\" class=\"data row6 col19\" >-0.190405</td>\n",
       "      <td id=\"T_97135_row6_col20\" class=\"data row6 col20\" >-0.053799</td>\n",
       "      <td id=\"T_97135_row6_col21\" class=\"data row6 col21\" >-0.049138</td>\n",
       "      <td id=\"T_97135_row6_col22\" class=\"data row6 col22\" >-0.043169</td>\n",
       "      <td id=\"T_97135_row6_col23\" class=\"data row6 col23\" >0.058575</td>\n",
       "      <td id=\"T_97135_row6_col24\" class=\"data row6 col24\" >-0.007725</td>\n",
       "      <td id=\"T_97135_row6_col25\" class=\"data row6 col25\" >-0.050052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row7\" class=\"row_heading level0 row7\" >Meteo_Sun_dusk</th>\n",
       "      <td id=\"T_97135_row7_col0\" class=\"data row7 col0\" >0.121910</td>\n",
       "      <td id=\"T_97135_row7_col1\" class=\"data row7 col1\" >0.108002</td>\n",
       "      <td id=\"T_97135_row7_col2\" class=\"data row7 col2\" >-0.052456</td>\n",
       "      <td id=\"T_97135_row7_col3\" class=\"data row7 col3\" >-0.083595</td>\n",
       "      <td id=\"T_97135_row7_col4\" class=\"data row7 col4\" >0.631730</td>\n",
       "      <td id=\"T_97135_row7_col5\" class=\"data row7 col5\" >0.629562</td>\n",
       "      <td id=\"T_97135_row7_col6\" class=\"data row7 col6\" >-0.005661</td>\n",
       "      <td id=\"T_97135_row7_col7\" class=\"data row7 col7\" >1.000000</td>\n",
       "      <td id=\"T_97135_row7_col8\" class=\"data row7 col8\" >0.541814</td>\n",
       "      <td id=\"T_97135_row7_col9\" class=\"data row7 col9\" >0.554923</td>\n",
       "      <td id=\"T_97135_row7_col10\" class=\"data row7 col10\" >0.544312</td>\n",
       "      <td id=\"T_97135_row7_col11\" class=\"data row7 col11\" >0.653682</td>\n",
       "      <td id=\"T_97135_row7_col12\" class=\"data row7 col12\" >0.711831</td>\n",
       "      <td id=\"T_97135_row7_col13\" class=\"data row7 col13\" >-0.214353</td>\n",
       "      <td id=\"T_97135_row7_col14\" class=\"data row7 col14\" >0.008430</td>\n",
       "      <td id=\"T_97135_row7_col15\" class=\"data row7 col15\" >0.068897</td>\n",
       "      <td id=\"T_97135_row7_col16\" class=\"data row7 col16\" >-0.004417</td>\n",
       "      <td id=\"T_97135_row7_col17\" class=\"data row7 col17\" >-0.003491</td>\n",
       "      <td id=\"T_97135_row7_col18\" class=\"data row7 col18\" >-0.005299</td>\n",
       "      <td id=\"T_97135_row7_col19\" class=\"data row7 col19\" >-0.010774</td>\n",
       "      <td id=\"T_97135_row7_col20\" class=\"data row7 col20\" >-0.004961</td>\n",
       "      <td id=\"T_97135_row7_col21\" class=\"data row7 col21\" >-0.001628</td>\n",
       "      <td id=\"T_97135_row7_col22\" class=\"data row7 col22\" >0.006315</td>\n",
       "      <td id=\"T_97135_row7_col23\" class=\"data row7 col23\" >0.053063</td>\n",
       "      <td id=\"T_97135_row7_col24\" class=\"data row7 col24\" >-0.007786</td>\n",
       "      <td id=\"T_97135_row7_col25\" class=\"data row7 col25\" >-0.003447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row8\" class=\"row_heading level0 row8\" >Meteo_Wind</th>\n",
       "      <td id=\"T_97135_row8_col0\" class=\"data row8 col0\" >0.029190</td>\n",
       "      <td id=\"T_97135_row8_col1\" class=\"data row8 col1\" >0.009194</td>\n",
       "      <td id=\"T_97135_row8_col2\" class=\"data row8 col2\" >-0.197537</td>\n",
       "      <td id=\"T_97135_row8_col3\" class=\"data row8 col3\" >-0.153276</td>\n",
       "      <td id=\"T_97135_row8_col4\" class=\"data row8 col4\" >0.545034</td>\n",
       "      <td id=\"T_97135_row8_col5\" class=\"data row8 col5\" >0.475906</td>\n",
       "      <td id=\"T_97135_row8_col6\" class=\"data row8 col6\" >0.239575</td>\n",
       "      <td id=\"T_97135_row8_col7\" class=\"data row8 col7\" >0.541814</td>\n",
       "      <td id=\"T_97135_row8_col8\" class=\"data row8 col8\" >1.000000</td>\n",
       "      <td id=\"T_97135_row8_col9\" class=\"data row8 col9\" >0.619047</td>\n",
       "      <td id=\"T_97135_row8_col10\" class=\"data row8 col10\" >0.065801</td>\n",
       "      <td id=\"T_97135_row8_col11\" class=\"data row8 col11\" >0.475860</td>\n",
       "      <td id=\"T_97135_row8_col12\" class=\"data row8 col12\" >0.618184</td>\n",
       "      <td id=\"T_97135_row8_col13\" class=\"data row8 col13\" >-0.292395</td>\n",
       "      <td id=\"T_97135_row8_col14\" class=\"data row8 col14\" >-0.052182</td>\n",
       "      <td id=\"T_97135_row8_col15\" class=\"data row8 col15\" >0.220667</td>\n",
       "      <td id=\"T_97135_row8_col16\" class=\"data row8 col16\" >0.108638</td>\n",
       "      <td id=\"T_97135_row8_col17\" class=\"data row8 col17\" >-0.087515</td>\n",
       "      <td id=\"T_97135_row8_col18\" class=\"data row8 col18\" >0.102875</td>\n",
       "      <td id=\"T_97135_row8_col19\" class=\"data row8 col19\" >-0.093561</td>\n",
       "      <td id=\"T_97135_row8_col20\" class=\"data row8 col20\" >0.105391</td>\n",
       "      <td id=\"T_97135_row8_col21\" class=\"data row8 col21\" >0.118377</td>\n",
       "      <td id=\"T_97135_row8_col22\" class=\"data row8 col22\" >-0.076702</td>\n",
       "      <td id=\"T_97135_row8_col23\" class=\"data row8 col23\" >0.217681</td>\n",
       "      <td id=\"T_97135_row8_col24\" class=\"data row8 col24\" >-0.003101</td>\n",
       "      <td id=\"T_97135_row8_col25\" class=\"data row8 col25\" >0.102235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row9\" class=\"row_heading level0 row9\" >Meteo_Sun_light_in_west_facade</th>\n",
       "      <td id=\"T_97135_row9_col0\" class=\"data row9 col0\" >0.146489</td>\n",
       "      <td id=\"T_97135_row9_col1\" class=\"data row9 col1\" >0.115046</td>\n",
       "      <td id=\"T_97135_row9_col2\" class=\"data row9 col2\" >-0.100505</td>\n",
       "      <td id=\"T_97135_row9_col3\" class=\"data row9 col3\" >-0.130920</td>\n",
       "      <td id=\"T_97135_row9_col4\" class=\"data row9 col4\" >0.426375</td>\n",
       "      <td id=\"T_97135_row9_col5\" class=\"data row9 col5\" >0.315060</td>\n",
       "      <td id=\"T_97135_row9_col6\" class=\"data row9 col6\" >-0.116674</td>\n",
       "      <td id=\"T_97135_row9_col7\" class=\"data row9 col7\" >0.554923</td>\n",
       "      <td id=\"T_97135_row9_col8\" class=\"data row9 col8\" >0.619047</td>\n",
       "      <td id=\"T_97135_row9_col9\" class=\"data row9 col9\" >1.000000</td>\n",
       "      <td id=\"T_97135_row9_col10\" class=\"data row9 col10\" >0.111847</td>\n",
       "      <td id=\"T_97135_row9_col11\" class=\"data row9 col11\" >0.416614</td>\n",
       "      <td id=\"T_97135_row9_col12\" class=\"data row9 col12\" >0.601980</td>\n",
       "      <td id=\"T_97135_row9_col13\" class=\"data row9 col13\" >-0.359863</td>\n",
       "      <td id=\"T_97135_row9_col14\" class=\"data row9 col14\" >0.033980</td>\n",
       "      <td id=\"T_97135_row9_col15\" class=\"data row9 col15\" >0.335288</td>\n",
       "      <td id=\"T_97135_row9_col16\" class=\"data row9 col16\" >0.008222</td>\n",
       "      <td id=\"T_97135_row9_col17\" class=\"data row9 col17\" >0.020483</td>\n",
       "      <td id=\"T_97135_row9_col18\" class=\"data row9 col18\" >0.011721</td>\n",
       "      <td id=\"T_97135_row9_col19\" class=\"data row9 col19\" >-0.038201</td>\n",
       "      <td id=\"T_97135_row9_col20\" class=\"data row9 col20\" >0.012834</td>\n",
       "      <td id=\"T_97135_row9_col21\" class=\"data row9 col21\" >-0.000028</td>\n",
       "      <td id=\"T_97135_row9_col22\" class=\"data row9 col22\" >-0.057237</td>\n",
       "      <td id=\"T_97135_row9_col23\" class=\"data row9 col23\" >0.175101</td>\n",
       "      <td id=\"T_97135_row9_col24\" class=\"data row9 col24\" >-0.004690</td>\n",
       "      <td id=\"T_97135_row9_col25\" class=\"data row9 col25\" >0.022096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row10\" class=\"row_heading level0 row10\" >Meteo_Sun_light_in_east_facade</th>\n",
       "      <td id=\"T_97135_row10_col0\" class=\"data row10 col0\" >0.023633</td>\n",
       "      <td id=\"T_97135_row10_col1\" class=\"data row10 col1\" >0.012565</td>\n",
       "      <td id=\"T_97135_row10_col2\" class=\"data row10 col2\" >-0.016503</td>\n",
       "      <td id=\"T_97135_row10_col3\" class=\"data row10 col3\" >-0.067384</td>\n",
       "      <td id=\"T_97135_row10_col4\" class=\"data row10 col4\" >0.404444</td>\n",
       "      <td id=\"T_97135_row10_col5\" class=\"data row10 col5\" >0.565679</td>\n",
       "      <td id=\"T_97135_row10_col6\" class=\"data row10 col6\" >-0.105728</td>\n",
       "      <td id=\"T_97135_row10_col7\" class=\"data row10 col7\" >0.544312</td>\n",
       "      <td id=\"T_97135_row10_col8\" class=\"data row10 col8\" >0.065801</td>\n",
       "      <td id=\"T_97135_row10_col9\" class=\"data row10 col9\" >0.111847</td>\n",
       "      <td id=\"T_97135_row10_col10\" class=\"data row10 col10\" >1.000000</td>\n",
       "      <td id=\"T_97135_row10_col11\" class=\"data row10 col11\" >0.609949</td>\n",
       "      <td id=\"T_97135_row10_col12\" class=\"data row10 col12\" >0.490077</td>\n",
       "      <td id=\"T_97135_row10_col13\" class=\"data row10 col13\" >-0.060787</td>\n",
       "      <td id=\"T_97135_row10_col14\" class=\"data row10 col14\" >0.082131</td>\n",
       "      <td id=\"T_97135_row10_col15\" class=\"data row10 col15\" >-0.269034</td>\n",
       "      <td id=\"T_97135_row10_col16\" class=\"data row10 col16\" >-0.016034</td>\n",
       "      <td id=\"T_97135_row10_col17\" class=\"data row10 col17\" >0.057416</td>\n",
       "      <td id=\"T_97135_row10_col18\" class=\"data row10 col18\" >-0.008315</td>\n",
       "      <td id=\"T_97135_row10_col19\" class=\"data row10 col19\" >0.046686</td>\n",
       "      <td id=\"T_97135_row10_col20\" class=\"data row10 col20\" >-0.009691</td>\n",
       "      <td id=\"T_97135_row10_col21\" class=\"data row10 col21\" >-0.022178</td>\n",
       "      <td id=\"T_97135_row10_col22\" class=\"data row10 col22\" >0.025335</td>\n",
       "      <td id=\"T_97135_row10_col23\" class=\"data row10 col23\" >-0.161038</td>\n",
       "      <td id=\"T_97135_row10_col24\" class=\"data row10 col24\" >0.004136</td>\n",
       "      <td id=\"T_97135_row10_col25\" class=\"data row10 col25\" >-0.012571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row11\" class=\"row_heading level0 row11\" >Meteo_Sun_light_in_south_facade</th>\n",
       "      <td id=\"T_97135_row11_col0\" class=\"data row11 col0\" >0.256665</td>\n",
       "      <td id=\"T_97135_row11_col1\" class=\"data row11 col1\" >0.242475</td>\n",
       "      <td id=\"T_97135_row11_col2\" class=\"data row11 col2\" >-0.057019</td>\n",
       "      <td id=\"T_97135_row11_col3\" class=\"data row11 col3\" >-0.133493</td>\n",
       "      <td id=\"T_97135_row11_col4\" class=\"data row11 col4\" >0.949340</td>\n",
       "      <td id=\"T_97135_row11_col5\" class=\"data row11 col5\" >0.965505</td>\n",
       "      <td id=\"T_97135_row11_col6\" class=\"data row11 col6\" >-0.137075</td>\n",
       "      <td id=\"T_97135_row11_col7\" class=\"data row11 col7\" >0.653682</td>\n",
       "      <td id=\"T_97135_row11_col8\" class=\"data row11 col8\" >0.475860</td>\n",
       "      <td id=\"T_97135_row11_col9\" class=\"data row11 col9\" >0.416614</td>\n",
       "      <td id=\"T_97135_row11_col10\" class=\"data row11 col10\" >0.609949</td>\n",
       "      <td id=\"T_97135_row11_col11\" class=\"data row11 col11\" >1.000000</td>\n",
       "      <td id=\"T_97135_row11_col12\" class=\"data row11 col12\" >0.948131</td>\n",
       "      <td id=\"T_97135_row11_col13\" class=\"data row11 col13\" >-0.215892</td>\n",
       "      <td id=\"T_97135_row11_col14\" class=\"data row11 col14\" >0.067982</td>\n",
       "      <td id=\"T_97135_row11_col15\" class=\"data row11 col15\" >0.000072</td>\n",
       "      <td id=\"T_97135_row11_col16\" class=\"data row11 col16\" >-0.068185</td>\n",
       "      <td id=\"T_97135_row11_col17\" class=\"data row11 col17\" >0.093603</td>\n",
       "      <td id=\"T_97135_row11_col18\" class=\"data row11 col18\" >-0.058856</td>\n",
       "      <td id=\"T_97135_row11_col19\" class=\"data row11 col19\" >0.006718</td>\n",
       "      <td id=\"T_97135_row11_col20\" class=\"data row11 col20\" >-0.058892</td>\n",
       "      <td id=\"T_97135_row11_col21\" class=\"data row11 col21\" >-0.082974</td>\n",
       "      <td id=\"T_97135_row11_col22\" class=\"data row11 col22\" >-0.024887</td>\n",
       "      <td id=\"T_97135_row11_col23\" class=\"data row11 col23\" >-0.025020</td>\n",
       "      <td id=\"T_97135_row11_col24\" class=\"data row11 col24\" >0.003957</td>\n",
       "      <td id=\"T_97135_row11_col25\" class=\"data row11 col25\" >-0.043801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row12\" class=\"row_heading level0 row12\" >Meteo_Sun_irradiance</th>\n",
       "      <td id=\"T_97135_row12_col0\" class=\"data row12 col0\" >0.226493</td>\n",
       "      <td id=\"T_97135_row12_col1\" class=\"data row12 col1\" >0.204212</td>\n",
       "      <td id=\"T_97135_row12_col2\" class=\"data row12 col2\" >-0.045240</td>\n",
       "      <td id=\"T_97135_row12_col3\" class=\"data row12 col3\" >-0.120310</td>\n",
       "      <td id=\"T_97135_row12_col4\" class=\"data row12 col4\" >0.948145</td>\n",
       "      <td id=\"T_97135_row12_col5\" class=\"data row12 col5\" >0.932237</td>\n",
       "      <td id=\"T_97135_row12_col6\" class=\"data row12 col6\" >-0.139149</td>\n",
       "      <td id=\"T_97135_row12_col7\" class=\"data row12 col7\" >0.711831</td>\n",
       "      <td id=\"T_97135_row12_col8\" class=\"data row12 col8\" >0.618184</td>\n",
       "      <td id=\"T_97135_row12_col9\" class=\"data row12 col9\" >0.601980</td>\n",
       "      <td id=\"T_97135_row12_col10\" class=\"data row12 col10\" >0.490077</td>\n",
       "      <td id=\"T_97135_row12_col11\" class=\"data row12 col11\" >0.948131</td>\n",
       "      <td id=\"T_97135_row12_col12\" class=\"data row12 col12\" >1.000000</td>\n",
       "      <td id=\"T_97135_row12_col13\" class=\"data row12 col13\" >-0.282847</td>\n",
       "      <td id=\"T_97135_row12_col14\" class=\"data row12 col14\" >0.051648</td>\n",
       "      <td id=\"T_97135_row12_col15\" class=\"data row12 col15\" >0.123390</td>\n",
       "      <td id=\"T_97135_row12_col16\" class=\"data row12 col16\" >0.013012</td>\n",
       "      <td id=\"T_97135_row12_col17\" class=\"data row12 col17\" >0.021265</td>\n",
       "      <td id=\"T_97135_row12_col18\" class=\"data row12 col18\" >0.017197</td>\n",
       "      <td id=\"T_97135_row12_col19\" class=\"data row12 col19\" >-0.011760</td>\n",
       "      <td id=\"T_97135_row12_col20\" class=\"data row12 col20\" >0.017501</td>\n",
       "      <td id=\"T_97135_row12_col21\" class=\"data row12 col21\" >0.006892</td>\n",
       "      <td id=\"T_97135_row12_col22\" class=\"data row12 col22\" >-0.029101</td>\n",
       "      <td id=\"T_97135_row12_col23\" class=\"data row12 col23\" >0.033625</td>\n",
       "      <td id=\"T_97135_row12_col24\" class=\"data row12 col24\" >0.002627</td>\n",
       "      <td id=\"T_97135_row12_col25\" class=\"data row12 col25\" >0.020612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row13\" class=\"row_heading level0 row13\" >Outdoor_relative_humidity_Sensor</th>\n",
       "      <td id=\"T_97135_row13_col0\" class=\"data row13 col0\" >-0.028235</td>\n",
       "      <td id=\"T_97135_row13_col1\" class=\"data row13 col1\" >-0.009462</td>\n",
       "      <td id=\"T_97135_row13_col2\" class=\"data row13 col2\" >0.696973</td>\n",
       "      <td id=\"T_97135_row13_col3\" class=\"data row13 col3\" >0.809993</td>\n",
       "      <td id=\"T_97135_row13_col4\" class=\"data row13 col4\" >-0.220635</td>\n",
       "      <td id=\"T_97135_row13_col5\" class=\"data row13 col5\" >-0.182360</td>\n",
       "      <td id=\"T_97135_row13_col6\" class=\"data row13 col6\" >0.294056</td>\n",
       "      <td id=\"T_97135_row13_col7\" class=\"data row13 col7\" >-0.214353</td>\n",
       "      <td id=\"T_97135_row13_col8\" class=\"data row13 col8\" >-0.292395</td>\n",
       "      <td id=\"T_97135_row13_col9\" class=\"data row13 col9\" >-0.359863</td>\n",
       "      <td id=\"T_97135_row13_col10\" class=\"data row13 col10\" >-0.060787</td>\n",
       "      <td id=\"T_97135_row13_col11\" class=\"data row13 col11\" >-0.215892</td>\n",
       "      <td id=\"T_97135_row13_col12\" class=\"data row13 col12\" >-0.282847</td>\n",
       "      <td id=\"T_97135_row13_col13\" class=\"data row13 col13\" >1.000000</td>\n",
       "      <td id=\"T_97135_row13_col14\" class=\"data row13 col14\" >-0.228048</td>\n",
       "      <td id=\"T_97135_row13_col15\" class=\"data row13 col15\" >-0.549681</td>\n",
       "      <td id=\"T_97135_row13_col16\" class=\"data row13 col16\" >-0.077643</td>\n",
       "      <td id=\"T_97135_row13_col17\" class=\"data row13 col17\" >-0.228580</td>\n",
       "      <td id=\"T_97135_row13_col18\" class=\"data row13 col18\" >-0.118636</td>\n",
       "      <td id=\"T_97135_row13_col19\" class=\"data row13 col19\" >-0.057800</td>\n",
       "      <td id=\"T_97135_row13_col20\" class=\"data row13 col20\" >-0.116571</td>\n",
       "      <td id=\"T_97135_row13_col21\" class=\"data row13 col21\" >-0.065641</td>\n",
       "      <td id=\"T_97135_row13_col22\" class=\"data row13 col22\" >-0.233745</td>\n",
       "      <td id=\"T_97135_row13_col23\" class=\"data row13 col23\" >-0.155185</td>\n",
       "      <td id=\"T_97135_row13_col24\" class=\"data row13 col24\" >0.000386</td>\n",
       "      <td id=\"T_97135_row13_col25\" class=\"data row13 col25\" >-0.107818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row14\" class=\"row_heading level0 row14\" >Day_of_the_week</th>\n",
       "      <td id=\"T_97135_row14_col0\" class=\"data row14 col0\" >-0.135281</td>\n",
       "      <td id=\"T_97135_row14_col1\" class=\"data row14 col1\" >-0.129085</td>\n",
       "      <td id=\"T_97135_row14_col2\" class=\"data row14 col2\" >-0.058968</td>\n",
       "      <td id=\"T_97135_row14_col3\" class=\"data row14 col3\" >-0.103301</td>\n",
       "      <td id=\"T_97135_row14_col4\" class=\"data row14 col4\" >0.045991</td>\n",
       "      <td id=\"T_97135_row14_col5\" class=\"data row14 col5\" >0.051008</td>\n",
       "      <td id=\"T_97135_row14_col6\" class=\"data row14 col6\" >-0.172599</td>\n",
       "      <td id=\"T_97135_row14_col7\" class=\"data row14 col7\" >0.008430</td>\n",
       "      <td id=\"T_97135_row14_col8\" class=\"data row14 col8\" >-0.052182</td>\n",
       "      <td id=\"T_97135_row14_col9\" class=\"data row14 col9\" >0.033980</td>\n",
       "      <td id=\"T_97135_row14_col10\" class=\"data row14 col10\" >0.082131</td>\n",
       "      <td id=\"T_97135_row14_col11\" class=\"data row14 col11\" >0.067982</td>\n",
       "      <td id=\"T_97135_row14_col12\" class=\"data row14 col12\" >0.051648</td>\n",
       "      <td id=\"T_97135_row14_col13\" class=\"data row14 col13\" >-0.228048</td>\n",
       "      <td id=\"T_97135_row14_col14\" class=\"data row14 col14\" >1.000000</td>\n",
       "      <td id=\"T_97135_row14_col15\" class=\"data row14 col15\" >0.016517</td>\n",
       "      <td id=\"T_97135_row14_col16\" class=\"data row14 col16\" >-0.087794</td>\n",
       "      <td id=\"T_97135_row14_col17\" class=\"data row14 col17\" >0.085064</td>\n",
       "      <td id=\"T_97135_row14_col18\" class=\"data row14 col18\" >-0.081838</td>\n",
       "      <td id=\"T_97135_row14_col19\" class=\"data row14 col19\" >0.521230</td>\n",
       "      <td id=\"T_97135_row14_col20\" class=\"data row14 col20\" >-0.097232</td>\n",
       "      <td id=\"T_97135_row14_col21\" class=\"data row14 col21\" >-0.046542</td>\n",
       "      <td id=\"T_97135_row14_col22\" class=\"data row14 col22\" >0.193919</td>\n",
       "      <td id=\"T_97135_row14_col23\" class=\"data row14 col23\" >-0.008617</td>\n",
       "      <td id=\"T_97135_row14_col24\" class=\"data row14 col24\" >-0.000016</td>\n",
       "      <td id=\"T_97135_row14_col25\" class=\"data row14 col25\" >-0.111628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row15\" class=\"row_heading level0 row15\" >Indoor_temperature_room</th>\n",
       "      <td id=\"T_97135_row15_col0\" class=\"data row15 col0\" >0.061361</td>\n",
       "      <td id=\"T_97135_row15_col1\" class=\"data row15 col1\" >0.056195</td>\n",
       "      <td id=\"T_97135_row15_col2\" class=\"data row15 col2\" >-0.275193</td>\n",
       "      <td id=\"T_97135_row15_col3\" class=\"data row15 col3\" >-0.417901</td>\n",
       "      <td id=\"T_97135_row15_col4\" class=\"data row15 col4\" >0.069264</td>\n",
       "      <td id=\"T_97135_row15_col5\" class=\"data row15 col5\" >0.002253</td>\n",
       "      <td id=\"T_97135_row15_col6\" class=\"data row15 col6\" >-0.262621</td>\n",
       "      <td id=\"T_97135_row15_col7\" class=\"data row15 col7\" >0.068897</td>\n",
       "      <td id=\"T_97135_row15_col8\" class=\"data row15 col8\" >0.220667</td>\n",
       "      <td id=\"T_97135_row15_col9\" class=\"data row15 col9\" >0.335288</td>\n",
       "      <td id=\"T_97135_row15_col10\" class=\"data row15 col10\" >-0.269034</td>\n",
       "      <td id=\"T_97135_row15_col11\" class=\"data row15 col11\" >0.000072</td>\n",
       "      <td id=\"T_97135_row15_col12\" class=\"data row15 col12\" >0.123390</td>\n",
       "      <td id=\"T_97135_row15_col13\" class=\"data row15 col13\" >-0.549681</td>\n",
       "      <td id=\"T_97135_row15_col14\" class=\"data row15 col14\" >0.016517</td>\n",
       "      <td id=\"T_97135_row15_col15\" class=\"data row15 col15\" >1.000000</td>\n",
       "      <td id=\"T_97135_row15_col16\" class=\"data row15 col16\" >0.129906</td>\n",
       "      <td id=\"T_97135_row15_col17\" class=\"data row15 col17\" >-0.157611</td>\n",
       "      <td id=\"T_97135_row15_col18\" class=\"data row15 col18\" >0.115979</td>\n",
       "      <td id=\"T_97135_row15_col19\" class=\"data row15 col19\" >0.164398</td>\n",
       "      <td id=\"T_97135_row15_col20\" class=\"data row15 col20\" >0.110726</td>\n",
       "      <td id=\"T_97135_row15_col21\" class=\"data row15 col21\" >0.162465</td>\n",
       "      <td id=\"T_97135_row15_col22\" class=\"data row15 col22\" >0.199432</td>\n",
       "      <td id=\"T_97135_row15_col23\" class=\"data row15 col23\" >0.417876</td>\n",
       "      <td id=\"T_97135_row15_col24\" class=\"data row15 col24\" >-0.000388</td>\n",
       "      <td id=\"T_97135_row15_col25\" class=\"data row15 col25\" >0.079934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row16\" class=\"row_heading level0 row16\" >DateTime_month</th>\n",
       "      <td id=\"T_97135_row16_col0\" class=\"data row16 col0\" >-0.240092</td>\n",
       "      <td id=\"T_97135_row16_col1\" class=\"data row16 col1\" >-0.259032</td>\n",
       "      <td id=\"T_97135_row16_col2\" class=\"data row16 col2\" >0.115456</td>\n",
       "      <td id=\"T_97135_row16_col3\" class=\"data row16 col3\" >0.055625</td>\n",
       "      <td id=\"T_97135_row16_col4\" class=\"data row16 col4\" >-0.025871</td>\n",
       "      <td id=\"T_97135_row16_col5\" class=\"data row16 col5\" >-0.008809</td>\n",
       "      <td id=\"T_97135_row16_col6\" class=\"data row16 col6\" >-0.053974</td>\n",
       "      <td id=\"T_97135_row16_col7\" class=\"data row16 col7\" >-0.004417</td>\n",
       "      <td id=\"T_97135_row16_col8\" class=\"data row16 col8\" >0.108638</td>\n",
       "      <td id=\"T_97135_row16_col9\" class=\"data row16 col9\" >0.008222</td>\n",
       "      <td id=\"T_97135_row16_col10\" class=\"data row16 col10\" >-0.016034</td>\n",
       "      <td id=\"T_97135_row16_col11\" class=\"data row16 col11\" >-0.068185</td>\n",
       "      <td id=\"T_97135_row16_col12\" class=\"data row16 col12\" >0.013012</td>\n",
       "      <td id=\"T_97135_row16_col13\" class=\"data row16 col13\" >-0.077643</td>\n",
       "      <td id=\"T_97135_row16_col14\" class=\"data row16 col14\" >-0.087794</td>\n",
       "      <td id=\"T_97135_row16_col15\" class=\"data row16 col15\" >0.129906</td>\n",
       "      <td id=\"T_97135_row16_col16\" class=\"data row16 col16\" >1.000000</td>\n",
       "      <td id=\"T_97135_row16_col17\" class=\"data row16 col17\" >-0.522260</td>\n",
       "      <td id=\"T_97135_row16_col18\" class=\"data row16 col18\" >0.991482</td>\n",
       "      <td id=\"T_97135_row16_col19\" class=\"data row16 col19\" >-0.076448</td>\n",
       "      <td id=\"T_97135_row16_col20\" class=\"data row16 col20\" >0.990993</td>\n",
       "      <td id=\"T_97135_row16_col21\" class=\"data row16 col21\" >0.965734</td>\n",
       "      <td id=\"T_97135_row16_col22\" class=\"data row16 col22\" >-0.082240</td>\n",
       "      <td id=\"T_97135_row16_col23\" class=\"data row16 col23\" >-0.045647</td>\n",
       "      <td id=\"T_97135_row16_col24\" class=\"data row16 col24\" >-0.001779</td>\n",
       "      <td id=\"T_97135_row16_col25\" class=\"data row16 col25\" >0.950836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row17\" class=\"row_heading level0 row17\" >DateTime_day</th>\n",
       "      <td id=\"T_97135_row17_col0\" class=\"data row17 col0\" >0.240166</td>\n",
       "      <td id=\"T_97135_row17_col1\" class=\"data row17 col1\" >0.228068</td>\n",
       "      <td id=\"T_97135_row17_col2\" class=\"data row17 col2\" >-0.258226</td>\n",
       "      <td id=\"T_97135_row17_col3\" class=\"data row17 col3\" >-0.260071</td>\n",
       "      <td id=\"T_97135_row17_col4\" class=\"data row17 col4\" >0.049451</td>\n",
       "      <td id=\"T_97135_row17_col5\" class=\"data row17 col5\" >0.032314</td>\n",
       "      <td id=\"T_97135_row17_col6\" class=\"data row17 col6\" >-0.009263</td>\n",
       "      <td id=\"T_97135_row17_col7\" class=\"data row17 col7\" >-0.003491</td>\n",
       "      <td id=\"T_97135_row17_col8\" class=\"data row17 col8\" >-0.087515</td>\n",
       "      <td id=\"T_97135_row17_col9\" class=\"data row17 col9\" >0.020483</td>\n",
       "      <td id=\"T_97135_row17_col10\" class=\"data row17 col10\" >0.057416</td>\n",
       "      <td id=\"T_97135_row17_col11\" class=\"data row17 col11\" >0.093603</td>\n",
       "      <td id=\"T_97135_row17_col12\" class=\"data row17 col12\" >0.021265</td>\n",
       "      <td id=\"T_97135_row17_col13\" class=\"data row17 col13\" >-0.228580</td>\n",
       "      <td id=\"T_97135_row17_col14\" class=\"data row17 col14\" >0.085064</td>\n",
       "      <td id=\"T_97135_row17_col15\" class=\"data row17 col15\" >-0.157611</td>\n",
       "      <td id=\"T_97135_row17_col16\" class=\"data row17 col16\" >-0.522260</td>\n",
       "      <td id=\"T_97135_row17_col17\" class=\"data row17 col17\" >1.000000</td>\n",
       "      <td id=\"T_97135_row17_col18\" class=\"data row17 col18\" >-0.406819</td>\n",
       "      <td id=\"T_97135_row17_col19\" class=\"data row17 col19\" >0.021850</td>\n",
       "      <td id=\"T_97135_row17_col20\" class=\"data row17 col20\" >-0.406333</td>\n",
       "      <td id=\"T_97135_row17_col21\" class=\"data row17 col21\" >-0.632199</td>\n",
       "      <td id=\"T_97135_row17_col22\" class=\"data row17 col22\" >0.297667</td>\n",
       "      <td id=\"T_97135_row17_col23\" class=\"data row17 col23\" >0.010401</td>\n",
       "      <td id=\"T_97135_row17_col24\" class=\"data row17 col24\" >0.000449</td>\n",
       "      <td id=\"T_97135_row17_col25\" class=\"data row17 col25\" >-0.345677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row18\" class=\"row_heading level0 row18\" >DateTime_day_of_year</th>\n",
       "      <td id=\"T_97135_row18_col0\" class=\"data row18 col0\" >-0.220575</td>\n",
       "      <td id=\"T_97135_row18_col1\" class=\"data row18 col1\" >-0.242740</td>\n",
       "      <td id=\"T_97135_row18_col2\" class=\"data row18 col2\" >0.083177</td>\n",
       "      <td id=\"T_97135_row18_col3\" class=\"data row18 col3\" >0.018974</td>\n",
       "      <td id=\"T_97135_row18_col4\" class=\"data row18 col4\" >-0.020278</td>\n",
       "      <td id=\"T_97135_row18_col5\" class=\"data row18 col5\" >-0.004483</td>\n",
       "      <td id=\"T_97135_row18_col6\" class=\"data row18 col6\" >-0.059673</td>\n",
       "      <td id=\"T_97135_row18_col7\" class=\"data row18 col7\" >-0.005299</td>\n",
       "      <td id=\"T_97135_row18_col8\" class=\"data row18 col8\" >0.102875</td>\n",
       "      <td id=\"T_97135_row18_col9\" class=\"data row18 col9\" >0.011721</td>\n",
       "      <td id=\"T_97135_row18_col10\" class=\"data row18 col10\" >-0.008315</td>\n",
       "      <td id=\"T_97135_row18_col11\" class=\"data row18 col11\" >-0.058856</td>\n",
       "      <td id=\"T_97135_row18_col12\" class=\"data row18 col12\" >0.017197</td>\n",
       "      <td id=\"T_97135_row18_col13\" class=\"data row18 col13\" >-0.118636</td>\n",
       "      <td id=\"T_97135_row18_col14\" class=\"data row18 col14\" >-0.081838</td>\n",
       "      <td id=\"T_97135_row18_col15\" class=\"data row18 col15\" >0.115979</td>\n",
       "      <td id=\"T_97135_row18_col16\" class=\"data row18 col16\" >0.991482</td>\n",
       "      <td id=\"T_97135_row18_col17\" class=\"data row18 col17\" >-0.406819</td>\n",
       "      <td id=\"T_97135_row18_col18\" class=\"data row18 col18\" >1.000000</td>\n",
       "      <td id=\"T_97135_row18_col19\" class=\"data row18 col19\" >-0.078642</td>\n",
       "      <td id=\"T_97135_row18_col20\" class=\"data row18 col20\" >0.999553</td>\n",
       "      <td id=\"T_97135_row18_col21\" class=\"data row18 col21\" >0.938161</td>\n",
       "      <td id=\"T_97135_row18_col22\" class=\"data row18 col22\" >-0.042102</td>\n",
       "      <td id=\"T_97135_row18_col23\" class=\"data row18 col23\" >-0.047483</td>\n",
       "      <td id=\"T_97135_row18_col24\" class=\"data row18 col24\" >-0.001843</td>\n",
       "      <td id=\"T_97135_row18_col25\" class=\"data row18 col25\" >0.965386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row19\" class=\"row_heading level0 row19\" >DateTime_day_of_week</th>\n",
       "      <td id=\"T_97135_row19_col0\" class=\"data row19 col0\" >-0.102890</td>\n",
       "      <td id=\"T_97135_row19_col1\" class=\"data row19 col1\" >-0.091499</td>\n",
       "      <td id=\"T_97135_row19_col2\" class=\"data row19 col2\" >0.057002</td>\n",
       "      <td id=\"T_97135_row19_col3\" class=\"data row19 col3\" >0.050301</td>\n",
       "      <td id=\"T_97135_row19_col4\" class=\"data row19 col4\" >-0.021075</td>\n",
       "      <td id=\"T_97135_row19_col5\" class=\"data row19 col5\" >0.009603</td>\n",
       "      <td id=\"T_97135_row19_col6\" class=\"data row19 col6\" >-0.190405</td>\n",
       "      <td id=\"T_97135_row19_col7\" class=\"data row19 col7\" >-0.010774</td>\n",
       "      <td id=\"T_97135_row19_col8\" class=\"data row19 col8\" >-0.093561</td>\n",
       "      <td id=\"T_97135_row19_col9\" class=\"data row19 col9\" >-0.038201</td>\n",
       "      <td id=\"T_97135_row19_col10\" class=\"data row19 col10\" >0.046686</td>\n",
       "      <td id=\"T_97135_row19_col11\" class=\"data row19 col11\" >0.006718</td>\n",
       "      <td id=\"T_97135_row19_col12\" class=\"data row19 col12\" >-0.011760</td>\n",
       "      <td id=\"T_97135_row19_col13\" class=\"data row19 col13\" >-0.057800</td>\n",
       "      <td id=\"T_97135_row19_col14\" class=\"data row19 col14\" >0.521230</td>\n",
       "      <td id=\"T_97135_row19_col15\" class=\"data row19 col15\" >0.164398</td>\n",
       "      <td id=\"T_97135_row19_col16\" class=\"data row19 col16\" >-0.076448</td>\n",
       "      <td id=\"T_97135_row19_col17\" class=\"data row19 col17\" >0.021850</td>\n",
       "      <td id=\"T_97135_row19_col18\" class=\"data row19 col18\" >-0.078642</td>\n",
       "      <td id=\"T_97135_row19_col19\" class=\"data row19 col19\" >1.000000</td>\n",
       "      <td id=\"T_97135_row19_col20\" class=\"data row19 col20\" >-0.108395</td>\n",
       "      <td id=\"T_97135_row19_col21\" class=\"data row19 col21\" >-0.071794</td>\n",
       "      <td id=\"T_97135_row19_col22\" class=\"data row19 col22\" >0.196673</td>\n",
       "      <td id=\"T_97135_row19_col23\" class=\"data row19 col23\" >-0.035601</td>\n",
       "      <td id=\"T_97135_row19_col24\" class=\"data row19 col24\" >-0.001299</td>\n",
       "      <td id=\"T_97135_row19_col25\" class=\"data row19 col25\" >-0.156449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row20\" class=\"row_heading level0 row20\" >DateTime_week_of_year</th>\n",
       "      <td id=\"T_97135_row20_col0\" class=\"data row20 col0\" >-0.216872</td>\n",
       "      <td id=\"T_97135_row20_col1\" class=\"data row20 col1\" >-0.239317</td>\n",
       "      <td id=\"T_97135_row20_col2\" class=\"data row20 col2\" >0.081235</td>\n",
       "      <td id=\"T_97135_row20_col3\" class=\"data row20 col3\" >0.017413</td>\n",
       "      <td id=\"T_97135_row20_col4\" class=\"data row20 col4\" >-0.019589</td>\n",
       "      <td id=\"T_97135_row20_col5\" class=\"data row20 col5\" >-0.004759</td>\n",
       "      <td id=\"T_97135_row20_col6\" class=\"data row20 col6\" >-0.053799</td>\n",
       "      <td id=\"T_97135_row20_col7\" class=\"data row20 col7\" >-0.004961</td>\n",
       "      <td id=\"T_97135_row20_col8\" class=\"data row20 col8\" >0.105391</td>\n",
       "      <td id=\"T_97135_row20_col9\" class=\"data row20 col9\" >0.012834</td>\n",
       "      <td id=\"T_97135_row20_col10\" class=\"data row20 col10\" >-0.009691</td>\n",
       "      <td id=\"T_97135_row20_col11\" class=\"data row20 col11\" >-0.058892</td>\n",
       "      <td id=\"T_97135_row20_col12\" class=\"data row20 col12\" >0.017501</td>\n",
       "      <td id=\"T_97135_row20_col13\" class=\"data row20 col13\" >-0.116571</td>\n",
       "      <td id=\"T_97135_row20_col14\" class=\"data row20 col14\" >-0.097232</td>\n",
       "      <td id=\"T_97135_row20_col15\" class=\"data row20 col15\" >0.110726</td>\n",
       "      <td id=\"T_97135_row20_col16\" class=\"data row20 col16\" >0.990993</td>\n",
       "      <td id=\"T_97135_row20_col17\" class=\"data row20 col17\" >-0.406333</td>\n",
       "      <td id=\"T_97135_row20_col18\" class=\"data row20 col18\" >0.999553</td>\n",
       "      <td id=\"T_97135_row20_col19\" class=\"data row20 col19\" >-0.108395</td>\n",
       "      <td id=\"T_97135_row20_col20\" class=\"data row20 col20\" >1.000000</td>\n",
       "      <td id=\"T_97135_row20_col21\" class=\"data row20 col21\" >0.937682</td>\n",
       "      <td id=\"T_97135_row20_col22\" class=\"data row20 col22\" >-0.047879</td>\n",
       "      <td id=\"T_97135_row20_col23\" class=\"data row20 col23\" >-0.046282</td>\n",
       "      <td id=\"T_97135_row20_col24\" class=\"data row20 col24\" >-0.001799</td>\n",
       "      <td id=\"T_97135_row20_col25\" class=\"data row20 col25\" >0.967369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row21\" class=\"row_heading level0 row21\" >DateTime_quarter</th>\n",
       "      <td id=\"T_97135_row21_col0\" class=\"data row21 col0\" >-0.256514</td>\n",
       "      <td id=\"T_97135_row21_col1\" class=\"data row21 col1\" >-0.272055</td>\n",
       "      <td id=\"T_97135_row21_col2\" class=\"data row21 col2\" >0.126092</td>\n",
       "      <td id=\"T_97135_row21_col3\" class=\"data row21 col3\" >0.073061</td>\n",
       "      <td id=\"T_97135_row21_col4\" class=\"data row21 col4\" >-0.037866</td>\n",
       "      <td id=\"T_97135_row21_col5\" class=\"data row21 col5\" >-0.014375</td>\n",
       "      <td id=\"T_97135_row21_col6\" class=\"data row21 col6\" >-0.049138</td>\n",
       "      <td id=\"T_97135_row21_col7\" class=\"data row21 col7\" >-0.001628</td>\n",
       "      <td id=\"T_97135_row21_col8\" class=\"data row21 col8\" >0.118377</td>\n",
       "      <td id=\"T_97135_row21_col9\" class=\"data row21 col9\" >-0.000028</td>\n",
       "      <td id=\"T_97135_row21_col10\" class=\"data row21 col10\" >-0.022178</td>\n",
       "      <td id=\"T_97135_row21_col11\" class=\"data row21 col11\" >-0.082974</td>\n",
       "      <td id=\"T_97135_row21_col12\" class=\"data row21 col12\" >0.006892</td>\n",
       "      <td id=\"T_97135_row21_col13\" class=\"data row21 col13\" >-0.065641</td>\n",
       "      <td id=\"T_97135_row21_col14\" class=\"data row21 col14\" >-0.046542</td>\n",
       "      <td id=\"T_97135_row21_col15\" class=\"data row21 col15\" >0.162465</td>\n",
       "      <td id=\"T_97135_row21_col16\" class=\"data row21 col16\" >0.965734</td>\n",
       "      <td id=\"T_97135_row21_col17\" class=\"data row21 col17\" >-0.632199</td>\n",
       "      <td id=\"T_97135_row21_col18\" class=\"data row21 col18\" >0.938161</td>\n",
       "      <td id=\"T_97135_row21_col19\" class=\"data row21 col19\" >-0.071794</td>\n",
       "      <td id=\"T_97135_row21_col20\" class=\"data row21 col20\" >0.937682</td>\n",
       "      <td id=\"T_97135_row21_col21\" class=\"data row21 col21\" >1.000000</td>\n",
       "      <td id=\"T_97135_row21_col22\" class=\"data row21 col22\" >-0.099552</td>\n",
       "      <td id=\"T_97135_row21_col23\" class=\"data row21 col23\" >-0.044270</td>\n",
       "      <td id=\"T_97135_row21_col24\" class=\"data row21 col24\" >-0.001713</td>\n",
       "      <td id=\"T_97135_row21_col25\" class=\"data row21 col25\" >0.862213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row22\" class=\"row_heading level0 row22\" >DateTime_is_month_end</th>\n",
       "      <td id=\"T_97135_row22_col0\" class=\"data row22 col0\" >-0.004804</td>\n",
       "      <td id=\"T_97135_row22_col1\" class=\"data row22 col1\" >0.011424</td>\n",
       "      <td id=\"T_97135_row22_col2\" class=\"data row22 col2\" >-0.259382</td>\n",
       "      <td id=\"T_97135_row22_col3\" class=\"data row22 col3\" >-0.289126</td>\n",
       "      <td id=\"T_97135_row22_col4\" class=\"data row22 col4\" >-0.040400</td>\n",
       "      <td id=\"T_97135_row22_col5\" class=\"data row22 col5\" >-0.017395</td>\n",
       "      <td id=\"T_97135_row22_col6\" class=\"data row22 col6\" >-0.043169</td>\n",
       "      <td id=\"T_97135_row22_col7\" class=\"data row22 col7\" >0.006315</td>\n",
       "      <td id=\"T_97135_row22_col8\" class=\"data row22 col8\" >-0.076702</td>\n",
       "      <td id=\"T_97135_row22_col9\" class=\"data row22 col9\" >-0.057237</td>\n",
       "      <td id=\"T_97135_row22_col10\" class=\"data row22 col10\" >0.025335</td>\n",
       "      <td id=\"T_97135_row22_col11\" class=\"data row22 col11\" >-0.024887</td>\n",
       "      <td id=\"T_97135_row22_col12\" class=\"data row22 col12\" >-0.029101</td>\n",
       "      <td id=\"T_97135_row22_col13\" class=\"data row22 col13\" >-0.233745</td>\n",
       "      <td id=\"T_97135_row22_col14\" class=\"data row22 col14\" >0.193919</td>\n",
       "      <td id=\"T_97135_row22_col15\" class=\"data row22 col15\" >0.199432</td>\n",
       "      <td id=\"T_97135_row22_col16\" class=\"data row22 col16\" >-0.082240</td>\n",
       "      <td id=\"T_97135_row22_col17\" class=\"data row22 col17\" >0.297667</td>\n",
       "      <td id=\"T_97135_row22_col18\" class=\"data row22 col18\" >-0.042102</td>\n",
       "      <td id=\"T_97135_row22_col19\" class=\"data row22 col19\" >0.196673</td>\n",
       "      <td id=\"T_97135_row22_col20\" class=\"data row22 col20\" >-0.047879</td>\n",
       "      <td id=\"T_97135_row22_col21\" class=\"data row22 col21\" >-0.099552</td>\n",
       "      <td id=\"T_97135_row22_col22\" class=\"data row22 col22\" >1.000000</td>\n",
       "      <td id=\"T_97135_row22_col23\" class=\"data row22 col23\" >-0.000544</td>\n",
       "      <td id=\"T_97135_row22_col24\" class=\"data row22 col24\" >0.000000</td>\n",
       "      <td id=\"T_97135_row22_col25\" class=\"data row22 col25\" >-0.054434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row23\" class=\"row_heading level0 row23\" >DateTime_hour</th>\n",
       "      <td id=\"T_97135_row23_col0\" class=\"data row23 col0\" >0.017826</td>\n",
       "      <td id=\"T_97135_row23_col1\" class=\"data row23 col1\" >0.014045</td>\n",
       "      <td id=\"T_97135_row23_col2\" class=\"data row23 col2\" >0.011194</td>\n",
       "      <td id=\"T_97135_row23_col3\" class=\"data row23 col3\" >-0.038387</td>\n",
       "      <td id=\"T_97135_row23_col4\" class=\"data row23 col4\" >0.014259</td>\n",
       "      <td id=\"T_97135_row23_col5\" class=\"data row23 col5\" >-0.025948</td>\n",
       "      <td id=\"T_97135_row23_col6\" class=\"data row23 col6\" >0.058575</td>\n",
       "      <td id=\"T_97135_row23_col7\" class=\"data row23 col7\" >0.053063</td>\n",
       "      <td id=\"T_97135_row23_col8\" class=\"data row23 col8\" >0.217681</td>\n",
       "      <td id=\"T_97135_row23_col9\" class=\"data row23 col9\" >0.175101</td>\n",
       "      <td id=\"T_97135_row23_col10\" class=\"data row23 col10\" >-0.161038</td>\n",
       "      <td id=\"T_97135_row23_col11\" class=\"data row23 col11\" >-0.025020</td>\n",
       "      <td id=\"T_97135_row23_col12\" class=\"data row23 col12\" >0.033625</td>\n",
       "      <td id=\"T_97135_row23_col13\" class=\"data row23 col13\" >-0.155185</td>\n",
       "      <td id=\"T_97135_row23_col14\" class=\"data row23 col14\" >-0.008617</td>\n",
       "      <td id=\"T_97135_row23_col15\" class=\"data row23 col15\" >0.417876</td>\n",
       "      <td id=\"T_97135_row23_col16\" class=\"data row23 col16\" >-0.045647</td>\n",
       "      <td id=\"T_97135_row23_col17\" class=\"data row23 col17\" >0.010401</td>\n",
       "      <td id=\"T_97135_row23_col18\" class=\"data row23 col18\" >-0.047483</td>\n",
       "      <td id=\"T_97135_row23_col19\" class=\"data row23 col19\" >-0.035601</td>\n",
       "      <td id=\"T_97135_row23_col20\" class=\"data row23 col20\" >-0.046282</td>\n",
       "      <td id=\"T_97135_row23_col21\" class=\"data row23 col21\" >-0.044270</td>\n",
       "      <td id=\"T_97135_row23_col22\" class=\"data row23 col22\" >-0.000544</td>\n",
       "      <td id=\"T_97135_row23_col23\" class=\"data row23 col23\" >1.000000</td>\n",
       "      <td id=\"T_97135_row23_col24\" class=\"data row23 col24\" >0.000350</td>\n",
       "      <td id=\"T_97135_row23_col25\" class=\"data row23 col25\" >-0.036818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row24\" class=\"row_heading level0 row24\" >DateTime_minute</th>\n",
       "      <td id=\"T_97135_row24_col0\" class=\"data row24 col0\" >0.000972</td>\n",
       "      <td id=\"T_97135_row24_col1\" class=\"data row24 col1\" >0.000976</td>\n",
       "      <td id=\"T_97135_row24_col2\" class=\"data row24 col2\" >-0.000469</td>\n",
       "      <td id=\"T_97135_row24_col3\" class=\"data row24 col3\" >-0.000602</td>\n",
       "      <td id=\"T_97135_row24_col4\" class=\"data row24 col4\" >0.008701</td>\n",
       "      <td id=\"T_97135_row24_col5\" class=\"data row24 col5\" >0.004786</td>\n",
       "      <td id=\"T_97135_row24_col6\" class=\"data row24 col6\" >-0.007725</td>\n",
       "      <td id=\"T_97135_row24_col7\" class=\"data row24 col7\" >-0.007786</td>\n",
       "      <td id=\"T_97135_row24_col8\" class=\"data row24 col8\" >-0.003101</td>\n",
       "      <td id=\"T_97135_row24_col9\" class=\"data row24 col9\" >-0.004690</td>\n",
       "      <td id=\"T_97135_row24_col10\" class=\"data row24 col10\" >0.004136</td>\n",
       "      <td id=\"T_97135_row24_col11\" class=\"data row24 col11\" >0.003957</td>\n",
       "      <td id=\"T_97135_row24_col12\" class=\"data row24 col12\" >0.002627</td>\n",
       "      <td id=\"T_97135_row24_col13\" class=\"data row24 col13\" >0.000386</td>\n",
       "      <td id=\"T_97135_row24_col14\" class=\"data row24 col14\" >-0.000016</td>\n",
       "      <td id=\"T_97135_row24_col15\" class=\"data row24 col15\" >-0.000388</td>\n",
       "      <td id=\"T_97135_row24_col16\" class=\"data row24 col16\" >-0.001779</td>\n",
       "      <td id=\"T_97135_row24_col17\" class=\"data row24 col17\" >0.000449</td>\n",
       "      <td id=\"T_97135_row24_col18\" class=\"data row24 col18\" >-0.001843</td>\n",
       "      <td id=\"T_97135_row24_col19\" class=\"data row24 col19\" >-0.001299</td>\n",
       "      <td id=\"T_97135_row24_col20\" class=\"data row24 col20\" >-0.001799</td>\n",
       "      <td id=\"T_97135_row24_col21\" class=\"data row24 col21\" >-0.001713</td>\n",
       "      <td id=\"T_97135_row24_col22\" class=\"data row24 col22\" >0.000000</td>\n",
       "      <td id=\"T_97135_row24_col23\" class=\"data row24 col23\" >0.000350</td>\n",
       "      <td id=\"T_97135_row24_col24\" class=\"data row24 col24\" >1.000000</td>\n",
       "      <td id=\"T_97135_row24_col25\" class=\"data row24 col25\" >-0.001442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_97135_level0_row25\" class=\"row_heading level0 row25\" >DateTime_season</th>\n",
       "      <td id=\"T_97135_row25_col0\" class=\"data row25 col0\" >-0.195800</td>\n",
       "      <td id=\"T_97135_row25_col1\" class=\"data row25 col1\" >-0.216379</td>\n",
       "      <td id=\"T_97135_row25_col2\" class=\"data row25 col2\" >0.073273</td>\n",
       "      <td id=\"T_97135_row25_col3\" class=\"data row25 col3\" >0.006435</td>\n",
       "      <td id=\"T_97135_row25_col4\" class=\"data row25 col4\" >-0.006951</td>\n",
       "      <td id=\"T_97135_row25_col5\" class=\"data row25 col5\" >-0.002783</td>\n",
       "      <td id=\"T_97135_row25_col6\" class=\"data row25 col6\" >-0.050052</td>\n",
       "      <td id=\"T_97135_row25_col7\" class=\"data row25 col7\" >-0.003447</td>\n",
       "      <td id=\"T_97135_row25_col8\" class=\"data row25 col8\" >0.102235</td>\n",
       "      <td id=\"T_97135_row25_col9\" class=\"data row25 col9\" >0.022096</td>\n",
       "      <td id=\"T_97135_row25_col10\" class=\"data row25 col10\" >-0.012571</td>\n",
       "      <td id=\"T_97135_row25_col11\" class=\"data row25 col11\" >-0.043801</td>\n",
       "      <td id=\"T_97135_row25_col12\" class=\"data row25 col12\" >0.020612</td>\n",
       "      <td id=\"T_97135_row25_col13\" class=\"data row25 col13\" >-0.107818</td>\n",
       "      <td id=\"T_97135_row25_col14\" class=\"data row25 col14\" >-0.111628</td>\n",
       "      <td id=\"T_97135_row25_col15\" class=\"data row25 col15\" >0.079934</td>\n",
       "      <td id=\"T_97135_row25_col16\" class=\"data row25 col16\" >0.950836</td>\n",
       "      <td id=\"T_97135_row25_col17\" class=\"data row25 col17\" >-0.345677</td>\n",
       "      <td id=\"T_97135_row25_col18\" class=\"data row25 col18\" >0.965386</td>\n",
       "      <td id=\"T_97135_row25_col19\" class=\"data row25 col19\" >-0.156449</td>\n",
       "      <td id=\"T_97135_row25_col20\" class=\"data row25 col20\" >0.967369</td>\n",
       "      <td id=\"T_97135_row25_col21\" class=\"data row25 col21\" >0.862213</td>\n",
       "      <td id=\"T_97135_row25_col22\" class=\"data row25 col22\" >-0.054434</td>\n",
       "      <td id=\"T_97135_row25_col23\" class=\"data row25 col23\" >-0.036818</td>\n",
       "      <td id=\"T_97135_row25_col24\" class=\"data row25 col24\" >-0.001442</td>\n",
       "      <td id=\"T_97135_row25_col25\" class=\"data row25 col25\" >1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fed3fd0db10>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = train_fe.corr()\n",
    "corr.style.background_gradient(cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "31c7e2a8",
   "metadata": {
    "_kg_hide-input": true,
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.797972Z",
     "iopub.status.busy": "2022-07-24T15:35:18.797033Z",
     "iopub.status.idle": "2022-07-24T15:35:18.806584Z",
     "shell.execute_reply": "2022-07-24T15:35:18.805762Z"
    },
    "papermill": {
     "duration": 0.030859,
     "end_time": "2022-07-24T15:35:18.808805",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.777946",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CO2_(dinning-room)                 0.061361\n",
       "CO2_room                           0.056195\n",
       "Lighting_(dinning-room)            0.069264\n",
       "Lighting_room                      0.002253\n",
       "Meteo_Sun_dusk                     0.068897\n",
       "Meteo_Wind                         0.220667\n",
       "Meteo_Sun_light_in_west_facade     0.335288\n",
       "Meteo_Sun_light_in_south_facade    0.000072\n",
       "Meteo_Sun_irradiance               0.123390\n",
       "Day_of_the_week                    0.016517\n",
       "Indoor_temperature_room            1.000000\n",
       "DateTime_month                     0.129906\n",
       "DateTime_day_of_year               0.115979\n",
       "DateTime_day_of_week               0.164398\n",
       "DateTime_week_of_year              0.110726\n",
       "DateTime_quarter                   0.162465\n",
       "DateTime_is_month_end              0.199432\n",
       "DateTime_hour                      0.417876\n",
       "DateTime_season                    0.079934\n",
       "Name: Indoor_temperature_room, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Selection of columns positively correlated with the target\n",
    "select_columns = corr['Indoor_temperature_room'][ corr['Indoor_temperature_room'] > 0 ].index.tolist()\n",
    "\n",
    "# Removing target columns to list\n",
    "select_columns.remove('Indoor_temperature_room')\n",
    "\n",
    "corr['Indoor_temperature_room'][ corr['Indoor_temperature_room'] > 0 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c621be73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.847147Z",
     "iopub.status.busy": "2022-07-24T15:35:18.846490Z",
     "iopub.status.idle": "2022-07-24T15:35:18.862199Z",
     "shell.execute_reply": "2022-07-24T15:35:18.860543Z"
    },
    "papermill": {
     "duration": 0.037909,
     "end_time": "2022-07-24T15:35:18.864805",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.826896",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2764 entries, 0 to 2763\n",
      "Data columns (total 27 columns):\n",
      " #   Column                            Non-Null Count  Dtype         \n",
      "---  ------                            --------------  -----         \n",
      " 0   CO2_(dinning-room)                2764 non-null   float64       \n",
      " 1   CO2_room                          2764 non-null   float64       \n",
      " 2   Relative_humidity_(dinning-room)  2764 non-null   float64       \n",
      " 3   Relative_humidity_room            2764 non-null   float64       \n",
      " 4   Lighting_(dinning-room)           2764 non-null   float64       \n",
      " 5   Lighting_room                     2764 non-null   float64       \n",
      " 6   Meteo_Rain                        2764 non-null   float64       \n",
      " 7   Meteo_Sun_dusk                    2764 non-null   float64       \n",
      " 8   Meteo_Wind                        2764 non-null   float64       \n",
      " 9   Meteo_Sun_light_in_west_facade    2764 non-null   float64       \n",
      " 10  Meteo_Sun_light_in_east_facade    2764 non-null   float64       \n",
      " 11  Meteo_Sun_light_in_south_facade   2764 non-null   float64       \n",
      " 12  Meteo_Sun_irradiance              2764 non-null   float64       \n",
      " 13  Outdoor_relative_humidity_Sensor  2764 non-null   float64       \n",
      " 14  Day_of_the_week                   2764 non-null   float64       \n",
      " 15  Indoor_temperature_room           2764 non-null   float64       \n",
      " 16  DateTime                          2764 non-null   datetime64[ns]\n",
      " 17  DateTime_month                    2764 non-null   int64         \n",
      " 18  DateTime_day                      2764 non-null   int64         \n",
      " 19  DateTime_day_of_year              2764 non-null   int64         \n",
      " 20  DateTime_day_of_week              2764 non-null   int64         \n",
      " 21  DateTime_week_of_year             2764 non-null   int64         \n",
      " 22  DateTime_quarter                  2764 non-null   int64         \n",
      " 23  DateTime_is_month_end             2764 non-null   bool          \n",
      " 24  DateTime_hour                     2764 non-null   int64         \n",
      " 25  DateTime_minute                   2764 non-null   int64         \n",
      " 26  DateTime_season                   2764 non-null   int64         \n",
      "dtypes: bool(1), datetime64[ns](1), float64(16), int64(9)\n",
      "memory usage: 585.7 KB\n"
     ]
    }
   ],
   "source": [
    "train_fe.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "425fc98f",
   "metadata": {
    "papermill": {
     "duration": 0.018036,
     "end_time": "2022-07-24T15:35:18.901298",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.883262",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Encoding bool columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "65c39a75",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:18.939276Z",
     "iopub.status.busy": "2022-07-24T15:35:18.938892Z",
     "iopub.status.idle": "2022-07-24T15:35:18.948694Z",
     "shell.execute_reply": "2022-07-24T15:35:18.947626Z"
    },
    "papermill": {
     "duration": 0.031486,
     "end_time": "2022-07-24T15:35:18.951076",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.919590",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train_fe['DateTime_is_month_end'] = train_fe['DateTime_is_month_end'].replace({False: 0, True: 1})\n",
    "test_fe['DateTime_is_month_end'] = test_fe['DateTime_is_month_end'].replace({False: 0, True: 1})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d5a5b60",
   "metadata": {
    "papermill": {
     "duration": 0.017956,
     "end_time": "2022-07-24T15:35:18.987172",
     "exception": false,
     "start_time": "2022-07-24T15:35:18.969216",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Drop `DateTime` column (we don't need it)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "241731b0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:19.026112Z",
     "iopub.status.busy": "2022-07-24T15:35:19.025293Z",
     "iopub.status.idle": "2022-07-24T15:35:19.035808Z",
     "shell.execute_reply": "2022-07-24T15:35:19.034197Z"
    },
    "papermill": {
     "duration": 0.032537,
     "end_time": "2022-07-24T15:35:19.038258",
     "exception": false,
     "start_time": "2022-07-24T15:35:19.005721",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data dimensions : (2764, 26) (1373, 25)\n"
     ]
    }
   ],
   "source": [
    "train_fe = train_fe.drop('DateTime', axis=1)\n",
    "test_fe = test_fe.drop('DateTime', axis=1)\n",
    "\n",
    "print(\"Data dimensions :\", train_fe.shape, test_fe.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a42a0600",
   "metadata": {
    "papermill": {
     "duration": 0.018305,
     "end_time": "2022-07-24T15:35:19.074963",
     "exception": false,
     "start_time": "2022-07-24T15:35:19.056658",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Free memories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b36d517a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:19.113582Z",
     "iopub.status.busy": "2022-07-24T15:35:19.112928Z",
     "iopub.status.idle": "2022-07-24T15:35:19.220330Z",
     "shell.execute_reply": "2022-07-24T15:35:19.219229Z"
    },
    "papermill": {
     "duration": 0.12926,
     "end_time": "2022-07-24T15:35:19.222816",
     "exception": false,
     "start_time": "2022-07-24T15:35:19.093556",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "89"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del train, test\n",
    "gc.collect()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94e89d11",
   "metadata": {
    "papermill": {
     "duration": 0.018167,
     "end_time": "2022-07-24T15:35:19.259551",
     "exception": false,
     "start_time": "2022-07-24T15:35:19.241384",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Splitting Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fbc17840",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:19.298151Z",
     "iopub.status.busy": "2022-07-24T15:35:19.297753Z",
     "iopub.status.idle": "2022-07-24T15:35:19.303711Z",
     "shell.execute_reply": "2022-07-24T15:35:19.302573Z"
    },
    "papermill": {
     "duration": 0.02818,
     "end_time": "2022-07-24T15:35:19.306177",
     "exception": false,
     "start_time": "2022-07-24T15:35:19.277997",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "X = train_fe.copy()\n",
    "y = X.pop('Indoor_temperature_room')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2de76fda",
   "metadata": {
    "papermill": {
     "duration": 0.018315,
     "end_time": "2022-07-24T15:35:19.343024",
     "exception": false,
     "start_time": "2022-07-24T15:35:19.324709",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Scaling Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e15777eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:19.382166Z",
     "iopub.status.busy": "2022-07-24T15:35:19.381773Z",
     "iopub.status.idle": "2022-07-24T15:35:20.304235Z",
     "shell.execute_reply": "2022-07-24T15:35:20.303080Z"
    },
    "papermill": {
     "duration": 0.945263,
     "end_time": "2022-07-24T15:35:20.306832",
     "exception": false,
     "start_time": "2022-07-24T15:35:19.361569",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import RobustScaler\n",
    "\n",
    "scaler= RobustScaler()\n",
    "\n",
    "scaler.fit(X)\n",
    "X = scaler.transform(X)\n",
    "test_fe = scaler.transform(test_fe)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fc67688",
   "metadata": {
    "papermill": {
     "duration": 0.018101,
     "end_time": "2022-07-24T15:35:20.343401",
     "exception": false,
     "start_time": "2022-07-24T15:35:20.325300",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e43f7d2e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:20.382124Z",
     "iopub.status.busy": "2022-07-24T15:35:20.381744Z",
     "iopub.status.idle": "2022-07-24T15:35:26.761148Z",
     "shell.execute_reply": "2022-07-24T15:35:26.759902Z"
    },
    "papermill": {
     "duration": 6.402,
     "end_time": "2022-07-24T15:35:26.763764",
     "exception": false,
     "start_time": "2022-07-24T15:35:20.361764",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#import libraries for muting unnecessary warnings if needed\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "from keras.layers import LSTM\n",
    "from keras.layers import Dropout\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.layers import Bidirectional\n",
    "\n",
    "# Import Data Visualization libraries\n",
    "import seaborn as sb\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3a4e7fed",
   "metadata": {
    "_kg_hide-input": true,
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:26.803950Z",
     "iopub.status.busy": "2022-07-24T15:35:26.802562Z",
     "iopub.status.idle": "2022-07-24T15:35:26.809946Z",
     "shell.execute_reply": "2022-07-24T15:35:26.808930Z"
    },
    "jupyter": {
     "source_hidden": true
    },
    "papermill": {
     "duration": 0.028973,
     "end_time": "2022-07-24T15:35:26.811923",
     "exception": false,
     "start_time": "2022-07-24T15:35:26.782950",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\nn_steps = X.shape[-2]\\nn_features =X.shape[-1]\\n\\ninput_shape=(n_steps, n_features)\\n\\nmodel = Sequential([\\n    Bidirectional(LSTM(256, return_sequences=True), input_shape= input_shape),\\n    Dense(20, activation='tanh'),\\n    Bidirectional(LSTM(128, return_sequences=True, activation = 'tanh')),\\n    Dense(20, activation='tanh'),\\n    Bidirectional(LSTM(128, return_sequences=False, activation = 'tanh')),\\n    Dense(20, activation='tanh'),\\n    tf.keras.layers.Dropout(0.20),\\n    Dense(units=3, activation = 'linear'),\\n])\\n\\nmodel.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.0005), loss='mse')\\n#model.summary()\\n\""
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "n_steps = X.shape[-2]\n",
    "n_features =X.shape[-1]\n",
    "\n",
    "input_shape=(n_steps, n_features)\n",
    "\n",
    "model = Sequential([\n",
    "    Bidirectional(LSTM(256, return_sequences=True), input_shape= input_shape),\n",
    "    Dense(20, activation='tanh'),\n",
    "    Bidirectional(LSTM(128, return_sequences=True, activation = 'tanh')),\n",
    "    Dense(20, activation='tanh'),\n",
    "    Bidirectional(LSTM(128, return_sequences=False, activation = 'tanh')),\n",
    "    Dense(20, activation='tanh'),\n",
    "    tf.keras.layers.Dropout(0.20),\n",
    "    Dense(units=3, activation = 'linear'),\n",
    "])\n",
    "\n",
    "model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.0005), loss='mse')\n",
    "#model.summary()\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3a378a7c",
   "metadata": {
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:26.851908Z",
     "iopub.status.busy": "2022-07-24T15:35:26.851033Z",
     "iopub.status.idle": "2022-07-24T15:35:27.107794Z",
     "shell.execute_reply": "2022-07-24T15:35:27.105973Z"
    },
    "papermill": {
     "duration": 0.28122,
     "end_time": "2022-07-24T15:35:27.111972",
     "exception": false,
     "start_time": "2022-07-24T15:35:26.830752",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense (Dense)                (None, 2048)              53248     \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1024)              2098176   \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 512)               524800    \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 256)               131328    \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 256)               0         \n",
      "_________________________________________________________________\n",
      "batch_normalization (BatchNo (None, 256)               1024      \n",
      "_________________________________________________________________\n",
      "dense_4 (Dense)              (None, 128)               32896     \n",
      "_________________________________________________________________\n",
      "dense_5 (Dense)              (None, 64)                8256      \n",
      "_________________________________________________________________\n",
      "dense_6 (Dense)              (None, 32)                2080      \n",
      "_________________________________________________________________\n",
      "dense_7 (Dense)              (None, 16)                528       \n",
      "_________________________________________________________________\n",
      "dense_8 (Dense)              (None, 8)                 136       \n",
      "_________________________________________________________________\n",
      "dense_9 (Dense)              (None, 1)                 9         \n",
      "=================================================================\n",
      "Total params: 2,852,481\n",
      "Trainable params: 2,851,969\n",
      "Non-trainable params: 512\n",
      "_________________________________________________________________\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-07-24 15:35:26.911953: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras import layers\n",
    "\n",
    "shape = X.shape[1]\n",
    "\n",
    "def build_model():\n",
    "    active = \"tanh\"\n",
    "    model = tf.keras.Sequential([\n",
    "        layers.Dense(units=2048, activation=active, input_shape=[shape], kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dense(units=1024, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dense(units=512, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dense(units=256, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dropout(0.1),\n",
    "        layers.BatchNormalization(),\n",
    "        layers.Dense(128, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dense(64, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        #layers.Dropout(0.1),\n",
    "        layers.Dense(32, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dense(16, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dense(8, activation=active, kernel_regularizer=tf.keras.regularizers.l2(35e-6)),\n",
    "        layers.Dense(units=1)\n",
    "    ])\n",
    "\n",
    "    return model\n",
    "\n",
    "model = build_model()\n",
    "\n",
    "model.compile(optimizer=\"adam\",     \n",
    "               loss='mean_squared_error',\n",
    "               metrics=['mae']\n",
    ")\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e3e62404",
   "metadata": {
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:27.152704Z",
     "iopub.status.busy": "2022-07-24T15:35:27.152331Z",
     "iopub.status.idle": "2022-07-24T15:35:28.320196Z",
     "shell.execute_reply": "2022-07-24T15:35:28.318826Z"
    },
    "papermill": {
     "duration": 1.191497,
     "end_time": "2022-07-24T15:35:28.322901",
     "exception": false,
     "start_time": "2022-07-24T15:35:27.131404",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.keras.utils.plot_model(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e620e348",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:28.367962Z",
     "iopub.status.busy": "2022-07-24T15:35:28.366928Z",
     "iopub.status.idle": "2022-07-24T15:35:39.486929Z",
     "shell.execute_reply": "2022-07-24T15:35:39.485819Z"
    },
    "papermill": {
     "duration": 11.145397,
     "end_time": "2022-07-24T15:35:39.489533",
     "exception": false,
     "start_time": "2022-07-24T15:35:28.344136",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-07-24 15:35:28.470645: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n",
      "85/85 [==============================] - 4s 25ms/step - loss: 280.4238 - mae: 16.4912 - val_loss: 387.9199 - val_mae: 19.6467\n",
      "Epoch 2/5\n",
      "85/85 [==============================] - 2s 21ms/step - loss: 231.7145 - mae: 14.9590 - val_loss: 349.6230 - val_mae: 18.6466\n",
      "Epoch 3/5\n",
      "85/85 [==============================] - 2s 22ms/step - loss: 206.9238 - mae: 14.1071 - val_loss: 320.3330 - val_mae: 17.8439\n",
      "Epoch 4/5\n",
      "85/85 [==============================] - 2s 21ms/step - loss: 187.7820 - mae: 13.3908 - val_loss: 294.3041 - val_mae: 17.0989\n",
      "Epoch 5/5\n",
      "85/85 [==============================] - 2s 22ms/step - loss: 167.1145 - mae: 12.6155 - val_loss: 270.4016 - val_mae: 16.3849\n"
     ]
    }
   ],
   "source": [
    "# Callback\n",
    "early_stopping = tf.keras.callbacks.EarlyStopping(\n",
    "    patience=3,\n",
    "    #min_delta=0.001,\n",
    "    monitor='val_loss', \n",
    "    mode='min', \n",
    "    verbose=1,\n",
    "    #restore_best_weights=True,\n",
    ")\n",
    "\n",
    "reduce_lr = tf.keras.callbacks.ReduceLROnPlateau(\n",
    "    monitor='val_loss', factor=0.75,\n",
    "    patience=1, #min_lr=1357e-6\n",
    ")\n",
    "\n",
    "# Training\n",
    "history = model.fit(X, y, \n",
    "                    epochs=5, \n",
    "                    validation_split=0.02, \n",
    "                    #batch_size=256,\n",
    "                    callbacks=[early_stopping, reduce_lr],\n",
    "                    #verbose=1\n",
    "                   )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e92e3889",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:39.553329Z",
     "iopub.status.busy": "2022-07-24T15:35:39.552549Z",
     "iopub.status.idle": "2022-07-24T15:35:40.088887Z",
     "shell.execute_reply": "2022-07-24T15:35:40.087693Z"
    },
    "papermill": {
     "duration": 0.570954,
     "end_time": "2022-07-24T15:35:40.091385",
     "exception": false,
     "start_time": "2022-07-24T15:35:39.520431",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum Validation Loss: 270.4016\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "history_df = pd.DataFrame(history.history)\n",
    "history_df.loc[0:, ['loss', 'val_loss']].plot()\n",
    "print((\"Minimum Validation Loss: {:0.4f}\").format(history_df['val_loss'].min()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df28de05",
   "metadata": {
    "papermill": {
     "duration": 0.03046,
     "end_time": "2022-07-24T15:35:40.152887",
     "exception": false,
     "start_time": "2022-07-24T15:35:40.122427",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cbd9a7d9",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:40.217596Z",
     "iopub.status.busy": "2022-07-24T15:35:40.216821Z",
     "iopub.status.idle": "2022-07-24T15:35:40.270224Z",
     "shell.execute_reply": "2022-07-24T15:35:40.269403Z"
    },
    "papermill": {
     "duration": 0.089112,
     "end_time": "2022-07-24T15:35:40.272804",
     "exception": false,
     "start_time": "2022-07-24T15:35:40.183692",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import math\n",
    "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error\n",
    "\n",
    "# Define Evaluate Function\n",
    "def evaluates_model(y_test, y_pred):\n",
    "    print(\"*\"*12, \"Evaluations\", \"*\"*12, '\\n')\n",
    "    \n",
    "    print(\"MAE model :\", mean_absolute_error(y_test, y_pred))\n",
    "    \n",
    "    print(\"MSE model :\", mean_squared_error(y_test, y_pred))\n",
    "    \n",
    "    #print(\"R2_Score model :\", r2_score(y_test, y_pred))\n",
    "    \n",
    "    #mse_1 = np.square(np.subtract(y_test,y_pred)).mean() \n",
    "    \n",
    "    #print(\"RMSE model :\", math.sqrt(mse_1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3399548e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:40.337109Z",
     "iopub.status.busy": "2022-07-24T15:35:40.336303Z",
     "iopub.status.idle": "2022-07-24T15:35:40.961793Z",
     "shell.execute_reply": "2022-07-24T15:35:40.960712Z"
    },
    "papermill": {
     "duration": 0.66025,
     "end_time": "2022-07-24T15:35:40.964156",
     "exception": false,
     "start_time": "2022-07-24T15:35:40.303906",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "************ Evaluations ************ \n",
      "\n",
      "MAE model : 12.315708514332531\n",
      "MSE model : 159.63362377506698\n"
     ]
    }
   ],
   "source": [
    "evaluates_model(y, model.predict(X))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38ff9bf6",
   "metadata": {
    "papermill": {
     "duration": 0.030651,
     "end_time": "2022-07-24T15:35:41.026028",
     "exception": false,
     "start_time": "2022-07-24T15:35:40.995377",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Save model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7e218a1b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:41.089082Z",
     "iopub.status.busy": "2022-07-24T15:35:41.088384Z",
     "iopub.status.idle": "2022-07-24T15:35:43.649210Z",
     "shell.execute_reply": "2022-07-24T15:35:43.648235Z"
    },
    "papermill": {
     "duration": 2.59555,
     "end_time": "2022-07-24T15:35:43.651937",
     "exception": false,
     "start_time": "2022-07-24T15:35:41.056387",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-07-24 15:35:41.902050: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.\n"
     ]
    }
   ],
   "source": [
    "model.save(\"sht_keras_model.v1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "424320b2",
   "metadata": {
    "papermill": {
     "duration": 0.031377,
     "end_time": "2022-07-24T15:35:43.714685",
     "exception": false,
     "start_time": "2022-07-24T15:35:43.683308",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Making test prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "db5ed5df",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:43.779055Z",
     "iopub.status.busy": "2022-07-24T15:35:43.778314Z",
     "iopub.status.idle": "2022-07-24T15:35:44.041006Z",
     "shell.execute_reply": "2022-07-24T15:35:44.039733Z"
    },
    "papermill": {
     "duration": 0.297973,
     "end_time": "2022-07-24T15:35:44.043749",
     "exception": false,
     "start_time": "2022-07-24T15:35:43.745776",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "y_pred = model.predict(test_fe)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6015d25d",
   "metadata": {
    "papermill": {
     "duration": 0.031127,
     "end_time": "2022-07-24T15:35:44.106064",
     "exception": false,
     "start_time": "2022-07-24T15:35:44.074937",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "1b0ea461",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:44.170125Z",
     "iopub.status.busy": "2022-07-24T15:35:44.169753Z",
     "iopub.status.idle": "2022-07-24T15:35:44.194153Z",
     "shell.execute_reply": "2022-07-24T15:35:44.193379Z"
    },
    "papermill": {
     "duration": 0.058898,
     "end_time": "2022-07-24T15:35:44.196155",
     "exception": false,
     "start_time": "2022-07-24T15:35:44.137257",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <td>1373.000000</td>\n",
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       "      <th>mean</th>\n",
       "      <td>3450.000000</td>\n",
       "      <td>6.481807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>396.495271</td>\n",
       "      <td>0.537580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2764.000000</td>\n",
       "      <td>-5.694692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3107.000000</td>\n",
       "      <td>6.507623</td>\n",
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       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3450.000000</td>\n",
       "      <td>6.507663</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3793.000000</td>\n",
       "      <td>6.507713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4136.000000</td>\n",
       "      <td>6.509975</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Id  Indoor_temperature_room\n",
       "count  1373.000000              1373.000000\n",
       "mean   3450.000000                 6.481807\n",
       "std     396.495271                 0.537580\n",
       "min    2764.000000                -5.694692\n",
       "25%    3107.000000                 6.507623\n",
       "50%    3450.000000                 6.507663\n",
       "75%    3793.000000                 6.507713\n",
       "max    4136.000000                 6.509975"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub = pd.read_csv('../input/smart-homes-temperature-time-series-forecasting/sample_submission.csv')\n",
    "sub['Indoor_temperature_room'] = y_pred\n",
    "\n",
    "sub.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "984d4648",
   "metadata": {
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2022-07-24T15:35:44.261777Z",
     "iopub.status.busy": "2022-07-24T15:35:44.261079Z",
     "iopub.status.idle": "2022-07-24T15:35:44.278989Z",
     "shell.execute_reply": "2022-07-24T15:35:44.278122Z"
    },
    "papermill": {
     "duration": 0.053048,
     "end_time": "2022-07-24T15:35:44.281068",
     "exception": false,
     "start_time": "2022-07-24T15:35:44.228020",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Indoor_temperature_room</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2764</td>\n",
       "      <td>6.507629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2765</td>\n",
       "      <td>6.507629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2766</td>\n",
       "      <td>6.507629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2767</td>\n",
       "      <td>6.507631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2768</td>\n",
       "      <td>6.507630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1368</th>\n",
       "      <td>4132</td>\n",
       "      <td>6.509956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>4133</td>\n",
       "      <td>6.509915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1370</th>\n",
       "      <td>4134</td>\n",
       "      <td>6.509932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1371</th>\n",
       "      <td>4135</td>\n",
       "      <td>6.509911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1372</th>\n",
       "      <td>4136</td>\n",
       "      <td>6.509900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1373 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Id  Indoor_temperature_room\n",
       "0     2764                 6.507629\n",
       "1     2765                 6.507629\n",
       "2     2766                 6.507629\n",
       "3     2767                 6.507631\n",
       "4     2768                 6.507630\n",
       "...    ...                      ...\n",
       "1368  4132                 6.509956\n",
       "1369  4133                 6.509915\n",
       "1370  4134                 6.509932\n",
       "1371  4135                 6.509911\n",
       "1372  4136                 6.509900\n",
       "\n",
       "[1373 rows x 2 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub.to_csv(\"submission.csv\", index=False)\n",
    "sub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7bf57141",
   "metadata": {
    "papermill": {
     "duration": 0.031168,
     "end_time": "2022-07-24T15:35:44.343876",
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     "start_time": "2022-07-24T15:35:44.312708",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
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