Exploratory_Data_Analysis_BCG.ipynb

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      "source": [
        "# Exploratory Data Analysis\n",
        "1.Gathering Data\n",
        "2.Accessing Data\n",
        "3.Cleaning Data\n"
      ],
      "metadata": {
        "id": "2vvLWFURFzrY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Import Package**\n",
        "\n",
        "1.Import pandas and numpy for data analysis.\n",
        "2.Import seaborn and matplotlib for data visualisation.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
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        "id": "0xnhjtbpHRMi"
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    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "metadata": {
        "id": "4M9m5VQHF9KK"
      },
      "execution_count": 6,
      "outputs": []
    },
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      "cell_type": "code",
      "source": [
        "# Shows plot in notebook\n",
        "sns.set(color_codes=True)"
      ],
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        "id": "b4s43Qo5HO2J"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# remove warning\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "metadata": {
        "id": "CNxiskKnI7Mm"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Loading data with pandas\n",
        "We need to load clent_data.csv and price_data.csv into individual dataframe."
      ],
      "metadata": {
        "id": "0K4CkxN_CkA5"
      }
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      "cell_type": "code",
      "source": [
        "client_df = pd.read_csv(\"/content/client_data.csv\")\n",
        "price_df = pd.read_csv(\"price_data.csv\")"
      ],
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        "id": "1VmkecrZ_yOp"
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      "execution_count": 9,
      "outputs": []
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      "source": [
        "# you can view the 1st 5 rows of a dataframe using head method.\n",
        "client_df.head(5)"
      ],
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              "                                 id                     channel_sales  \\\n",
              "0  24011ae4ebbe3035111d65fa7c15bc57  foosdfpfkusacimwkcsosbicdxkicaua   \n",
              "1  d29c2c54acc38ff3c0614d0a653813dd                           MISSING   \n",
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              "4  149d57cf92fc41cf94415803a877cb4b                           MISSING   \n",
              "\n",
              "   cons_12m  cons_gas_12m  cons_last_month  date_activ    date_end  \\\n",
              "0         0         54946                0  2013-06-15  2016-06-15   \n",
              "1      4660             0                0  2009-08-21  2016-08-30   \n",
              "2       544             0                0  2010-04-16  2016-04-16   \n",
              "3      1584             0                0  2010-03-30  2016-03-30   \n",
              "4      4425             0              526  2010-01-13  2016-03-07   \n",
              "\n",
              "  date_modif_prod date_renewal  forecast_cons_12m  ...  has_gas  imp_cons  \\\n",
              "0      2015-11-01   2015-06-23               0.00  ...        t      0.00   \n",
              "1      2009-08-21   2015-08-31             189.95  ...        f      0.00   \n",
              "2      2010-04-16   2015-04-17              47.96  ...        f      0.00   \n",
              "3      2010-03-30   2015-03-31             240.04  ...        f      0.00   \n",
              "4      2010-01-13   2015-03-09             445.75  ...        f     52.32   \n",
              "\n",
              "   margin_gross_pow_ele  margin_net_pow_ele  nb_prod_act  net_margin  \\\n",
              "0                 25.44               25.44            2      678.99   \n",
              "1                 16.38               16.38            1       18.89   \n",
              "2                 28.60               28.60            1        6.60   \n",
              "3                 30.22               30.22            1       25.46   \n",
              "4                 44.91               44.91            1       47.98   \n",
              "\n",
              "  num_years_antig                         origin_up  pow_max  churn  \n",
              "0               3  lxidpiddsbxsbosboudacockeimpuepw   43.648      1  \n",
              "1               6  kamkkxfxxuwbdslkwifmmcsiusiuosws   13.800      0  \n",
              "2               6  kamkkxfxxuwbdslkwifmmcsiusiuosws   13.856      0  \n",
              "3               6  kamkkxfxxuwbdslkwifmmcsiusiuosws   13.200      0  \n",
              "4               6  kamkkxfxxuwbdslkwifmmcsiusiuosws   19.800      0  \n",
              "\n",
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      "execution_count": 13,
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              "                                 id  price_date  price_off_peak_var  \\\n",
              "0  038af19179925da21a25619c5a24b745  2015-01-01            0.151367   \n",
              "1  038af19179925da21a25619c5a24b745  2015-02-01            0.151367   \n",
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              "3  038af19179925da21a25619c5a24b745  2015-04-01            0.149626   \n",
              "4  038af19179925da21a25619c5a24b745  2015-05-01            0.149626   \n",
              "\n",
              "   price_peak_var  price_mid_peak_var  price_off_peak_fix  price_peak_fix  \\\n",
              "0             0.0                 0.0           44.266931             0.0   \n",
              "1             0.0                 0.0           44.266931             0.0   \n",
              "2             0.0                 0.0           44.266931             0.0   \n",
              "3             0.0                 0.0           44.266931             0.0   \n",
              "4             0.0                 0.0           44.266931             0.0   \n",
              "\n",
              "   price_mid_peak_fix  \n",
              "0                 0.0  \n",
              "1                 0.0  \n",
              "2                 0.0  \n",
              "3                 0.0  \n",
              "4                 0.0  "
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              "      <th>3</th>\n",
              "      <td>038af19179925da21a25619c5a24b745</td>\n",
              "      <td>2015-04-01</td>\n",
              "      <td>0.149626</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>44.266931</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>038af19179925da21a25619c5a24b745</td>\n",
              "      <td>2015-05-01</td>\n",
              "      <td>0.149626</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>44.266931</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "    .colab-df-container {\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Descriptive statistic of data**\n",
        "\n",
        "It is useful to first understand the data that you're dealing with along with the data types of each column. "
      ],
      "metadata": {
        "id": "MremFHrHGt6f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "client_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vhQtO-3nE4s4",
        "outputId": "bfda5d67-7513-4c53-e656-85b7270f68a1"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 14606 entries, 0 to 14605\n",
            "Data columns (total 26 columns):\n",
            " #   Column                          Non-Null Count  Dtype  \n",
            "---  ------                          --------------  -----  \n",
            " 0   id                              14606 non-null  object \n",
            " 1   channel_sales                   14606 non-null  object \n",
            " 2   cons_12m                        14606 non-null  int64  \n",
            " 3   cons_gas_12m                    14606 non-null  int64  \n",
            " 4   cons_last_month                 14606 non-null  int64  \n",
            " 5   date_activ                      14606 non-null  object \n",
            " 6   date_end                        14606 non-null  object \n",
            " 7   date_modif_prod                 14606 non-null  object \n",
            " 8   date_renewal                    14606 non-null  object \n",
            " 9   forecast_cons_12m               14606 non-null  float64\n",
            " 10  forecast_cons_year              14606 non-null  int64  \n",
            " 11  forecast_discount_energy        14606 non-null  float64\n",
            " 12  forecast_meter_rent_12m         14606 non-null  float64\n",
            " 13  forecast_price_energy_off_peak  14606 non-null  float64\n",
            " 14  forecast_price_energy_peak      14606 non-null  float64\n",
            " 15  forecast_price_pow_off_peak     14606 non-null  float64\n",
            " 16  has_gas                         14606 non-null  object \n",
            " 17  imp_cons                        14606 non-null  float64\n",
            " 18  margin_gross_pow_ele            14606 non-null  float64\n",
            " 19  margin_net_pow_ele              14606 non-null  float64\n",
            " 20  nb_prod_act                     14606 non-null  int64  \n",
            " 21  net_margin                      14606 non-null  float64\n",
            " 22  num_years_antig                 14606 non-null  int64  \n",
            " 23  origin_up                       14606 non-null  object \n",
            " 24  pow_max                         14606 non-null  float64\n",
            " 25  churn                           14606 non-null  int64  \n",
            "dtypes: float64(11), int64(7), object(8)\n",
            "memory usage: 2.9+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "convert the date_active,date_end,date_modif_prod,date_renewal into datetime"
      ],
      "metadata": {
        "id": "oCmc_1i-IjoP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "date=[\"date_activ\", \"date_end\", \"date_modif_prod\", \"date_renewal\"]"
      ],
      "metadata": {
        "id": "CCtfhOs5HJGO"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for i in date:\n",
        "  client_df[i] = pd.to_datetime(client_df[i])"
      ],
      "metadata": {
        "id": "rdQwO5T-JH6K"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "client_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pkokrj_SJXON",
        "outputId": "e1b970a3-b14c-44fa-f4e7-c4ee0d851bf5"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 14606 entries, 0 to 14605\n",
            "Data columns (total 26 columns):\n",
            " #   Column                          Non-Null Count  Dtype         \n",
            "---  ------                          --------------  -----         \n",
            " 0   id                              14606 non-null  object        \n",
            " 1   channel_sales                   14606 non-null  object        \n",
            " 2   cons_12m                        14606 non-null  int64         \n",
            " 3   cons_gas_12m                    14606 non-null  int64         \n",
            " 4   cons_last_month                 14606 non-null  int64         \n",
            " 5   date_activ                      14606 non-null  datetime64[ns]\n",
            " 6   date_end                        14606 non-null  datetime64[ns]\n",
            " 7   date_modif_prod                 14606 non-null  datetime64[ns]\n",
            " 8   date_renewal                    14606 non-null  datetime64[ns]\n",
            " 9   forecast_cons_12m               14606 non-null  float64       \n",
            " 10  forecast_cons_year              14606 non-null  int64         \n",
            " 11  forecast_discount_energy        14606 non-null  float64       \n",
            " 12  forecast_meter_rent_12m         14606 non-null  float64       \n",
            " 13  forecast_price_energy_off_peak  14606 non-null  float64       \n",
            " 14  forecast_price_energy_peak      14606 non-null  float64       \n",
            " 15  forecast_price_pow_off_peak     14606 non-null  float64       \n",
            " 16  has_gas                         14606 non-null  object        \n",
            " 17  imp_cons                        14606 non-null  float64       \n",
            " 18  margin_gross_pow_ele            14606 non-null  float64       \n",
            " 19  margin_net_pow_ele              14606 non-null  float64       \n",
            " 20  nb_prod_act                     14606 non-null  int64         \n",
            " 21  net_margin                      14606 non-null  float64       \n",
            " 22  num_years_antig                 14606 non-null  int64         \n",
            " 23  origin_up                       14606 non-null  object        \n",
            " 24  pow_max                         14606 non-null  float64       \n",
            " 25  churn                           14606 non-null  int64         \n",
            "dtypes: datetime64[ns](4), float64(11), int64(7), object(4)\n",
            "memory usage: 2.9+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "price_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5dlR3ndWJkjk",
        "outputId": "3fe2b300-e279-4cd5-d648-c57520165572"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 193002 entries, 0 to 193001\n",
            "Data columns (total 8 columns):\n",
            " #   Column              Non-Null Count   Dtype  \n",
            "---  ------              --------------   -----  \n",
            " 0   id                  193002 non-null  object \n",
            " 1   price_date          193002 non-null  object \n",
            " 2   price_off_peak_var  193002 non-null  float64\n",
            " 3   price_peak_var      193002 non-null  float64\n",
            " 4   price_mid_peak_var  193002 non-null  float64\n",
            " 5   price_off_peak_fix  193002 non-null  float64\n",
            " 6   price_peak_fix      193002 non-null  float64\n",
            " 7   price_mid_peak_fix  193002 non-null  float64\n",
            "dtypes: float64(6), object(2)\n",
            "memory usage: 11.8+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "price_df[\"price_date\"] = pd.to_datetime(price_df[\"price_date\"])"
      ],
      "metadata": {
        "id": "CopjXB1hJpQ9"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# see the data shape of dataset\n",
        "client_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fakYcFSDJ207",
        "outputId": "32c03431-9fdf-4e8d-ac8f-7d41bb0cf7d1"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(14606, 26)"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "price_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wFNCE-mkKC7t",
        "outputId": "7b1c36cc-103a-4b6e-abb1-000663b77938"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(193002, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "client_df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "id": "ao6Z1IscKGbF",
        "outputId": "9af8092d-dc76-4a8e-fee1-99d4ef32ba6a"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           cons_12m  cons_gas_12m  cons_last_month  forecast_cons_12m  \\\n",
              "count  1.460600e+04  1.460600e+04     14606.000000       14606.000000   \n",
              "mean   1.592203e+05  2.809238e+04     16090.269752        1868.614880   \n",
              "std    5.734653e+05  1.629731e+05     64364.196422        2387.571531   \n",
              "min    0.000000e+00  0.000000e+00         0.000000           0.000000   \n",
              "25%    5.674750e+03  0.000000e+00         0.000000         494.995000   \n",
              "50%    1.411550e+04  0.000000e+00       792.500000        1112.875000   \n",
              "75%    4.076375e+04  0.000000e+00      3383.000000        2401.790000   \n",
              "max    6.207104e+06  4.154590e+06    771203.000000       82902.830000   \n",
              "\n",
              "       forecast_cons_year  forecast_discount_energy  forecast_meter_rent_12m  \\\n",
              "count        14606.000000              14606.000000             14606.000000   \n",
              "mean          1399.762906                  0.966726                63.086871   \n",
              "std           3247.786255                  5.108289                66.165783   \n",
              "min              0.000000                  0.000000                 0.000000   \n",
              "25%              0.000000                  0.000000                16.180000   \n",
              "50%            314.000000                  0.000000                18.795000   \n",
              "75%           1745.750000                  0.000000               131.030000   \n",
              "max         175375.000000                 30.000000               599.310000   \n",
              "\n",
              "       forecast_price_energy_off_peak  forecast_price_energy_peak  \\\n",
              "count                    14606.000000                14606.000000   \n",
              "mean                         0.137283                    0.050491   \n",
              "std                          0.024623                    0.049037   \n",
              "min                          0.000000                    0.000000   \n",
              "25%                          0.116340                    0.000000   \n",
              "50%                          0.143166                    0.084138   \n",
              "75%                          0.146348                    0.098837   \n",
              "max                          0.273963                    0.195975   \n",
              "\n",
              "       forecast_price_pow_off_peak      imp_cons  margin_gross_pow_ele  \\\n",
              "count                 14606.000000  14606.000000          14606.000000   \n",
              "mean                     43.130056    152.786896             24.565121   \n",
              "std                       4.485988    341.369366             20.231172   \n",
              "min                       0.000000      0.000000              0.000000   \n",
              "25%                      40.606701      0.000000             14.280000   \n",
              "50%                      44.311378     37.395000             21.640000   \n",
              "75%                      44.311378    193.980000             29.880000   \n",
              "max                      59.266378  15042.790000            374.640000   \n",
              "\n",
              "       margin_net_pow_ele   nb_prod_act    net_margin  num_years_antig  \\\n",
              "count        14606.000000  14606.000000  14606.000000     14606.000000   \n",
              "mean            24.562517      1.292346    189.264522         4.997809   \n",
              "std             20.230280      0.709774    311.798130         1.611749   \n",
              "min              0.000000      1.000000      0.000000         1.000000   \n",
              "25%             14.280000      1.000000     50.712500         4.000000   \n",
              "50%             21.640000      1.000000    112.530000         5.000000   \n",
              "75%             29.880000      1.000000    243.097500         6.000000   \n",
              "max            374.640000     32.000000  24570.650000        13.000000   \n",
              "\n",
              "            pow_max         churn  \n",
              "count  14606.000000  14606.000000  \n",
              "mean      18.135136      0.097152  \n",
              "std       13.534743      0.296175  \n",
              "min        3.300000      0.000000  \n",
              "25%       12.500000      0.000000  \n",
              "50%       13.856000      0.000000  \n",
              "75%       19.172500      0.000000  \n",
              "max      320.000000      1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-aa3c0d6d-9123-4168-9473-baedba10dd16\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>cons_12m</th>\n",
              "      <th>cons_gas_12m</th>\n",
              "      <th>cons_last_month</th>\n",
              "      <th>forecast_cons_12m</th>\n",
              "      <th>forecast_cons_year</th>\n",
              "      <th>forecast_discount_energy</th>\n",
              "      <th>forecast_meter_rent_12m</th>\n",
              "      <th>forecast_price_energy_off_peak</th>\n",
              "      <th>forecast_price_energy_peak</th>\n",
              "      <th>forecast_price_pow_off_peak</th>\n",
              "      <th>imp_cons</th>\n",
              "      <th>margin_gross_pow_ele</th>\n",
              "      <th>margin_net_pow_ele</th>\n",
              "      <th>nb_prod_act</th>\n",
              "      <th>net_margin</th>\n",
              "      <th>num_years_antig</th>\n",
              "      <th>pow_max</th>\n",
              "      <th>churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1.460600e+04</td>\n",
              "      <td>1.460600e+04</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "      <td>14606.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.592203e+05</td>\n",
              "      <td>2.809238e+04</td>\n",
              "      <td>16090.269752</td>\n",
              "      <td>1868.614880</td>\n",
              "      <td>1399.762906</td>\n",
              "      <td>0.966726</td>\n",
              "      <td>63.086871</td>\n",
              "      <td>0.137283</td>\n",
              "      <td>0.050491</td>\n",
              "      <td>43.130056</td>\n",
              "      <td>152.786896</td>\n",
              "      <td>24.565121</td>\n",
              "      <td>24.562517</td>\n",
              "      <td>1.292346</td>\n",
              "      <td>189.264522</td>\n",
              "      <td>4.997809</td>\n",
              "      <td>18.135136</td>\n",
              "      <td>0.097152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>5.734653e+05</td>\n",
              "      <td>1.629731e+05</td>\n",
              "      <td>64364.196422</td>\n",
              "      <td>2387.571531</td>\n",
              "      <td>3247.786255</td>\n",
              "      <td>5.108289</td>\n",
              "      <td>66.165783</td>\n",
              "      <td>0.024623</td>\n",
              "      <td>0.049037</td>\n",
              "      <td>4.485988</td>\n",
              "      <td>341.369366</td>\n",
              "      <td>20.231172</td>\n",
              "      <td>20.230280</td>\n",
              "      <td>0.709774</td>\n",
              "      <td>311.798130</td>\n",
              "      <td>1.611749</td>\n",
              "      <td>13.534743</td>\n",
              "      <td>0.296175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.300000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>5.674750e+03</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>494.995000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>16.180000</td>\n",
              "      <td>0.116340</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>40.606701</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>14.280000</td>\n",
              "      <td>14.280000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>50.712500</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>12.500000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.411550e+04</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>792.500000</td>\n",
              "      <td>1112.875000</td>\n",
              "      <td>314.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>18.795000</td>\n",
              "      <td>0.143166</td>\n",
              "      <td>0.084138</td>\n",
              "      <td>44.311378</td>\n",
              "      <td>37.395000</td>\n",
              "      <td>21.640000</td>\n",
              "      <td>21.640000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>112.530000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>13.856000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>4.076375e+04</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>3383.000000</td>\n",
              "      <td>2401.790000</td>\n",
              "      <td>1745.750000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>131.030000</td>\n",
              "      <td>0.146348</td>\n",
              "      <td>0.098837</td>\n",
              "      <td>44.311378</td>\n",
              "      <td>193.980000</td>\n",
              "      <td>29.880000</td>\n",
              "      <td>29.880000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>243.097500</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>19.172500</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>6.207104e+06</td>\n",
              "      <td>4.154590e+06</td>\n",
              "      <td>771203.000000</td>\n",
              "      <td>82902.830000</td>\n",
              "      <td>175375.000000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>599.310000</td>\n",
              "      <td>0.273963</td>\n",
              "      <td>0.195975</td>\n",
              "      <td>59.266378</td>\n",
              "      <td>15042.790000</td>\n",
              "      <td>374.640000</td>\n",
              "      <td>374.640000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>24570.650000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>320.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aa3c0d6d-9123-4168-9473-baedba10dd16')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-aa3c0d6d-9123-4168-9473-baedba10dd16 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-aa3c0d6d-9123-4168-9473-baedba10dd16');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "price_df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "rajWKg_eKMR5",
        "outputId": "17e25aee-227a-4983-ae9d-d822b25ccc83"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       price_off_peak_var  price_peak_var  price_mid_peak_var  \\\n",
              "count       193002.000000   193002.000000       193002.000000   \n",
              "mean             0.141027        0.054630            0.030496   \n",
              "std              0.025032        0.049924            0.036298   \n",
              "min              0.000000        0.000000            0.000000   \n",
              "25%              0.125976        0.000000            0.000000   \n",
              "50%              0.146033        0.085483            0.000000   \n",
              "75%              0.151635        0.101673            0.072558   \n",
              "max              0.280700        0.229788            0.114102   \n",
              "\n",
              "       price_off_peak_fix  price_peak_fix  price_mid_peak_fix  \n",
              "count       193002.000000   193002.000000       193002.000000  \n",
              "mean            43.334477       10.622875            6.409984  \n",
              "std              5.410297       12.841895            7.773592  \n",
              "min              0.000000        0.000000            0.000000  \n",
              "25%             40.728885        0.000000            0.000000  \n",
              "50%             44.266930        0.000000            0.000000  \n",
              "75%             44.444710       24.339581           16.226389  \n",
              "max             59.444710       36.490692           17.458221  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5a13a117-b689-466c-9fc9-2206b6d7ec2c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\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>price_off_peak_var</th>\n",
              "      <th>price_peak_var</th>\n",
              "      <th>price_mid_peak_var</th>\n",
              "      <th>price_off_peak_fix</th>\n",
              "      <th>price_peak_fix</th>\n",
              "      <th>price_mid_peak_fix</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>193002.000000</td>\n",
              "      <td>193002.000000</td>\n",
              "      <td>193002.000000</td>\n",
              "      <td>193002.000000</td>\n",
              "      <td>193002.000000</td>\n",
              "      <td>193002.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.141027</td>\n",
              "      <td>0.054630</td>\n",
              "      <td>0.030496</td>\n",
              "      <td>43.334477</td>\n",
              "      <td>10.622875</td>\n",
              "      <td>6.409984</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.025032</td>\n",
              "      <td>0.049924</td>\n",
              "      <td>0.036298</td>\n",
              "      <td>5.410297</td>\n",
              "      <td>12.841895</td>\n",
              "      <td>7.773592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.125976</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>40.728885</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.146033</td>\n",
              "      <td>0.085483</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.266930</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.151635</td>\n",
              "      <td>0.101673</td>\n",
              "      <td>0.072558</td>\n",
              "      <td>44.444710</td>\n",
              "      <td>24.339581</td>\n",
              "      <td>16.226389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>0.280700</td>\n",
              "      <td>0.229788</td>\n",
              "      <td>0.114102</td>\n",
              "      <td>59.444710</td>\n",
              "      <td>36.490692</td>\n",
              "      <td>17.458221</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5a13a117-b689-466c-9fc9-2206b6d7ec2c')\"\n",
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              "              style=\"display:none;\">\n",
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              "\n",
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              "\n",
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              "          document.querySelector('#df-5a13a117-b689-466c-9fc9-2206b6d7ec2c button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5a13a117-b689-466c-9fc9-2206b6d7ec2c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Missing Data"
      ],
      "metadata": {
        "id": "7Jz5k1a9KTSu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# check how much of our data is missing\n",
        "# pd.DataFrame({\"Missing value (%)\": client_df.isnull().sum()/len(client_df.index)*100})\n",
        "client_df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X7si5WHlKQ_S",
        "outputId": "5fc557b3-9fd7-4542-e27c-5eb70ea89e84"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                                0\n",
              "channel_sales                     0\n",
              "cons_12m                          0\n",
              "cons_gas_12m                      0\n",
              "cons_last_month                   0\n",
              "date_activ                        0\n",
              "date_end                          0\n",
              "date_modif_prod                   0\n",
              "date_renewal                      0\n",
              "forecast_cons_12m                 0\n",
              "forecast_cons_year                0\n",
              "forecast_discount_energy          0\n",
              "forecast_meter_rent_12m           0\n",
              "forecast_price_energy_off_peak    0\n",
              "forecast_price_energy_peak        0\n",
              "forecast_price_pow_off_peak       0\n",
              "has_gas                           0\n",
              "imp_cons                          0\n",
              "margin_gross_pow_ele              0\n",
              "margin_net_pow_ele                0\n",
              "nb_prod_act                       0\n",
              "net_margin                        0\n",
              "num_years_antig                   0\n",
              "origin_up                         0\n",
              "pow_max                           0\n",
              "churn                             0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "price_df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NOZ6pqsRLTJr",
        "outputId": "add294e9-b31d-48ce-f431-d6bda73e9019"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                    0\n",
              "price_date            0\n",
              "price_off_peak_var    0\n",
              "price_peak_var        0\n",
              "price_mid_peak_var    0\n",
              "price_off_peak_fix    0\n",
              "price_peak_fix        0\n",
              "price_mid_peak_fix    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Data Visualisation\n",
        "## churn Percentage"
      ],
      "metadata": {
        "id": "LQA1jaRqMkNH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "churn=client_df[['id','churn']]\n",
        "churn.columns=['Companies','churn']\n",
        "churn_total=churn.groupby(churn['churn']).count()\n",
        "churn_percentage=churn_total/churn_total.sum()*100"
      ],
      "metadata": {
        "id": "OXnUD41zMfAn"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_percentage"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "gxCX83anNena",
        "outputId": "90a0d0fb-a2a7-491e-a77a-017afdfd9270"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Companies\n",
              "churn           \n",
              "0      90.284814\n",
              "1       9.715186"
            ],
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              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Companies</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>churn</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>90.284814</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>9.715186</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7bedc721-a9c9-42f1-b371-46f0ba8dea8b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7bedc721-a9c9-42f1-b371-46f0ba8dea8b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7bedc721-a9c9-42f1-b371-46f0ba8dea8b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def annotate_stacked_bars(ax, pad=0.99, colour=\"white\", textsize=13):\n",
        "    \n",
        "\n",
        "    # Iterate over the plotted rectanges/bars\n",
        "    for p in ax.patches:\n",
        "        \n",
        "        # Calculate annotation\n",
        "        value = str(round(p.get_height(),1))\n",
        "        # If value is 0 do not annotate\n",
        "        if value == '0.0':\n",
        "            continue\n",
        "        ax.annotate(\n",
        "            value,\n",
        "            ((p.get_x()+ p.get_width()/2)*pad-0.05, (p.get_y()+p.get_height()/2)*pad),\n",
        "            color=colour,\n",
        "            size=textsize\n",
        "        )"
      ],
      "metadata": {
        "id": "7WDyZrJBNiM5"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ax=churn_percentage.transpose().plot(kind='bar',stacked=True,figsize=(8,6),rot=0)\n",
        "annotate_stacked_bars(ax, textsize=14)\n",
        "plt.legend(['Retention','Churn'],loc='upper right')\n",
        "plt.ylabel('Company base(%')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "KXzvLTIpPT49",
        "outputId": "8f1a71da-bc46-4527-e11a-9c9c2b99b748"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Company base(%')"
            ]
          },
          "metadata": {},
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Consumption**\n",
        "\n",
        "consumption of customer during the last month, 12 months against the churn"
      ],
      "metadata": {
        "id": "ujwVaubiWHSY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "consumption = client_df[[\"cons_12m\", \"cons_gas_12m\", \"cons_last_month\", \"imp_cons\"]]"
      ],
      "metadata": {
        "id": "_dm0-Nv7Pakl"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for col in consumption:\n",
        "  client_df.boxplot(column=col, by=\"churn\", figsize=(5,5))\n",
        "  plt.title(col)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "_fmqVwlXWwxq",
        "outputId": "ff69ac2a-8bd0-4341-e296-1c1c0cbc6293"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "consumption = client_df[[\"cons_12m\", \"cons_gas_12m\", \"cons_last_month\", \"imp_cons\", \"has_gas\", \"churn\"]]"
      ],
      "metadata": {
        "id": "yjiaQICJXJFL"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_distribution(dataframe, column, ax, bins_=50):\n",
        "    \"\"\"\n",
        "    Plot variable distirbution in a stacked histogram of churned or retained company\n",
        "    \"\"\"\n",
        "    # Create a temporal dataframe with the data to be plot\n",
        "    temp = pd.DataFrame({\"Retention\": dataframe[dataframe[\"churn\"]==0][column],\n",
        "    \"Churn\":dataframe[dataframe[\"churn\"]==1][column]})\n",
        "    # Plot the histogram\n",
        "    temp[[\"Retention\",\"Churn\"]].plot(kind='hist', bins=bins_, ax=ax, stacked=True)\n",
        "    # X-axis label\n",
        "    ax.set_xlabel(column)\n",
        "    # Change the x-axis to plain style\n",
        "    ax.ticklabel_format(style='plain', axis='x')"
      ],
      "metadata": {
        "id": "zJIDS4XxXeeY"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig, axs = plt.subplots(nrows=4, figsize=(18, 25))\n",
        "\n",
        "plot_distribution(consumption, 'cons_12m', axs[0])\n",
        "plot_distribution(consumption[consumption['has_gas'] == 't'], 'cons_gas_12m', axs[1])\n",
        "plot_distribution(consumption, 'cons_last_month', axs[2])\n",
        "plot_distribution(consumption, 'imp_cons', axs[3])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "V29RnxzgXlb_",
        "outputId": "2e0b5324-2c7a-4e77-e2a6-5d8a5ce07e8e"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1296x1800 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Forecast**"
      ],
      "metadata": {
        "id": "2fqBDVwzX8BG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "forecast = client_df[[\"forecast_cons_12m\", \"forecast_cons_year\",\"forecast_discount_energy\",\"forecast_meter_rent_12m\",\n",
        "    \"forecast_price_energy_off_peak\",\"forecast_price_energy_peak\", \"forecast_price_pow_off_peak\"]]"
      ],
      "metadata": {
        "id": "UnJMWo3OX5jO"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for col in forecast:\n",
        "    client_df.boxplot(column=col, by='churn', figsize=(6,6))\n",
        "    plt.title(col)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "xiZEYSFwYNwX",
        "outputId": "704748b7-7dab-43b4-f77e-9f0a51d32f3c"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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D7wDgX//6F5588kn06tULL730Es6fPw8AeO655wBAPtyWmZkJANi5cyeGDx8OrVaLiIgI/P777/K6goODsXLlSoSFhcHPz8/kF35N8x4+fBgRERHQarUYNmwYcnJy5PnHjh2L5ORkREREwN/fXx6aFYD8kMJevXrB39//tsd636pdu3Z47rnn0L179xrbp02bBm9vbygUCjz66KPo2bOn/Lj1O/l8yUKZbew4smhjxoyRh+qcMWOGNHnyZKmsrEw6e/asNHjwYLltw4YNko+Pj/T5559Ler1eKi8vlxYuXChNmjRJ+uOPP6SysjJp0qRJ8lCPP/30k9SjRw8pOztbMhgM0oULF6Tjx49LkiRJO3fulE6fPi0ZjUYpJydH8vX1lY4cOSJJ0s1hKGfPni1VVlZKlZWV0oEDBySj0ShJ0s2hI7/77rs631P1UJGzZ8+Wbty4Ie3du1fq1q2bNGXKFOny5cvShQsXpD59+kg5OTmSJEnSv//9b2nQoEHS8ePHJb1eL6Wmpkrh4eHy+m4dtlOSJOnXX3+V+vTpIx0+fFiqqqqSdDqdNGDAAHmI0AEDBkjDhg2TCgoKpPLycpO1/nneCxcuSL1795Z27dolGQwGKTs7W+rdu7c8NOqYMWOkgQMHSidPnpTKy8ulMWPGSEuWLBHet16vr/MzqqbX6yW1Wi2dPXu21nnKy8ulxx9/XNq9e/cdfb5kudhjIJMMBgMyMzPx5ptvwtnZGR07dsSLL76IzZs3y/N4eHhg7NixsLW1hb29PdavX4/Y2Fi4uLjA2dkZkyZNwtatWwHc/A386aefxuOPPw6FQgFPT095MJn+/fujU6dOsLGxQe/evfH444/L4x7Y2tqiqKgIBQUFsLOzg1arrfeobX/26quvwt7eHoGBgXByckJoaCjc3Nzg6ekJrVYrDyKzbt06TJw4Ed7e3rC1tcXkyZPx22+/yb2GP/v6668RHh6ORx99FEqlEiNGjICdnZ0wgNHYsWOhUqng4OBQZ523zpueno6goCD069cPCoUCjz/+OLp164bdu3fL848cORIPPPAAHBwcMGTIEPz222939PnUV3x8PDQaDfr27StMr+/nS5aLD9Ejk/744w/o9Xp4eXnJ07y8vHDx4kX59a2P2i4pKUF5eTlGjhwpT5MkST70VFhYiH79+tW4rd27dyM1NRX5+fkwGo24ceMG1Go1AOCll17CsmXL5IFnwsPDMXHixDt6T25ubvLf7e3tb3t9/fp1ADfPsyQkJCAxMVF4LxcvXqxxzOuCggJs2rQJ//znP+Vper1eGL1MpVLVu85b5y0oKMA333yDnTt3ytOqqqqEYULd3d3lvzs6OsrvoykkJibi2LFj+Pzzz28L6Pp+vmS5GAxkUtu2bWFnZ4eCggJ06dIFwM0v91sH4Ln1i6Ft27ZwcHDA1q1baxykR6VS1ThAS2VlJaZNm4bExEQMHDgQdnZ2eOWVV+SxfZ2dnRETE4OYmBjk5eXh+eefR/fu3fHYY4819lsWap08eXK9x0Wunn/KlCm1ztOQXs6t86pUKgwfPhwLFiyo9/J3ss36+OCDD7B3716sXbuWT2m9R/FQEpmkVCoxZMgQvP/++7h69SrOnz+PTz/9tNYvS4VCgWeffRYJCQkoLi4GAFy8eBF79+4FADzzzDPQ6XTYv38/jEYjLl68iBMnTqCyshKVlZVwdXWFra0tdu/eje+++05e786dO3H69GlIkoRWrVpBqVTKX3jt2rXD2bNnG/29R0REYOXKlTh27BgAoKysDNu2bZPb/7zdZ599FuvWrcNPP/0ESZJw/fp17Nq1SxgH+k4NGzYMO3fuxN69e2EwGFBRUYGcnBxcuHChzmVdXV2hUCjq/RlVVFSgsrISwM3Arh4fHAA++ugjZGRk4NNPP0Xbtm3v7M2QxWMwUJ1mz54NR0dHDBo0CJGRkQgNDTU50MuMGTNw//33Y9SoUejRowdeeOEFedxiX19fLFq0CAkJCejZsyfGjBmDgoICODs74+2330ZUVBR69eqFjIwMYeS106dP48UXX4S/vz/Cw8MxevRo9OnTBwAwceJEfPjhh9BqtVi1alWjve8nnngCEyZMwBtvvIEePXogNDRUvoIKAKZOnYqYmBhotVpkZmaie/fumD9/PubNm4devXph8ODB0Ol0jVKLSqXC8uXL8dFHH+Gxxx5Dv379sGrVKvkQnSmOjo6YPHkyRo8eDa1WK5zzqImvry/8/f0BAE8++SR8fX3ltvfeew8FBQXyvQz+/v5YsWLFX3tzZHE4HgMREQnYYyAiIgFPPtM9ZfPmzYiPj79tupeXl3zJrCUoKCjA3//+9xrbtm7dKlwF1tji4uKwZcuW26aHhYXxBjQCwENJRET0JzyUREREAos+lPTHH9dgNLJD05jc3JxRXPzXL58kai7cZxufQmGDtm1b1tpu0cFgNEoMhibAz5TuNtxnmxcPJRERkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCSoVzBUVFQgPj4egwcPRlhYGGbPng0AOHXqFMLDwxESEoLw8HDk5+fLy5hqIyIiy1WvYFiyZAns7e2RlZWFLVu24PXXXwdwczDwyMhIZGVlITIyEnFxcfIyptqo+fn5+cDDozVsbGzg4dEafn4+5i6JiCxUncFw7do1bNq0Ca+//rowlGJxcTFyc3MRGhoKAAgNDUVubi5KSkpMtlHz8/PzQUHBeWi1vVFQUPD/P88zHIioRnU+K+ns2bNwcXHBsmXLkJOTg5YtW+L111+Hg4MDPD09oVQqAdwcG9jDwwOFhYWQJKnWNldX16Z9R3Sb6lDIzPwW7u6tkJn5LYYOHYSDB38wd2lEZIHqDAaDwYCzZ8/i4YcfxltvvYWffvoJkydPxtKlS5u8ODc35ybfhrXYvHkT3N1bAQDc3Vth8+ZN8PLykqcRWTLup82rzmBQqVSwtbWVDws9+uijaNu2LRwcHHDx4kUYDAYolUoYDAZcunQJKpUKkiTV2tYQxcVX+VTFRjJs2FNyj6GoqAzDhj0FACgqKjNzZUSmVe+z1HgUChuTv3jXeY7B1dUVAQEB+O677wDcvNqouLgYnTt3ho+PDzIyMgAAGRkZ8PHxgaurK9zc3Gpto+bn5dUBBw/+gKFDB6GwsFA+jOTl1cHcpRGRBarX0J5nz55FbGwsSktLYWtri6ioKPTr1w8nTpxATEwMrly5gtatWyMxMREPPvggAJhsqy/2GBpP9Qnoal5eHXD48G9mrIiofthjaHx19RgsesxnBkPj0enSkJychLy8o1CrNYiKisbIkc+auyyiOjEYGl9dwWDRI7hR49Dp0pCQMB/JycsQGjoYGRnbERU1FQAYDkR0Gz4SwwokJychOXkZAgODYGdnh8DAICQnL0NycpK5SyMiC8RgsAJ5eUcREPCYMC0g4DHk5R01U0VEZMkYDFZArdYgJ2e/MC0nZz/Uao2ZKiIiS8ZgsAJRUdGIipqK7Ow90Ov1yM7eg6ioqYiKijZ3aURkgXjy2QpUn2COjZ2BZ54ZBrVag9jY2TzxTEQ14uWqVoaX/tHdhvts4/vLdz4TEZF1YTAQEZGAwUBERAIGg5XQ6dIQFBQApVKJoKAA6HRp5i6JiCwUr0qyAnwkBhE1BHsMVoCPxCCihmAwWAE+EoOIGoLBYAX4SAwiagieY7ACUVHRePnlF+Dk5ITz58+hQ4eOuH79OhYuTDR3aURkgdhjsBI2Njd/Vt/oXv2aiOjPGAxWIDk5CStXrsGhQ0dgNBpx6NARrFy5hiefyaLxEmvz4aEkK8CTz3S34SXW5sUegxXgyWe62/ASa/NiMFgBjsdAdxv2cs2Lh5KsAMdjoLtNdS83MDBInsZebvPheAxWhs+2p7tBbecY+AtN46hrPAb2GIjI4rCXa17sMVgZ9hjobsN9tvFxBDciImoQBgMREQkYDEREJGAwEBGRgMFAREQCBgMREQkYDEREJGAwEBGRgMFAREQCBgMREQkYDEREJGAwEBGRgMFAREQCBgMREQkYDEREJKjXQD3BwcFo0aIF7O3tAQDR0dHo27cvDh8+jLi4OFRUVKBDhw5YsmQJ3NzcAMBkGxERWa569xg++OADpKenIz09HX379oXRaMSMGTMQFxeHrKwsaLVaJCUlAYDJNiIismx3fCjpyJEjsLe3h1arBQBERETgm2++qbONiIgsW73HfI6OjoYkSejZsyfeeOMNFBYWwsvLS253dXWF0WhEaWmpyTYXF5fGfQdERNSo6hUMX3zxBVQqFSorK7Fw4ULMmzcPTzzxRFPXZnJMUrpz7u6tzF0CUYNwn21e9QoGlUoFAGjRogUiIyMxZcoUjBs3DgUFBfI8JSUlUCgUcHFxgUqlqrWtIYqLr8JolBq0DJnGgdXpbsN9tvEpFDYmf/Gu8xzD9evXUVZ28x9FkiRkZmbCx8cH3bp1w40bN3Dw4EEAwLp16zBkyBAAMNlGRESWrc4eQ3FxMV577TUYDAYYjUZ4e3sjPj4eCoUCixcvRnx8vHBJKgCTbUREZNlsJEmy2GM1PJTU+Ngtp7sN99nG95cPJRERkXVhMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBCRRdLp0hAUFAClUomgoADodGnmLslq2Jq7ACKiP9Pp0pCQMB/JycsQGjoYGRnbERU1FQAwcuSzZq7u3sceAxFZnOTkJCQnL0NgYBDs7OwQGBiE5ORlSE5OMndpVoHBYCXYLae7SV7eUQQEPCZMCwh4DHl5R81UkXVhMFiB6m55QsIS3LhxAwkJS5CQMJ/hQBZLrdYgJ2e/MC0nZz/Uao2ZKrIuDAYrwG453W2ioqIRFTUV2dl7oNfrkZ29B1FRUxEVFW3u0qyCjSRJkrmLqE1x8VUYjRZb3l2jfXsXnD1bBDs7O7i7t0JRURn0ej3uu88dFy6Umrs8ohrpdGlITk5CXt5RqNUaREVF88RzI1EobODm5lxrO69KsgLV3fLAwCB5GrvlZOlGjnwWI0c+K/8yQ82Hh5KsALvlRNQQ7DFYgerud2zsDDzzzDCo1RrExs5mt5yIasRzDFaG3XK623CfbXx1nWPgoSQiIhIwGIiISMBgICIiAYOBiIgEDAYiIhIwGKxE584qeHi0ho2NDTw8WqNzZ5W5SyIyadSop+Dp2QY2Njbw9GyDUaOeMndJVoPBYAU6d1bh+vVrwrTr168xHMhijRr1FHbt2oHnnx+P0tJSPP/8eOzatYPh0EwYDFagOhTmzk3AtWvXMHdugjCdyNLs3r0TL7zwEhYvfh9t2rTB4sXv44UXXsLu3TvNXZpVaFAwLFu2DBqNBnl5eQCAw4cPY9iwYQgJCcH48eNRXFwsz2uqjZrf1KnTMWXKVDg5OWHKlKmYOnW6uUsiqpUkSZg1a44wbdasObDg+3HvKfUOhl9//RWHDx9Ghw4dAABGoxEzZsxAXFwcsrKyoNVqkZSUVGcbmcfGjWkmXxNZEhsbGyxcOEeYtnDhHNjY2JinICtTr2CorKzEvHnzMGfOHHnakSNHYG9vD61WCwCIiIjAN998U2cbmcf58+fg5eUKpVIJLy9XnD9/ztwlEdWqX78BWLNmFWbOnI7//e9/mDlzOtasWYV+/QaYuzSrUK9gWLp0KYYNG4aOHTvK0woLC+Hl5SW/dnV1hdFoRGlpqck2an79+wcDAKqqqmA0GlFVVSVMJ7I069dvQv/+wfjss9VwcXHBZ5+tRv/+wVi/fpO5S7MKdT5d9ccff8SRI0cQHd38j2g29ZAnqr/jx/Pg5OQEvV4PvV4POzs72NnZ4fjxPLi7tzJ3eUQ12rnzP+YuwWrVGQwHDhzAiRMnMHDgQADAhQsX8NJLL2Hs2LEoKCiQ5yspKYFCoYCLiwtUKlWtbQ3Bp6s2jnPnziEkZKj8H83GRoG+ffsjKyuTT60ki8enqza+v/x01YkTJyI7Oxs7duzAjh070L59e6xatQoTJkzAjRs3cJVbixsAABKFSURBVPDgQQDAunXrMGTIEABAt27dam0j88jKypQPIVVVVSErK9PMFRGRpbrj+xgUCgUWL16MuXPnYvDgwThw4ADefPPNOtvIfMaNewGlpaUYN+4Fc5dCRBaMA/VYAQ+P1nB0dEK7du1w/vw5dOjQEZcvX0Z5+XVcunTF3OUR1UinS0NychLy8o5CrdYgKiqaow42Eg7UQwCAkJAn0bJlSwBAy5YtERLypJkrIqqdTpeGhIT5SEhYghs3biAhYQkSEuZDp+P9N82BwWAFFAoFNm/eiNGjx6KsrAyjR4/F5s0boVDwn58sU3JyEpKTlyEwMAh2dnYIDAxCcvIyJCfzRtnmwENJVuAf/4jG6tUfQ6FQwGAwQKlUwmg0Yvz4l7FoEf+jkeVp394FZ88Wwc7OTr4qSa/X47773HHhAu+H+qt4KImwaFES+vUbAKPRCODmI0v69RvAUCCLpVZrkJOzX5iWk7MfarXGTBVZFwaDFdDp0nDw4AEolTdvW1EqbXHw4AEeryWLFRUVjaioqcjO3gO9Xo/s7D2IipqKqKjmv9HWGvFQkhVQqzvhf//7H9zd3XH58mW0a9cORUVFaNOmDfLyzpi7PKIa8aqkplPXoSQGgxXw8GgNF5e2WL16LUJDByMjYzvGjx+L0tI/eLkqWTze+dz46gqGOh+JQfcGb+8uiIh4GpWVFWjRwh7du/vi0KED5i6LiCwQg8FKHDp0QL48tapKz1Agolrx5LMVqT4sx8NzRGQKg8GqSH/6SUR0OwYDEVkknS4NQUEBUCqVCAoK4OXVzYjnGIjI4uh0aZg8+SX59e+//ya/5iWrTY+Xq1oBD4/WtbbxclWyRNX7rJNTS+zduwd9+wbh+vVrALjPNgY+EoNkSqVS+ElkyRwdnZCfX4gePXogP78Qjo5O5i7JajAYrIjBYBB+ElmyESOeFs4xjBjxtLlLshoMBiKySF9+uVZ4VPyXX641d0lWg+cYrADPMdDdhvts0+I5BiIiahAGgxWpfiQGR26ju4GzszN0ugxUVlZCp8uAs3Ptv+FS4+I3hBVxdHQUfhJZsj9fhcSrkpoPg8GKXLt2TfhJZMkCA4MQGzsDDg4OiI2dgcDAIHOXZDUYDFbExcUFCoUCLi4u5i6FyCQXFxekp28UrkpKT9/IfbeZ8KokK8ArPOhuo9OlYcaMKJSX30BVlR62tnZwdHTAkiXJfCRGI+BVSQQvLy/Y2bUQptnZtYCXl5eZKiIybeTIZ7FkSTK6dOkChUKBLl26MBSaEXsMVkCnS8OsWW/ByckJ58+fQ4cOHXH9+nUsXJjI/2hk8Ti0Z+PjmM8EAOjY0R2VlRXy6xYt7HHuXJEZKyKqHwZD4+OhJELnziohFACgsrICnTurzFQREVkyBoMVqH5ccUjIkygqKkJIyJPCdCKiWzEYrIRa3RWnT+fD09MTp0/nQ63uau6SiMhCMRisxPHjeUhIWIIbN24gIWEJjh/PM3dJRGShGAxWwmg0Ytq0KThz5gymTZsCo9Fo7pKIyEJxzGcrcu7cWXTp0sXcZRCRhWOPwQp07eqDTp3uF6Z16nQ/unb1MVNFRHXT6dKEEdx0ujRzl2Q1GAxWICoqGoCN8AhjwOb/pxNZHp0uDQkJ84XzYgkJ8xkOzYQ3uFkJnS4NyclJyMs7CrVag6ioaN71TBYrKCgACQlLEBgYJN/glp29B7GxM7BnT465y7vr8QY3Irrr5OUdRUDAY8K0gIDHkJd31EwVWRcGgxVgt5zuNmq1Bjk5+4VpOTn7oVZrzFSRdWEwWIHk5CQkJy9DYGAQ7OzsEBgYhOTkZUhOTjJ3aUQ1ioqKRlTUVGRn74Fer0d29h5ERU3lebFmwnMMVqB9execPVsEOzs7+XitXq/Hffe548KFUnOXR1QjnhdrOnWdY+B9DFagult+69CI7JaTpRs58lmMHPksn65qBvU6lPTKK69g2LBheOqppxAZGYnffvsNAHDq1CmEh4cjJCQE4eHhyM/Pl5cx1UbNi91yImqIeh1KKisrQ6tWrQAA3377LVJTU7Fx40aMGzcOTz/9NIYPH4709HRs2LABn3/+OQCYbKsvHkpqPOyW092KPYbG1yiXq1aHAgBcvXoVNjY2KC4uRm5uLkJDQwEAoaGhyM3NRUlJick2Mo+RI5/Fnj05MBgM2LMnh6FARLWq9zmGWbNm4bvvvoMkSfjkk09QWFgIT09PKJVKAIBSqYSHhwcKCwshSVKtba6urvUuzlSikWnBwcE4erRh13xrNBrs2LGjiSoiunPu7q3qnokaTb2DYeHChQCATZs2YfHixXj99debrKhqPJR0577+Or3G6ePHR2L16i9rXY5ddrI0PJTU+Br9zuennnoKOTk5aN++PS5evAiDwQAAMBgMuHTpElQqFVQqVa1tRERk2eoMhmvXrqGwsFB+vWPHDrRp0wZubm7w8fFBRkYGACAjIwM+Pj5wdXU12UZERJatzkNJ5eXleP3111FeXg6FQoE2bdpgxYoVsLGxwZw5cxATE4Ply5ejdevWSExMlJcz1UZERJaLdz5bmbrOMRBZGp5jaHx8uioRETUIg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiJBnUN7EhE1taefDsOJE8catIy390PYsGFLE1Vk3RgMRGR2pr7gORxt8+OhJCIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEtQZDH/88QdefvllhISEICwsDFOnTkVJSQkA4PDhwxg2bBhCQkIwfvx4FBcXy8uZaiMiIstVZzDY2NhgwoQJyMrKwpYtW3DfffchKSkJRqMRM2bMQFxcHLKysqDVapGUlAQAJtuIiMiy1RkMLi4uCAgIkF/7+fmhoKAAR44cgb29PbRaLQAgIiIC33zzDQCYbCMiIstm25CZjUYjvvrqKwQHB6OwsBBeXl5ym6urK4xGI0pLS022ubi41Ht7bm7ODSmP6sndvZW5SyBqEO6zzatBwTB//nw4OTlhzJgx+Pe//91UNcmKi6/CaJSafDvWpqiozNwlEDUI99nGpVDYmPzFu97BkJiYiNOnT2PFihVQKBRQqVQoKCiQ20tKSqBQKODi4mKyjYiILFu9Lld97733cOTIEaSmpqJFixYAgG7duuHGjRs4ePAgAGDdunUYMmRInW1ERGTZ6uwxHDt2DB999BE6d+6MiIgIAEDHjh2RmpqKxYsXIz4+HhUVFejQoQOWLFkCAFAoFLW2ERGRZaszGB566CEcPXq0xrYePXpgy5YtDW4jIiLLxTufiYhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEthIkiSZu4jaFBdfhdFoseWZ3WuvvYxr1641+XZatmyJlJSPm3w7dO/jPmsZFAobuLk519pu24y1UCO7du0aVq/+skHLuLu3QlFRWYOWGT8+skHzE9WG++zdgYeSiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiJBncGQmJiI4OBgaDQa5OXlydNPnTqF8PBwhISEIDw8HPn5+fVqIyIiy1ZnMAwcOBBffPEFOnToIEyPj49HZGQksrKyEBkZibi4uHq1ERGRZaszGLRaLVQqlTCtuLgYubm5CA0NBQCEhoYiNzcXJSUlJtuIiMjy3dHTVQsLC+Hp6QmlUgkAUCqV8PDwQGFhISRJqrXN1dW1Qdsx9VhYusndvZXFLkNUE+6zls+iH7vN8Rjq1tDHEd/JI4zvZDtEteE+a35NMh6DSqXCxYsXYTAYoFQqYTAYcOnSJahUKkiSVGsbERFZvju6XNXNzQ0+Pj7IyMgAAGRkZMDHxweurq4m24iIyPLV2WNYsGABtm/fjsuXL+PFF1+Ei4sLtm7dijlz5iAmJgbLly9H69atkZiYKC9jqo2IiCxbncHw9ttv4+23375ture3N9LS0mpcxlQbERFZNt75TEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJGAxERCRgMBARkYDBQEREAgYDEREJbCRJksxdRG2Ki6/CaLTY8swuI+NfcHV1bfLtlJSUIDT0mSbfDt37uM9aBoXCBm5uzrW22zZjLdTIdDodVq/+skHLuLu3QlFRWYOWGT8+kv/JqFFwn707MBjucuPHRzb5Nlq2bNnk2yDrwX3W8vFQkpUZPz6ywb+xEZkT99nGV9ehJJ58JiIiAYOBiIgETRoMp06dQnh4OEJCQhAeHo78/Pym3BwRETWCJg2G+Ph4REZGIisrC5GRkYiLi2vKzRERUSNosmAoLi5Gbm4uQkNDAQChoaHIzc1FSUlJU22SiIgaQZMFQ2FhITw9PaFUKgEASqUSHh4eKCwsbKpNEhFRI7Do+xhMXU5FpgUHB+Po0aM1tvn5da1xukajwY4dO5qyLKIamdpfgZr3We6vTafJ7mMoLi5GSEgIcnJyoFQqYTAYEBAQgO3bt9f7lnjex9D47uQuUiJz4j7b+Mx2H4Obmxt8fHyQkZEBAMjIyICPj0+zPCeFiIjuXJPe+XzixAnExMTgypUraN26NRITE/Hggw/We3n2GBoff/uiuw332cZXV4+Bj8SwMvxPRncb7rONj4/EICKiBmEwEBGRgMFAREQCBgMREQkYDEREJGAwEBGRgMFAREQCBgMREQks+iF6CoWNuUu4J/FzpbsN99nGVdfnadF3PhMRUfPjoSQiIhIwGIiISMBgICIiAYOBiIgEDAYiIhIwGIiISMBgICIiAYOBiIgEDAYiIhIwGKzEqVOnEB4ejpCQEISHhyM/P9/cJRGZlJiYiODgYGg0GuTl5Zm7HKvCYLAS8fHxiIyMRFZWFiIjIxEXF2fukohMGjhwIL744gt06NDB3KVYHQaDFSguLkZubi5CQ0MBAKGhocjNzUVJSYmZKyOqnVarhUqlMncZVonBYAUKCwvh6ekJpVIJAFAqlfDw8EBhYaGZKyMiS8RgICIiAYPBCqhUKly8eBEGgwEAYDAYcOnSJXbTiahGDAYr4ObmBh8fH2RkZAAAMjIy4OPjA1dXVzNXRkSWiAP1WIkTJ04gJiYGV65cQevWrZGYmIgHH3zQ3GUR1WrBggXYvn07Ll++jLZt28LFxQVbt241d1lWgcFAREQCHkoiIiIBg4GIiAQMBiIiEjAYiIhIwGAgIiIBg4HIBJ1Oh9GjR5u7DKJmxWAgIiIBg4GomVRVVZm7BKJ6YTAQ/b/CwkJMnToVffr0QUBAAObNmye3JSYmolevXggODsbu3bvl6cHBwdi3b5/8OiUlBdHR0QCAc+fOQaPRIC0tDf3798fzzz8vH5qqbX1EloDBQISbDxacNGkSvLy8sGPHDuzZswdDhw4FAPz888944IEH8P3332PChAmYNWsWGvLAgAMHDiAzMxOrVq1qlPURNTUGAxFufllfunQJM2fOhJOTE+zt7aHVagEAXl5eGDVqFJRKJUaMGIGioiJcvny53ut+7bXX4OTkBAcHh0ZZH1FTYzAQ4eZhJC8vL9ja2t7W1q5dO/nvjo6OAIDr16/Xe93t27dv1PURNTUGAxFujllRWFjY4BPEjo6OKC8vl18XFRXdNo+Njc1fro+oOTEYiAD4+vrC3d0d7777Lq5fv46KigocOnSozuW6du2KzMxM6PV6/PLLL8jKymqGaomaFoOBCDfHwV6xYgVOnz6NAQMGICgoCNu2batzuaioKJw5cwa9e/dGSkoKwsLCmqFaoqbF8RiIiEjAHgMREQkYDEREJGAwEBGRgMFAREQCBgMREQkYDEREJGAwEBGRgMFAREQCBgMREQn+D8Y8IeP208/gAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, axs = plt.subplots(nrows=7, figsize=(18,50))\n",
        "\n",
        "# Plot histogram\n",
        "plot_distribution(client_df, \"forecast_cons_12m\", axs[0])\n",
        "plot_distribution(client_df, \"forecast_cons_year\", axs[1])\n",
        "plot_distribution(client_df, \"forecast_discount_energy\", axs[2])\n",
        "plot_distribution(client_df, \"forecast_meter_rent_12m\", axs[3])\n",
        "plot_distribution(client_df, \"forecast_price_energy_off_peak\", axs[4])\n",
        "plot_distribution(client_df, \"forecast_price_energy_peak\", axs[5])\n",
        "plot_distribution(client_df, \"forecast_price_pow_off_peak\", axs[6])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "HRGGCNwxYiO5",
        "outputId": "f5cace2d-6f8b-4127-8025-6c7988a747d2"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1296x3600 with 7 Axes>"
            ],
            "image/png": 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xHuUMjgBSUFCg7OxsJSQkSJISEhKUnZ2twsLCCuutW7dOd999t5xOpyIjI9WnTx+tX7/epzbUDjNq2r17d9WvX1+SdPXVV8swDB0/frxuJwJJ5tSzMn/96181ePBgSVKrVq3Utm1bbd682fyJwMvsmr733ntKTExUSEhInYwfFVW1ni1btlRcXJyCgoLO6oPjaGAxo6YcRwOHGfWsDMfRumd2TTmO+ldV61nZ52pl78O6eI8ScASQ3NxcxcTEyOVySZJcLpcaN26s3Nzcs9Zr2rSp93FsbKwOHz7sUxtqhxk1/blVq1bp8ssvV5MmTbzLFi9erMTERD3yyCPas2dPLc0Eknn1XLt2rRITEzVs2DD95z//8S7PyclRs2bNzrsdzGfme7S0tFQZGRkaNGhQheXnqzfMV9V6XqgPjqOBw4ya/hzHUf8yq54cRwOHme9RjqP+V5N6/vJztbL3YV28R6sXiwLwm88//1yzZ8/Wa6+95l32+OOPKzo6Wk6nU6tWrdIf//hHbdy40fuhhMAzZMgQjRgxQsHBwdqyZYseeeQRrVu3To0aNfL30OCjjRs3qmnTpoqLi/Muo95A4OA4ag98rtoXx1HrOdfnqr9xBkcAiY2NVV5entxut6Qfb2aWn5+v2NjYs9bLycnxPs7NzfUmZjVtQ+0wo6aS9J///Edjx47VvHnz1Lp1a+/ymJgYOZ0/vo3vuOMOnT59mr9U1CIz6hkdHa3g4GBJUteuXRUbG6tvvvlGktS0aVMdOnTonNuhdpj1HpWkFStWnPVXp8rqDfNVtZ4X6oPjaOAwo6YSx9FAYUY9OY4GFrPeoxLH0UBQnXqe73O1svdhXbxHCTgCSFRUlOLi4pSZmSlJyszMVFxcnCIjIyusN2DAAC1fvlwej0eFhYXauHGj+vfv71MbaocZNf3yyy/1+OOPa86cObruuusqbJeXl+f9+ZNPPpHT6VRMTEwtz+riZUY9f16zXbt26dChQ/rVr37l3e6dd96RJO3bt0///e9/1b1797qY2kXLjJpK0uHDh/Wvf/1LiYmJFbarrN4wX1XrWRmOo4HFjJpyHA0cZtST42hgMaOmEsfRQFHVelb2uVrZ+7Au3qMOwzAMU3uET/bs2aOUlBSdOHFCDRs2VHp6ulq3bq0HH3xQI0eO1PXXXy+3261JkyZpy5YtkqQHH3zQe7OWmrah9vha00GDBunQoUMV/sM1ffp0XX311brvvvtUUFAgh8OhBg0a6KmnnlL79u39Ms+Lha/1HDdunHbu3Cmn06ng4GCNHDlSPXr0kCSdPn1aKSkp2rVrl5xOp8aOHas+ffr4ba4XC19rKkkLFizQ119/rVmzZlXou7J6o3ZUpZ7btm3TE088oVOnTskwDIWHh2vq1Knq3r07x9EA5GtNOY4GFl/ryXE08PhaU4njaCCpSj0r+1yt7H1YF+9RAg4AAAAAAGB5XKICAAAAAAAsj4ADAAAAAABYHgEHAAAAAACwPAIOAAAAAABgeQQcAAAAAADA8gg4AAAIQN99952SkpJ044036vXXX/f3cPxm4cKFmjBhgr+HcdHp1auXPvvsM38PAwCAagny9wAAAMDZFi1apC5dumj16tX+HsoF9erVS1OmTNEtt9xiet8jRowwvU8AAGBPnMEBAEAAysnJ0ZVXXlnt7crLy2thNP5hl7nYZR4AAAQ6Ag4AAALMvffeq3/+85+aNGmSbrzxRu3evVtPPfWUbrrpJvXs2VPz58+Xx+ORJK1cuVJDhgzRtGnT1KVLF82dO1elpaVKT0/Xr3/9a91yyy1KTU3VmTNnvP1v3LhRSUlJ6tChg/r06aPNmzdLklasWKFbb71VN954o3r37q1ly5Z5tyksLNTw4cMVHx+vzp07Kzk5WR6PR2PHjlVOTo5GjBihG2+8Ua+88sp553Xw4EFdffXVeuedd9StWzd169ZNr776qrd97ty5GjlypJ588kl16NBB77//vubOnasnn3zSu862bds0ZMgQxcfHq0ePHlq5cqUkXXDO5/PRRx8pKSlJ8fHxGjJkiHbv3u1t69Wrl1599VUlJiaqY8eOGj16tEpKSqq87V/+8hclJiaqffv2Ki8v16pVq9SzZ0916dJF8+bN814GcuTIEd1www06duyYd/udO3fqpptuUllZ2XnH/lPtJ02apI4dO2rAgAH6+9//7m0/efKkxo8fr27duql79+6aNWuW3G63JOn777/Xvffeqy5duqhLly4aM2aMTpw4cc7n2bNnj3r16qXMzMwLvp4AAPiVAQAAAs4999xjvPvuu4ZhGMbYsWONESNGGCdPnjQOHDhg9OvXz9u2YsUKIy4uznj99deNsrIyo7i42Jg6daoxfPhw49ixY8bJkyeN4cOHGzNnzjQMwzC++OILo0OHDsann35quN1u4/Dhw8a3335rGIZhfPTRR8b+/fsNj8dj/POf/zTatWtn7NixwzAMw5g5c6bxzDPPGKWlpUZpaamxdetWw+PxGIZhGD179jS2bNlywTkdOHDAuOqqq4zHH3/cKCoqMnbv3m106dLFu+2cOXOMa6+91vjggw8Mt9ttFBcXG3PmzDHGjBljGIZhHDx40Gjfvr2RkZFhlJaWGoWFhUZ2drZhGEalcz6fnTt3GjfddJOxfft2o7y83Fi5cqXRs2dPo6SkxDuvQYMGGYcPHzaOHTtmDBgwwHjrrbeqvO3AgQONnJwco7i42Pjmm2+M9u3bG1u3bjVKSkqM5557zrj22mu9c//jH/9oLF261Du2qVOnGpMmTap0/D/VfvHixUZpaamxdu1ao0OHDsaxY8cMwzCMRx55xHjmmWeMoqIi4+jRo8agQYOMt99+2zAMw9i3b5/x6aefGiUlJUZBQYGRnJxsTJkyxdv3TzXdsWOH0aNHD2PTpk0XrC8AAP7GGRwAAAQwt9utdevWacyYMWrQoIGaN2+u+++/X2vWrPGu07hxYw0dOlRBQUEKDQ3Vu+++q/HjxysiIkINGjTQ8OHDtXbtWknSe++9p0GDBqlr165yOp2KiYlRmzZtJEm//vWvdfnll8vhcKhz587q2rWrtm3bJkkKCgrSkSNHlJOTo+DgYMXHx8vhcNRoTo8++qjCwsJ09dVX684776xwZkD79u3Vp08fOZ1O1atXr8J2mZmZuuWWW5SQkKDg4GA1atRIcXFxMgyj0jmfzzvvvKPBgwfrhhtukMvl0m9+8xsFBwdr+/bt3nWGDh2qmJgYRUREqGfPntq1a1e1to2NjVW9evW0fv169ezZU/Hx8QoJCdHIkSMrvH6/+c1vvDV1u91au3atkpKSLvhaRkZG6g9/+IOCg4N122236Ve/+pX+9re/6ejRo/r44481fvx4hYWFKSoqSvfdd5/3NWnZsqW6du2qkJAQRUZG6v7779fWrVsr9L1t2zY9/PDDSk9PV8+ePS84FgAA/I2bjAIAEMCOHTumsrIyNW3a1LusadOmysvL8z5u0qSJ9+fCwkIVFxfrzjvv9C4zDMN7SUtubq569Ohxzuf6+OOPNW/ePO3bt08ej0dnzpzRVVddJUl64IEH9NJLL2nYsGGSpMGDB+uhhx6q0ZxiY2O9Pzdr1kxff/31OefyS7m5ubr88svPWn6hOZ9PTk6OVq1apTfffNO7rKysTPn5+d7H0dHR3p/r16/vbavKtj+fZ35+foW51a9fXxEREd7HvXv3Vlpamg4cOKC9e/eqQYMGateuXaXjl6SYmJgKQUnTpk2Vn5+vnJwclZeXq1u3bt42j8fjHdPRo0c1depUbdu2TUVFRTIMQw0bNqzQ97Jly9SpUyd16dLlguMAACAQEHAAABDAGjVqpODgYOXk5OiKK66Q9OMv+jExMd51fv4LbqNGjVSvXj2tXbu2wjo/iY2N1ffff3/W8tLSUo0cOVLp6enq3bu3goOD9cgjj8gwDElSgwYNlJKSopSUFH399df6wx/+oOuvv14333xzteeUm5vrPWskJydHjRs3PudczjX2L7/88qzlF5pzZf2NGDFCDz/8cDVGX/Vtfz6Xxo0ba+/evd7HZ86c0fHjx72PQ0NDdeutt2rNmjXerwiuiry8PBmG4X2u3Nxc9erVS02aNFFISIj+8Y9/KCjo7P/uvfDCC3I4HMrIyFBERIQ2btyoSZMmVVjn2Wef1SuvvKJp06Zp/PjxVRoPAAD+xCUqAAAEMJfLpQEDBmjWrFk6deqUDh06pMWLF2vgwIHnXN/pdOruu+/WtGnTVFBQIOnHX4I/+eQTSdJdd92llStX6u9//7s8Ho/y8vK0Z88elZaWqrS0VJGRkQoKCtLHH3+sLVu2ePv96KOPtH//fhmGofDwcLlcLu8v1ZdddpkOHDhQ5TnNnz9fxcXF+uabb7Ry5UrddtttVdouMTFRn332mdatW6fy8nIdO3ZMu3btuuCcz+fuu+/WsmXL9MUXX8gwDJ0+fVp/+9vfdOrUqQuOpbrb9u/fX5s2bdK///1vlZaWau7cud7w6CdJSUl6//33tWnTpioHHIWFhXr99ddVVlamv/71r9qzZ4969Oihxo0bq2vXro1goOUAACAASURBVHruued06tQpeTweff/99/r8888lSUVFRQoLC1N4eLjy8vK0aNGis/q+5JJLtGjRIm3btk0zZ86s0ngAAPAnAg4AAALcM888o/r166tPnz5KTk5WQkKCBg0adN71x44dq5YtW+q3v/2tOnTooPvuu8979kC7du305z//WdOmTVPHjh11zz33KCcnRw0aNNDTTz+t0aNHq1OnTsrMzFSvXr28fe7fv1/333+/brzxRg0ePFi/+93vdNNNN0mSHnroIS1YsEDx8fEVvhXlfDp37qy+ffvqvvvu07BhwypcRlGZpk2b6pVXXtHixYvVuXNn3XHHHd5vLqlszudz/fXXa/LkyZo0aZI6deqkfv36eb+V5UKqu+2VV16pZ555Rk888YS6d++usLAwRUZGKiQkxLtOx44d5XQ6dd1116lZs2ZVGke7du20f/9+3XTTTXrxxRc1Z84cNWrUSJI0ffp0lZWV6bbbblOnTp00cuRIHTlyRJL02GOPKTs7W/Hx8XrooYfUr1+/c/bfsGFDvfbaa9q8ebNefPHFKo0JAAB/cRi//PMBAABALTh48KB69+6tnTt3nvOyiYtJUVGROnXqpKysLLVo0cK7/N5771ViYqLuvvvuC/axcuVKLV++XG+//XZtDhUAAMvgDA4AAIA6sGnTJhUXF+v06dNKT0/XVVddpebNm3vbv/zyS2VnZ+vWW2/14ygBALCui/vPJwAAwFRr1qxRWlraWcubNm2ql19+uc7Hs3DhwnM+b8eOHc9534na9OGHH+qpp56SYRhq27at90afkjRu3Dht3LhREyZMUIMGDbzbpKamKiMj46y+EhMT1b59+zobOwAAVsAlKgAAAAAAwPK4RAUAAAAAAFgeAQcAAAAAALA8Ag4AAAAAAGB5BBwAAAAAAMDyCDgAAAAAAIDlEXAAAAAAAADLI+AAAAAAAACWR8ABAAAAAAAsj4ADAAAAAABYHgEHAAAAAACwPAIOAAAAAABgeQQcAAAAAADA8gg4AAAAAACA5RFwAAAAAAAAyyPgAAAAAAAAlkfAAQAAAAAALI+AAwAAAAAAWB4BBwAAAAAAsDwCDgAAAAAAYHkEHAAAAAAAwPIIOAAAAAAAgOURcAAAAAAAAMsj4AAAAAAAAJZHwAEAAAAAACyPgAMAAAAAAFgeAQcAAAAAALA8Ag4AAAAAAGB5BBwAAAAAAMDyCDgAAAAAAIDlBfl7AIHq2LEieTyGv4dRZVFRDVRQcMrfw4DNsZ+hLrCfoa6wr6EusJ+hLrCfoS4Ewn7mdDrUqNEl520n4DgPj8ewVMAhyXLjhTWxn6EusJ+hrrCvoS6wn6EusJ+hLgT6fsYlKgAAAAAAwPIIOAAAAAAAgOVxiQoAAAAAABdgGIaOHTui0tIzkgL7Uo3akJ/vlMfjqZPncrmC1KBBhOrXP//9Ns6FgAMAAAAAgAs4deoHORwOxcQ0l8Nx8V0MERTkVHl57QcchmGorKxUx48fkaRqhRwXX1UAAAAAAKim4uJTCg+PuCjDjbrkcDgUEhKqiIhonTp1vFrbUhkAAAAAAC7A43HL5eIiiLoSHBwit7u8WtsQcAAAAAAAUAUOh8PfQ7ho1OS1Jn4CAAAAAKCawhvWV71Q83+lPlNSrpMnik3v92JAwAEAAAAAQDXVCw1S4pjVpveb8XySTlZhvbvuSlRISIiCg0NUXl6mIUPuUWLiHZVu8+qrL+vee4cpODjYpzGuW5ehtm3b6fLLW0qSPv30Y33xxXY9+ugon/r1FQEHAAAAAAAWNGVKulq3vkLfffethg27Rzff3FWXXRZ93vUXL35Fv/vdUFMCjksvjfAGHN269VC3bj186tMMfg84Dh48qEcffdT7+OTJkzp16pQ+//xz7d27VykpKTp+/LgiIiKUnp6uVq1aSVKN2wAAAAAAsJPWra9QeHhDHTmSr9OnizR79gv64YfjKisr029/+zvdfvtAPf98uiTp4YeHyeFwau7cl+V0OjR37izt2fONSktLdeON8frTnx6Xy+XSY489pLi467Rjx5c6evSo+vTpq+HDH9PatWv01Ve79OKLM/XKKwv06KOjdORIvj777BNNmTJdkvTmm0uUlbVOkhQXd51Gjx6rsLAwvfrqy/r++/0qKjqlnJxDatasuSZPTle9evVMeR38fpPR5s2ba/Xq1d5/vXv3VkJCgiQpLS1NycnJysrKUnJyslJTU73b1bQNAAAAAAA7+fLL7br00ghdccVVmjjxaY0c+YQWLXpdCxYs0ptvLtH+/fs0Zsw4SdKCBa9pyZK3FB4errlzZ6l9+w565ZXXtXjxWzp2rFBr167x9puXd1jz5r2ixYuXas2aVTpw4HvdfvtAXX11nEaPflJLlrylTp26VBjL3/++RVlZ67Rw4Wt6/fV35Ha7tWTJIm/7V1/tUlraVC1d+p7Ky8u1YcNfTXsd/H4Gx8+VlpYqIyNDr776qgoKCpSdna3FixdLkhISEjR58mQVFhbKMIwatUVGRvptbgAAAAAAmOnpp8fJMAwdOnRQkyc/p4MHD2j//r1KSxvvXaesrEz79u1Vy5atztr+0083a9eunVq2bKkk6cyZM2rcOMbb3rNnbzmdTjVo0ECtWrXSoUMH1aLF5ZWOadu2z9W7dz9dckkDSdLAgXdq9uyZ3vbOnW9SeHi4JOnaa9vq0KGDNZ7/LwVUwLFp0ybFxMTouuuu044dOxQTEyOXyyVJcrlcaty4sXJzc2UYRo3aqhNwREU1MH+CtSw6OtzfQ8BFgP0MdYH9DHWFfQ114WLZzzzlpXIGhQRMPxebi2U/86f8fKeCgurmIoiqPs+f/zxDbdpcoQ8//EDTpk3SjBmzFBHRSG++uazSvv+vf0PTp7+gZs2an7Wew+FQ/fr1vOs6nS5JHgUFOeVwOORyOX7W5pDD8eNjp9Mhp/P/nsPlcsjhkLetXr3/6zMoyKWystLzztfpdFZr3w6ogGPFihUaNGiQv4chSSooOCWPx/D3MKosOjpcR45U5V67QM2xn6EusJ+hrrCvoS5cTPtZdHS4vpvq+//lW09YcdG8Zma5mPYzf/J4PCov99TJc1X1edzuH8fUo0dvffDBBm3cuEGhoaHKzMzQgAG3S5L279+nyy67TJdc0kBhYZfohx9OKCTkx3tedO36P1qyZLGefDJFLpdLx48f1+nTRWratJkMw5DbbVQYy0+Pw8LCdOLESW+bx2PIMH5s69ChkxYsmKO77hqs+vXDtHr1+4qP76Lyco88HkMej1Fhu58//iWPx1Nh33Y6HZWejBAwAUdeXp62bt2q6dN/vClJbGys8vLy5Ha75XK55Ha7lZ+fr9jYWBmGUaM2AAAAAADMcKakXBnPJ9VKvzUxYsRjeuCBezR9+ot6880levvtN+R2exQZGalJk56TJA0Z8nuNHDlCoaH1NHfuyxo1aozmz5+j++77nRwOh4KDQzRy5Bg1bdqs0ucaOPBOvfTSLL311htnfTXszTd31Z4932j48PslSddcc63+8IcHajSn6nIYhhEQpyksXLhQu3bt0uzZs73Lhg4dqrvuuktJSUlavXq13nvvPb3xxhs+tVUVZ3AAZ2M/Q11gP0NdYV9DXbiY9jPO4PCfi2k/86fDh/erSZOW/h6G3wQFOevsDJaf/PI1t8wZHO+//74mTJhQYdnEiROVkpKi+fPnq2HDhkpPT/e5DQAAAAAA2E/ABBxZWVlnLWvTpo2WL19+zvVr2gYAAAAAAOynbm4BCwAAAAAAUIsIOAAAAAAAgOURcAAAAAAAAMsj4AAAAAAAAJYXMDcZBQAAAADAKhpdGqKgkFDT+y0vLdGxH0ovvF55uZYsWaSNGzcoNDRETqdTHTp0UsuWrfT553/XlCnTTR9boCPgAAAAAACgmoJCQvXd1EGm99t6wgpJFw44pk17ViUlZ/Taa28oLOwSlZeXa+3aNSoru/C2F+LxeORwOORwOHzuqy4RcAAAAAAAYCEHDnyvzZs/0sqV6xQWdokkKSgoSElJd2rdugwVFRUpNfX/6bvv9ig8vIGmTJmuqKjL9OqrL6u4uFiPPTZakio8fvXVl7V373cqKjqlvLzDmjhxqh5//FENHHin/vGPLSopKdG4cc/ohhva+3PqleIeHAAAAAAAWMjXX3+l5s0vV8OGDc/ZvmtXth59dJTefPNdtWrVWu+9906V+s3O3qG0tKl6660VCg9vqB9++EFt27bT4sVvadiwB7Vw4Rwzp2E6Ag4AAAAAAGykXbsbFBPTRJJ03XVtlZNzsErb3XxzV0VERHgf168fpq5du0uS2ra9XocOHTJ/sCYi4AAAAAAAwEKuuupqHTz4vU6cOHHO9pCQEO/PTqdLbrdbkuRyuWQYHm9baWnF+3XUrx/2i36Cf9FPuc9jr00EHAAAAAAAWEiLFpera9f/0YwZ03T6dJEkye12KyNjlYqLT593u+bNW+irr3bL4/Ho9OkiffbZJ3U15DrBTUYBAAAAAKim8tKS//3GE/P7rYqnn35Wr732Fw0bNlTBwUEyDEM33dRVl1/e8rzb9OjRSx9++IF+//u7FBPTRFdfHWfWsAOCwzAMw9+DCEQFBafk8VjnpYmODteRIyf9PQzYHPsZ6gL7GeoK+xrqwsW0n0VHh5vylZmtJ6y4aF4zs1xM+5k/HT68X02anD88sLugIKfKyz0XXtFEv3zNnU6HoqIanHd9LlEBAAD/v717j7OqrPcH/pkZbhLoMAg4oGWaGeUpLyOU2jHRBAvB0+XoobTUvKeYaXK0wJfX8FKpYPrSjr1MTx47Gjc9YGaZWZGkVkheUjKUEXAGjqjI6Mz+/dFpfuEFcNjMnjW+33/NXs9ez3rWmu9rb+bD86wFAFB4Ag4AAACg8AQcAAAAsBHc4aHzdORaCzgAAABgA4rwmNTu5JVXWlJT89aeiyLgAAAAgA3YYot+Wb16VUqlzr3R5ttNqVRKS8varFq1Iv361b6lfT0mFgAAADagX7+tsnLliixb9nSSt99Slerq6rS1dU64U1PTI/37D8gWW7zjLe0n4AAAAIANqKqqSl3d4EoPo2KK8DhiAQcAALDJ2l5pyQ5n31qWfgA6QsABAABssuqevXLwV2ducj+zLxufZO2mDwh423GTUQAAAKDwBBwAAABA4Qk4AAAAgMITcAAAAACFJ+AAAAAACk/AAQAAABSegAMAAAAoPAEHAAAAUHgCDgAAAKDwBBwAAABA4Qk4AAAAgMITcAAAAACFJ+AAAAAACk/AAQAAABRelwg41q5dmylTpuTAAw/MwQcfnG984xtJksWLF+fQQw/N6NGjc+ihh+Yvf/lL+z4dbQMAAAC6ny4RcFxyySXp3bt35s2bl9mzZ2fixIlJkilTpmTChAmZN29eJkyYkMmTJ7fv09E2AAAAoPupeMDx4osvZsaMGZk4cWKqqqqSJFtvvXWampqyaNGijB07NkkyduzYLFq0KM3NzR1uAwAAALqnHpUewJIlS1JbW5tp06Zl/vz5ecc73pGJEyemT58+GTJkSGpqapIkNTU1GTx4cBobG1MqlTrUVldXt9HjGjiwX/lPdjMbNKh/pYfA24A6ozOoMzqLWqMzqLO3zjV761wzOkNXr7OKBxytra1ZsmRJ3v/+9+fMM8/M73//+xx//PG5/PLLKzqupqYX0tZWqugY3opBg/pnxYrVlR4G3Zw6ozOoMzqLWqMzvJ3qrJx/+Lxdrlm5vJ3qjMrpCnVWXV213skIFQ846uvr06NHj/YlJR/60IcyYMCA9OnTJ8uWLUtra2tqamrS2tqa5cuXp76+PqVSqUNtAAAAQPdU8Xtw1NXVZeTIkbnvvvuS/O0JKE1NTdl+++0zfPjwzJkzJ0kyZ86cDB8+PHV1dRk4cGCH2gAAAIDuqapUKlV8HcaSJUty1llnZdWqVenRo0dOPfXU7LvvvnniiScyadKkPP/889lyyy0zderU7LDDDknS4baNZYkKvJ46ozOoMzqLWqMzvJ3qbNCg/jn4qzM3uZ/Zl41/21yzcnk71RmV0xXqrMsvUUmS7bbbLj/4wQ9et33HHXfMj370ozfcp6NtAAAAQPdT8SUqAAAAAJtKwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8HpUegAAAPB2MWCrXunRq3dZ+nq1ZW1W/m9LWfoC6A4EHAAA0El69OqdJy/4dFn62uHsW5MIOAD+zhIVAAAAoPAEHAAAAEDhCTgAAACAwhNwAAAAAIUn4AAAAAAKT8ABAAAAFJ6AAwAAACg8AQcAAABQeAIOAAAAoPAEHAAAAEDhCTgAAACAwhNwAAAAAIUn4AAAAAAKr0elB5Ako0aNSq9evdK7d+8kyemnn56PfvSjeeihhzJ58uSsXbs2w4YNyyWXXJKBAwcmSYfbAAAAgO6ny8zguOKKKzJz5szMnDkzH/3oR9PW1pYzzjgjkydPzrx589LQ0JBLL700STrcBgAAAHRPXSbgeK2FCxemd+/eaWhoSJIcdthhmTt37ia1AQAAAN1Tl1iikvxtWUqpVMoee+yR0047LY2NjRk6dGh7e11dXdra2rJq1aoOt9XW1m70eAYO7FeeE+tEgwb1r/QQeBtQZ3QGdUZnUWt0hs1ZZ921hrvreW1OrhmdoavXWZcIOG666abU19enpaUlF1xwQc4999x8/OMfr+iYmppeSFtbqaJjeCsGDeqfFStWV3oYdHPqjM6gzugsao3O8No6K/cfB12phst5bl3pvIrA5xmdoSvUWXV11XonI3SJJSr19fVJkl69emXChAl54IEHUl9fn6VLl7a/p7m5OdXV1amtre1wGwAAANA9VTzgeOmll7J69d9SoFKplDvuuCPDhw/PLrvskpdffjkLFixIktx8880ZM2ZMknS4DQAAAOieKr5EpampKSeffHJaW1vT1taWHXfcMVOmTEl1dXUuvvjiTJkyZZ3HvSbpcBsAAADQPVU84Nhuu+0yY8aMN2zbfffdM3v27LK2AQAAAN1PxZeoAAAAAGwqAQcAAABQeAIOAAAAoPAEHAAAAEDhVfwmowAA8HbR9kpLdjj71rL1BcD/J+AAAIBOUt2zVw7+6syy9DX7svFJ1palL4DuwBIVAAAAoPAEHAAAAEDhCTgAAACAwhNwAAAAAIUn4AAAAAAKT8ABAAAAFJ6AAwAAACg8AQcAAABQeAIOAAAAoPAEHAAAAEDhCTgAAACAwhNwAAAAAIUn4AAAAAAKT8ABAAAAFJ6AAwAAACg8AQcAAABQeAIOAAAAoPAEHAAAAEDhCTgAAACAwhNwAAAAAIVXloDjrrvuyquvvlqOrgAAAADesrIEHFdccUX22WefnHvuufn9739fji4BAAAANlpZAo5Zs2bl+9//fnr37p2TTz45o0ePzlVXXZWnn366HN0DAAAArFfZ7sHxvve9L2eeeWbuueeeTJkyJXPnzs3HP/7xfO5zn8usWbPS1tZWrkMBAAAArKNHOTv761//mlmzZmXWrFmpqqrKKaeckvr6+tx000258847M23atHIeDgAAACBJmQKOm266KTNnzsxTTz2Vgw46KBdffHF23XXX9vbRo0dnr732KsehAAAAAF6nLAHHL37xixx55JHZf//906tXr9e1b7HFFrnyyivLcSgAAACA1ylLwHHFFVekuro6PXv2bN/2yiuvpFQqtQce++yzTzkOBQAAAPA6ZbnJ6FFHHZWHH354nW0PP/xwjj766HJ0DwAAALBeZQk4Hn300XzoQx9aZ9sHP/jBPPLII+XoHgAAAGC9yhJwbLnllnnuuefW2fbcc89liy22eEv9TJs2LTvvvHMee+yxJMlDDz2UcePGZfTo0TnqqKPS1NTU/t6OtgEAAADdT1kCjgMPPDBf/epX89hjj2XNmjV59NFHc+aZZ+aggw7a6D4efvjhPPTQQxk2bFiSpK2tLWeccUYmT56cefPmpaGhIZdeeukmtQEAAADdU1kCjq985SvZcccd89nPfja77757Dj300Lz73e/OaaedtlH7t7S05Nxzz80555zTvm3hwoXp3bt3GhoakiSHHXZY5s6du0ltAAAAQPdUlqeo9O7dO1OmTMnkyZOzcuXKDBgwIFVVVRu9/+WXX55x48Zl2223bd/W2NiYoUOHtr+uq6tLW1tbVq1a1eG22trajR7TwIH9Nvq9XcWgQf0rPQTeBtQZnUGd0VnUGp1hc9ZZd63h7npem5NrRmfo6nVWloAjSVavXp3FixfnxRdfXGf7Rz7ykfXu9+CDD2bhwoU5/fTTyzWUsmhqeiFtbaVKD2OjDRrUPytWrK70MOjm1BmdQZ3RWdQaneG1dVbuPw66Ug2X89y60nkVgc8zOkNXqLPq6qr1TkYoS8Bx22235dxzz03fvn3Tp0+f9u1VVVX56U9/ut5977///jzxxBPZf//9kyTPPvtsjj766Bx++OFZunRp+/uam5tTXV2d2tra1NfXd6gNAAAA6J7KEnB8+9vfzuWXX5599933Le977LHH5thjj21/PWrUqFx99dV5z3vek1tuuSULFixIQ0NDbr755owZMyZJsssuu+Tll19+y20AAABA91SWgKO1tTX77LNPObpqV11dnYsvvjhTpkzJ2rVrM2zYsFxyySWb1AYAAAB0T2UJOI455ph897vfzYknnpjq6k17MMvdd9/d/vPuu++e2bNnv+H7OtoGAAAAdD9lCTi+//3v57nnnst11133untd/PznPy/HIQAAAADeVFkCDktAAAAAgEoqS8AxYsSIcnQDAAAA0CGbdsOM/9PS0pJvf/vb2X///bPHHnskSX75y1/mxhtvLEf3AAAAAOtVloDjwgsvzGOPPZZLL700VVVVSZKddtopP/zhD8vRPQAAAMB6lWWJyl133ZU777wzffv2bX+KypAhQ7Js2bJydA8AAACwXmWZwdGzZ8+0traus625ufl1T1QBAAAA2BzKEnCMGTMmZ555ZpYsWZIkWb58ec4999x88pOfLEf3AAAAAOtVloDjK1/5SrbddtuMGzcuzz//fEaPHp3BgwfnpJNOKkf3AAAAAOtVlntw9OrVK2eddVbOOuusNDc3Z8CAAe03GwUAAADY3MoScPx9acrfvfjii+0/b7fdduU4BAAAAMCbKkvA8fGPfzxVVVUplUrt2/4+g+NPf/pTOQ4BAAAA8KbKEnA88sgj67xesWJFpk2bloaGhnJ0DwAAALBeZbnJ6GsNGjQoZ599dr71rW9tju4BAAAA1rFZAo4kefLJJ7NmzZrN1T0AAABAu7IsUZkwYcI6T01Zs2ZN/vznP3tMLAAAANApyhJwfPazn13n9RZbbJH3ve992X777cvRPQAAAMB6lSXg+Jd/+ZdydAMAAADQIWUJOC6//PKNet/EiRPLcTgAAACAdZQl4Hjqqady5513ZpdddsmwYcOydOnS/PGPf8yBBx6Y3r17l+MQAAAAAG+qLAFHqVTKZZddltGjR7dvu/POOzN37txcdNFF5TgEAAAAwJsqy2Nif/GLX+SAAw5YZ9uoUaNyzz33lKN7AAAAgPUqS8Dxrne9KzfddNM62374wx/mne98Zzm6BwAAAFivsixROf/88/PlL3851113XYYMGZJly5alR48eufLKK8vRPQAAAMB6lSXgeP/735958+bl97//fZYvX55BgwZl1113Tc+ePcvRPQAAAMB6lWWJymvtueeeeeWVV/LSSy9tju4BAAAA1lGWGRyPPvpoTjjhhPTq1SvLli3LJz7xidx///358Y9/nO985zvlOAQAAADAmyrLDI5zzjknp5xySubOnZsePf6Wmey555753e9+V47uAQAAANarLAHHn//854wfPz5JUlVVlSTp27dv1q5dW47uAQAAANarLAHHsGHDsnDhwnW2/eEPf/CYWAAAAKBTlOUeHBMnTsxxxx2Xww47LK+88kquueaa3HzzzTnvvPPK0T0AAADAepVlBsd+++2X6667Ls3Nzdlzzz3zzDPP5Morr8w+++xTju4BAAAA1muTZ3C0trZm9OjRueOOO3LOOeeUYUgAAAAAb80mz+CoqalJTU2NG4oCAAAAFVOWe3AcccQROfXUU3Pcccdlm222aX+SSpJst9125TgEAAAAwJvapIBjxYoVGTRoUPvNRH/1q1+lVCq1t1dVVeVPf/rTpo0QAAAAYAM2KeAYPXp0HnjggTzyyCNJkpNOOinTp09/y/2ceOKJefrpp1NdXZ2+ffvmG9/4RoYPH57Fixdn0qRJWbVqVWprazN16tRsv/32SdLhNgAAAKD72aR7cPzjbI0kuf/++zvUz9SpUzNr1qzMmDEjRx11VM4666wkyZQpUzJhwoTMmzcvEyZMyOTJk9v36WgbAAAA0P1sUsDxj/faSF4feGys/v37t//8wgsvpKqqKk1NTVm0aFHGjh2bJBk7dmwWLVqU5ubmDrcBAAAA3dMmLVFpbW3Nb37zm/Zg47Wvk+QjH/nIRvV19tln57777kupVMp1112XxsbGDBkyJDU1NUn+9rSWwYMHp7GxMaVSqUNtdXV1G31uAwf22+j3dhWDBvXf8JtgE6kzOoM6o7OoNTrD5qyz7lrD3fW8NifXjM7Q1etskwKOgQMHti8nSZLa2tp1XldVVeWnP/3pRvV1wQUXJElmzJiRiy++OBMnTtyUoW2ypqYX0tbWsRkplTBoUP+sWLG60sOgm1NndAZ1RmdRa3SG19ZZuf846Eo1XM5z60rnVQQ+z+gMXaHOqqur1jsZYZMCjrvvpFxxdwAAGqBJREFUvntTdn9DhxxySCZPnpxtttkmy5YtS2tra2pqatLa2prly5envr4+pVKpQ20AAABA97RJ9+AohxdffDGNjY3tr+++++5stdVWGThwYIYPH545c+YkSebMmZPhw4enrq6uw20AAABA97RJMzjKYc2aNZk4cWLWrFmT6urqbLXVVrn66qtTVVWVc845J5MmTcpVV12VLbfcMlOnTm3fr6NtAAAAQPdT8YBj6623zi233PKGbTvuuGN+9KMflbUNAAAA6H4qvkQFAAAAYFMJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAAqv4gHHypUrc8wxx2T06NE5+OCD8+UvfznNzc1Jkoceeijjxo3L6NGjc9RRR6Wpqal9v462AQAAAN1PxQOOqqqqfOlLX8q8efMye/bsbLfddrn00kvT1taWM844I5MnT868efPS0NCQSy+9NEk63AYAAAB0TxUPOGprazNy5Mj217vuumuWLl2ahQsXpnfv3mloaEiSHHbYYZk7d26SdLgNAAAA6J56VHoA/6itrS0//OEPM2rUqDQ2Nmbo0KHtbXV1dWlra8uqVas63FZbW7vRYxk4sF95TqoTDRrUv9JD4G1AndEZ1BmdRa3RGTZnnXXXGu6u57U5uWZ0hq5eZ10q4DjvvPPSt2/ffP7zn89PfvKTio6lqemFtLWVKjqGt2LQoP5ZsWJ1pYdBN6fO6AzqjM6i1ugMr62zcv9x0JVquJzn1pXOqwh8ntEZukKdVVdXrXcyQpcJOKZOnZqnnnoqV199daqrq1NfX5+lS5e2tzc3N6e6ujq1tbUdbgMAAAC6p4rfgyNJvvWtb2XhwoWZPn16evXqlSTZZZdd8vLLL2fBggVJkptvvjljxozZpDYAAACge6r4DI7HH38811xzTbbffvscdthhSZJtt90206dPz8UXX5wpU6Zk7dq1GTZsWC655JIkSXV1dYfaAAAAgO6p4gHHTjvtlEcfffQN23bffffMnj27rG0AAABA99MllqgAAAAAbAoBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAAqvR6UHAAAA8Hdtr7Zk0KD+Zenr1Za1Wfm/LWXpC+j6BBwAAECXUd2jV5684NNl6WuHs29NIuCAtwtLVAAAAIDCE3AAAAAAhSfgAAAAAAqv4vfgmDp1aubNm5dnnnkms2fPznvf+94kyeLFizNp0qSsWrUqtbW1mTp1arbffvtNagMAALq2tlda/u/eGeXpC3j7qHjAsf/+++eII47I5z73uXW2T5kyJRMmTMj48eMzc+bMTJ48OTfccMMmtQEAAF1bdc9eOfirM8vS1+zLxidZW5a+gK6v4ktUGhoaUl9fv862pqamLFq0KGPHjk2SjB07NosWLUpzc3OH2wAAAIDuq+IzON5IY2NjhgwZkpqamiRJTU1NBg8enMbGxpRKpQ611dXVvaUxDBzYr7wn1QnK9bxwWB91RmdQZ3QWtUZn2Jx1poY37O1yjd4u50lldfU665IBR1fQ1PRC2tpKlR7GRhs0qH9WrFhd6WHQzakzOoM6o7OoNTrDa+us3H8cdKUa7qp/+HSla7S5+DyjM3SFOquurlrvZIQuGXDU19dn2bJlaW1tTU1NTVpbW7N8+fLU19enVCp1qA0AAADovip+D443MnDgwAwfPjxz5sxJksyZMyfDhw9PXV1dh9sAAACA7qviMzjOP//83HnnnXnuuedy5JFHpra2NrfffnvOOeecTJo0KVdddVW23HLLTJ06tX2fjrYBAAAA3VPFA46vf/3r+frXv/667TvuuGN+9KMfveE+HW0DAAAAuqcuuUQFAAAA4K0QcAAAAACFJ+AAAAAACk/AAQAAABSegAMAAAAoPAEHAAAAUHgCDgAAAKDwBBwAAABA4Qk4AAAAgMLrUekBAAAAbA5tr7Zk0KD+m9zPqy1rs/J/W8owImBzEnAAAADdUnWPXnnygk9vcj87nH1rEgEHdHUCDgAAoFtqe6Xl/8KJTe8H6PoEHAAAQLdU3bNXDv7qzE3uZ/Zl45Os3fQBAZuVm4wCAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDCE3AAAAAAhSfgAAAAAApPwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQcAAAAQOEJOAAAAIDC61HpAQAAAAAbZ8BWvdKjV+9N7ufVlrVZ+b8tZRhR12EGBwAAABREdVVVl+qnKzGDAwAAAAqiumevHPzVmZvcz+zLxidZu+kD6kLM4AAAAAAKT8ABAAAAFJ6AAwAAACg89+DoJlpb2zJoUP+y9PXqq21ZufLFsvQFAAAAnaHbBhyLFy/OpEmTsmrVqtTW1mbq1KnZfvvtKz2szaamprosN5pJ/n6zGQAAACiObrtEZcqUKZkwYULmzZuXCRMmZPLkyZUeEgAAALCZdMsZHE1NTVm0aFGuv/76JMnYsWNz3nnnpbm5OXV1dRvVR3V18Z4JPHjAFmXrq4jnT+dQG3QGdUZnUWt0htfWWXf+N1u5zq2c16hcfXW1a/1aXX18lFel6rrSdbah41eVSqVSJ42l0yxcuDBnnnlmbr/99vZtn/jEJ3LJJZfkAx/4QAVHBgAAAGwO3XaJCgAAAPD20S0Djvr6+ixbtiytra1JktbW1ixfvjz19fUVHhkAAACwOXTLgGPgwIEZPnx45syZkySZM2dOhg8fvtH33wAAAACKpVvegyNJnnjiiUyaNCnPP/98ttxyy0ydOjU77LBDpYcFAAAAbAbdNuAAAAAA3j665RIVAAAA4O1FwAEAAAAUnoADAAAAKDwBBwAAAFB4Ag4AAACg8AQc3cDixYtz6KGHZvTo0Tn00EPzl7/8pdJDohuYOnVqRo0alZ133jmPPfZY+3b1RrmsXLkyxxxzTEaPHp2DDz44X/7yl9Pc3JwkeeihhzJu3LiMHj06Rx11VJqamio8WorsxBNPzLhx43LIIYdkwoQJ+dOf/pTE5xmbx7Rp09b57vR5RrmNGjUqY8aMyfjx4zN+/Pjce++9SdQa5bN27dpMmTIlBx54YA4++OB84xvfSFKQ780ShXf44YeXZsyYUSqVSqUZM2aUDj/88AqPiO7g/vvvLy1durS03377lR599NH27eqNclm5cmXpN7/5Tfvrb37zm6V///d/L7W2tpYOOOCA0v33318qlUql6dOnlyZNmlSpYdINPP/88+0//+QnPykdcsghpVLJ5xnlt3DhwtLRRx/d/t3p84zN4bX/NiuVSmqNsjrvvPNKF1xwQamtra1UKpVKK1asKJVKxfjeNIOj4JqamrJo0aKMHTs2STJ27NgsWrSo/X9BoaMaGhpSX1+/zjb1RjnV1tZm5MiR7a933XXXLF26NAsXLkzv3r3T0NCQJDnssMMyd+7cSg2TbqB///7tP7/wwgupqqryeUbZtbS05Nxzz80555zTvs3nGZ1FrVEuL774YmbMmJGJEyemqqoqSbL11lsX5nuzR6UHwKZpbGzMkCFDUlNTkySpqanJ4MGD09jYmLq6ugqPju5GvbG5tLW15Yc//GFGjRqVxsbGDB06tL2trq4ubW1tWbVqVWprays4Sors7LPPzn333ZdSqZTrrrvO5xlld/nll2fcuHHZdttt27f5PGNzOf3001MqlbLHHnvktNNOU2uUzZIlS1JbW5tp06Zl/vz5ecc73pGJEyemT58+hfjeNIMDgIo777zz0rdv33z+85+v9FDopi644IL8/Oc/z1e+8pVcfPHFlR4O3cyDDz6YhQsXZsKECZUeCm8DN910U2bNmpVbb701pVIp5557bqWHRDfS2tqaJUuW5P3vf39uu+22nH766Tn55JPz0ksvVXpoG0XAUXD19fVZtmxZWltbk/ytIJcvX/66pQVQDuqNzWHq1Kl56qmn8p3vfCfV1dWpr6/P0qVL29ubm5tTXV3tf6Aoi0MOOSTz58/PNtts4/OMsrn//vvzxBNPZP/998+oUaPy7LPP5uijj85TTz3l84yy+/vnVK9evTJhwoQ88MADvjspm/r6+vTo0aN9KcqHPvShDBgwIH369CnE96aAo+AGDhyY4cOHZ86cOUmSOXPmZPjw4V1qmhDdh3qj3L71rW9l4cKFmT59enr16pUk2WWXXfLyyy9nwYIFSZKbb745Y8aMqeQwKbAXX3wxjY2N7a/vvvvubLXVVj7PKKtjjz02v/zlL3P33Xfn7rvvzjbbbJPvfe97+dKXvuTzjLJ66aWXsnr16iRJqVTKHXfckeHDh/vupGzq6uoycuTI3HfffUn+9uSUpqambL/99oX43qwqlUqlSg+CTfPEE09k0qRJef7557Pllltm6tSp2WGHHSo9LAru/PPPz5133pnnnnsuAwYMSG1tbW6//Xb1Rtk8/vjjGTt2bLbffvv06dMnSbLttttm+vTpeeCBBzJlypSsXbs2w4YNyyWXXJKtt966wiOmiJ577rmceOKJWbNmTaqrq7PVVlvlzDPPzAc+8AGfZ2w2o0aNytVXX533vve9Ps8oqyVLluTkk09Oa2tr2trasuOOO+brX/96Bg8erNYomyVLluSss87KqlWr0qNHj5x66qnZd999C/G9KeAAAAAACs8SFQAAAKDwBBwAAABA4Qk4AAAAgMITcAAAAACFJ+AAAAAACk/AAQBdyJNPPpnx48dnt912yw033FDp4VTM1VdfnbPPPrvSw+h0//mf/5m99toru+22W1auXJnf/e53OfDAA7Pbbrvlrrvu6vTxzJ8/P//8z//c6ccFgI7oUekBAAD/33XXXZeRI0dm5syZlR7KBo0aNSrnn39+9tprr7L3ffzxx5e9z67ulVdeyTe/+c3ccssted/73pckueKKK/K5z30uX/jCFyo8OgDo+szgAIAuZOnSpdlpp53e8n6vvvrqZhhNZXSnc3krmpqasnbt2rznPe9p39bRegCAtyMBBwB0EUcccUTmz5+fc889N7vttlseeeSRfO1rX8uHP/zh7LfffrnqqqvS1taWJLntttty2GGH5cILL8zIkSNz5ZVXpqWlJVOnTs3HPvax7LXXXpk8eXJefvnl9v7vuuuujB8/PrvvvnsOOOCA/OIXv0iS3HrrrTnooIOy2267Zf/998/NN9/cvk9zc3OOO+64NDQ0ZMSIEZkwYULa2tpyxhlnZOnSpTn++OOz22675dprr33T83r66aez884757/+67+yzz77ZJ999sn3vve99vYrr7wyp5xySk4//fTsvvvu+fGPf5wrr7wyp59+evt7FixYkMMOOywNDQ3Zd999c9tttyXJBs/5jfx92cXVV1+dkSNHZtSoUZk1a1Z7++rVq9/0uu+3335ZuHBhkmTWrFnZeeed8/jjjydJfvSjH+XEE09c77FbWlpywQUXtF+HCy64IC0tLVm8eHHGjBmTJNlzzz1zxBFH5IADDsiSJUvar3FLS8ub9nv44Yfnsssuy2c+85nsvvvuOeGEE7Jq1ar29oceeqj9+o0bNy7z589vb1vf7/+1brjhhnziE5/Is88+u97zBIBKEHAAQBdxww03pKGhIZMnT86DDz6Y//iP/8jq1atz11135Qc/+EFmzpyZW2+9tf39f/jDH7LddtvlvvvuywknnJBLL700ixcvzowZM3LnnXdm+fLlmT59evt7zzzzzHzta1/LggULctNNN2XYsGFJkoEDB+aaa67JAw88kIsuuigXXXRRHn744STJ9ddfnyFDhuTXv/517rvvvpx22mmpqqrKJZdckqFDh+bqq6/Ogw8+mGOOOWaD5zd//vzceeed+d73vpdrr702v/rVr9rbfvrTn2bMmDFZsGBBDj744HX2e+aZZ3LMMcfk85//fH79619nxowZGT58eJKs95zX57nnnsvKlStz77335pvf/GYmT56cJ598Mkly3nnnvel133PPPfPb3/42SXL//fdnu+22y/3339/+esSIEes97ne/+938/ve/z8yZMzNr1qz88Y9/zFVXXZV3v/vdmTNnTns/N9xwQ+666651rnGvXr3W2/eMGTNy4YUX5pe//GV69OiR888/P0mybNmyHHfccTnhhBPy29/+NmeeeWZOOeWUNDc3J1n/7/8fTZs2LT/+8Y9z4403ZpttttngNQaAzibgAIAuqLW1NXfccUe++tWvpl+/ftl2221z5JFHrjPTYPDgwTn88MPTo0eP9O7dO7fcckvOOuus1NbWpl+/fjnuuONy++23J0n++7//O5/+9Kez9957p7q6OkOGDMmOO+6YJPnYxz6Wd77znamqqsqIESOy9957Z8GCBUmSHj16ZMWKFVm6dGl69uyZhoaGVFVVdeicTjrppPTt2zc777xzPvWpT7X/QZ8ku+66aw444IBUV1enT58+6+w3Z86c7LXXXhk7dmx69uyZAQMGZPjw4SmVSus95w2ZOHFievXqlREjRmTffffN//zP/2zwuv9jwLFgwYIcd9xx6wQce+6553qPOXv27Jx00kkZOHBg6urqctJJJ63zO90U48ePz3vf+9707ds3EydOzNy5c9Pa2pqZM2fmn//5n7Pvvvumuro6e++9d3bZZZfcc889Sdb/+0+SUqmUiy66KPfdd19uuOGG1NXVlWW8AFBubjIKAF3QypUr88orr2To0KHt24YOHZply5a1v/7H/0Vvbm7OmjVr8qlPfap9W6lUal9a0djYmH333fcNj3XPPfdk+vTp+ctf/pK2tra8/PLLee9735skOfroozNt2rQcddRRSZJDDz00xx57bIfOqb6+vv3nYcOG5bHHHnvDc3mtxsbGvPOd73zd9g2d8/psueWW6du3b/vroUOHZvny5Ru87iNGjMjFF1+c5cuXp62tLQcddFCmTZuWp59+OqtXr26fWfJmli9f/rq+ly9fvsHxbox/vL5Dhw7NK6+8kpUrV2bp0qWZO3dufvazn7W3v/rqqxk5cmSS9f/+k78t2bnlllvy7W9/O/379y/LWAFgcxBwAEAXNGDAgPTs2TNLly5tv+lkY2NjhgwZ0v6ef5xJMWDAgPTp0ye33377Ou/5u/r6+vz1r3993faWlpaccsopmTp1avbff//07NkzJ554YkqlUpKkX79+mTRpUiZNmpTHHnssX/jCF/JP//RP+chHPvKWz6mxsbF91sjSpUszePDgNzyXNxr7H/7wh9dt39A5r8/zzz+fl156qT3kaGxszE477bTB6/6ud70rffr0yY033piGhob069cvW2+9dW655Zbsscceqa5e/+TYwYMHr3Pj0MbGxnWuw6ZobGxc5+e/z3apr6/P+PHj25es/KMN/f6Tv4VBl1xySU499dRMmzYte+yxR1nGCwDlZokKAHRBNTU1GTNmTL797W/nhRdeyDPPPJPrr78+48aNe8P3V1dX57Of/WwuvPDCNDU1JfnbvRfuvffeJMlnPvOZ3Hbbbfn1r3+dtra2LFu2LE888URaWlrS0tKSurq69OjRI/fcc0/uu+++9n5/9rOf5amnnkqpVEr//v1TU1PTHkZsvfXWWbJkyUaf01VXXZU1a9bk8ccfz2233ZZPfOITG7XfwQcfnF/96le544478uqrr2blypX505/+tMFz3pC/35h1wYIF+fnPf54xY8Zs1HUfMWJEbrzxxvblKK99vT6f/OQn893vfjfNzc1pbm7O9OnTX3fPkY6aNWtW/vznP2fNmjW5/PLLM3r06NTU1GTcuHH52c9+lnvvvTetra1Zu3Zt5s+fn2effXaDv/+/GzlyZC699NKcfPLJbxg2AUBXIOAAgC7qG9/4RrbYYosccMABmTBhQsaOHZtPf/rTb/r+M844I+9617vyr//6r9l9993zxS9+MYsXL06SfPCDH8xFF12UCy+8MHvssUc+//nPZ+nSpenXr1++/vWv59RTT82ee+6ZOXPmZNSoUe19PvXUUznyyCOz22675dBDD82//du/5cMf/nCS5Nhjj813v/vdNDQ0rPNUlDczYsSIfPzjH88Xv/jFHHXUUdlnn3026joMHTo01157ba6//vqMGDEihxxySB555JENnvP6bL311tlyyy3z0Y9+NKeffnrOOeec9tklG7rue+65Z1588cV1Ao5/fL0+J554YnbZZZeMGzcu48aNywc+8IENPnllY40fPz6TJk3K3nvvnZaWlpx99tlJ/jYD5qqrrso111yTj3zkI9l3333zve99L21tbRv8/f+jvffeOxdeeGGOP/74N7wJKQBUWlXpH+cgAgCU2dNPP539998/Dz/8cHr0qPzq2Pnz5+eMM85of0xud3D44Ydn3Lhx+exnP1vpoQBAxZjBAQAAABRe5f8bBQAovFmzZmXKlCmv2z506NBcc801nT6eq6+++g2Pu8cee+SYY47ZrMf+0pe+lN/97nev237cccfl+OOP73C/u+222xtuv/baazvcJwB0J5aoAAAAAIVniQoAAABQeAIOAAAAoPAEHAAAAEDhCTgAAACAwhNwAAAAAIX3/wD9MHZKevm8CAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Price Dataset**"
      ],
      "metadata": {
        "id": "BwwDHiM4ZSCA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "price_df[\"id\"].value_counts().value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bVD97rmSYS_S",
        "outputId": "7f891cfc-1363-45ce-c843-71e126465111"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "12    15990\n",
              "11       83\n",
              "10       11\n",
              "9         6\n",
              "8         3\n",
              "7         3\n",
              "Name: id, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "price_df[\"price_date\"].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hdLbmLgiZgYA",
        "outputId": "bb249543-f2b6-49e4-81e4-ee9a7efd0fb7"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2015-08-01    16094\n",
              "2015-12-01    16094\n",
              "2015-07-01    16090\n",
              "2015-11-01    16087\n",
              "2015-06-01    16085\n",
              "2015-10-01    16085\n",
              "2015-02-01    16082\n",
              "2015-09-01    16082\n",
              "2015-05-01    16080\n",
              "2015-04-01    16079\n",
              "2015-03-01    16074\n",
              "2015-01-01    16070\n",
              "Name: price_date, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# plot histogram\n",
        "def plot_histogram_by_churn(df, target_variable, figsize=(20,5), bins=100, if_churn=True):\n",
        "    fig = plt.figure(figsize=figsize)\n",
        "    if if_churn:\n",
        "        ax = sns.histplot(data=df, x=target_variable, bins=bins, hue='churn')\n",
        "    else:\n",
        "        ax = sns.histplot(data=df, x=target_variable, bins=bins)"
      ],
      "metadata": {
        "id": "XmMMfHAuZ09m"
      },
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for attr in ['price_off_peak_var', 'price_peak_var', 'price_mid_peak_var', 'price_off_peak_fix', 'price_peak_fix', 'price_mid_peak_fix']:\n",
        "    plot_histogram_by_churn(df=price_df, target_variable=attr, if_churn=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ZsYMP5P1Z-V_",
        "outputId": "5230a312-5954-407a-b81f-8f292aad43bc"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Plot histograms of price features. The values of each feature are centred around some points.\n",
        "\n",
        "There are lots of 0 peak prices and mid-peak prices, but very few 0 off peak prices. So, I will analyse price sensivity only based on off-peak prices"
      ],
      "metadata": {
        "id": "eKf2rDCOaPsH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Hypothesis Investigation\n",
        "Now, let's check customers sensitivity to price. When the price increases and some cutomers leave, then we can say these customers are sensitive to price as the increase in prices lead the customer churn. In case there is a decrease or no change in the price and cutomers still switch, it is hard to say these cutomers are sensitive to price.\n",
        "\n",
        "Since we have the consumption data for each of the companies for the year of 2015, we will create new features to measure price sensitivity using the average of the year, the last 6 months and the last 3 months"
      ],
      "metadata": {
        "id": "0_MMMrjrajfC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create mean average data\n",
        "mean_year = price_df.groupby(['id']).mean().reset_index()\n",
        "mean_6m = price_df[price_df['price_date'] > '2015-06-01'].groupby(['id']).mean().reset_index()\n",
        "mean_3m = price_df[price_df['price_date'] > '2015-10-01'].groupby(['id']).mean().reset_index()"
      ],
      "metadata": {
        "id": "-gkWsQyQaHw1"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_year.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 270
        },
        "id": "kPwzWZPJa-3O",
        "outputId": "d1ee942b-aef9-466e-ccb3-735d2ff66825"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                 id  price_off_peak_var  price_peak_var  \\\n",
              "0  0002203ffbb812588b632b9e628cc38d            0.124338        0.103794   \n",
              "1  0004351ebdd665e6ee664792efc4fd13            0.146426        0.000000   \n",
              "2  0010bcc39e42b3c2131ed2ce55246e3c            0.181558        0.000000   \n",
              "3  0010ee3855fdea87602a5b7aba8e42de            0.118757        0.098292   \n",
              "4  00114d74e963e47177db89bc70108537            0.147926        0.000000   \n",
              "\n",
              "   price_mid_peak_var  price_off_peak_fix  price_peak_fix  price_mid_peak_fix  \n",
              "0            0.073160           40.701732       24.421038           16.280694  \n",
              "1            0.000000           44.385450        0.000000            0.000000  \n",
              "2            0.000000           45.319710        0.000000            0.000000  \n",
              "3            0.069032           40.647427       24.388455           16.258971  \n",
              "4            0.000000           44.266930        0.000000            0.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f99988c1-0189-461c-8631-78daedae076e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>price_off_peak_var</th>\n",
              "      <th>price_peak_var</th>\n",
              "      <th>price_mid_peak_var</th>\n",
              "      <th>price_off_peak_fix</th>\n",
              "      <th>price_peak_fix</th>\n",
              "      <th>price_mid_peak_fix</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0002203ffbb812588b632b9e628cc38d</td>\n",
              "      <td>0.124338</td>\n",
              "      <td>0.103794</td>\n",
              "      <td>0.073160</td>\n",
              "      <td>40.701732</td>\n",
              "      <td>24.421038</td>\n",
              "      <td>16.280694</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0004351ebdd665e6ee664792efc4fd13</td>\n",
              "      <td>0.146426</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.385450</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0010bcc39e42b3c2131ed2ce55246e3c</td>\n",
              "      <td>0.181558</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>45.319710</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0010ee3855fdea87602a5b7aba8e42de</td>\n",
              "      <td>0.118757</td>\n",
              "      <td>0.098292</td>\n",
              "      <td>0.069032</td>\n",
              "      <td>40.647427</td>\n",
              "      <td>24.388455</td>\n",
              "      <td>16.258971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>00114d74e963e47177db89bc70108537</td>\n",
              "      <td>0.147926</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# rename the columns of mean year\n",
        "mean_year = mean_year.rename(\n",
        "\n",
        "    columns={\n",
        "        \"price_off_peak_var\": \"mean_year_price_off_peak_var\",\n",
        "        \"price_peak_var\": \"mean_year_price_peak_var\",\n",
        "        \"price_mid_peak_var\": \"mean_year_price_mid_peak_var\",\n",
        "        \"price_off_peak_fix\": \"mean_year_price_off_peak_fix\",\n",
        "        \"price_peak_fix\": \"mean_year_price_peak_fix\",\n",
        "        \"price_mid_peak_fix\": \"mean_year_price_mid_peak_fix\"\n",
        "    }\n",
        ")"
      ],
      "metadata": {
        "id": "AnvncVXJbBqo"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_year[\"mean_year_price_off_peak\"] = mean_year[\"mean_year_price_off_peak_var\"] + mean_year[\"mean_year_price_off_peak_fix\"]\n",
        "mean_year[\"mean_year_price_peak\"] = mean_year[\"mean_year_price_peak_var\"] + mean_year[\"mean_year_price_peak_fix\"]\n",
        "mean_year[\"mean_year_price_med_peak\"] = mean_year[\"mean_year_price_mid_peak_var\"] + mean_year[\"mean_year_price_mid_peak_fix\"]"
      ],
      "metadata": {
        "id": "ELdKbrUfbHnh"
      },
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#rename the columns of mean 6 month\n",
        "mean_6m = mean_6m.rename(\n",
        "\n",
        "    columns={\n",
        "        \"price_off_peak_var\": \"mean_year_price_off_peak_var\",\n",
        "        \"price_peak_var\": \"mean_year_price_peak_var\",\n",
        "        \"price_mid_peak_var\": \"mean_year_price_mid_peak_var\",\n",
        "        \"price_off_peak_fix\": \"mean_year_price_off_peak_fix\",\n",
        "        \"price_peak_fix\": \"mean_year_price_peak_fix\",\n",
        "        \"price_mid_peak_fix\": \"mean_year_price_mid_peak_fix\"\n",
        "    }\n",
        ")\n",
        "\n",
        "mean_6m[\"mean_year_price_off_peak\"] = mean_6m[\"mean_year_price_off_peak_var\"] + mean_6m[\"mean_year_price_off_peak_fix\"]\n",
        "mean_6m[\"mean_year_price_peak\"] = mean_6m[\"mean_year_price_peak_var\"] + mean_6m[\"mean_year_price_peak_fix\"]\n",
        "mean_6m[\"mean_year_price_med_peak\"] = mean_6m[\"mean_year_price_mid_peak_var\"] + mean_6m[\"mean_year_price_mid_peak_fix\"]"
      ],
      "metadata": {
        "id": "ikC2rWscbSUJ"
      },
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#rename the columns of mean 3 month\n",
        "mean_3m = mean_3m.rename(\n",
        "\n",
        "    columns={\n",
        "        \"price_off_peak_var\": \"mean_year_price_off_peak_var\",\n",
        "        \"price_peak_var\": \"mean_year_price_peak_var\",\n",
        "        \"price_mid_peak_var\": \"mean_year_price_mid_peak_var\",\n",
        "        \"price_off_peak_fix\": \"mean_year_price_off_peak_fix\",\n",
        "        \"price_peak_fix\": \"mean_year_price_peak_fix\",\n",
        "        \"price_mid_peak_fix\": \"mean_year_price_mid_peak_fix\"\n",
        "    }\n",
        ")\n",
        "\n",
        "mean_3m[\"mean_year_price_off_peak\"] = mean_3m[\"mean_year_price_off_peak_var\"] + mean_3m[\"mean_year_price_off_peak_fix\"]\n",
        "mean_3m[\"mean_year_price_peak\"] = mean_3m[\"mean_year_price_peak_var\"] + mean_3m[\"mean_year_price_peak_fix\"]\n",
        "mean_3m[\"mean_year_price_med_peak\"] = mean_3m[\"mean_year_price_mid_peak_var\"] + mean_3m[\"mean_year_price_mid_peak_fix\"]"
      ],
      "metadata": {
        "id": "kW-Niei4bZC9"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Merge into 1 dataframe\n",
        "price_features = pd.merge(mean_year, mean_6m, on='id')\n",
        "price_features = pd.merge(price_features, mean_3m, on='id')"
      ],
      "metadata": {
        "id": "V7ziSjW7be3V"
      },
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "price_features.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "16FPkPjIbi4E",
        "outputId": "f58b4358-d929-4717-ab6d-89248b9ff69e"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                 id  mean_year_price_off_peak_var_x  \\\n",
              "0  0002203ffbb812588b632b9e628cc38d                        0.124338   \n",
              "1  0004351ebdd665e6ee664792efc4fd13                        0.146426   \n",
              "2  0010bcc39e42b3c2131ed2ce55246e3c                        0.181558   \n",
              "3  0010ee3855fdea87602a5b7aba8e42de                        0.118757   \n",
              "4  00114d74e963e47177db89bc70108537                        0.147926   \n",
              "\n",
              "   mean_year_price_peak_var_x  mean_year_price_mid_peak_var_x  \\\n",
              "0                    0.103794                        0.073160   \n",
              "1                    0.000000                        0.000000   \n",
              "2                    0.000000                        0.000000   \n",
              "3                    0.098292                        0.069032   \n",
              "4                    0.000000                        0.000000   \n",
              "\n",
              "   mean_year_price_off_peak_fix_x  mean_year_price_peak_fix_x  \\\n",
              "0                       40.701732                   24.421038   \n",
              "1                       44.385450                    0.000000   \n",
              "2                       45.319710                    0.000000   \n",
              "3                       40.647427                   24.388455   \n",
              "4                       44.266930                    0.000000   \n",
              "\n",
              "   mean_year_price_mid_peak_fix_x  mean_year_price_off_peak_x  \\\n",
              "0                       16.280694                   40.826071   \n",
              "1                        0.000000                   44.531877   \n",
              "2                        0.000000                   45.501268   \n",
              "3                       16.258971                   40.766185   \n",
              "4                        0.000000                   44.414856   \n",
              "\n",
              "   mean_year_price_peak_x  mean_year_price_med_peak_x  ...  \\\n",
              "0               24.524832                   16.353854  ...   \n",
              "1                0.000000                    0.000000  ...   \n",
              "2                0.000000                    0.000000  ...   \n",
              "3               24.486748                   16.328003  ...   \n",
              "4                0.000000                    0.000000  ...   \n",
              "\n",
              "   mean_year_price_med_peak_y  mean_year_price_off_peak_var  \\\n",
              "0                   16.365283                      0.119906   \n",
              "1                    0.000000                      0.143943   \n",
              "2                    0.000000                      0.201280   \n",
              "3                   16.360973                      0.113068   \n",
              "4                    0.000000                      0.145440   \n",
              "\n",
              "   mean_year_price_peak_var  mean_year_price_mid_peak_var  \\\n",
              "0                  0.101673                      0.073719   \n",
              "1                  0.000000                      0.000000   \n",
              "2                  0.000000                      0.000000   \n",
              "3                  0.095385                      0.069409   \n",
              "4                  0.000000                      0.000000   \n",
              "\n",
              "   mean_year_price_off_peak_fix  mean_year_price_peak_fix  \\\n",
              "0                     40.728885                  24.43733   \n",
              "1                     44.444710                   0.00000   \n",
              "2                     45.944710                   0.00000   \n",
              "3                     40.728885                  24.43733   \n",
              "4                     44.266930                   0.00000   \n",
              "\n",
              "   mean_year_price_mid_peak_fix  mean_year_price_off_peak  \\\n",
              "0                     16.291555                 40.848791   \n",
              "1                      0.000000                 44.588653   \n",
              "2                      0.000000                 46.145990   \n",
              "3                     16.291555                 40.841953   \n",
              "4                      0.000000                 44.412370   \n",
              "\n",
              "   mean_year_price_peak  mean_year_price_med_peak  \n",
              "0             24.539003                 16.365274  \n",
              "1              0.000000                  0.000000  \n",
              "2              0.000000                  0.000000  \n",
              "3             24.532715                 16.360964  \n",
              "4              0.000000                  0.000000  \n",
              "\n",
              "[5 rows x 28 columns]"
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              "      <th>mean_year_price_off_peak_var_x</th>\n",
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              "      <th>mean_year_price_peak_var</th>\n",
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              "      <th>mean_year_price_peak_fix</th>\n",
              "      <th>mean_year_price_mid_peak_fix</th>\n",
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              "      <th>mean_year_price_peak</th>\n",
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              "      <td>0.113068</td>\n",
              "      <td>0.095385</td>\n",
              "      <td>0.069409</td>\n",
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              "<p>5 rows × 28 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-771dcddf-eff8-47ff-9b65-9a16506c3682')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Let's merge the price feature dataset with churn variable to check whether price sensitivity has any correlation with churn."
      ],
      "metadata": {
        "id": "TOjZtd1dbtpF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "price_churn = pd.merge(price_features, client_df[['id', 'churn']], on='id')\n",
        "price_churn.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "62meLJQ3bp6k",
        "outputId": "734691e3-cdef-4b72-82c8-b12dcc087035"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                                 id  mean_year_price_off_peak_var_x  \\\n",
              "0  0002203ffbb812588b632b9e628cc38d                        0.124338   \n",
              "1  0004351ebdd665e6ee664792efc4fd13                        0.146426   \n",
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              "4  0013f326a839a2f6ad87a1859952d227                        0.126076   \n",
              "\n",
              "   mean_year_price_peak_var_x  mean_year_price_mid_peak_var_x  \\\n",
              "0                    0.103794                        0.073160   \n",
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              "2                    0.000000                        0.000000   \n",
              "3                    0.000000                        0.000000   \n",
              "4                    0.105542                        0.074921   \n",
              "\n",
              "   mean_year_price_off_peak_fix_x  mean_year_price_peak_fix_x  \\\n",
              "0                       40.701732                   24.421038   \n",
              "1                       44.385450                    0.000000   \n",
              "2                       45.319710                    0.000000   \n",
              "3                       44.266930                    0.000000   \n",
              "4                       40.728885                   24.437330   \n",
              "\n",
              "   mean_year_price_mid_peak_fix_x  mean_year_price_off_peak_x  \\\n",
              "0                       16.280694                   40.826071   \n",
              "1                        0.000000                   44.531877   \n",
              "2                        0.000000                   45.501268   \n",
              "3                        0.000000                   44.414856   \n",
              "4                       16.291555                   40.854961   \n",
              "\n",
              "   mean_year_price_peak_x  mean_year_price_med_peak_x  ...  \\\n",
              "0               24.524832                   16.353854  ...   \n",
              "1                0.000000                    0.000000  ...   \n",
              "2                0.000000                    0.000000  ...   \n",
              "3                0.000000                    0.000000  ...   \n",
              "4               24.542872                   16.366476  ...   \n",
              "\n",
              "   mean_year_price_off_peak_var  mean_year_price_peak_var  \\\n",
              "0                      0.119906                  0.101673   \n",
              "1                      0.143943                  0.000000   \n",
              "2                      0.201280                  0.000000   \n",
              "3                      0.145440                  0.000000   \n",
              "4                      0.121647                  0.103413   \n",
              "\n",
              "   mean_year_price_mid_peak_var  mean_year_price_off_peak_fix  \\\n",
              "0                      0.073719                     40.728885   \n",
              "1                      0.000000                     44.444710   \n",
              "2                      0.000000                     45.944710   \n",
              "3                      0.000000                     44.266930   \n",
              "4                      0.075460                     40.728885   \n",
              "\n",
              "   mean_year_price_peak_fix  mean_year_price_mid_peak_fix  \\\n",
              "0                  24.43733                     16.291555   \n",
              "1                   0.00000                      0.000000   \n",
              "2                   0.00000                      0.000000   \n",
              "3                   0.00000                      0.000000   \n",
              "4                  24.43733                     16.291555   \n",
              "\n",
              "   mean_year_price_off_peak  mean_year_price_peak  mean_year_price_med_peak  \\\n",
              "0                 40.848791             24.539003                 16.365274   \n",
              "1                 44.588653              0.000000                  0.000000   \n",
              "2                 46.145990              0.000000                  0.000000   \n",
              "3                 44.412370              0.000000                  0.000000   \n",
              "4                 40.850532             24.540743                 16.367015   \n",
              "\n",
              "   churn  \n",
              "0      0  \n",
              "1      0  \n",
              "2      0  \n",
              "3      0  \n",
              "4      0  \n",
              "\n",
              "[5 rows x 29 columns]"
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              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr = price_churn.corr()\n",
        "# Plot correlation\n",
        "plt.figure(figsize=(20,18))\n",
        "sns.heatmap(corr, xticklabels=corr.columns.values, yticklabels=corr.columns.values, cmap='Greens', annot = True, annot_kws={'size':10})\n",
        "# Axis ticks size\n",
        "plt.xticks(fontsize=10)\n",
        "plt.yticks(fontsize=10)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ITh8u-iGbz1Z",
        "outputId": "1beaa7b8-2dbf-41fb-b7d8-ba2a1e3d4f49"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1296 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The above plot shows the correlation betweeen price variables with each other and with churn, however, the correlation between churn and prices variables is very low, which mean customers' churn is not sensitive to price change.\n",
        "\n",
        "Now, we will merge the client data with price churn data for modeling in the next move."
      ],
      "metadata": {
        "id": "k1EFPV8DcAMR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data = pd.merge(client_df.drop(columns=['churn']), price_churn, on='id')"
      ],
      "metadata": {
        "id": "kInttqT0b32s"
      },
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "Ipez07lFcH_L",
        "outputId": "80e11f29-d7c8-4ba1-e335-296a644de8d9"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                 id                     channel_sales  \\\n",
              "0  24011ae4ebbe3035111d65fa7c15bc57  foosdfpfkusacimwkcsosbicdxkicaua   \n",
              "1  d29c2c54acc38ff3c0614d0a653813dd                           MISSING   \n",
              "2  764c75f661154dac3a6c254cd082ea7d  foosdfpfkusacimwkcsosbicdxkicaua   \n",
              "3  bba03439a292a1e166f80264c16191cb  lmkebamcaaclubfxadlmueccxoimlema   \n",
              "4  149d57cf92fc41cf94415803a877cb4b                           MISSING   \n",
              "\n",
              "   cons_12m  cons_gas_12m  cons_last_month date_activ   date_end  \\\n",
              "0         0         54946                0 2013-06-15 2016-06-15   \n",
              "1      4660             0                0 2009-08-21 2016-08-30   \n",
              "2       544             0                0 2010-04-16 2016-04-16   \n",
              "3      1584             0                0 2010-03-30 2016-03-30   \n",
              "4      4425             0              526 2010-01-13 2016-03-07   \n",
              "\n",
              "  date_modif_prod date_renewal  forecast_cons_12m  ...  \\\n",
              "0      2015-11-01   2015-06-23               0.00  ...   \n",
              "1      2009-08-21   2015-08-31             189.95  ...   \n",
              "2      2010-04-16   2015-04-17              47.96  ...   \n",
              "3      2010-03-30   2015-03-31             240.04  ...   \n",
              "4      2010-01-13   2015-03-09             445.75  ...   \n",
              "\n",
              "   mean_year_price_off_peak_var  mean_year_price_peak_var  \\\n",
              "0                      0.131756                  0.092638   \n",
              "1                      0.147600                  0.000000   \n",
              "2                      0.167798                  0.088409   \n",
              "3                      0.148586                  0.000000   \n",
              "4                      0.119906                  0.101673   \n",
              "\n",
              "   mean_year_price_mid_peak_var  mean_year_price_off_peak_fix  \\\n",
              "0                      0.036909                     42.497907   \n",
              "1                      0.000000                     44.444710   \n",
              "2                      0.000000                     44.444710   \n",
              "3                      0.000000                     44.444710   \n",
              "4                      0.073719                     40.728885   \n",
              "\n",
              "   mean_year_price_peak_fix  mean_year_price_mid_peak_fix  \\\n",
              "0                 12.218665                      8.145777   \n",
              "1                  0.000000                      0.000000   \n",
              "2                  0.000000                      0.000000   \n",
              "3                  0.000000                      0.000000   \n",
              "4                 24.437330                     16.291555   \n",
              "\n",
              "  mean_year_price_off_peak  mean_year_price_peak  mean_year_price_med_peak  \\\n",
              "0                42.629663             12.311304                  8.182687   \n",
              "1                44.592310              0.000000                  0.000000   \n",
              "2                44.612508              0.088409                  0.000000   \n",
              "3                44.593296              0.000000                  0.000000   \n",
              "4                40.848791             24.539003                 16.365274   \n",
              "\n",
              "   churn  \n",
              "0      1  \n",
              "1      0  \n",
              "2      0  \n",
              "3      0  \n",
              "4      0  \n",
              "\n",
              "[5 rows x 53 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-70c872b3-9c5d-4c52-84f3-ec46106f1288\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>id</th>\n",
              "      <th>channel_sales</th>\n",
              "      <th>cons_12m</th>\n",
              "      <th>cons_gas_12m</th>\n",
              "      <th>cons_last_month</th>\n",
              "      <th>date_activ</th>\n",
              "      <th>date_end</th>\n",
              "      <th>date_modif_prod</th>\n",
              "      <th>date_renewal</th>\n",
              "      <th>forecast_cons_12m</th>\n",
              "      <th>...</th>\n",
              "      <th>mean_year_price_off_peak_var</th>\n",
              "      <th>mean_year_price_peak_var</th>\n",
              "      <th>mean_year_price_mid_peak_var</th>\n",
              "      <th>mean_year_price_off_peak_fix</th>\n",
              "      <th>mean_year_price_peak_fix</th>\n",
              "      <th>mean_year_price_mid_peak_fix</th>\n",
              "      <th>mean_year_price_off_peak</th>\n",
              "      <th>mean_year_price_peak</th>\n",
              "      <th>mean_year_price_med_peak</th>\n",
              "      <th>churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>24011ae4ebbe3035111d65fa7c15bc57</td>\n",
              "      <td>foosdfpfkusacimwkcsosbicdxkicaua</td>\n",
              "      <td>0</td>\n",
              "      <td>54946</td>\n",
              "      <td>0</td>\n",
              "      <td>2013-06-15</td>\n",
              "      <td>2016-06-15</td>\n",
              "      <td>2015-11-01</td>\n",
              "      <td>2015-06-23</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.131756</td>\n",
              "      <td>0.092638</td>\n",
              "      <td>0.036909</td>\n",
              "      <td>42.497907</td>\n",
              "      <td>12.218665</td>\n",
              "      <td>8.145777</td>\n",
              "      <td>42.629663</td>\n",
              "      <td>12.311304</td>\n",
              "      <td>8.182687</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>d29c2c54acc38ff3c0614d0a653813dd</td>\n",
              "      <td>MISSING</td>\n",
              "      <td>4660</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2009-08-21</td>\n",
              "      <td>2016-08-30</td>\n",
              "      <td>2009-08-21</td>\n",
              "      <td>2015-08-31</td>\n",
              "      <td>189.95</td>\n",
              "      <td>...</td>\n",
              "      <td>0.147600</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.444710</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.592310</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>764c75f661154dac3a6c254cd082ea7d</td>\n",
              "      <td>foosdfpfkusacimwkcsosbicdxkicaua</td>\n",
              "      <td>544</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2010-04-16</td>\n",
              "      <td>2016-04-16</td>\n",
              "      <td>2010-04-16</td>\n",
              "      <td>2015-04-17</td>\n",
              "      <td>47.96</td>\n",
              "      <td>...</td>\n",
              "      <td>0.167798</td>\n",
              "      <td>0.088409</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.444710</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.612508</td>\n",
              "      <td>0.088409</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>bba03439a292a1e166f80264c16191cb</td>\n",
              "      <td>lmkebamcaaclubfxadlmueccxoimlema</td>\n",
              "      <td>1584</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2010-03-30</td>\n",
              "      <td>2016-03-30</td>\n",
              "      <td>2010-03-30</td>\n",
              "      <td>2015-03-31</td>\n",
              "      <td>240.04</td>\n",
              "      <td>...</td>\n",
              "      <td>0.148586</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.444710</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.593296</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>149d57cf92fc41cf94415803a877cb4b</td>\n",
              "      <td>MISSING</td>\n",
              "      <td>4425</td>\n",
              "      <td>0</td>\n",
              "      <td>526</td>\n",
              "      <td>2010-01-13</td>\n",
              "      <td>2016-03-07</td>\n",
              "      <td>2010-01-13</td>\n",
              "      <td>2015-03-09</td>\n",
              "      <td>445.75</td>\n",
              "      <td>...</td>\n",
              "      <td>0.119906</td>\n",
              "      <td>0.101673</td>\n",
              "      <td>0.073719</td>\n",
              "      <td>40.728885</td>\n",
              "      <td>24.437330</td>\n",
              "      <td>16.291555</td>\n",
              "      <td>40.848791</td>\n",
              "      <td>24.539003</td>\n",
              "      <td>16.365274</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 53 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-70c872b3-9c5d-4c52-84f3-ec46106f1288')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-70c872b3-9c5d-4c52-84f3-ec46106f1288 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-70c872b3-9c5d-4c52-84f3-ec46106f1288');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.to_csv('churn_data_modeling.csv')"
      ],
      "metadata": {
        "id": "8EUZJuF6cOoy"
      },
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "NT1mSkyKcRyR"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}