Electricity Consumption.ipynb

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   "source": [
    "import pandas as pd"
   ]
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   "source": [
    "df = pd.read_excel(\"data/electricity-consumption-in-france-2019-2022.xlsx\")"
   ]
  },
  {
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   "execution_count": 9,
   "id": "d1363be2",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>Consomation eletric</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-01 00:00:00</td>\n",
       "      <td>63028</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-08-01 00:00:00</td>\n",
       "      <td>72241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01/15/2019</td>\n",
       "      <td>71740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/22/2019</td>\n",
       "      <td>77543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01/29/2019</td>\n",
       "      <td>76566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "                 date   Consomation eletric\n",
       "0  2019-01-01 00:00:00                63028\n",
       "1  2019-08-01 00:00:00                72241\n",
       "2           01/15/2019                71740\n",
       "3           01/22/2019                77543\n",
       "4           01/29/2019                76566"
      ]
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     "execution_count": 9,
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   "source": [
    "df.head()"
   ]
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   "execution_count": 10,
   "id": "69c34448",
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   "outputs": [
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 164 entries, 0 to 163\n",
      "Data columns (total 2 columns):\n",
      " #   Column               Non-Null Count  Dtype \n",
      "---  ------               --------------  ----- \n",
      " 0   date                 164 non-null    object\n",
      " 1   Consomation eletric  164 non-null    int64 \n",
      "dtypes: int64(1), object(1)\n",
      "memory usage: 2.7+ KB\n"
     ]
    }
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   "source": [
    "df.info()"
   ]
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  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a6c7b586",
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   "outputs": [
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       "      <th>Consomation eletric</th>\n",
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       "      <td>164.000000</td>\n",
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       "      <th>mean</th>\n",
       "      <td>55779.067073</td>\n",
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       "      <th>std</th>\n",
       "      <td>10299.670911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>40307.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>46786.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>52997.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>63826.250000</td>\n",
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       "       Consomation eletric\n",
       "count           164.000000\n",
       "mean          55779.067073\n",
       "std           10299.670911\n",
       "min           40307.000000\n",
       "25%           46786.000000\n",
       "50%           52997.500000\n",
       "75%           63826.250000\n",
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   "source": [
    "df.describe()"
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   "execution_count": null,
   "id": "6042bf5e",
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