Telecom churn Prediction.ipynb

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      "cell_type": "markdown",
      "source": [
        "# Ulwe Dataset-Customer Churn Prediction\n",
        "# Machine Learning Assignment\n",
        "## Solomon Amaning Odum\n"
      ],
      "metadata": {
        "id": "fYiC1ZjdS-Dl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Exploratory Data Analysis"
      ],
      "metadata": {
        "id": "nGgY1bwfTGJ2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "import plotly.express as px\n",
        "import matplotlib.pyplot as plt\n",
        "import statsmodels.formula.api as smf\n",
        "import seaborn as sns\n",
        "from scipy.stats import linregress\n",
        "from pandas.io.formats.info import DataFrameInfo\n",
        "from sklearn.metrics import roc_auc_score\n",
        "from sklearn.metrics import roc_curve\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.metrics import accuracy_score, f1_score, confusion_matrix\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "#load packages\n",
        "import sys #access to system parameters https://docs.python.org/3/library/sys.html\n",
        "print(\"Python version: {}\". format(sys.version))\n",
        "\n",
        "import pandas as pd #collection of functions for data processing and analysis modeled after R dataframes with SQL like features\n",
        "print(\"pandas version: {}\". format(pd.__version__))\n",
        "\n",
        "import matplotlib #collection of functions for scientific and publication-ready visualization\n",
        "print(\"matplotlib version: {}\". format(matplotlib.__version__))\n",
        "\n",
        "import numpy as np #foundational package for scientific computing\n",
        "print(\"NumPy version: {}\". format(np.__version__))\n",
        "\n",
        "import scipy as sp #collection of functions for scientific computing and advance mathematics\n",
        "print(\"SciPy version: {}\". format(sp.__version__)) \n",
        "\n",
        "import IPython\n",
        "from IPython import display #pretty printing of dataframes in Jupyter notebook\n",
        "print(\"IPython version: {}\". format(IPython.__version__)) \n",
        "\n",
        "import sklearn #collection of machine learning algorithms\n",
        "print(\"scikit-learn version: {}\". format(sklearn.__version__))\n",
        "\n",
        "#misc libraries\n",
        "import random\n",
        "import time\n",
        "\n",
        "\n",
        "#ignore warnings\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "print('-'*25)\n"
      ],
      "metadata": {
        "id": "-8wzwY8GTLB5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
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        "outputId": "e3679544-3666-4aee-b460-a4b2b19cf2fb"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python version: 3.8.16 (default, Dec  7 2022, 01:12:13) \n",
            "[GCC 7.5.0]\n",
            "pandas version: 1.3.5\n",
            "matplotlib version: 3.2.2\n",
            "NumPy version: 1.21.6\n",
            "SciPy version: 1.7.3\n",
            "IPython version: 7.9.0\n",
            "scikit-learn version: 1.0.2\n",
            "-------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data=pd.read_csv(\"/content/drive/MyDrive/Ulwe dataset/Dataset (1).csv\", index_col=[0])\n",
        "data.head(5)\n"
      ],
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        "id": "Vgxy9E0uVMb1",
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          "height": 331
        },
        "outputId": "07cf196f-63b0-4d90-c7bb-6ffdccd71bec"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "              ownership  activation_plan_code  mnp_flag  calls_incoming_cnt  \\\n",
              "customer_id                                                                   \n",
              "10000        individual                     4         0                31.0   \n",
              "10001        individual                     6         0                 8.0   \n",
              "10002        individual                     8         1                13.0   \n",
              "10003        individual                     7         0                20.0   \n",
              "10004        individual                     3         1                22.0   \n",
              "\n",
              "             calls_outgoing_cnt  calls_incoming_duration  \\\n",
              "customer_id                                                \n",
              "10000                     333.0                31.980873   \n",
              "10001                      42.0                 9.577651   \n",
              "10002                       0.0                15.368591   \n",
              "10003                      38.0                21.091508   \n",
              "10004                      29.0                25.592874   \n",
              "\n",
              "             calls_outgoing_duration  total_call_count  total_sum_duration  \\\n",
              "customer_id                                                                  \n",
              "10000                     548.719449             364.0          580.700321   \n",
              "10001                      43.988952              50.0           53.566603   \n",
              "10002                       0.000000              13.0           15.368591   \n",
              "10003                      52.044282              58.0           73.135790   \n",
              "10004                      41.290402              51.0           66.883276   \n",
              "\n",
              "             tot_usage_mb  ...  last_cycle_plan_mrp  last_cycle_plan_validity  \\\n",
              "customer_id                ...                                                  \n",
              "10000         3163.351573  ...                 2999                       700   \n",
              "10001         3672.746526  ...                 2999                       700   \n",
              "10002         4712.106937  ...                  500                       120   \n",
              "10003        11356.222392  ...                  500                       120   \n",
              "10004        11302.446568  ...                  999                       180   \n",
              "\n",
              "             avg_days_bw_rchg_and_expiry  stddev_days_bw_rchg_and_expiry  \\\n",
              "customer_id                                                                \n",
              "10000                          -1.113238                        2.801930   \n",
              "10001                          -2.032090                        1.600223   \n",
              "10002                          -2.350133                        0.782016   \n",
              "10003                           2.366904                        1.255292   \n",
              "10004                           2.121814                        3.132883   \n",
              "\n",
              "             price_per_day  gb_per_day_quota  pcnt_quota_used  device_avg_asp  \\\n",
              "customer_id                                                                     \n",
              "10000             3.333333               1.5         6.864912      10K_to_20K   \n",
              "10001             5.550000               3.0         3.985185      10K_to_20K   \n",
              "10002             4.571429               1.0        15.338890      20K_to_30K   \n",
              "10003             4.284286               4.0         9.241717        less_10K   \n",
              "10004             4.109589               3.0        12.263939      10K_to_20K   \n",
              "\n",
              "             recharge_delay  churn  \n",
              "customer_id                         \n",
              "10000             -3.221785      0  \n",
              "10001             -4.916200      0  \n",
              "10002              4.455835      0  \n",
              "10003              0.180850      0  \n",
              "10004              4.690059      0  \n",
              "\n",
              "[5 rows x 47 columns]"
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              "      <td>-4.916200</td>\n",
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    {
      "cell_type": "code",
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        "y=data.isnull().sum()\n",
        "y"
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ownership                             0\n",
              "activation_plan_code                  0\n",
              "mnp_flag                              0\n",
              "calls_incoming_cnt                    0\n",
              "calls_outgoing_cnt                    0\n",
              "calls_incoming_duration               0\n",
              "calls_outgoing_duration               0\n",
              "total_call_count                      0\n",
              "total_sum_duration                    0\n",
              "tot_usage_mb                          0\n",
              "upload_usage_mb                       0\n",
              "download_usage_mb                     0\n",
              "days_since_latch                      0\n",
              "cnt_open_qrc                          0\n",
              "avg_days_to_close                    26\n",
              "cnt_call_drops                        0\n",
              "pcnt_dropped_calls                    0\n",
              "rsrp_voice_pcnt_poor_duration         0\n",
              "rsrp_data_pcnt_poor_duration          0\n",
              "mean_cqi_voice_pcnt_poor_duration     0\n",
              "sinr_voice_pcnt_poor_duration         0\n",
              "sinr_data_pcnt_poor_duration          0\n",
              "age_on_network                        0\n",
              "cnt_connections                       0\n",
              "current_plan_code                     0\n",
              "cnt_recharges_made                    0\n",
              "total_payment_made                    0\n",
              "cnt_main_plans_taken                  0\n",
              "total_main_plans_mrp                  0\n",
              "cnt_addon_plans_taken                 0\n",
              "total_addon_plans_mrp                 0\n",
              "cnt_rchg_offline                      0\n",
              "cnt_rchg_online                       0\n",
              "cnt_rchg_on_or_before_expiry          0\n",
              "cnt_rchg_after_expiry                 0\n",
              "current_active_plan_mrp               0\n",
              "current_active_plan_validity          0\n",
              "last_cycle_plan_mrp                   0\n",
              "last_cycle_plan_validity              0\n",
              "avg_days_bw_rchg_and_expiry           0\n",
              "stddev_days_bw_rchg_and_expiry        0\n",
              "price_per_day                         0\n",
              "gb_per_day_quota                      0\n",
              "pcnt_quota_used                       0\n",
              "device_avg_asp                        0\n",
              "recharge_delay                        0\n",
              "churn                                 0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#checking categorical variable\n",
        "data.select_dtypes(include=['object']).columns.tolist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "HgSr402riTLP",
        "outputId": "fc6edb46-68af-4fa6-c505-f7839b95bb18"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['ownership', 'device_avg_asp']"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "nyQAauamMZzW",
        "outputId": "25b307c6-0076-4177-e90c-16f9625b7dee"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1000, 47)"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        },
        "id": "_G-XNW-KMoJo",
        "outputId": "ddca38ab-1b70-495a-9d42-8437c15d2f74"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              ownership  activation_plan_code  mnp_flag  calls_incoming_cnt  \\\n",
              "customer_id                                                                   \n",
              "10000        individual                     4         0                31.0   \n",
              "10001        individual                     6         0                 8.0   \n",
              "10002        individual                     8         1                13.0   \n",
              "10003        individual                     7         0                20.0   \n",
              "10004        individual                     3         1                22.0   \n",
              "\n",
              "             calls_outgoing_cnt  calls_incoming_duration  \\\n",
              "customer_id                                                \n",
              "10000                     333.0                31.980873   \n",
              "10001                      42.0                 9.577651   \n",
              "10002                       0.0                15.368591   \n",
              "10003                      38.0                21.091508   \n",
              "10004                      29.0                25.592874   \n",
              "\n",
              "             calls_outgoing_duration  total_call_count  total_sum_duration  \\\n",
              "customer_id                                                                  \n",
              "10000                     548.719449             364.0          580.700321   \n",
              "10001                      43.988952              50.0           53.566603   \n",
              "10002                       0.000000              13.0           15.368591   \n",
              "10003                      52.044282              58.0           73.135790   \n",
              "10004                      41.290402              51.0           66.883276   \n",
              "\n",
              "             tot_usage_mb  ...  last_cycle_plan_mrp  last_cycle_plan_validity  \\\n",
              "customer_id                ...                                                  \n",
              "10000         3163.351573  ...                 2999                       700   \n",
              "10001         3672.746526  ...                 2999                       700   \n",
              "10002         4712.106937  ...                  500                       120   \n",
              "10003        11356.222392  ...                  500                       120   \n",
              "10004        11302.446568  ...                  999                       180   \n",
              "\n",
              "             avg_days_bw_rchg_and_expiry  stddev_days_bw_rchg_and_expiry  \\\n",
              "customer_id                                                                \n",
              "10000                          -1.113238                        2.801930   \n",
              "10001                          -2.032090                        1.600223   \n",
              "10002                          -2.350133                        0.782016   \n",
              "10003                           2.366904                        1.255292   \n",
              "10004                           2.121814                        3.132883   \n",
              "\n",
              "             price_per_day  gb_per_day_quota  pcnt_quota_used  device_avg_asp  \\\n",
              "customer_id                                                                     \n",
              "10000             3.333333               1.5         6.864912      10K_to_20K   \n",
              "10001             5.550000               3.0         3.985185      10K_to_20K   \n",
              "10002             4.571429               1.0        15.338890      20K_to_30K   \n",
              "10003             4.284286               4.0         9.241717        less_10K   \n",
              "10004             4.109589               3.0        12.263939      10K_to_20K   \n",
              "\n",
              "             recharge_delay  churn  \n",
              "customer_id                         \n",
              "10000             -3.221785      0  \n",
              "10001             -4.916200      0  \n",
              "10002              4.455835      0  \n",
              "10003              0.180850      0  \n",
              "10004              4.690059      0  \n",
              "\n",
              "[5 rows x 47 columns]"
            ],
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              "\n",
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              "      <th>ownership</th>\n",
              "      <th>activation_plan_code</th>\n",
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              "      <th>avg_days_bw_rchg_and_expiry</th>\n",
              "      <th>stddev_days_bw_rchg_and_expiry</th>\n",
              "      <th>price_per_day</th>\n",
              "      <th>gb_per_day_quota</th>\n",
              "      <th>pcnt_quota_used</th>\n",
              "      <th>device_avg_asp</th>\n",
              "      <th>recharge_delay</th>\n",
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              "      <th>customer_id</th>\n",
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              "      <th>10000</th>\n",
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              "      <td>4</td>\n",
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              "      <td>31.0</td>\n",
              "      <td>333.0</td>\n",
              "      <td>31.980873</td>\n",
              "      <td>548.719449</td>\n",
              "      <td>364.0</td>\n",
              "      <td>580.700321</td>\n",
              "      <td>3163.351573</td>\n",
              "      <td>...</td>\n",
              "      <td>2999</td>\n",
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              "      <td>-1.113238</td>\n",
              "      <td>2.801930</td>\n",
              "      <td>3.333333</td>\n",
              "      <td>1.5</td>\n",
              "      <td>6.864912</td>\n",
              "      <td>10K_to_20K</td>\n",
              "      <td>-3.221785</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10001</th>\n",
              "      <td>individual</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>9.577651</td>\n",
              "      <td>43.988952</td>\n",
              "      <td>50.0</td>\n",
              "      <td>53.566603</td>\n",
              "      <td>3672.746526</td>\n",
              "      <td>...</td>\n",
              "      <td>2999</td>\n",
              "      <td>700</td>\n",
              "      <td>-2.032090</td>\n",
              "      <td>1.600223</td>\n",
              "      <td>5.550000</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.985185</td>\n",
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              "      <td>-4.916200</td>\n",
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              "      <th>10002</th>\n",
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              "      <td>8</td>\n",
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              "      <td>13.0</td>\n",
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              "      <td>15.368591</td>\n",
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              "      <td>13.0</td>\n",
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              "      <td>4712.106937</td>\n",
              "      <td>...</td>\n",
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              "      <td>120</td>\n",
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              "      <td>0.782016</td>\n",
              "      <td>4.571429</td>\n",
              "      <td>1.0</td>\n",
              "      <td>15.338890</td>\n",
              "      <td>20K_to_30K</td>\n",
              "      <td>4.455835</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10003</th>\n",
              "      <td>individual</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>21.091508</td>\n",
              "      <td>52.044282</td>\n",
              "      <td>58.0</td>\n",
              "      <td>73.135790</td>\n",
              "      <td>11356.222392</td>\n",
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              "      <td>500</td>\n",
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              "      <td>2.366904</td>\n",
              "      <td>1.255292</td>\n",
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              "      <td>4.0</td>\n",
              "      <td>9.241717</td>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>10004</th>\n",
              "      <td>individual</td>\n",
              "      <td>3</td>\n",
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              "      <td>29.0</td>\n",
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              "      <td>51.0</td>\n",
              "      <td>66.883276</td>\n",
              "      <td>11302.446568</td>\n",
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              "</table>\n",
              "<p>5 rows × 47 columns</p>\n",
              "</div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.get_dummies(data, columns=['ownership', 'device_avg_asp'])"
      ],
      "metadata": {
        "id": "kPBvN6mcn80H"
      },
      "execution_count": 64,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "LLsWshDQb56X",
        "outputId": "3ef737e4-c930-41ab-ddae-a482d4bdc314"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "activation_plan_code                  0\n",
              "mnp_flag                              0\n",
              "calls_incoming_cnt                    0\n",
              "calls_outgoing_cnt                    0\n",
              "calls_incoming_duration               0\n",
              "calls_outgoing_duration               0\n",
              "total_call_count                      0\n",
              "total_sum_duration                    0\n",
              "tot_usage_mb                          0\n",
              "upload_usage_mb                       0\n",
              "download_usage_mb                     0\n",
              "days_since_latch                      0\n",
              "cnt_open_qrc                          0\n",
              "avg_days_to_close                    26\n",
              "cnt_call_drops                        0\n",
              "pcnt_dropped_calls                    0\n",
              "rsrp_voice_pcnt_poor_duration         0\n",
              "rsrp_data_pcnt_poor_duration          0\n",
              "mean_cqi_voice_pcnt_poor_duration     0\n",
              "sinr_voice_pcnt_poor_duration         0\n",
              "sinr_data_pcnt_poor_duration          0\n",
              "age_on_network                        0\n",
              "cnt_connections                       0\n",
              "current_plan_code                     0\n",
              "cnt_recharges_made                    0\n",
              "total_payment_made                    0\n",
              "cnt_main_plans_taken                  0\n",
              "total_main_plans_mrp                  0\n",
              "cnt_addon_plans_taken                 0\n",
              "total_addon_plans_mrp                 0\n",
              "cnt_rchg_offline                      0\n",
              "cnt_rchg_online                       0\n",
              "cnt_rchg_on_or_before_expiry          0\n",
              "cnt_rchg_after_expiry                 0\n",
              "current_active_plan_mrp               0\n",
              "current_active_plan_validity          0\n",
              "last_cycle_plan_mrp                   0\n",
              "last_cycle_plan_validity              0\n",
              "avg_days_bw_rchg_and_expiry           0\n",
              "stddev_days_bw_rchg_and_expiry        0\n",
              "price_per_day                         0\n",
              "gb_per_day_quota                      0\n",
              "pcnt_quota_used                       0\n",
              "recharge_delay                        0\n",
              "churn                                 0\n",
              "ownership_corporate                   0\n",
              "ownership_individual                  0\n",
              "device_avg_asp_10K_to_20K             0\n",
              "device_avg_asp_20K_to_30K             0\n",
              "device_avg_asp_30K_to_50K             0\n",
              "device_avg_asp_50K_above              0\n",
              "device_avg_asp_less_10K               0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# replacing missing values of 'avg_days_to_close' with its mode\n",
        "mode_value = data['avg_days_to_close'].mode()[0]\n",
        "\n",
        "#Replace missing values with mode\n",
        "data['avg_days_to_close'].fillna(mode_value, inplace=True)\n",
        "print(data)\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "Oxjc-MYucCdN",
        "outputId": "7bf0ded6-b293-47da-aba9-41dbf99e2f9c"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "             activation_plan_code  mnp_flag  calls_incoming_cnt  \\\n",
            "customer_id                                                       \n",
            "10000                           4         0                31.0   \n",
            "10001                           6         0                 8.0   \n",
            "10002                           8         1                13.0   \n",
            "10003                           7         0                20.0   \n",
            "10004                           3         1                22.0   \n",
            "...                           ...       ...                 ...   \n",
            "10995                           7         0                22.0   \n",
            "10996                           5         0                28.0   \n",
            "10997                           7         0                55.0   \n",
            "10998                           3         0                22.0   \n",
            "10999                           6         0                21.0   \n",
            "\n",
            "             calls_outgoing_cnt  calls_incoming_duration  \\\n",
            "customer_id                                                \n",
            "10000                     333.0                31.980873   \n",
            "10001                      42.0                 9.577651   \n",
            "10002                       0.0                15.368591   \n",
            "10003                      38.0                21.091508   \n",
            "10004                      29.0                25.592874   \n",
            "...                         ...                      ...   \n",
            "10995                     109.0                29.519157   \n",
            "10996                     241.0                53.689309   \n",
            "10997                      31.0                67.539216   \n",
            "10998                     123.0                26.616933   \n",
            "10999                     187.0                26.359661   \n",
            "\n",
            "             calls_outgoing_duration  total_call_count  total_sum_duration  \\\n",
            "customer_id                                                                  \n",
            "10000                     548.719449             364.0          580.700321   \n",
            "10001                      43.988952              50.0           53.566603   \n",
            "10002                       0.000000              13.0           15.368591   \n",
            "10003                      52.044282              58.0           73.135790   \n",
            "10004                      41.290402              51.0           66.883276   \n",
            "...                              ...               ...                 ...   \n",
            "10995                     182.174628             131.0          211.693785   \n",
            "10996                     271.012107             269.0          324.701416   \n",
            "10997                      42.551143              86.0          110.090359   \n",
            "10998                     156.702089             145.0          183.319022   \n",
            "10999                     305.788987             208.0          332.148647   \n",
            "\n",
            "             tot_usage_mb  upload_usage_mb  ...  pcnt_quota_used  \\\n",
            "customer_id                                 ...                    \n",
            "10000         3163.351573       218.669764  ...         6.864912   \n",
            "10001         3672.746526      1406.966020  ...         3.985185   \n",
            "10002         4712.106937      1218.473756  ...        15.338890   \n",
            "10003        11356.222392      1327.000054  ...         9.241717   \n",
            "10004        11302.446568        84.280664  ...        12.263939   \n",
            "...                   ...              ...  ...              ...   \n",
            "10995         9352.115842      1438.312518  ...         7.610771   \n",
            "10996        15957.218754       178.496381  ...       103.888143   \n",
            "10997        14424.664424      1237.202222  ...        15.651763   \n",
            "10998         3925.163027       198.088999  ...         8.518149   \n",
            "10999        14425.056309       408.196561  ...        15.652188   \n",
            "\n",
            "             recharge_delay  churn  ownership_corporate  ownership_individual  \\\n",
            "customer_id                                                                     \n",
            "10000             -3.221785      0                    0                     1   \n",
            "10001             -4.916200      0                    0                     1   \n",
            "10002              4.455835      0                    0                     1   \n",
            "10003              0.180850      0                    0                     1   \n",
            "10004              4.690059      0                    0                     1   \n",
            "...                     ...    ...                  ...                   ...   \n",
            "10995             10.653616      1                    0                     1   \n",
            "10996             -9.548742      0                    0                     1   \n",
            "10997              4.770953      0                    0                     1   \n",
            "10998             11.623861      1                    0                     1   \n",
            "10999             -2.609718      0                    1                     0   \n",
            "\n",
            "             device_avg_asp_10K_to_20K  device_avg_asp_20K_to_30K  \\\n",
            "customer_id                                                         \n",
            "10000                                1                          0   \n",
            "10001                                1                          0   \n",
            "10002                                0                          1   \n",
            "10003                                0                          0   \n",
            "10004                                1                          0   \n",
            "...                                ...                        ...   \n",
            "10995                                0                          0   \n",
            "10996                                0                          0   \n",
            "10997                                0                          0   \n",
            "10998                                0                          1   \n",
            "10999                                1                          0   \n",
            "\n",
            "             device_avg_asp_30K_to_50K  device_avg_asp_50K_above  \\\n",
            "customer_id                                                        \n",
            "10000                                0                         0   \n",
            "10001                                0                         0   \n",
            "10002                                0                         0   \n",
            "10003                                0                         0   \n",
            "10004                                0                         0   \n",
            "...                                ...                       ...   \n",
            "10995                                1                         0   \n",
            "10996                                1                         0   \n",
            "10997                                0                         0   \n",
            "10998                                0                         0   \n",
            "10999                                0                         0   \n",
            "\n",
            "             device_avg_asp_less_10K  \n",
            "customer_id                           \n",
            "10000                              0  \n",
            "10001                              0  \n",
            "10002                              0  \n",
            "10003                              1  \n",
            "10004                              0  \n",
            "...                              ...  \n",
            "10995                              0  \n",
            "10996                              0  \n",
            "10997                              1  \n",
            "10998                              0  \n",
            "10999                              0  \n",
            "\n",
            "[1000 rows x 52 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['avg_days_to_close'].isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "R4BKkPcbcVeX",
        "outputId": "447ebd5b-f081-4329-9010-6603d6104533"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.describe()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "lB0WjiJpYHuz",
        "outputId": "47dbdbc6-2f1e-4cb0-de9c-cf32cdb44ffd"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       activation_plan_code     mnp_flag  calls_incoming_cnt  \\\n",
              "count           1000.000000  1000.000000         1000.000000   \n",
              "mean               5.547000     0.095000           59.098000   \n",
              "std                2.871243     0.293362           59.655588   \n",
              "min                1.000000     0.000000            0.000000   \n",
              "25%                3.000000     0.000000           19.000000   \n",
              "50%                5.000000     0.000000           40.000000   \n",
              "75%                8.000000     0.000000           79.000000   \n",
              "max               10.000000     1.000000          531.000000   \n",
              "\n",
              "       calls_outgoing_cnt  calls_incoming_duration  calls_outgoing_duration  \\\n",
              "count         1000.000000              1000.000000              1000.000000   \n",
              "mean            60.789000                89.315690                91.910980   \n",
              "std             59.257032                93.959748                92.734500   \n",
              "min              0.000000                 0.000000                 0.000000   \n",
              "25%             19.000000                26.809249                28.211860   \n",
              "50%             42.000000                59.200418                65.136142   \n",
              "75%             85.000000               116.496060               127.278434   \n",
              "max            427.000000               957.042270               643.949805   \n",
              "\n",
              "       total_call_count  total_sum_duration  tot_usage_mb  upload_usage_mb  \\\n",
              "count       1000.000000         1000.000000   1000.000000      1000.000000   \n",
              "mean         119.887000          181.226670  11494.474601      1492.948029   \n",
              "std           81.974557          128.538379   9479.334765      1507.621368   \n",
              "min            4.000000            4.046349     65.061020         3.044787   \n",
              "25%           60.000000           88.102851   4714.380636       423.033975   \n",
              "50%          102.000000          147.924803   8792.473829      1023.183572   \n",
              "75%          156.000000          248.868696  15856.359078      2002.049789   \n",
              "max          567.000000          975.014814  55675.724435     10505.096786   \n",
              "\n",
              "       ...  pcnt_quota_used  recharge_delay       churn  ownership_corporate  \\\n",
              "count  ...      1000.000000    1.000000e+03  1000.00000           1000.00000   \n",
              "mean   ...        28.606507    4.895639e-15     0.25600              0.16300   \n",
              "std    ...        37.037698    9.698316e+00     0.43664              0.36955   \n",
              "min    ...         0.070596   -3.798367e+01     0.00000              0.00000   \n",
              "25%    ...         7.314737   -5.583596e+00     0.00000              0.00000   \n",
              "50%    ...        15.631628    1.001490e-01     0.00000              0.00000   \n",
              "75%    ...        34.260930    5.339966e+00     1.00000              0.00000   \n",
              "max    ...       343.030058    3.362982e+01     1.00000              1.00000   \n",
              "\n",
              "       ownership_individual  device_avg_asp_10K_to_20K  \\\n",
              "count            1000.00000                1000.000000   \n",
              "mean                0.83700                   0.210000   \n",
              "std                 0.36955                   0.407512   \n",
              "min                 0.00000                   0.000000   \n",
              "25%                 1.00000                   0.000000   \n",
              "50%                 1.00000                   0.000000   \n",
              "75%                 1.00000                   0.000000   \n",
              "max                 1.00000                   1.000000   \n",
              "\n",
              "       device_avg_asp_20K_to_30K  device_avg_asp_30K_to_50K  \\\n",
              "count                  1000.0000                1000.000000   \n",
              "mean                      0.2000                   0.196000   \n",
              "std                       0.4002                   0.397167   \n",
              "min                       0.0000                   0.000000   \n",
              "25%                       0.0000                   0.000000   \n",
              "50%                       0.0000                   0.000000   \n",
              "75%                       0.0000                   0.000000   \n",
              "max                       1.0000                   1.000000   \n",
              "\n",
              "       device_avg_asp_50K_above  device_avg_asp_less_10K  \n",
              "count               1000.000000              1000.000000  \n",
              "mean                   0.204000                 0.190000  \n",
              "std                    0.403171                 0.392497  \n",
              "min                    0.000000                 0.000000  \n",
              "25%                    0.000000                 0.000000  \n",
              "50%                    0.000000                 0.000000  \n",
              "75%                    0.000000                 0.000000  \n",
              "max                    1.000000                 1.000000  \n",
              "\n",
              "[8 rows x 52 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e0840437-9c14-48bb-a404-383971529b9c\">\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>activation_plan_code</th>\n",
              "      <th>mnp_flag</th>\n",
              "      <th>calls_incoming_cnt</th>\n",
              "      <th>calls_outgoing_cnt</th>\n",
              "      <th>calls_incoming_duration</th>\n",
              "      <th>calls_outgoing_duration</th>\n",
              "      <th>total_call_count</th>\n",
              "      <th>total_sum_duration</th>\n",
              "      <th>tot_usage_mb</th>\n",
              "      <th>upload_usage_mb</th>\n",
              "      <th>...</th>\n",
              "      <th>pcnt_quota_used</th>\n",
              "      <th>recharge_delay</th>\n",
              "      <th>churn</th>\n",
              "      <th>ownership_corporate</th>\n",
              "      <th>ownership_individual</th>\n",
              "      <th>device_avg_asp_10K_to_20K</th>\n",
              "      <th>device_avg_asp_20K_to_30K</th>\n",
              "      <th>device_avg_asp_30K_to_50K</th>\n",
              "      <th>device_avg_asp_50K_above</th>\n",
              "      <th>device_avg_asp_less_10K</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1.000000e+03</td>\n",
              "      <td>1000.00000</td>\n",
              "      <td>1000.00000</td>\n",
              "      <td>1000.00000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.0000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>1000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>5.547000</td>\n",
              "      <td>0.095000</td>\n",
              "      <td>59.098000</td>\n",
              "      <td>60.789000</td>\n",
              "      <td>89.315690</td>\n",
              "      <td>91.910980</td>\n",
              "      <td>119.887000</td>\n",
              "      <td>181.226670</td>\n",
              "      <td>11494.474601</td>\n",
              "      <td>1492.948029</td>\n",
              "      <td>...</td>\n",
              "      <td>28.606507</td>\n",
              "      <td>4.895639e-15</td>\n",
              "      <td>0.25600</td>\n",
              "      <td>0.16300</td>\n",
              "      <td>0.83700</td>\n",
              "      <td>0.210000</td>\n",
              "      <td>0.2000</td>\n",
              "      <td>0.196000</td>\n",
              "      <td>0.204000</td>\n",
              "      <td>0.190000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.871243</td>\n",
              "      <td>0.293362</td>\n",
              "      <td>59.655588</td>\n",
              "      <td>59.257032</td>\n",
              "      <td>93.959748</td>\n",
              "      <td>92.734500</td>\n",
              "      <td>81.974557</td>\n",
              "      <td>128.538379</td>\n",
              "      <td>9479.334765</td>\n",
              "      <td>1507.621368</td>\n",
              "      <td>...</td>\n",
              "      <td>37.037698</td>\n",
              "      <td>9.698316e+00</td>\n",
              "      <td>0.43664</td>\n",
              "      <td>0.36955</td>\n",
              "      <td>0.36955</td>\n",
              "      <td>0.407512</td>\n",
              "      <td>0.4002</td>\n",
              "      <td>0.397167</td>\n",
              "      <td>0.403171</td>\n",
              "      <td>0.392497</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</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>4.000000</td>\n",
              "      <td>4.046349</td>\n",
              "      <td>65.061020</td>\n",
              "      <td>3.044787</td>\n",
              "      <td>...</td>\n",
              "      <td>0.070596</td>\n",
              "      <td>-3.798367e+01</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</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>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>26.809249</td>\n",
              "      <td>28.211860</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>88.102851</td>\n",
              "      <td>4714.380636</td>\n",
              "      <td>423.033975</td>\n",
              "      <td>...</td>\n",
              "      <td>7.314737</td>\n",
              "      <td>-5.583596e+00</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>40.000000</td>\n",
              "      <td>42.000000</td>\n",
              "      <td>59.200418</td>\n",
              "      <td>65.136142</td>\n",
              "      <td>102.000000</td>\n",
              "      <td>147.924803</td>\n",
              "      <td>8792.473829</td>\n",
              "      <td>1023.183572</td>\n",
              "      <td>...</td>\n",
              "      <td>15.631628</td>\n",
              "      <td>1.001490e-01</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>8.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>79.000000</td>\n",
              "      <td>85.000000</td>\n",
              "      <td>116.496060</td>\n",
              "      <td>127.278434</td>\n",
              "      <td>156.000000</td>\n",
              "      <td>248.868696</td>\n",
              "      <td>15856.359078</td>\n",
              "      <td>2002.049789</td>\n",
              "      <td>...</td>\n",
              "      <td>34.260930</td>\n",
              "      <td>5.339966e+00</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>531.000000</td>\n",
              "      <td>427.000000</td>\n",
              "      <td>957.042270</td>\n",
              "      <td>643.949805</td>\n",
              "      <td>567.000000</td>\n",
              "      <td>975.014814</td>\n",
              "      <td>55675.724435</td>\n",
              "      <td>10505.096786</td>\n",
              "      <td>...</td>\n",
              "      <td>343.030058</td>\n",
              "      <td>3.362982e+01</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 52 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e0840437-9c14-48bb-a404-383971529b9c')\"\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",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\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",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e0840437-9c14-48bb-a404-383971529b9c 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-e0840437-9c14-48bb-a404-383971529b9c');\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": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "AQpd82C-VSTM",
        "outputId": "c22de00a-b706-4cc1-9adf-1a6e020ce51c"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['activation_plan_code', 'mnp_flag', 'calls_incoming_cnt',\n",
              "       'calls_outgoing_cnt', 'calls_incoming_duration',\n",
              "       'calls_outgoing_duration', 'total_call_count', 'total_sum_duration',\n",
              "       'tot_usage_mb', 'upload_usage_mb', 'download_usage_mb',\n",
              "       'days_since_latch', 'cnt_open_qrc', 'avg_days_to_close',\n",
              "       'cnt_call_drops', 'pcnt_dropped_calls', 'rsrp_voice_pcnt_poor_duration',\n",
              "       'rsrp_data_pcnt_poor_duration', 'mean_cqi_voice_pcnt_poor_duration',\n",
              "       'sinr_voice_pcnt_poor_duration', 'sinr_data_pcnt_poor_duration',\n",
              "       'age_on_network', 'cnt_connections', 'current_plan_code',\n",
              "       'cnt_recharges_made', 'total_payment_made', 'cnt_main_plans_taken',\n",
              "       'total_main_plans_mrp', 'cnt_addon_plans_taken',\n",
              "       'total_addon_plans_mrp', 'cnt_rchg_offline', 'cnt_rchg_online',\n",
              "       'cnt_rchg_on_or_before_expiry', 'cnt_rchg_after_expiry',\n",
              "       'current_active_plan_mrp', 'current_active_plan_validity',\n",
              "       'last_cycle_plan_mrp', 'last_cycle_plan_validity',\n",
              "       'avg_days_bw_rchg_and_expiry', 'stddev_days_bw_rchg_and_expiry',\n",
              "       'price_per_day', 'gb_per_day_quota', 'pcnt_quota_used',\n",
              "       'recharge_delay', 'churn', 'ownership_corporate',\n",
              "       'ownership_individual', 'device_avg_asp_10K_to_20K',\n",
              "       'device_avg_asp_20K_to_30K', 'device_avg_asp_30K_to_50K',\n",
              "       'device_avg_asp_50K_above', 'device_avg_asp_less_10K'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "NZCN_Fh0GT68",
        "outputId": "76117ea7-999c-40a5-f56c-50847ecd95a3"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "activation_plan_code                 0\n",
              "mnp_flag                             0\n",
              "calls_incoming_cnt                   0\n",
              "calls_outgoing_cnt                   0\n",
              "calls_incoming_duration              0\n",
              "calls_outgoing_duration              0\n",
              "total_call_count                     0\n",
              "total_sum_duration                   0\n",
              "tot_usage_mb                         0\n",
              "upload_usage_mb                      0\n",
              "download_usage_mb                    0\n",
              "days_since_latch                     0\n",
              "cnt_open_qrc                         0\n",
              "avg_days_to_close                    0\n",
              "cnt_call_drops                       0\n",
              "pcnt_dropped_calls                   0\n",
              "rsrp_voice_pcnt_poor_duration        0\n",
              "rsrp_data_pcnt_poor_duration         0\n",
              "mean_cqi_voice_pcnt_poor_duration    0\n",
              "sinr_voice_pcnt_poor_duration        0\n",
              "sinr_data_pcnt_poor_duration         0\n",
              "age_on_network                       0\n",
              "cnt_connections                      0\n",
              "current_plan_code                    0\n",
              "cnt_recharges_made                   0\n",
              "total_payment_made                   0\n",
              "cnt_main_plans_taken                 0\n",
              "total_main_plans_mrp                 0\n",
              "cnt_addon_plans_taken                0\n",
              "total_addon_plans_mrp                0\n",
              "cnt_rchg_offline                     0\n",
              "cnt_rchg_online                      0\n",
              "cnt_rchg_on_or_before_expiry         0\n",
              "cnt_rchg_after_expiry                0\n",
              "current_active_plan_mrp              0\n",
              "current_active_plan_validity         0\n",
              "last_cycle_plan_mrp                  0\n",
              "last_cycle_plan_validity             0\n",
              "avg_days_bw_rchg_and_expiry          0\n",
              "stddev_days_bw_rchg_and_expiry       0\n",
              "price_per_day                        0\n",
              "gb_per_day_quota                     0\n",
              "pcnt_quota_used                      0\n",
              "recharge_delay                       0\n",
              "churn                                0\n",
              "ownership_corporate                  0\n",
              "ownership_individual                 0\n",
              "device_avg_asp_10K_to_20K            0\n",
              "device_avg_asp_20K_to_30K            0\n",
              "device_avg_asp_30K_to_50K            0\n",
              "device_avg_asp_50K_above             0\n",
              "device_avg_asp_less_10K              0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# creating correlation matrix \n",
        "data.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 2364
        },
        "id": "nR5jjV4fcCDd",
        "outputId": "d48d39ad-8f93-4fd9-b7b5-cd7ba38664ca"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                   activation_plan_code      mnp_flag  \\\n",
              "activation_plan_code                           1.000000 -1.303076e-02   \n",
              "mnp_flag                                      -0.013031  1.000000e+00   \n",
              "calls_incoming_cnt                             0.011042 -3.393608e-02   \n",
              "calls_outgoing_cnt                             0.042704 -2.435485e-02   \n",
              "calls_incoming_duration                        0.019123 -2.084438e-02   \n",
              "calls_outgoing_duration                        0.042834 -2.986479e-02   \n",
              "total_call_count                               0.038905 -4.230182e-02   \n",
              "total_sum_duration                             0.044881 -3.678302e-02   \n",
              "tot_usage_mb                                  -0.004974 -4.138960e-02   \n",
              "upload_usage_mb                               -0.033514 -4.765681e-02   \n",
              "download_usage_mb                              0.000361 -3.427937e-02   \n",
              "days_since_latch                               0.039919 -4.324241e-02   \n",
              "cnt_open_qrc                                   0.011120  1.388366e-02   \n",
              "avg_days_to_close                             -0.021725  3.107836e-02   \n",
              "cnt_call_drops                                 0.031177 -2.202008e-02   \n",
              "pcnt_dropped_calls                            -0.004628  2.493265e-03   \n",
              "rsrp_voice_pcnt_poor_duration                  0.048468  2.658813e-02   \n",
              "rsrp_data_pcnt_poor_duration                   0.051820  2.257050e-02   \n",
              "mean_cqi_voice_pcnt_poor_duration              0.017128  1.196293e-02   \n",
              "sinr_voice_pcnt_poor_duration                 -0.021508  6.436111e-02   \n",
              "sinr_data_pcnt_poor_duration                  -0.023007  7.590998e-02   \n",
              "age_on_network                                -0.010357 -1.747536e-02   \n",
              "cnt_connections                               -0.024122  2.506571e-02   \n",
              "current_plan_code                              0.051528 -3.905369e-02   \n",
              "cnt_recharges_made                            -0.010539 -1.790240e-02   \n",
              "total_payment_made                             0.017207 -1.759391e-02   \n",
              "cnt_main_plans_taken                          -0.005301 -2.623892e-02   \n",
              "total_main_plans_mrp                           0.005707 -9.757167e-03   \n",
              "cnt_addon_plans_taken                         -0.009651  5.777274e-04   \n",
              "total_addon_plans_mrp                          0.024814 -2.185133e-02   \n",
              "cnt_rchg_offline                              -0.010539 -1.790240e-02   \n",
              "cnt_rchg_online                               -0.010539 -1.790240e-02   \n",
              "cnt_rchg_on_or_before_expiry                  -0.034484 -4.700325e-03   \n",
              "cnt_rchg_after_expiry                          0.023885 -1.395202e-02   \n",
              "current_active_plan_mrp                       -0.011095  9.726128e-04   \n",
              "current_active_plan_validity                  -0.015075  4.399905e-03   \n",
              "last_cycle_plan_mrp                            0.009111 -1.726746e-02   \n",
              "last_cycle_plan_validity                       0.005211 -1.812047e-02   \n",
              "avg_days_bw_rchg_and_expiry                   -0.033716  4.275533e-02   \n",
              "stddev_days_bw_rchg_and_expiry                 0.023346 -2.300015e-02   \n",
              "price_per_day                                 -0.005425 -3.618395e-02   \n",
              "gb_per_day_quota                              -0.000649 -4.037389e-03   \n",
              "pcnt_quota_used                               -0.028850 -3.030680e-02   \n",
              "recharge_delay                                 0.182931  5.468647e-02   \n",
              "churn                                          0.112554  2.094316e-02   \n",
              "ownership_corporate                            0.015886  2.322177e-02   \n",
              "ownership_individual                          -0.015886 -2.322177e-02   \n",
              "device_avg_asp_10K_to_20K                     -0.055497  4.228459e-02   \n",
              "device_avg_asp_20K_to_30K                      0.050178 -6.626164e-18   \n",
              "device_avg_asp_30K_to_50K                     -0.033542 -3.110043e-02   \n",
              "device_avg_asp_50K_above                       0.034080 -1.167942e-02   \n",
              "device_avg_asp_less_10K                        0.005392 -4.346749e-04   \n",
              "\n",
              "                                   calls_incoming_cnt  calls_outgoing_cnt  \\\n",
              "activation_plan_code                         0.011042            0.042704   \n",
              "mnp_flag                                    -0.033936           -0.024355   \n",
              "calls_incoming_cnt                           1.000000           -0.049555   \n",
              "calls_outgoing_cnt                          -0.049555            1.000000   \n",
              "calls_incoming_duration                      0.968497           -0.051584   \n",
              "calls_outgoing_duration                     -0.050906            0.969809   \n",
              "total_call_count                             0.691911            0.686808   \n",
              "total_sum_duration                           0.671232            0.661966   \n",
              "tot_usage_mb                                -0.013832            0.011526   \n",
              "upload_usage_mb                              0.069212           -0.017589   \n",
              "download_usage_mb                           -0.025185            0.014522   \n",
              "days_since_latch                             0.686616            0.684613   \n",
              "cnt_open_qrc                                 0.027595           -0.071406   \n",
              "avg_days_to_close                           -0.002644           -0.030774   \n",
              "cnt_call_drops                               0.575499            0.512637   \n",
              "pcnt_dropped_calls                           0.016975           -0.045067   \n",
              "rsrp_voice_pcnt_poor_duration               -0.042777           -0.005555   \n",
              "rsrp_data_pcnt_poor_duration                -0.041969            0.003461   \n",
              "mean_cqi_voice_pcnt_poor_duration            0.017857           -0.001043   \n",
              "sinr_voice_pcnt_poor_duration               -0.013584           -0.018462   \n",
              "sinr_data_pcnt_poor_duration                -0.011640           -0.013585   \n",
              "age_on_network                              -0.022528            0.012191   \n",
              "cnt_connections                             -0.020241            0.021944   \n",
              "current_plan_code                            0.042753            0.015233   \n",
              "cnt_recharges_made                          -0.024226            0.012651   \n",
              "total_payment_made                          -0.020226            0.060546   \n",
              "cnt_main_plans_taken                        -0.019573            0.043363   \n",
              "total_main_plans_mrp                        -0.020894            0.081549   \n",
              "cnt_addon_plans_taken                       -0.014910           -0.024849   \n",
              "total_addon_plans_mrp                       -0.016434            0.032132   \n",
              "cnt_rchg_offline                            -0.024226            0.012651   \n",
              "cnt_rchg_online                             -0.024226            0.012651   \n",
              "cnt_rchg_on_or_before_expiry                -0.029662           -0.026638   \n",
              "cnt_rchg_after_expiry                        0.004701            0.040179   \n",
              "current_active_plan_mrp                     -0.010818            0.064075   \n",
              "current_active_plan_validity                -0.005487            0.066068   \n",
              "last_cycle_plan_mrp                         -0.027422            0.016909   \n",
              "last_cycle_plan_validity                    -0.030829            0.017860   \n",
              "avg_days_bw_rchg_and_expiry                  0.010903            0.034216   \n",
              "stddev_days_bw_rchg_and_expiry               0.030297            0.007986   \n",
              "price_per_day                                0.002018           -0.051553   \n",
              "gb_per_day_quota                            -0.019957            0.067294   \n",
              "pcnt_quota_used                             -0.003534           -0.017548   \n",
              "recharge_delay                              -0.214768           -0.021893   \n",
              "churn                                       -0.064641            0.015244   \n",
              "ownership_corporate                          0.008855            0.075944   \n",
              "ownership_individual                        -0.008855           -0.075944   \n",
              "device_avg_asp_10K_to_20K                    0.018258            0.033507   \n",
              "device_avg_asp_20K_to_30K                   -0.023379            0.015879   \n",
              "device_avg_asp_30K_to_50K                   -0.021513           -0.045750   \n",
              "device_avg_asp_50K_above                     0.003122           -0.002093   \n",
              "device_avg_asp_less_10K                      0.023444           -0.002535   \n",
              "\n",
              "                                   calls_incoming_duration  \\\n",
              "activation_plan_code                              0.019123   \n",
              "mnp_flag                                         -0.020844   \n",
              "calls_incoming_cnt                                0.968497   \n",
              "calls_outgoing_cnt                               -0.051584   \n",
              "calls_incoming_duration                           1.000000   \n",
              "calls_outgoing_duration                          -0.051990   \n",
              "total_call_count                                  0.667519   \n",
              "total_sum_duration                                0.693478   \n",
              "tot_usage_mb                                     -0.026354   \n",
              "upload_usage_mb                                   0.065350   \n",
              "download_usage_mb                                -0.037257   \n",
              "days_since_latch                                  0.661405   \n",
              "cnt_open_qrc                                      0.026962   \n",
              "avg_days_to_close                                -0.006533   \n",
              "cnt_call_drops                                    0.554846   \n",
              "pcnt_dropped_calls                                0.017262   \n",
              "rsrp_voice_pcnt_poor_duration                    -0.040526   \n",
              "rsrp_data_pcnt_poor_duration                     -0.039479   \n",
              "mean_cqi_voice_pcnt_poor_duration                 0.019824   \n",
              "sinr_voice_pcnt_poor_duration                    -0.012657   \n",
              "sinr_data_pcnt_poor_duration                     -0.010051   \n",
              "age_on_network                                   -0.036609   \n",
              "cnt_connections                                  -0.019779   \n",
              "current_plan_code                                 0.039803   \n",
              "cnt_recharges_made                               -0.038227   \n",
              "total_payment_made                               -0.024348   \n",
              "cnt_main_plans_taken                             -0.031548   \n",
              "total_main_plans_mrp                             -0.023361   \n",
              "cnt_addon_plans_taken                            -0.022872   \n",
              "total_addon_plans_mrp                            -0.021390   \n",
              "cnt_rchg_offline                                 -0.038227   \n",
              "cnt_rchg_online                                  -0.038227   \n",
              "cnt_rchg_on_or_before_expiry                     -0.051968   \n",
              "cnt_rchg_after_expiry                             0.012645   \n",
              "current_active_plan_mrp                          -0.018400   \n",
              "current_active_plan_validity                     -0.013586   \n",
              "last_cycle_plan_mrp                              -0.041762   \n",
              "last_cycle_plan_validity                         -0.045960   \n",
              "avg_days_bw_rchg_and_expiry                       0.007045   \n",
              "stddev_days_bw_rchg_and_expiry                    0.028709   \n",
              "price_per_day                                     0.005371   \n",
              "gb_per_day_quota                                 -0.024900   \n",
              "pcnt_quota_used                                  -0.007456   \n",
              "recharge_delay                                   -0.193109   \n",
              "churn                                            -0.059434   \n",
              "ownership_corporate                               0.009433   \n",
              "ownership_individual                             -0.009433   \n",
              "device_avg_asp_10K_to_20K                         0.025624   \n",
              "device_avg_asp_20K_to_30K                        -0.008817   \n",
              "device_avg_asp_30K_to_50K                        -0.023384   \n",
              "device_avg_asp_50K_above                         -0.002495   \n",
              "device_avg_asp_less_10K                           0.008611   \n",
              "\n",
              "                                   calls_outgoing_duration  total_call_count  \\\n",
              "activation_plan_code                              0.042834          0.038905   \n",
              "mnp_flag                                         -0.029865         -0.042302   \n",
              "calls_incoming_cnt                               -0.050906          0.691911   \n",
              "calls_outgoing_cnt                                0.969809          0.686808   \n",
              "calls_incoming_duration                          -0.051990          0.667519   \n",
              "calls_outgoing_duration                           1.000000          0.664001   \n",
              "total_call_count                                  0.664001          1.000000   \n",
              "total_sum_duration                                0.683450          0.966993   \n",
              "tot_usage_mb                                      0.001780         -0.001734   \n",
              "upload_usage_mb                                  -0.019657          0.037653   \n",
              "download_usage_mb                                 0.004975         -0.007830   \n",
              "days_since_latch                                  0.662565          0.994560   \n",
              "cnt_open_qrc                                     -0.078205         -0.031535   \n",
              "avg_days_to_close                                -0.040116         -0.024170   \n",
              "cnt_call_drops                                    0.508201          0.789380   \n",
              "pcnt_dropped_calls                               -0.035669         -0.020225   \n",
              "rsrp_voice_pcnt_poor_duration                     0.003556         -0.035146   \n",
              "rsrp_data_pcnt_poor_duration                      0.011202         -0.028041   \n",
              "mean_cqi_voice_pcnt_poor_duration                -0.001994          0.012241   \n",
              "sinr_voice_pcnt_poor_duration                    -0.028246         -0.023231   \n",
              "sinr_data_pcnt_poor_duration                     -0.022632         -0.018291   \n",
              "age_on_network                                    0.007507         -0.007582   \n",
              "cnt_connections                                   0.019657          0.001133   \n",
              "current_plan_code                                 0.014615          0.042124   \n",
              "cnt_recharges_made                                0.008112         -0.008485   \n",
              "total_payment_made                                0.069227          0.029047   \n",
              "cnt_main_plans_taken                              0.033336          0.017102   \n",
              "total_main_plans_mrp                              0.085510          0.043744   \n",
              "cnt_addon_plans_taken                            -0.021380         -0.028813   \n",
              "total_addon_plans_mrp                             0.043680          0.011268   \n",
              "cnt_rchg_offline                                  0.008112         -0.008485   \n",
              "cnt_rchg_online                                   0.008112         -0.008485   \n",
              "cnt_rchg_on_or_before_expiry                     -0.026893         -0.040842   \n",
              "cnt_rchg_after_expiry                             0.035694          0.032466   \n",
              "current_active_plan_mrp                           0.064712          0.038445   \n",
              "current_active_plan_validity                      0.065094          0.043765   \n",
              "last_cycle_plan_mrp                               0.016300         -0.007733   \n",
              "last_cycle_plan_validity                          0.017148         -0.009525   \n",
              "avg_days_bw_rchg_and_expiry                       0.043168          0.032669   \n",
              "stddev_days_bw_rchg_and_expiry                    0.012090          0.027821   \n",
              "price_per_day                                    -0.047608         -0.035797   \n",
              "gb_per_day_quota                                  0.071373          0.034122   \n",
              "pcnt_quota_used                                  -0.026867         -0.015257   \n",
              "recharge_delay                                   -0.006295         -0.172120   \n",
              "churn                                             0.009969         -0.036022   \n",
              "ownership_corporate                               0.061281          0.061342   \n",
              "ownership_individual                             -0.061281         -0.061342   \n",
              "device_avg_asp_10K_to_20K                         0.028880          0.037508   \n",
              "device_avg_asp_20K_to_30K                         0.013659         -0.005535   \n",
              "device_avg_asp_30K_to_50K                        -0.034369         -0.048727   \n",
              "device_avg_asp_50K_above                          0.007460          0.000759   \n",
              "device_avg_asp_less_10K                          -0.016797          0.015228   \n",
              "\n",
              "                                   total_sum_duration  tot_usage_mb  \\\n",
              "activation_plan_code                         0.044881     -0.004974   \n",
              "mnp_flag                                    -0.036783     -0.041390   \n",
              "calls_incoming_cnt                           0.671232     -0.013832   \n",
              "calls_outgoing_cnt                           0.661966      0.011526   \n",
              "calls_incoming_duration                      0.693478     -0.026354   \n",
              "calls_outgoing_duration                      0.683450      0.001780   \n",
              "total_call_count                             0.966993     -0.001734   \n",
              "total_sum_duration                           1.000000     -0.017980   \n",
              "tot_usage_mb                                -0.017980      1.000000   \n",
              "upload_usage_mb                              0.033588      0.165004   \n",
              "download_usage_mb                           -0.023645      0.987272   \n",
              "days_since_latch                             0.961488     -0.004368   \n",
              "cnt_open_qrc                                -0.036713     -0.086214   \n",
              "avg_days_to_close                           -0.033717     -0.043603   \n",
              "cnt_call_drops                               0.772228      0.000356   \n",
              "pcnt_dropped_calls                          -0.013116     -0.030641   \n",
              "rsrp_voice_pcnt_poor_duration               -0.027058     -0.037922   \n",
              "rsrp_data_pcnt_poor_duration                -0.020777     -0.041274   \n",
              "mean_cqi_voice_pcnt_poor_duration            0.013052     -0.050049   \n",
              "sinr_voice_pcnt_poor_duration               -0.029630      0.036908   \n",
              "sinr_data_pcnt_poor_duration                -0.023675      0.040235   \n",
              "age_on_network                              -0.021345     -0.020669   \n",
              "cnt_connections                             -0.000276      0.041153   \n",
              "current_plan_code                            0.039639     -0.031018   \n",
              "cnt_recharges_made                          -0.022091     -0.020497   \n",
              "total_payment_made                           0.032146     -0.021461   \n",
              "cnt_main_plans_taken                         0.000989     -0.005704   \n",
              "total_main_plans_mrp                         0.044615     -0.005193   \n",
              "cnt_addon_plans_taken                       -0.032144     -0.023304   \n",
              "total_addon_plans_mrp                        0.015877     -0.032677   \n",
              "cnt_rchg_offline                            -0.022091     -0.020497   \n",
              "cnt_rchg_online                             -0.022091     -0.020497   \n",
              "cnt_rchg_on_or_before_expiry                -0.057390      0.001991   \n",
              "cnt_rchg_after_expiry                        0.034995     -0.023436   \n",
              "current_active_plan_mrp                      0.033236     -0.043027   \n",
              "current_active_plan_validity                 0.037031     -0.040261   \n",
              "last_cycle_plan_mrp                         -0.018768     -0.023384   \n",
              "last_cycle_plan_validity                    -0.021224     -0.024345   \n",
              "avg_days_bw_rchg_and_expiry                  0.036293      0.079777   \n",
              "stddev_days_bw_rchg_and_expiry               0.029708      0.027694   \n",
              "price_per_day                               -0.030421     -0.017795   \n",
              "gb_per_day_quota                             0.033291     -0.020823   \n",
              "pcnt_quota_used                             -0.024834      0.634894   \n",
              "recharge_delay                              -0.145702     -0.524368   \n",
              "churn                                       -0.036254     -0.193900   \n",
              "ownership_corporate                          0.051106      0.019971   \n",
              "ownership_individual                        -0.051106     -0.019971   \n",
              "device_avg_asp_10K_to_20K                    0.039566     -0.057422   \n",
              "device_avg_asp_20K_to_30K                    0.003409      0.001731   \n",
              "device_avg_asp_30K_to_50K                   -0.041889     -0.023842   \n",
              "device_avg_asp_50K_above                     0.003559      0.016038   \n",
              "device_avg_asp_less_10K                     -0.005824      0.065505   \n",
              "\n",
              "                                   upload_usage_mb  ...  pcnt_quota_used  \\\n",
              "activation_plan_code                     -0.033514  ...        -0.028850   \n",
              "mnp_flag                                 -0.047657  ...        -0.030307   \n",
              "calls_incoming_cnt                        0.069212  ...        -0.003534   \n",
              "calls_outgoing_cnt                       -0.017589  ...        -0.017548   \n",
              "calls_incoming_duration                   0.065350  ...        -0.007456   \n",
              "calls_outgoing_duration                  -0.019657  ...        -0.026867   \n",
              "total_call_count                          0.037653  ...        -0.015257   \n",
              "total_sum_duration                        0.033588  ...        -0.024834   \n",
              "tot_usage_mb                              0.165004  ...         0.634894   \n",
              "upload_usage_mb                           1.000000  ...         0.113954   \n",
              "download_usage_mb                         0.006043  ...         0.625330   \n",
              "days_since_latch                          0.029369  ...        -0.014117   \n",
              "cnt_open_qrc                              0.034701  ...        -0.077220   \n",
              "avg_days_to_close                        -0.054486  ...        -0.026733   \n",
              "cnt_call_drops                            0.039784  ...        -0.009056   \n",
              "pcnt_dropped_calls                       -0.008881  ...        -0.043017   \n",
              "rsrp_voice_pcnt_poor_duration             0.004022  ...        -0.030237   \n",
              "rsrp_data_pcnt_poor_duration              0.004693  ...        -0.036340   \n",
              "mean_cqi_voice_pcnt_poor_duration        -0.028548  ...         0.021159   \n",
              "sinr_voice_pcnt_poor_duration             0.013974  ...         0.002028   \n",
              "sinr_data_pcnt_poor_duration              0.020379  ...         0.001541   \n",
              "age_on_network                            0.032244  ...        -0.008422   \n",
              "cnt_connections                          -0.011370  ...         0.057286   \n",
              "current_plan_code                        -0.003785  ...        -0.044783   \n",
              "cnt_recharges_made                        0.031804  ...        -0.008673   \n",
              "total_payment_made                        0.006661  ...        -0.013849   \n",
              "cnt_main_plans_taken                      0.004295  ...         0.034454   \n",
              "total_main_plans_mrp                     -0.009788  ...         0.014472   \n",
              "cnt_addon_plans_taken                     0.040646  ...        -0.046165   \n",
              "total_addon_plans_mrp                     0.020376  ...        -0.037087   \n",
              "cnt_rchg_offline                          0.031804  ...        -0.008673   \n",
              "cnt_rchg_online                           0.031804  ...        -0.008673   \n",
              "cnt_rchg_on_or_before_expiry              0.002929  ...        -0.026416   \n",
              "cnt_rchg_after_expiry                     0.030273  ...         0.017671   \n",
              "current_active_plan_mrp                   0.028588  ...        -0.379430   \n",
              "current_active_plan_validity              0.030146  ...        -0.375655   \n",
              "last_cycle_plan_mrp                       0.030197  ...         0.002461   \n",
              "last_cycle_plan_validity                  0.029936  ...        -0.000413   \n",
              "avg_days_bw_rchg_and_expiry              -0.046676  ...         0.057372   \n",
              "stddev_days_bw_rchg_and_expiry           -0.015073  ...         0.025662   \n",
              "price_per_day                             0.005620  ...         0.409157   \n",
              "gb_per_day_quota                          0.008891  ...        -0.508677   \n",
              "pcnt_quota_used                           0.113954  ...         1.000000   \n",
              "recharge_delay                           -0.111315  ...        -0.483431   \n",
              "churn                                    -0.041746  ...        -0.133075   \n",
              "ownership_corporate                       0.040639  ...         0.035300   \n",
              "ownership_individual                     -0.040639  ...        -0.035300   \n",
              "device_avg_asp_10K_to_20K                 0.025811  ...        -0.028893   \n",
              "device_avg_asp_20K_to_30K                 0.022992  ...         0.027688   \n",
              "device_avg_asp_30K_to_50K                -0.055827  ...        -0.002000   \n",
              "device_avg_asp_50K_above                  0.006779  ...        -0.009240   \n",
              "device_avg_asp_less_10K                  -0.000713  ...         0.013283   \n",
              "\n",
              "                                   recharge_delay     churn  \\\n",
              "activation_plan_code                     0.182931  0.112554   \n",
              "mnp_flag                                 0.054686  0.020943   \n",
              "calls_incoming_cnt                      -0.214768 -0.064641   \n",
              "calls_outgoing_cnt                      -0.021893  0.015244   \n",
              "calls_incoming_duration                 -0.193109 -0.059434   \n",
              "calls_outgoing_duration                 -0.006295  0.009969   \n",
              "total_call_count                        -0.172120 -0.036022   \n",
              "total_sum_duration                      -0.145702 -0.036254   \n",
              "tot_usage_mb                            -0.524368 -0.193900   \n",
              "upload_usage_mb                         -0.111315 -0.041746   \n",
              "download_usage_mb                       -0.513696 -0.189860   \n",
              "days_since_latch                        -0.166547 -0.035729   \n",
              "cnt_open_qrc                             0.161511  0.086211   \n",
              "avg_days_to_close                        0.028123  0.008777   \n",
              "cnt_call_drops                          -0.108770 -0.012932   \n",
              "pcnt_dropped_calls                       0.068873  0.038479   \n",
              "rsrp_voice_pcnt_poor_duration            0.181885  0.097518   \n",
              "rsrp_data_pcnt_poor_duration             0.189493  0.102385   \n",
              "mean_cqi_voice_pcnt_poor_duration        0.245270  0.086170   \n",
              "sinr_voice_pcnt_poor_duration            0.001700 -0.034929   \n",
              "sinr_data_pcnt_poor_duration            -0.001470 -0.035574   \n",
              "age_on_network                          -0.134359 -0.029707   \n",
              "cnt_connections                         -0.294678 -0.213540   \n",
              "current_plan_code                        0.070604  0.047956   \n",
              "cnt_recharges_made                      -0.134247 -0.029708   \n",
              "total_payment_made                      -0.031230 -0.006064   \n",
              "cnt_main_plans_taken                    -0.086729 -0.002302   \n",
              "total_main_plans_mrp                    -0.020033  0.010894   \n",
              "cnt_addon_plans_taken                   -0.104018 -0.039651   \n",
              "total_addon_plans_mrp                   -0.036351 -0.020329   \n",
              "cnt_rchg_offline                        -0.134247 -0.029708   \n",
              "cnt_rchg_online                         -0.134247 -0.029708   \n",
              "cnt_rchg_on_or_before_expiry            -0.117727 -0.032923   \n",
              "cnt_rchg_after_expiry                   -0.021152  0.002273   \n",
              "current_active_plan_mrp                  0.058261 -0.010374   \n",
              "current_active_plan_validity             0.055297 -0.007135   \n",
              "last_cycle_plan_mrp                     -0.132491 -0.029927   \n",
              "last_cycle_plan_validity                -0.136420 -0.035575   \n",
              "avg_days_bw_rchg_and_expiry              0.259295  0.150594   \n",
              "stddev_days_bw_rchg_and_expiry          -0.005294 -0.001068   \n",
              "price_per_day                           -0.084624 -0.022522   \n",
              "gb_per_day_quota                         0.079132 -0.015206   \n",
              "pcnt_quota_used                         -0.483431 -0.133075   \n",
              "recharge_delay                           1.000000  0.522126   \n",
              "churn                                    0.522126  1.000000   \n",
              "ownership_corporate                     -0.027508 -0.010720   \n",
              "ownership_individual                     0.027508  0.010720   \n",
              "device_avg_asp_10K_to_20K                0.004698  0.035104   \n",
              "device_avg_asp_20K_to_30K                0.056356  0.056138   \n",
              "device_avg_asp_30K_to_50K               -0.018497 -0.035649   \n",
              "device_avg_asp_50K_above                 0.037058 -0.006960   \n",
              "device_avg_asp_less_10K                 -0.081688 -0.050465   \n",
              "\n",
              "                                   ownership_corporate  ownership_individual  \\\n",
              "activation_plan_code                          0.015886             -0.015886   \n",
              "mnp_flag                                      0.023222             -0.023222   \n",
              "calls_incoming_cnt                            0.008855             -0.008855   \n",
              "calls_outgoing_cnt                            0.075944             -0.075944   \n",
              "calls_incoming_duration                       0.009433             -0.009433   \n",
              "calls_outgoing_duration                       0.061281             -0.061281   \n",
              "total_call_count                              0.061342             -0.061342   \n",
              "total_sum_duration                            0.051106             -0.051106   \n",
              "tot_usage_mb                                  0.019971             -0.019971   \n",
              "upload_usage_mb                               0.040639             -0.040639   \n",
              "download_usage_mb                             0.013695             -0.013695   \n",
              "days_since_latch                              0.059490             -0.059490   \n",
              "cnt_open_qrc                                 -0.054869              0.054869   \n",
              "avg_days_to_close                            -0.033501              0.033501   \n",
              "cnt_call_drops                                0.025791             -0.025791   \n",
              "pcnt_dropped_calls                           -0.016552              0.016552   \n",
              "rsrp_voice_pcnt_poor_duration                 0.017945             -0.017945   \n",
              "rsrp_data_pcnt_poor_duration                  0.013111             -0.013111   \n",
              "mean_cqi_voice_pcnt_poor_duration             0.012613             -0.012613   \n",
              "sinr_voice_pcnt_poor_duration                 0.029831             -0.029831   \n",
              "sinr_data_pcnt_poor_duration                  0.028317             -0.028317   \n",
              "age_on_network                                0.010790             -0.010790   \n",
              "cnt_connections                               0.055949             -0.055949   \n",
              "current_plan_code                             0.007612             -0.007612   \n",
              "cnt_recharges_made                            0.010712             -0.010712   \n",
              "total_payment_made                            0.015571             -0.015571   \n",
              "cnt_main_plans_taken                          0.053277             -0.053277   \n",
              "total_main_plans_mrp                          0.047527             -0.047527   \n",
              "cnt_addon_plans_taken                        -0.037349              0.037349   \n",
              "total_addon_plans_mrp                        -0.015574              0.015574   \n",
              "cnt_rchg_offline                              0.010712             -0.010712   \n",
              "cnt_rchg_online                               0.010712             -0.010712   \n",
              "cnt_rchg_on_or_before_expiry                  0.046271             -0.046271   \n",
              "cnt_rchg_after_expiry                        -0.035633              0.035633   \n",
              "current_active_plan_mrp                      -0.024496              0.024496   \n",
              "current_active_plan_validity                 -0.024727              0.024727   \n",
              "last_cycle_plan_mrp                          -0.007797              0.007797   \n",
              "last_cycle_plan_validity                     -0.007152              0.007152   \n",
              "avg_days_bw_rchg_and_expiry                   0.014424             -0.014424   \n",
              "stddev_days_bw_rchg_and_expiry                0.035967             -0.035967   \n",
              "price_per_day                                 0.020379             -0.020379   \n",
              "gb_per_day_quota                             -0.031512              0.031512   \n",
              "pcnt_quota_used                               0.035300             -0.035300   \n",
              "recharge_delay                               -0.027508              0.027508   \n",
              "churn                                        -0.010720              0.010720   \n",
              "ownership_corporate                           1.000000             -1.000000   \n",
              "ownership_individual                         -1.000000              1.000000   \n",
              "device_avg_asp_10K_to_20K                     0.031706             -0.031706   \n",
              "device_avg_asp_20K_to_30K                    -0.044671              0.044671   \n",
              "device_avg_asp_30K_to_50K                     0.007175             -0.007175   \n",
              "device_avg_asp_50K_above                      0.031899             -0.031899   \n",
              "device_avg_asp_less_10K                      -0.027398              0.027398   \n",
              "\n",
              "                                   device_avg_asp_10K_to_20K  \\\n",
              "activation_plan_code                               -0.055497   \n",
              "mnp_flag                                            0.042285   \n",
              "calls_incoming_cnt                                  0.018258   \n",
              "calls_outgoing_cnt                                  0.033507   \n",
              "calls_incoming_duration                             0.025624   \n",
              "calls_outgoing_duration                             0.028880   \n",
              "total_call_count                                    0.037508   \n",
              "total_sum_duration                                  0.039566   \n",
              "tot_usage_mb                                       -0.057422   \n",
              "upload_usage_mb                                     0.025811   \n",
              "download_usage_mb                                  -0.062381   \n",
              "days_since_latch                                    0.031336   \n",
              "cnt_open_qrc                                        0.003703   \n",
              "avg_days_to_close                                  -0.001320   \n",
              "cnt_call_drops                                      0.048435   \n",
              "pcnt_dropped_calls                                  0.016028   \n",
              "rsrp_voice_pcnt_poor_duration                       0.026410   \n",
              "rsrp_data_pcnt_poor_duration                        0.026949   \n",
              "mean_cqi_voice_pcnt_poor_duration                   0.005298   \n",
              "sinr_voice_pcnt_poor_duration                       0.053960   \n",
              "sinr_data_pcnt_poor_duration                        0.056557   \n",
              "age_on_network                                      0.016993   \n",
              "cnt_connections                                    -0.002065   \n",
              "current_plan_code                                   0.067695   \n",
              "cnt_recharges_made                                  0.016063   \n",
              "total_payment_made                                  0.049962   \n",
              "cnt_main_plans_taken                               -0.000658   \n",
              "total_main_plans_mrp                                0.037124   \n",
              "cnt_addon_plans_taken                               0.023314   \n",
              "total_addon_plans_mrp                               0.053600   \n",
              "cnt_rchg_offline                                    0.016063   \n",
              "cnt_rchg_online                                     0.016063   \n",
              "cnt_rchg_on_or_before_expiry                       -0.032826   \n",
              "cnt_rchg_after_expiry                               0.050008   \n",
              "current_active_plan_mrp                             0.033618   \n",
              "current_active_plan_validity                        0.034425   \n",
              "last_cycle_plan_mrp                                 0.043933   \n",
              "last_cycle_plan_validity                            0.044614   \n",
              "avg_days_bw_rchg_and_expiry                         0.012244   \n",
              "stddev_days_bw_rchg_and_expiry                     -0.008787   \n",
              "price_per_day                                       0.027915   \n",
              "gb_per_day_quota                                    0.013691   \n",
              "pcnt_quota_used                                    -0.028893   \n",
              "recharge_delay                                      0.004698   \n",
              "churn                                               0.035104   \n",
              "ownership_corporate                                 0.031706   \n",
              "ownership_individual                               -0.031706   \n",
              "device_avg_asp_10K_to_20K                           1.000000   \n",
              "device_avg_asp_20K_to_30K                          -0.257790   \n",
              "device_avg_asp_30K_to_50K                          -0.254563   \n",
              "device_avg_asp_50K_above                           -0.261009   \n",
              "device_avg_asp_less_10K                            -0.249707   \n",
              "\n",
              "                                   device_avg_asp_20K_to_30K  \\\n",
              "activation_plan_code                            5.017759e-02   \n",
              "mnp_flag                                       -6.626164e-18   \n",
              "calls_incoming_cnt                             -2.337916e-02   \n",
              "calls_outgoing_cnt                              1.587948e-02   \n",
              "calls_incoming_duration                        -8.817263e-03   \n",
              "calls_outgoing_duration                         1.365919e-02   \n",
              "total_call_count                               -5.534972e-03   \n",
              "total_sum_duration                              3.409178e-03   \n",
              "tot_usage_mb                                    1.731145e-03   \n",
              "upload_usage_mb                                 2.299174e-02   \n",
              "download_usage_mb                              -1.952253e-03   \n",
              "days_since_latch                               -9.352830e-04   \n",
              "cnt_open_qrc                                    1.662417e-02   \n",
              "avg_days_to_close                               4.033144e-02   \n",
              "cnt_call_drops                                 -7.662723e-03   \n",
              "pcnt_dropped_calls                             -3.467459e-02   \n",
              "rsrp_voice_pcnt_poor_duration                  -3.572786e-02   \n",
              "rsrp_data_pcnt_poor_duration                   -3.069555e-02   \n",
              "mean_cqi_voice_pcnt_poor_duration               2.480806e-02   \n",
              "sinr_voice_pcnt_poor_duration                  -2.784684e-02   \n",
              "sinr_data_pcnt_poor_duration                   -2.868667e-02   \n",
              "age_on_network                                 -1.394936e-02   \n",
              "cnt_connections                                -4.859086e-02   \n",
              "current_plan_code                              -2.163506e-02   \n",
              "cnt_recharges_made                             -1.226275e-02   \n",
              "total_payment_made                             -5.682059e-02   \n",
              "cnt_main_plans_taken                            1.380191e-02   \n",
              "total_main_plans_mrp                           -2.821797e-02   \n",
              "cnt_addon_plans_taken                          -3.089356e-02   \n",
              "total_addon_plans_mrp                          -7.352671e-02   \n",
              "cnt_rchg_offline                               -1.226275e-02   \n",
              "cnt_rchg_online                                -1.226275e-02   \n",
              "cnt_rchg_on_or_before_expiry                   -4.840467e-03   \n",
              "cnt_rchg_after_expiry                          -7.916483e-03   \n",
              "current_active_plan_mrp                        -2.846180e-02   \n",
              "current_active_plan_validity                   -2.817962e-02   \n",
              "last_cycle_plan_mrp                            -1.034701e-02   \n",
              "last_cycle_plan_validity                       -8.752370e-03   \n",
              "avg_days_bw_rchg_and_expiry                     4.593394e-03   \n",
              "stddev_days_bw_rchg_and_expiry                  8.729603e-03   \n",
              "price_per_day                                  -5.788310e-03   \n",
              "gb_per_day_quota                               -3.122170e-02   \n",
              "pcnt_quota_used                                 2.768792e-02   \n",
              "recharge_delay                                  5.635595e-02   \n",
              "churn                                           5.613835e-02   \n",
              "ownership_corporate                            -4.467118e-02   \n",
              "ownership_individual                            4.467118e-02   \n",
              "device_avg_asp_10K_to_20K                      -2.577900e-01   \n",
              "device_avg_asp_20K_to_30K                       1.000000e+00   \n",
              "device_avg_asp_30K_to_50K                      -2.468710e-01   \n",
              "device_avg_asp_50K_above                       -2.531212e-01   \n",
              "device_avg_asp_less_10K                        -2.421611e-01   \n",
              "\n",
              "                                   device_avg_asp_30K_to_50K  \\\n",
              "activation_plan_code                               -0.033542   \n",
              "mnp_flag                                           -0.031100   \n",
              "calls_incoming_cnt                                 -0.021513   \n",
              "calls_outgoing_cnt                                 -0.045750   \n",
              "calls_incoming_duration                            -0.023384   \n",
              "calls_outgoing_duration                            -0.034369   \n",
              "total_call_count                                   -0.048727   \n",
              "total_sum_duration                                 -0.041889   \n",
              "tot_usage_mb                                       -0.023842   \n",
              "upload_usage_mb                                    -0.055827   \n",
              "download_usage_mb                                  -0.015171   \n",
              "days_since_latch                                   -0.040725   \n",
              "cnt_open_qrc                                       -0.000131   \n",
              "avg_days_to_close                                  -0.010948   \n",
              "cnt_call_drops                                     -0.043577   \n",
              "pcnt_dropped_calls                                  0.034803   \n",
              "rsrp_voice_pcnt_poor_duration                      -0.002104   \n",
              "rsrp_data_pcnt_poor_duration                       -0.010846   \n",
              "mean_cqi_voice_pcnt_poor_duration                  -0.024695   \n",
              "sinr_voice_pcnt_poor_duration                       0.045591   \n",
              "sinr_data_pcnt_poor_duration                        0.052234   \n",
              "age_on_network                                     -0.015479   \n",
              "cnt_connections                                     0.033079   \n",
              "current_plan_code                                  -0.034600   \n",
              "cnt_recharges_made                                 -0.014963   \n",
              "total_payment_made                                  0.011271   \n",
              "cnt_main_plans_taken                                0.008432   \n",
              "total_main_plans_mrp                                0.022532   \n",
              "cnt_addon_plans_taken                              -0.029416   \n",
              "total_addon_plans_mrp                              -0.000618   \n",
              "cnt_rchg_offline                                   -0.014963   \n",
              "cnt_rchg_online                                    -0.014963   \n",
              "cnt_rchg_on_or_before_expiry                        0.044017   \n",
              "cnt_rchg_after_expiry                              -0.060184   \n",
              "current_active_plan_mrp                             0.004590   \n",
              "current_active_plan_validity                        0.000522   \n",
              "last_cycle_plan_mrp                                -0.042179   \n",
              "last_cycle_plan_validity                           -0.042549   \n",
              "avg_days_bw_rchg_and_expiry                        -0.028555   \n",
              "stddev_days_bw_rchg_and_expiry                     -0.014728   \n",
              "price_per_day                                       0.035695   \n",
              "gb_per_day_quota                                    0.015005   \n",
              "pcnt_quota_used                                    -0.002000   \n",
              "recharge_delay                                     -0.018497   \n",
              "churn                                              -0.035649   \n",
              "ownership_corporate                                 0.007175   \n",
              "ownership_individual                               -0.007175   \n",
              "device_avg_asp_10K_to_20K                          -0.254563   \n",
              "device_avg_asp_20K_to_30K                          -0.246871   \n",
              "device_avg_asp_30K_to_50K                           1.000000   \n",
              "device_avg_asp_50K_above                           -0.249953   \n",
              "device_avg_asp_less_10K                            -0.239130   \n",
              "\n",
              "                                   device_avg_asp_50K_above  \\\n",
              "activation_plan_code                               0.034080   \n",
              "mnp_flag                                          -0.011679   \n",
              "calls_incoming_cnt                                 0.003122   \n",
              "calls_outgoing_cnt                                -0.002093   \n",
              "calls_incoming_duration                           -0.002495   \n",
              "calls_outgoing_duration                            0.007460   \n",
              "total_call_count                                   0.000759   \n",
              "total_sum_duration                                 0.003559   \n",
              "tot_usage_mb                                       0.016038   \n",
              "upload_usage_mb                                    0.006779   \n",
              "download_usage_mb                                  0.015167   \n",
              "days_since_latch                                  -0.003516   \n",
              "cnt_open_qrc                                      -0.040320   \n",
              "avg_days_to_close                                 -0.046613   \n",
              "cnt_call_drops                                     0.013960   \n",
              "pcnt_dropped_calls                                -0.002028   \n",
              "rsrp_voice_pcnt_poor_duration                      0.007674   \n",
              "rsrp_data_pcnt_poor_duration                       0.008393   \n",
              "mean_cqi_voice_pcnt_poor_duration                  0.044289   \n",
              "sinr_voice_pcnt_poor_duration                     -0.015569   \n",
              "sinr_data_pcnt_poor_duration                      -0.015930   \n",
              "age_on_network                                    -0.016203   \n",
              "cnt_connections                                    0.008293   \n",
              "current_plan_code                                 -0.002049   \n",
              "cnt_recharges_made                                -0.016869   \n",
              "total_payment_made                                -0.001305   \n",
              "cnt_main_plans_taken                              -0.027605   \n",
              "total_main_plans_mrp                              -0.010992   \n",
              "cnt_addon_plans_taken                              0.003381   \n",
              "total_addon_plans_mrp                              0.007597   \n",
              "cnt_rchg_offline                                  -0.016869   \n",
              "cnt_rchg_online                                   -0.016869   \n",
              "cnt_rchg_on_or_before_expiry                       0.010181   \n",
              "cnt_rchg_after_expiry                             -0.027932   \n",
              "current_active_plan_mrp                           -0.027091   \n",
              "current_active_plan_validity                      -0.027790   \n",
              "last_cycle_plan_mrp                               -0.011756   \n",
              "last_cycle_plan_validity                          -0.011690   \n",
              "avg_days_bw_rchg_and_expiry                        0.063314   \n",
              "stddev_days_bw_rchg_and_expiry                     0.015399   \n",
              "price_per_day                                     -0.011911   \n",
              "gb_per_day_quota                                  -0.016503   \n",
              "pcnt_quota_used                                   -0.009240   \n",
              "recharge_delay                                     0.037058   \n",
              "churn                                             -0.006960   \n",
              "ownership_corporate                                0.031899   \n",
              "ownership_individual                              -0.031899   \n",
              "device_avg_asp_10K_to_20K                         -0.261009   \n",
              "device_avg_asp_20K_to_30K                         -0.253121   \n",
              "device_avg_asp_30K_to_50K                         -0.249953   \n",
              "device_avg_asp_50K_above                           1.000000   \n",
              "device_avg_asp_less_10K                           -0.245184   \n",
              "\n",
              "                                   device_avg_asp_less_10K  \n",
              "activation_plan_code                              0.005392  \n",
              "mnp_flag                                         -0.000435  \n",
              "calls_incoming_cnt                                0.023444  \n",
              "calls_outgoing_cnt                               -0.002535  \n",
              "calls_incoming_duration                           0.008611  \n",
              "calls_outgoing_duration                          -0.016797  \n",
              "total_call_count                                  0.015228  \n",
              "total_sum_duration                               -0.005824  \n",
              "tot_usage_mb                                      0.065505  \n",
              "upload_usage_mb                                  -0.000713  \n",
              "download_usage_mb                                 0.066530  \n",
              "days_since_latch                                  0.013240  \n",
              "cnt_open_qrc                                      0.020754  \n",
              "avg_days_to_close                                 0.019207  \n",
              "cnt_call_drops                                   -0.012720  \n",
              "pcnt_dropped_calls                               -0.014420  \n",
              "rsrp_voice_pcnt_poor_duration                     0.003255  \n",
              "rsrp_data_pcnt_poor_duration                      0.005672  \n",
              "mean_cqi_voice_pcnt_poor_duration                -0.051300  \n",
              "sinr_voice_pcnt_poor_duration                    -0.057772  \n",
              "sinr_data_pcnt_poor_duration                     -0.065963  \n",
              "age_on_network                                    0.028887  \n",
              "cnt_connections                                   0.009698  \n",
              "current_plan_code                                -0.011109  \n",
              "cnt_recharges_made                                0.028294  \n",
              "total_payment_made                               -0.004003  \n",
              "cnt_main_plans_taken                              0.006434  \n",
              "total_main_plans_mrp                             -0.021281  \n",
              "cnt_addon_plans_taken                             0.033587  \n",
              "total_addon_plans_mrp                             0.012140  \n",
              "cnt_rchg_offline                                  0.028294  \n",
              "cnt_rchg_online                                   0.028294  \n",
              "cnt_rchg_on_or_before_expiry                     -0.015981  \n",
              "cnt_rchg_after_expiry                             0.045742  \n",
              "current_active_plan_mrp                           0.017299  \n",
              "current_active_plan_validity                      0.021008  \n",
              "last_cycle_plan_mrp                               0.019692  \n",
              "last_cycle_plan_validity                          0.017667  \n",
              "avg_days_bw_rchg_and_expiry                      -0.053536  \n",
              "stddev_days_bw_rchg_and_expiry                   -0.000691  \n",
              "price_per_day                                    -0.046965  \n",
              "gb_per_day_quota                                  0.019388  \n",
              "pcnt_quota_used                                   0.013283  \n",
              "recharge_delay                                   -0.081688  \n",
              "churn                                            -0.050465  \n",
              "ownership_corporate                              -0.027398  \n",
              "ownership_individual                              0.027398  \n",
              "device_avg_asp_10K_to_20K                        -0.249707  \n",
              "device_avg_asp_20K_to_30K                        -0.242161  \n",
              "device_avg_asp_30K_to_50K                        -0.239130  \n",
              "device_avg_asp_50K_above                         -0.245184  \n",
              "device_avg_asp_less_10K                           1.000000  \n",
              "\n",
              "[52 rows x 52 columns]"
            ],
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              "\n",
              "  <div id=\"df-4da9f79b-2edf-4ee1-8f3d-1b413a27b34b\">\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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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>activation_plan_code</th>\n",
              "      <th>mnp_flag</th>\n",
              "      <th>calls_incoming_cnt</th>\n",
              "      <th>calls_outgoing_cnt</th>\n",
              "      <th>calls_incoming_duration</th>\n",
              "      <th>calls_outgoing_duration</th>\n",
              "      <th>total_call_count</th>\n",
              "      <th>total_sum_duration</th>\n",
              "      <th>tot_usage_mb</th>\n",
              "      <th>upload_usage_mb</th>\n",
              "      <th>...</th>\n",
              "      <th>pcnt_quota_used</th>\n",
              "      <th>recharge_delay</th>\n",
              "      <th>churn</th>\n",
              "      <th>ownership_corporate</th>\n",
              "      <th>ownership_individual</th>\n",
              "      <th>device_avg_asp_10K_to_20K</th>\n",
              "      <th>device_avg_asp_20K_to_30K</th>\n",
              "      <th>device_avg_asp_30K_to_50K</th>\n",
              "      <th>device_avg_asp_50K_above</th>\n",
              "      <th>device_avg_asp_less_10K</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>activation_plan_code</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-1.303076e-02</td>\n",
              "      <td>0.011042</td>\n",
              "      <td>0.042704</td>\n",
              "      <td>0.019123</td>\n",
              "      <td>0.042834</td>\n",
              "      <td>0.038905</td>\n",
              "      <td>0.044881</td>\n",
              "      <td>-0.004974</td>\n",
              "      <td>-0.033514</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.028850</td>\n",
              "      <td>0.182931</td>\n",
              "      <td>0.112554</td>\n",
              "      <td>0.015886</td>\n",
              "      <td>-0.015886</td>\n",
              "      <td>-0.055497</td>\n",
              "      <td>5.017759e-02</td>\n",
              "      <td>-0.033542</td>\n",
              "      <td>0.034080</td>\n",
              "      <td>0.005392</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mnp_flag</th>\n",
              "      <td>-0.013031</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>-0.033936</td>\n",
              "      <td>-0.024355</td>\n",
              "      <td>-0.020844</td>\n",
              "      <td>-0.029865</td>\n",
              "      <td>-0.042302</td>\n",
              "      <td>-0.036783</td>\n",
              "      <td>-0.041390</td>\n",
              "      <td>-0.047657</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.030307</td>\n",
              "      <td>0.054686</td>\n",
              "      <td>0.020943</td>\n",
              "      <td>0.023222</td>\n",
              "      <td>-0.023222</td>\n",
              "      <td>0.042285</td>\n",
              "      <td>-6.626164e-18</td>\n",
              "      <td>-0.031100</td>\n",
              "      <td>-0.011679</td>\n",
              "      <td>-0.000435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>calls_incoming_cnt</th>\n",
              "      <td>0.011042</td>\n",
              "      <td>-3.393608e-02</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.049555</td>\n",
              "      <td>0.968497</td>\n",
              "      <td>-0.050906</td>\n",
              "      <td>0.691911</td>\n",
              "      <td>0.671232</td>\n",
              "      <td>-0.013832</td>\n",
              "      <td>0.069212</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.003534</td>\n",
              "      <td>-0.214768</td>\n",
              "      <td>-0.064641</td>\n",
              "      <td>0.008855</td>\n",
              "      <td>-0.008855</td>\n",
              "      <td>0.018258</td>\n",
              "      <td>-2.337916e-02</td>\n",
              "      <td>-0.021513</td>\n",
              "      <td>0.003122</td>\n",
              "      <td>0.023444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>calls_outgoing_cnt</th>\n",
              "      <td>0.042704</td>\n",
              "      <td>-2.435485e-02</td>\n",
              "      <td>-0.049555</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.051584</td>\n",
              "      <td>0.969809</td>\n",
              "      <td>0.686808</td>\n",
              "      <td>0.661966</td>\n",
              "      <td>0.011526</td>\n",
              "      <td>-0.017589</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.017548</td>\n",
              "      <td>-0.021893</td>\n",
              "      <td>0.015244</td>\n",
              "      <td>0.075944</td>\n",
              "      <td>-0.075944</td>\n",
              "      <td>0.033507</td>\n",
              "      <td>1.587948e-02</td>\n",
              "      <td>-0.045750</td>\n",
              "      <td>-0.002093</td>\n",
              "      <td>-0.002535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>calls_incoming_duration</th>\n",
              "      <td>0.019123</td>\n",
              "      <td>-2.084438e-02</td>\n",
              "      <td>0.968497</td>\n",
              "      <td>-0.051584</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.051990</td>\n",
              "      <td>0.667519</td>\n",
              "      <td>0.693478</td>\n",
              "      <td>-0.026354</td>\n",
              "      <td>0.065350</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.007456</td>\n",
              "      <td>-0.193109</td>\n",
              "      <td>-0.059434</td>\n",
              "      <td>0.009433</td>\n",
              "      <td>-0.009433</td>\n",
              "      <td>0.025624</td>\n",
              "      <td>-8.817263e-03</td>\n",
              "      <td>-0.023384</td>\n",
              "      <td>-0.002495</td>\n",
              "      <td>0.008611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>calls_outgoing_duration</th>\n",
              "      <td>0.042834</td>\n",
              "      <td>-2.986479e-02</td>\n",
              "      <td>-0.050906</td>\n",
              "      <td>0.969809</td>\n",
              "      <td>-0.051990</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.664001</td>\n",
              "      <td>0.683450</td>\n",
              "      <td>0.001780</td>\n",
              "      <td>-0.019657</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.026867</td>\n",
              "      <td>-0.006295</td>\n",
              "      <td>0.009969</td>\n",
              "      <td>0.061281</td>\n",
              "      <td>-0.061281</td>\n",
              "      <td>0.028880</td>\n",
              "      <td>1.365919e-02</td>\n",
              "      <td>-0.034369</td>\n",
              "      <td>0.007460</td>\n",
              "      <td>-0.016797</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_call_count</th>\n",
              "      <td>0.038905</td>\n",
              "      <td>-4.230182e-02</td>\n",
              "      <td>0.691911</td>\n",
              "      <td>0.686808</td>\n",
              "      <td>0.667519</td>\n",
              "      <td>0.664001</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.966993</td>\n",
              "      <td>-0.001734</td>\n",
              "      <td>0.037653</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.015257</td>\n",
              "      <td>-0.172120</td>\n",
              "      <td>-0.036022</td>\n",
              "      <td>0.061342</td>\n",
              "      <td>-0.061342</td>\n",
              "      <td>0.037508</td>\n",
              "      <td>-5.534972e-03</td>\n",
              "      <td>-0.048727</td>\n",
              "      <td>0.000759</td>\n",
              "      <td>0.015228</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_sum_duration</th>\n",
              "      <td>0.044881</td>\n",
              "      <td>-3.678302e-02</td>\n",
              "      <td>0.671232</td>\n",
              "      <td>0.661966</td>\n",
              "      <td>0.693478</td>\n",
              "      <td>0.683450</td>\n",
              "      <td>0.966993</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.017980</td>\n",
              "      <td>0.033588</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.024834</td>\n",
              "      <td>-0.145702</td>\n",
              "      <td>-0.036254</td>\n",
              "      <td>0.051106</td>\n",
              "      <td>-0.051106</td>\n",
              "      <td>0.039566</td>\n",
              "      <td>3.409178e-03</td>\n",
              "      <td>-0.041889</td>\n",
              "      <td>0.003559</td>\n",
              "      <td>-0.005824</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tot_usage_mb</th>\n",
              "      <td>-0.004974</td>\n",
              "      <td>-4.138960e-02</td>\n",
              "      <td>-0.013832</td>\n",
              "      <td>0.011526</td>\n",
              "      <td>-0.026354</td>\n",
              "      <td>0.001780</td>\n",
              "      <td>-0.001734</td>\n",
              "      <td>-0.017980</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.165004</td>\n",
              "      <td>...</td>\n",
              "      <td>0.634894</td>\n",
              "      <td>-0.524368</td>\n",
              "      <td>-0.193900</td>\n",
              "      <td>0.019971</td>\n",
              "      <td>-0.019971</td>\n",
              "      <td>-0.057422</td>\n",
              "      <td>1.731145e-03</td>\n",
              "      <td>-0.023842</td>\n",
              "      <td>0.016038</td>\n",
              "      <td>0.065505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>upload_usage_mb</th>\n",
              "      <td>-0.033514</td>\n",
              "      <td>-4.765681e-02</td>\n",
              "      <td>0.069212</td>\n",
              "      <td>-0.017589</td>\n",
              "      <td>0.065350</td>\n",
              "      <td>-0.019657</td>\n",
              "      <td>0.037653</td>\n",
              "      <td>0.033588</td>\n",
              "      <td>0.165004</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.113954</td>\n",
              "      <td>-0.111315</td>\n",
              "      <td>-0.041746</td>\n",
              "      <td>0.040639</td>\n",
              "      <td>-0.040639</td>\n",
              "      <td>0.025811</td>\n",
              "      <td>2.299174e-02</td>\n",
              "      <td>-0.055827</td>\n",
              "      <td>0.006779</td>\n",
              "      <td>-0.000713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>download_usage_mb</th>\n",
              "      <td>0.000361</td>\n",
              "      <td>-3.427937e-02</td>\n",
              "      <td>-0.025185</td>\n",
              "      <td>0.014522</td>\n",
              "      <td>-0.037257</td>\n",
              "      <td>0.004975</td>\n",
              "      <td>-0.007830</td>\n",
              "      <td>-0.023645</td>\n",
              "      <td>0.987272</td>\n",
              "      <td>0.006043</td>\n",
              "      <td>...</td>\n",
              "      <td>0.625330</td>\n",
              "      <td>-0.513696</td>\n",
              "      <td>-0.189860</td>\n",
              "      <td>0.013695</td>\n",
              "      <td>-0.013695</td>\n",
              "      <td>-0.062381</td>\n",
              "      <td>-1.952253e-03</td>\n",
              "      <td>-0.015171</td>\n",
              "      <td>0.015167</td>\n",
              "      <td>0.066530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>days_since_latch</th>\n",
              "      <td>0.039919</td>\n",
              "      <td>-4.324241e-02</td>\n",
              "      <td>0.686616</td>\n",
              "      <td>0.684613</td>\n",
              "      <td>0.661405</td>\n",
              "      <td>0.662565</td>\n",
              "      <td>0.994560</td>\n",
              "      <td>0.961488</td>\n",
              "      <td>-0.004368</td>\n",
              "      <td>0.029369</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.014117</td>\n",
              "      <td>-0.166547</td>\n",
              "      <td>-0.035729</td>\n",
              "      <td>0.059490</td>\n",
              "      <td>-0.059490</td>\n",
              "      <td>0.031336</td>\n",
              "      <td>-9.352830e-04</td>\n",
              "      <td>-0.040725</td>\n",
              "      <td>-0.003516</td>\n",
              "      <td>0.013240</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_open_qrc</th>\n",
              "      <td>0.011120</td>\n",
              "      <td>1.388366e-02</td>\n",
              "      <td>0.027595</td>\n",
              "      <td>-0.071406</td>\n",
              "      <td>0.026962</td>\n",
              "      <td>-0.078205</td>\n",
              "      <td>-0.031535</td>\n",
              "      <td>-0.036713</td>\n",
              "      <td>-0.086214</td>\n",
              "      <td>0.034701</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.077220</td>\n",
              "      <td>0.161511</td>\n",
              "      <td>0.086211</td>\n",
              "      <td>-0.054869</td>\n",
              "      <td>0.054869</td>\n",
              "      <td>0.003703</td>\n",
              "      <td>1.662417e-02</td>\n",
              "      <td>-0.000131</td>\n",
              "      <td>-0.040320</td>\n",
              "      <td>0.020754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>avg_days_to_close</th>\n",
              "      <td>-0.021725</td>\n",
              "      <td>3.107836e-02</td>\n",
              "      <td>-0.002644</td>\n",
              "      <td>-0.030774</td>\n",
              "      <td>-0.006533</td>\n",
              "      <td>-0.040116</td>\n",
              "      <td>-0.024170</td>\n",
              "      <td>-0.033717</td>\n",
              "      <td>-0.043603</td>\n",
              "      <td>-0.054486</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.026733</td>\n",
              "      <td>0.028123</td>\n",
              "      <td>0.008777</td>\n",
              "      <td>-0.033501</td>\n",
              "      <td>0.033501</td>\n",
              "      <td>-0.001320</td>\n",
              "      <td>4.033144e-02</td>\n",
              "      <td>-0.010948</td>\n",
              "      <td>-0.046613</td>\n",
              "      <td>0.019207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_call_drops</th>\n",
              "      <td>0.031177</td>\n",
              "      <td>-2.202008e-02</td>\n",
              "      <td>0.575499</td>\n",
              "      <td>0.512637</td>\n",
              "      <td>0.554846</td>\n",
              "      <td>0.508201</td>\n",
              "      <td>0.789380</td>\n",
              "      <td>0.772228</td>\n",
              "      <td>0.000356</td>\n",
              "      <td>0.039784</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.009056</td>\n",
              "      <td>-0.108770</td>\n",
              "      <td>-0.012932</td>\n",
              "      <td>0.025791</td>\n",
              "      <td>-0.025791</td>\n",
              "      <td>0.048435</td>\n",
              "      <td>-7.662723e-03</td>\n",
              "      <td>-0.043577</td>\n",
              "      <td>0.013960</td>\n",
              "      <td>-0.012720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pcnt_dropped_calls</th>\n",
              "      <td>-0.004628</td>\n",
              "      <td>2.493265e-03</td>\n",
              "      <td>0.016975</td>\n",
              "      <td>-0.045067</td>\n",
              "      <td>0.017262</td>\n",
              "      <td>-0.035669</td>\n",
              "      <td>-0.020225</td>\n",
              "      <td>-0.013116</td>\n",
              "      <td>-0.030641</td>\n",
              "      <td>-0.008881</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.043017</td>\n",
              "      <td>0.068873</td>\n",
              "      <td>0.038479</td>\n",
              "      <td>-0.016552</td>\n",
              "      <td>0.016552</td>\n",
              "      <td>0.016028</td>\n",
              "      <td>-3.467459e-02</td>\n",
              "      <td>0.034803</td>\n",
              "      <td>-0.002028</td>\n",
              "      <td>-0.014420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>rsrp_voice_pcnt_poor_duration</th>\n",
              "      <td>0.048468</td>\n",
              "      <td>2.658813e-02</td>\n",
              "      <td>-0.042777</td>\n",
              "      <td>-0.005555</td>\n",
              "      <td>-0.040526</td>\n",
              "      <td>0.003556</td>\n",
              "      <td>-0.035146</td>\n",
              "      <td>-0.027058</td>\n",
              "      <td>-0.037922</td>\n",
              "      <td>0.004022</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.030237</td>\n",
              "      <td>0.181885</td>\n",
              "      <td>0.097518</td>\n",
              "      <td>0.017945</td>\n",
              "      <td>-0.017945</td>\n",
              "      <td>0.026410</td>\n",
              "      <td>-3.572786e-02</td>\n",
              "      <td>-0.002104</td>\n",
              "      <td>0.007674</td>\n",
              "      <td>0.003255</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>rsrp_data_pcnt_poor_duration</th>\n",
              "      <td>0.051820</td>\n",
              "      <td>2.257050e-02</td>\n",
              "      <td>-0.041969</td>\n",
              "      <td>0.003461</td>\n",
              "      <td>-0.039479</td>\n",
              "      <td>0.011202</td>\n",
              "      <td>-0.028041</td>\n",
              "      <td>-0.020777</td>\n",
              "      <td>-0.041274</td>\n",
              "      <td>0.004693</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.036340</td>\n",
              "      <td>0.189493</td>\n",
              "      <td>0.102385</td>\n",
              "      <td>0.013111</td>\n",
              "      <td>-0.013111</td>\n",
              "      <td>0.026949</td>\n",
              "      <td>-3.069555e-02</td>\n",
              "      <td>-0.010846</td>\n",
              "      <td>0.008393</td>\n",
              "      <td>0.005672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean_cqi_voice_pcnt_poor_duration</th>\n",
              "      <td>0.017128</td>\n",
              "      <td>1.196293e-02</td>\n",
              "      <td>0.017857</td>\n",
              "      <td>-0.001043</td>\n",
              "      <td>0.019824</td>\n",
              "      <td>-0.001994</td>\n",
              "      <td>0.012241</td>\n",
              "      <td>0.013052</td>\n",
              "      <td>-0.050049</td>\n",
              "      <td>-0.028548</td>\n",
              "      <td>...</td>\n",
              "      <td>0.021159</td>\n",
              "      <td>0.245270</td>\n",
              "      <td>0.086170</td>\n",
              "      <td>0.012613</td>\n",
              "      <td>-0.012613</td>\n",
              "      <td>0.005298</td>\n",
              "      <td>2.480806e-02</td>\n",
              "      <td>-0.024695</td>\n",
              "      <td>0.044289</td>\n",
              "      <td>-0.051300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sinr_voice_pcnt_poor_duration</th>\n",
              "      <td>-0.021508</td>\n",
              "      <td>6.436111e-02</td>\n",
              "      <td>-0.013584</td>\n",
              "      <td>-0.018462</td>\n",
              "      <td>-0.012657</td>\n",
              "      <td>-0.028246</td>\n",
              "      <td>-0.023231</td>\n",
              "      <td>-0.029630</td>\n",
              "      <td>0.036908</td>\n",
              "      <td>0.013974</td>\n",
              "      <td>...</td>\n",
              "      <td>0.002028</td>\n",
              "      <td>0.001700</td>\n",
              "      <td>-0.034929</td>\n",
              "      <td>0.029831</td>\n",
              "      <td>-0.029831</td>\n",
              "      <td>0.053960</td>\n",
              "      <td>-2.784684e-02</td>\n",
              "      <td>0.045591</td>\n",
              "      <td>-0.015569</td>\n",
              "      <td>-0.057772</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sinr_data_pcnt_poor_duration</th>\n",
              "      <td>-0.023007</td>\n",
              "      <td>7.590998e-02</td>\n",
              "      <td>-0.011640</td>\n",
              "      <td>-0.013585</td>\n",
              "      <td>-0.010051</td>\n",
              "      <td>-0.022632</td>\n",
              "      <td>-0.018291</td>\n",
              "      <td>-0.023675</td>\n",
              "      <td>0.040235</td>\n",
              "      <td>0.020379</td>\n",
              "      <td>...</td>\n",
              "      <td>0.001541</td>\n",
              "      <td>-0.001470</td>\n",
              "      <td>-0.035574</td>\n",
              "      <td>0.028317</td>\n",
              "      <td>-0.028317</td>\n",
              "      <td>0.056557</td>\n",
              "      <td>-2.868667e-02</td>\n",
              "      <td>0.052234</td>\n",
              "      <td>-0.015930</td>\n",
              "      <td>-0.065963</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>age_on_network</th>\n",
              "      <td>-0.010357</td>\n",
              "      <td>-1.747536e-02</td>\n",
              "      <td>-0.022528</td>\n",
              "      <td>0.012191</td>\n",
              "      <td>-0.036609</td>\n",
              "      <td>0.007507</td>\n",
              "      <td>-0.007582</td>\n",
              "      <td>-0.021345</td>\n",
              "      <td>-0.020669</td>\n",
              "      <td>0.032244</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.008422</td>\n",
              "      <td>-0.134359</td>\n",
              "      <td>-0.029707</td>\n",
              "      <td>0.010790</td>\n",
              "      <td>-0.010790</td>\n",
              "      <td>0.016993</td>\n",
              "      <td>-1.394936e-02</td>\n",
              "      <td>-0.015479</td>\n",
              "      <td>-0.016203</td>\n",
              "      <td>0.028887</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_connections</th>\n",
              "      <td>-0.024122</td>\n",
              "      <td>2.506571e-02</td>\n",
              "      <td>-0.020241</td>\n",
              "      <td>0.021944</td>\n",
              "      <td>-0.019779</td>\n",
              "      <td>0.019657</td>\n",
              "      <td>0.001133</td>\n",
              "      <td>-0.000276</td>\n",
              "      <td>0.041153</td>\n",
              "      <td>-0.011370</td>\n",
              "      <td>...</td>\n",
              "      <td>0.057286</td>\n",
              "      <td>-0.294678</td>\n",
              "      <td>-0.213540</td>\n",
              "      <td>0.055949</td>\n",
              "      <td>-0.055949</td>\n",
              "      <td>-0.002065</td>\n",
              "      <td>-4.859086e-02</td>\n",
              "      <td>0.033079</td>\n",
              "      <td>0.008293</td>\n",
              "      <td>0.009698</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>current_plan_code</th>\n",
              "      <td>0.051528</td>\n",
              "      <td>-3.905369e-02</td>\n",
              "      <td>0.042753</td>\n",
              "      <td>0.015233</td>\n",
              "      <td>0.039803</td>\n",
              "      <td>0.014615</td>\n",
              "      <td>0.042124</td>\n",
              "      <td>0.039639</td>\n",
              "      <td>-0.031018</td>\n",
              "      <td>-0.003785</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.044783</td>\n",
              "      <td>0.070604</td>\n",
              "      <td>0.047956</td>\n",
              "      <td>0.007612</td>\n",
              "      <td>-0.007612</td>\n",
              "      <td>0.067695</td>\n",
              "      <td>-2.163506e-02</td>\n",
              "      <td>-0.034600</td>\n",
              "      <td>-0.002049</td>\n",
              "      <td>-0.011109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_recharges_made</th>\n",
              "      <td>-0.010539</td>\n",
              "      <td>-1.790240e-02</td>\n",
              "      <td>-0.024226</td>\n",
              "      <td>0.012651</td>\n",
              "      <td>-0.038227</td>\n",
              "      <td>0.008112</td>\n",
              "      <td>-0.008485</td>\n",
              "      <td>-0.022091</td>\n",
              "      <td>-0.020497</td>\n",
              "      <td>0.031804</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.008673</td>\n",
              "      <td>-0.134247</td>\n",
              "      <td>-0.029708</td>\n",
              "      <td>0.010712</td>\n",
              "      <td>-0.010712</td>\n",
              "      <td>0.016063</td>\n",
              "      <td>-1.226275e-02</td>\n",
              "      <td>-0.014963</td>\n",
              "      <td>-0.016869</td>\n",
              "      <td>0.028294</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_payment_made</th>\n",
              "      <td>0.017207</td>\n",
              "      <td>-1.759391e-02</td>\n",
              "      <td>-0.020226</td>\n",
              "      <td>0.060546</td>\n",
              "      <td>-0.024348</td>\n",
              "      <td>0.069227</td>\n",
              "      <td>0.029047</td>\n",
              "      <td>0.032146</td>\n",
              "      <td>-0.021461</td>\n",
              "      <td>0.006661</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.013849</td>\n",
              "      <td>-0.031230</td>\n",
              "      <td>-0.006064</td>\n",
              "      <td>0.015571</td>\n",
              "      <td>-0.015571</td>\n",
              "      <td>0.049962</td>\n",
              "      <td>-5.682059e-02</td>\n",
              "      <td>0.011271</td>\n",
              "      <td>-0.001305</td>\n",
              "      <td>-0.004003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_main_plans_taken</th>\n",
              "      <td>-0.005301</td>\n",
              "      <td>-2.623892e-02</td>\n",
              "      <td>-0.019573</td>\n",
              "      <td>0.043363</td>\n",
              "      <td>-0.031548</td>\n",
              "      <td>0.033336</td>\n",
              "      <td>0.017102</td>\n",
              "      <td>0.000989</td>\n",
              "      <td>-0.005704</td>\n",
              "      <td>0.004295</td>\n",
              "      <td>...</td>\n",
              "      <td>0.034454</td>\n",
              "      <td>-0.086729</td>\n",
              "      <td>-0.002302</td>\n",
              "      <td>0.053277</td>\n",
              "      <td>-0.053277</td>\n",
              "      <td>-0.000658</td>\n",
              "      <td>1.380191e-02</td>\n",
              "      <td>0.008432</td>\n",
              "      <td>-0.027605</td>\n",
              "      <td>0.006434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_main_plans_mrp</th>\n",
              "      <td>0.005707</td>\n",
              "      <td>-9.757167e-03</td>\n",
              "      <td>-0.020894</td>\n",
              "      <td>0.081549</td>\n",
              "      <td>-0.023361</td>\n",
              "      <td>0.085510</td>\n",
              "      <td>0.043744</td>\n",
              "      <td>0.044615</td>\n",
              "      <td>-0.005193</td>\n",
              "      <td>-0.009788</td>\n",
              "      <td>...</td>\n",
              "      <td>0.014472</td>\n",
              "      <td>-0.020033</td>\n",
              "      <td>0.010894</td>\n",
              "      <td>0.047527</td>\n",
              "      <td>-0.047527</td>\n",
              "      <td>0.037124</td>\n",
              "      <td>-2.821797e-02</td>\n",
              "      <td>0.022532</td>\n",
              "      <td>-0.010992</td>\n",
              "      <td>-0.021281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_addon_plans_taken</th>\n",
              "      <td>-0.009651</td>\n",
              "      <td>5.777274e-04</td>\n",
              "      <td>-0.014910</td>\n",
              "      <td>-0.024849</td>\n",
              "      <td>-0.022872</td>\n",
              "      <td>-0.021380</td>\n",
              "      <td>-0.028813</td>\n",
              "      <td>-0.032144</td>\n",
              "      <td>-0.023304</td>\n",
              "      <td>0.040646</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.046165</td>\n",
              "      <td>-0.104018</td>\n",
              "      <td>-0.039651</td>\n",
              "      <td>-0.037349</td>\n",
              "      <td>0.037349</td>\n",
              "      <td>0.023314</td>\n",
              "      <td>-3.089356e-02</td>\n",
              "      <td>-0.029416</td>\n",
              "      <td>0.003381</td>\n",
              "      <td>0.033587</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_addon_plans_mrp</th>\n",
              "      <td>0.024814</td>\n",
              "      <td>-2.185133e-02</td>\n",
              "      <td>-0.016434</td>\n",
              "      <td>0.032132</td>\n",
              "      <td>-0.021390</td>\n",
              "      <td>0.043680</td>\n",
              "      <td>0.011268</td>\n",
              "      <td>0.015877</td>\n",
              "      <td>-0.032677</td>\n",
              "      <td>0.020376</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.037087</td>\n",
              "      <td>-0.036351</td>\n",
              "      <td>-0.020329</td>\n",
              "      <td>-0.015574</td>\n",
              "      <td>0.015574</td>\n",
              "      <td>0.053600</td>\n",
              "      <td>-7.352671e-02</td>\n",
              "      <td>-0.000618</td>\n",
              "      <td>0.007597</td>\n",
              "      <td>0.012140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_rchg_offline</th>\n",
              "      <td>-0.010539</td>\n",
              "      <td>-1.790240e-02</td>\n",
              "      <td>-0.024226</td>\n",
              "      <td>0.012651</td>\n",
              "      <td>-0.038227</td>\n",
              "      <td>0.008112</td>\n",
              "      <td>-0.008485</td>\n",
              "      <td>-0.022091</td>\n",
              "      <td>-0.020497</td>\n",
              "      <td>0.031804</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.008673</td>\n",
              "      <td>-0.134247</td>\n",
              "      <td>-0.029708</td>\n",
              "      <td>0.010712</td>\n",
              "      <td>-0.010712</td>\n",
              "      <td>0.016063</td>\n",
              "      <td>-1.226275e-02</td>\n",
              "      <td>-0.014963</td>\n",
              "      <td>-0.016869</td>\n",
              "      <td>0.028294</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_rchg_online</th>\n",
              "      <td>-0.010539</td>\n",
              "      <td>-1.790240e-02</td>\n",
              "      <td>-0.024226</td>\n",
              "      <td>0.012651</td>\n",
              "      <td>-0.038227</td>\n",
              "      <td>0.008112</td>\n",
              "      <td>-0.008485</td>\n",
              "      <td>-0.022091</td>\n",
              "      <td>-0.020497</td>\n",
              "      <td>0.031804</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.008673</td>\n",
              "      <td>-0.134247</td>\n",
              "      <td>-0.029708</td>\n",
              "      <td>0.010712</td>\n",
              "      <td>-0.010712</td>\n",
              "      <td>0.016063</td>\n",
              "      <td>-1.226275e-02</td>\n",
              "      <td>-0.014963</td>\n",
              "      <td>-0.016869</td>\n",
              "      <td>0.028294</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_rchg_on_or_before_expiry</th>\n",
              "      <td>-0.034484</td>\n",
              "      <td>-4.700325e-03</td>\n",
              "      <td>-0.029662</td>\n",
              "      <td>-0.026638</td>\n",
              "      <td>-0.051968</td>\n",
              "      <td>-0.026893</td>\n",
              "      <td>-0.040842</td>\n",
              "      <td>-0.057390</td>\n",
              "      <td>0.001991</td>\n",
              "      <td>0.002929</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.026416</td>\n",
              "      <td>-0.117727</td>\n",
              "      <td>-0.032923</td>\n",
              "      <td>0.046271</td>\n",
              "      <td>-0.046271</td>\n",
              "      <td>-0.032826</td>\n",
              "      <td>-4.840467e-03</td>\n",
              "      <td>0.044017</td>\n",
              "      <td>0.010181</td>\n",
              "      <td>-0.015981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cnt_rchg_after_expiry</th>\n",
              "      <td>0.023885</td>\n",
              "      <td>-1.395202e-02</td>\n",
              "      <td>0.004701</td>\n",
              "      <td>0.040179</td>\n",
              "      <td>0.012645</td>\n",
              "      <td>0.035694</td>\n",
              "      <td>0.032466</td>\n",
              "      <td>0.034995</td>\n",
              "      <td>-0.023436</td>\n",
              "      <td>0.030273</td>\n",
              "      <td>...</td>\n",
              "      <td>0.017671</td>\n",
              "      <td>-0.021152</td>\n",
              "      <td>0.002273</td>\n",
              "      <td>-0.035633</td>\n",
              "      <td>0.035633</td>\n",
              "      <td>0.050008</td>\n",
              "      <td>-7.916483e-03</td>\n",
              "      <td>-0.060184</td>\n",
              "      <td>-0.027932</td>\n",
              "      <td>0.045742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>current_active_plan_mrp</th>\n",
              "      <td>-0.011095</td>\n",
              "      <td>9.726128e-04</td>\n",
              "      <td>-0.010818</td>\n",
              "      <td>0.064075</td>\n",
              "      <td>-0.018400</td>\n",
              "      <td>0.064712</td>\n",
              "      <td>0.038445</td>\n",
              "      <td>0.033236</td>\n",
              "      <td>-0.043027</td>\n",
              "      <td>0.028588</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.379430</td>\n",
              "      <td>0.058261</td>\n",
              "      <td>-0.010374</td>\n",
              "      <td>-0.024496</td>\n",
              "      <td>0.024496</td>\n",
              "      <td>0.033618</td>\n",
              "      <td>-2.846180e-02</td>\n",
              "      <td>0.004590</td>\n",
              "      <td>-0.027091</td>\n",
              "      <td>0.017299</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>current_active_plan_validity</th>\n",
              "      <td>-0.015075</td>\n",
              "      <td>4.399905e-03</td>\n",
              "      <td>-0.005487</td>\n",
              "      <td>0.066068</td>\n",
              "      <td>-0.013586</td>\n",
              "      <td>0.065094</td>\n",
              "      <td>0.043765</td>\n",
              "      <td>0.037031</td>\n",
              "      <td>-0.040261</td>\n",
              "      <td>0.030146</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.375655</td>\n",
              "      <td>0.055297</td>\n",
              "      <td>-0.007135</td>\n",
              "      <td>-0.024727</td>\n",
              "      <td>0.024727</td>\n",
              "      <td>0.034425</td>\n",
              "      <td>-2.817962e-02</td>\n",
              "      <td>0.000522</td>\n",
              "      <td>-0.027790</td>\n",
              "      <td>0.021008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>last_cycle_plan_mrp</th>\n",
              "      <td>0.009111</td>\n",
              "      <td>-1.726746e-02</td>\n",
              "      <td>-0.027422</td>\n",
              "      <td>0.016909</td>\n",
              "      <td>-0.041762</td>\n",
              "      <td>0.016300</td>\n",
              "      <td>-0.007733</td>\n",
              "      <td>-0.018768</td>\n",
              "      <td>-0.023384</td>\n",
              "      <td>0.030197</td>\n",
              "      <td>...</td>\n",
              "      <td>0.002461</td>\n",
              "      <td>-0.132491</td>\n",
              "      <td>-0.029927</td>\n",
              "      <td>-0.007797</td>\n",
              "      <td>0.007797</td>\n",
              "      <td>0.043933</td>\n",
              "      <td>-1.034701e-02</td>\n",
              "      <td>-0.042179</td>\n",
              "      <td>-0.011756</td>\n",
              "      <td>0.019692</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>last_cycle_plan_validity</th>\n",
              "      <td>0.005211</td>\n",
              "      <td>-1.812047e-02</td>\n",
              "      <td>-0.030829</td>\n",
              "      <td>0.017860</td>\n",
              "      <td>-0.045960</td>\n",
              "      <td>0.017148</td>\n",
              "      <td>-0.009525</td>\n",
              "      <td>-0.021224</td>\n",
              "      <td>-0.024345</td>\n",
              "      <td>0.029936</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000413</td>\n",
              "      <td>-0.136420</td>\n",
              "      <td>-0.035575</td>\n",
              "      <td>-0.007152</td>\n",
              "      <td>0.007152</td>\n",
              "      <td>0.044614</td>\n",
              "      <td>-8.752370e-03</td>\n",
              "      <td>-0.042549</td>\n",
              "      <td>-0.011690</td>\n",
              "      <td>0.017667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>avg_days_bw_rchg_and_expiry</th>\n",
              "      <td>-0.033716</td>\n",
              "      <td>4.275533e-02</td>\n",
              "      <td>0.010903</td>\n",
              "      <td>0.034216</td>\n",
              "      <td>0.007045</td>\n",
              "      <td>0.043168</td>\n",
              "      <td>0.032669</td>\n",
              "      <td>0.036293</td>\n",
              "      <td>0.079777</td>\n",
              "      <td>-0.046676</td>\n",
              "      <td>...</td>\n",
              "      <td>0.057372</td>\n",
              "      <td>0.259295</td>\n",
              "      <td>0.150594</td>\n",
              "      <td>0.014424</td>\n",
              "      <td>-0.014424</td>\n",
              "      <td>0.012244</td>\n",
              "      <td>4.593394e-03</td>\n",
              "      <td>-0.028555</td>\n",
              "      <td>0.063314</td>\n",
              "      <td>-0.053536</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>stddev_days_bw_rchg_and_expiry</th>\n",
              "      <td>0.023346</td>\n",
              "      <td>-2.300015e-02</td>\n",
              "      <td>0.030297</td>\n",
              "      <td>0.007986</td>\n",
              "      <td>0.028709</td>\n",
              "      <td>0.012090</td>\n",
              "      <td>0.027821</td>\n",
              "      <td>0.029708</td>\n",
              "      <td>0.027694</td>\n",
              "      <td>-0.015073</td>\n",
              "      <td>...</td>\n",
              "      <td>0.025662</td>\n",
              "      <td>-0.005294</td>\n",
              "      <td>-0.001068</td>\n",
              "      <td>0.035967</td>\n",
              "      <td>-0.035967</td>\n",
              "      <td>-0.008787</td>\n",
              "      <td>8.729603e-03</td>\n",
              "      <td>-0.014728</td>\n",
              "      <td>0.015399</td>\n",
              "      <td>-0.000691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>price_per_day</th>\n",
              "      <td>-0.005425</td>\n",
              "      <td>-3.618395e-02</td>\n",
              "      <td>0.002018</td>\n",
              "      <td>-0.051553</td>\n",
              "      <td>0.005371</td>\n",
              "      <td>-0.047608</td>\n",
              "      <td>-0.035797</td>\n",
              "      <td>-0.030421</td>\n",
              "      <td>-0.017795</td>\n",
              "      <td>0.005620</td>\n",
              "      <td>...</td>\n",
              "      <td>0.409157</td>\n",
              "      <td>-0.084624</td>\n",
              "      <td>-0.022522</td>\n",
              "      <td>0.020379</td>\n",
              "      <td>-0.020379</td>\n",
              "      <td>0.027915</td>\n",
              "      <td>-5.788310e-03</td>\n",
              "      <td>0.035695</td>\n",
              "      <td>-0.011911</td>\n",
              "      <td>-0.046965</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>gb_per_day_quota</th>\n",
              "      <td>-0.000649</td>\n",
              "      <td>-4.037389e-03</td>\n",
              "      <td>-0.019957</td>\n",
              "      <td>0.067294</td>\n",
              "      <td>-0.024900</td>\n",
              "      <td>0.071373</td>\n",
              "      <td>0.034122</td>\n",
              "      <td>0.033291</td>\n",
              "      <td>-0.020823</td>\n",
              "      <td>0.008891</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.508677</td>\n",
              "      <td>0.079132</td>\n",
              "      <td>-0.015206</td>\n",
              "      <td>-0.031512</td>\n",
              "      <td>0.031512</td>\n",
              "      <td>0.013691</td>\n",
              "      <td>-3.122170e-02</td>\n",
              "      <td>0.015005</td>\n",
              "      <td>-0.016503</td>\n",
              "      <td>0.019388</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pcnt_quota_used</th>\n",
              "      <td>-0.028850</td>\n",
              "      <td>-3.030680e-02</td>\n",
              "      <td>-0.003534</td>\n",
              "      <td>-0.017548</td>\n",
              "      <td>-0.007456</td>\n",
              "      <td>-0.026867</td>\n",
              "      <td>-0.015257</td>\n",
              "      <td>-0.024834</td>\n",
              "      <td>0.634894</td>\n",
              "      <td>0.113954</td>\n",
              "      <td>...</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.483431</td>\n",
              "      <td>-0.133075</td>\n",
              "      <td>0.035300</td>\n",
              "      <td>-0.035300</td>\n",
              "      <td>-0.028893</td>\n",
              "      <td>2.768792e-02</td>\n",
              "      <td>-0.002000</td>\n",
              "      <td>-0.009240</td>\n",
              "      <td>0.013283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>recharge_delay</th>\n",
              "      <td>0.182931</td>\n",
              "      <td>5.468647e-02</td>\n",
              "      <td>-0.214768</td>\n",
              "      <td>-0.021893</td>\n",
              "      <td>-0.193109</td>\n",
              "      <td>-0.006295</td>\n",
              "      <td>-0.172120</td>\n",
              "      <td>-0.145702</td>\n",
              "      <td>-0.524368</td>\n",
              "      <td>-0.111315</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.483431</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.522126</td>\n",
              "      <td>-0.027508</td>\n",
              "      <td>0.027508</td>\n",
              "      <td>0.004698</td>\n",
              "      <td>5.635595e-02</td>\n",
              "      <td>-0.018497</td>\n",
              "      <td>0.037058</td>\n",
              "      <td>-0.081688</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>churn</th>\n",
              "      <td>0.112554</td>\n",
              "      <td>2.094316e-02</td>\n",
              "      <td>-0.064641</td>\n",
              "      <td>0.015244</td>\n",
              "      <td>-0.059434</td>\n",
              "      <td>0.009969</td>\n",
              "      <td>-0.036022</td>\n",
              "      <td>-0.036254</td>\n",
              "      <td>-0.193900</td>\n",
              "      <td>-0.041746</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.133075</td>\n",
              "      <td>0.522126</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.010720</td>\n",
              "      <td>0.010720</td>\n",
              "      <td>0.035104</td>\n",
              "      <td>5.613835e-02</td>\n",
              "      <td>-0.035649</td>\n",
              "      <td>-0.006960</td>\n",
              "      <td>-0.050465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ownership_corporate</th>\n",
              "      <td>0.015886</td>\n",
              "      <td>2.322177e-02</td>\n",
              "      <td>0.008855</td>\n",
              "      <td>0.075944</td>\n",
              "      <td>0.009433</td>\n",
              "      <td>0.061281</td>\n",
              "      <td>0.061342</td>\n",
              "      <td>0.051106</td>\n",
              "      <td>0.019971</td>\n",
              "      <td>0.040639</td>\n",
              "      <td>...</td>\n",
              "      <td>0.035300</td>\n",
              "      <td>-0.027508</td>\n",
              "      <td>-0.010720</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>0.031706</td>\n",
              "      <td>-4.467118e-02</td>\n",
              "      <td>0.007175</td>\n",
              "      <td>0.031899</td>\n",
              "      <td>-0.027398</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ownership_individual</th>\n",
              "      <td>-0.015886</td>\n",
              "      <td>-2.322177e-02</td>\n",
              "      <td>-0.008855</td>\n",
              "      <td>-0.075944</td>\n",
              "      <td>-0.009433</td>\n",
              "      <td>-0.061281</td>\n",
              "      <td>-0.061342</td>\n",
              "      <td>-0.051106</td>\n",
              "      <td>-0.019971</td>\n",
              "      <td>-0.040639</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.035300</td>\n",
              "      <td>0.027508</td>\n",
              "      <td>0.010720</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.031706</td>\n",
              "      <td>4.467118e-02</td>\n",
              "      <td>-0.007175</td>\n",
              "      <td>-0.031899</td>\n",
              "      <td>0.027398</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>device_avg_asp_10K_to_20K</th>\n",
              "      <td>-0.055497</td>\n",
              "      <td>4.228459e-02</td>\n",
              "      <td>0.018258</td>\n",
              "      <td>0.033507</td>\n",
              "      <td>0.025624</td>\n",
              "      <td>0.028880</td>\n",
              "      <td>0.037508</td>\n",
              "      <td>0.039566</td>\n",
              "      <td>-0.057422</td>\n",
              "      <td>0.025811</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.028893</td>\n",
              "      <td>0.004698</td>\n",
              "      <td>0.035104</td>\n",
              "      <td>0.031706</td>\n",
              "      <td>-0.031706</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-2.577900e-01</td>\n",
              "      <td>-0.254563</td>\n",
              "      <td>-0.261009</td>\n",
              "      <td>-0.249707</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>device_avg_asp_20K_to_30K</th>\n",
              "      <td>0.050178</td>\n",
              "      <td>-6.626164e-18</td>\n",
              "      <td>-0.023379</td>\n",
              "      <td>0.015879</td>\n",
              "      <td>-0.008817</td>\n",
              "      <td>0.013659</td>\n",
              "      <td>-0.005535</td>\n",
              "      <td>0.003409</td>\n",
              "      <td>0.001731</td>\n",
              "      <td>0.022992</td>\n",
              "      <td>...</td>\n",
              "      <td>0.027688</td>\n",
              "      <td>0.056356</td>\n",
              "      <td>0.056138</td>\n",
              "      <td>-0.044671</td>\n",
              "      <td>0.044671</td>\n",
              "      <td>-0.257790</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>-0.246871</td>\n",
              "      <td>-0.253121</td>\n",
              "      <td>-0.242161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>device_avg_asp_30K_to_50K</th>\n",
              "      <td>-0.033542</td>\n",
              "      <td>-3.110043e-02</td>\n",
              "      <td>-0.021513</td>\n",
              "      <td>-0.045750</td>\n",
              "      <td>-0.023384</td>\n",
              "      <td>-0.034369</td>\n",
              "      <td>-0.048727</td>\n",
              "      <td>-0.041889</td>\n",
              "      <td>-0.023842</td>\n",
              "      <td>-0.055827</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.002000</td>\n",
              "      <td>-0.018497</td>\n",
              "      <td>-0.035649</td>\n",
              "      <td>0.007175</td>\n",
              "      <td>-0.007175</td>\n",
              "      <td>-0.254563</td>\n",
              "      <td>-2.468710e-01</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.249953</td>\n",
              "      <td>-0.239130</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>device_avg_asp_50K_above</th>\n",
              "      <td>0.034080</td>\n",
              "      <td>-1.167942e-02</td>\n",
              "      <td>0.003122</td>\n",
              "      <td>-0.002093</td>\n",
              "      <td>-0.002495</td>\n",
              "      <td>0.007460</td>\n",
              "      <td>0.000759</td>\n",
              "      <td>0.003559</td>\n",
              "      <td>0.016038</td>\n",
              "      <td>0.006779</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.009240</td>\n",
              "      <td>0.037058</td>\n",
              "      <td>-0.006960</td>\n",
              "      <td>0.031899</td>\n",
              "      <td>-0.031899</td>\n",
              "      <td>-0.261009</td>\n",
              "      <td>-2.531212e-01</td>\n",
              "      <td>-0.249953</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.245184</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>device_avg_asp_less_10K</th>\n",
              "      <td>0.005392</td>\n",
              "      <td>-4.346749e-04</td>\n",
              "      <td>0.023444</td>\n",
              "      <td>-0.002535</td>\n",
              "      <td>0.008611</td>\n",
              "      <td>-0.016797</td>\n",
              "      <td>0.015228</td>\n",
              "      <td>-0.005824</td>\n",
              "      <td>0.065505</td>\n",
              "      <td>-0.000713</td>\n",
              "      <td>...</td>\n",
              "      <td>0.013283</td>\n",
              "      <td>-0.081688</td>\n",
              "      <td>-0.050465</td>\n",
              "      <td>-0.027398</td>\n",
              "      <td>0.027398</td>\n",
              "      <td>-0.249707</td>\n",
              "      <td>-2.421611e-01</td>\n",
              "      <td>-0.239130</td>\n",
              "      <td>-0.245184</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>52 rows × 52 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4da9f79b-2edf-4ee1-8f3d-1b413a27b34b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "      fill: #D2E3FC;\n",
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              "        buttonEl.style.display =\n",
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              "          const element = document.querySelector('#df-4da9f79b-2edf-4ee1-8f3d-1b413a27b34b');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "X68dm0q1EPBm",
        "outputId": "8ec1d7f8-dd35-4555-c549-c89785941a8e"
      },
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "activation_plan_code                   int64\n",
              "mnp_flag                               int64\n",
              "calls_incoming_cnt                   float64\n",
              "calls_outgoing_cnt                   float64\n",
              "calls_incoming_duration              float64\n",
              "calls_outgoing_duration              float64\n",
              "total_call_count                     float64\n",
              "total_sum_duration                   float64\n",
              "tot_usage_mb                         float64\n",
              "upload_usage_mb                      float64\n",
              "download_usage_mb                    float64\n",
              "days_since_latch                       int64\n",
              "cnt_open_qrc                           int64\n",
              "avg_days_to_close                    float64\n",
              "cnt_call_drops                       float64\n",
              "pcnt_dropped_calls                   float64\n",
              "rsrp_voice_pcnt_poor_duration        float64\n",
              "rsrp_data_pcnt_poor_duration         float64\n",
              "mean_cqi_voice_pcnt_poor_duration    float64\n",
              "sinr_voice_pcnt_poor_duration        float64\n",
              "sinr_data_pcnt_poor_duration         float64\n",
              "age_on_network                         int64\n",
              "cnt_connections                        int64\n",
              "current_plan_code                      int64\n",
              "cnt_recharges_made                     int64\n",
              "total_payment_made                   float64\n",
              "cnt_main_plans_taken                   int64\n",
              "total_main_plans_mrp                 float64\n",
              "cnt_addon_plans_taken                  int64\n",
              "total_addon_plans_mrp                float64\n",
              "cnt_rchg_offline                       int64\n",
              "cnt_rchg_online                        int64\n",
              "cnt_rchg_on_or_before_expiry         float64\n",
              "cnt_rchg_after_expiry                float64\n",
              "current_active_plan_mrp                int64\n",
              "current_active_plan_validity           int64\n",
              "last_cycle_plan_mrp                    int64\n",
              "last_cycle_plan_validity               int64\n",
              "avg_days_bw_rchg_and_expiry          float64\n",
              "stddev_days_bw_rchg_and_expiry       float64\n",
              "price_per_day                        float64\n",
              "gb_per_day_quota                     float64\n",
              "pcnt_quota_used                      float64\n",
              "recharge_delay                       float64\n",
              "churn                                  int64\n",
              "ownership_corporate                    uint8\n",
              "ownership_individual                   uint8\n",
              "device_avg_asp_10K_to_20K              uint8\n",
              "device_avg_asp_20K_to_30K              uint8\n",
              "device_avg_asp_30K_to_50K              uint8\n",
              "device_avg_asp_50K_above               uint8\n",
              "device_avg_asp_less_10K                uint8\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# plotting a correlation matrix using plotly to make it more readable\n",
        "px.imshow(data.corr(), width=900,height=900)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 917
        },
        "id": "-aeKJ5SucQyc",
        "outputId": "1dd449f0-d223-4588-b092-01ee6b9b3b66"
      },
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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      "cell_type": "markdown",
      "source": [
        "## Performing Lasso Regression to Identify good predictors of recharge delay"
      ],
      "metadata": {
        "id": "ejpGIwEQc0Wd"
      }
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      "cell_type": "code",
      "source": [
        "#  I want to use lasso regression to predict recharge delay and see the features that are important for its prediction. I'll keep only those features\n",
        "#  I will use recharge delay to form a churn column in the future\n",
        "\n",
        "from sklearn.linear_model import Lasso\n",
        "from sklearn.linear_model import Lasso\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import mean_squared_error, r2_score\n",
        "\n",
        "\n",
        "# specify the dependent variable (i.e., the target variable)\n",
        "y = data['recharge_delay']\n",
        "\n",
        "# specify the independent variables (i.e., the features)\n",
        "X = data.drop('recharge_delay', axis=1)\n",
        "\n",
        "# split the data into training and test sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# initialize the Lasso model with a fixed regularization strength\n",
        "lasso = Lasso(alpha=0.99)\n",
        "\n",
        "# fit the model on the training data\n",
        "lasso.fit(X_train, y_train)\n",
        "\n",
        "# make predictions on the test data\n",
        "y_pred = lasso.predict(X_test)\n",
        "\n",
        "# evaluate the model using mean squared error and R-squared\n",
        "mse = mean_squared_error(y_test, y_pred)\n",
        "r2 = r2_score(y_test, y_pred)\n",
        "\n",
        "print(\"Mean Squared Error: \", mse)\n",
        "print(\"R-squared: \", r2)\n",
        "print(\"Lasso_coefficient:\", lasso.coef_)\n"
      ],
      "metadata": {
        "id": "Zh1uWII6UkOI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "8e395ea0-5dbd-4360-cb7e-82a6acb270f4"
      },
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mean Squared Error:  30.506788758415095\n",
            "R-squared:  0.6544641260373295\n",
            "Lasso_coefficient: [ 4.58924451e-01 -0.00000000e+00 -3.48965146e-02  0.00000000e+00\n",
            "  0.00000000e+00  0.00000000e+00 -1.39880185e-02  6.66592822e-03\n",
            " -3.46144177e-04  8.15172356e-05 -1.41367882e-05  0.00000000e+00\n",
            "  1.92719018e-01  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
            "  0.00000000e+00  4.35436564e-02  6.36642996e-02  0.00000000e+00\n",
            "  0.00000000e+00 -1.60376630e-03 -8.29726182e-01  0.00000000e+00\n",
            " -0.00000000e+00  4.19308172e-06 -5.05576171e-03  6.31024870e-05\n",
            "  0.00000000e+00 -5.41638297e-05 -0.00000000e+00 -0.00000000e+00\n",
            " -2.63574431e-02  0.00000000e+00 -1.80557033e-03  4.51844506e-03\n",
            "  2.63569431e-03 -1.44523252e-02  8.68102172e-01  0.00000000e+00\n",
            " -0.00000000e+00 -0.00000000e+00 -7.58265588e-02  6.76870220e-01\n",
            " -0.00000000e+00  0.00000000e+00 -0.00000000e+00  0.00000000e+00\n",
            " -0.00000000e+00  0.00000000e+00 -0.00000000e+00]\n"
          ]
        }
      ]
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      "cell_type": "code",
      "source": [
        "# Extracting the feature names\n",
        "feature_names = X.columns\n",
        "\n",
        "# Get the non-zero coefficients\n",
        "coef = lasso.coef_\n",
        "non_zero_coef = []\n",
        "for i in range(len(coef)):\n",
        "    if coef[i] != 0:\n",
        "        non_zero_coef.append(feature_names[i])\n",
        "\n",
        "# Print the non-zero coefficients\n",
        "print(non_zero_coef)"
      ],
      "metadata": {
        "id": "2SDqcnWSmjmx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "27e0c7ca-38aa-400f-96eb-41b4471df115"
      },
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['activation_plan_code', 'calls_incoming_cnt', 'total_call_count', 'total_sum_duration', 'tot_usage_mb', 'upload_usage_mb', 'download_usage_mb', 'cnt_open_qrc', 'rsrp_data_pcnt_poor_duration', 'mean_cqi_voice_pcnt_poor_duration', 'age_on_network', 'cnt_connections', 'total_payment_made', 'cnt_main_plans_taken', 'total_main_plans_mrp', 'total_addon_plans_mrp', 'cnt_rchg_on_or_before_expiry', 'current_active_plan_mrp', 'current_active_plan_validity', 'last_cycle_plan_mrp', 'last_cycle_plan_validity', 'avg_days_bw_rchg_and_expiry', 'pcnt_quota_used', 'churn']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(non_zero_coef)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "vp1KPad8KwOe",
        "outputId": "e9afeaf5-c4f0-4b21-d364-b1b3edd09882"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "24"
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "*The above Lasso may not explain the features well since there may be non-linear relationship between the features and recharge delay. I will explore other models for feature selection.*"
      ],
      "metadata": {
        "id": "J5_bUOqpuA0H"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Finding the correlation with all values to recharge delay and displaying the top 10 variables. "
      ],
      "metadata": {
        "id": "oTRce4V8idR_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate the correlation between all variables and 'recharge_delay'\n",
        "corr = data.corr()['recharge_delay'].sort_values()\n",
        "\n",
        "# Select the 10 best features based on the correlation values\n",
        "top_10_features = corr.dropna()[-12:-2] # it should be [-10:] but it selects churn and recharge delay]\n",
        "\n",
        "# Print the top 10 features and their correlation values\n",
        "print(top_10_features)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "92dTtzuNiTJH",
        "outputId": "52c94872-63d8-4c22-9c11-ef42118b24a2"
      },
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "current_active_plan_mrp              0.058261\n",
            "pcnt_dropped_calls                   0.068873\n",
            "current_plan_code                    0.070604\n",
            "gb_per_day_quota                     0.079132\n",
            "cnt_open_qrc                         0.161511\n",
            "rsrp_voice_pcnt_poor_duration        0.181885\n",
            "activation_plan_code                 0.182931\n",
            "rsrp_data_pcnt_poor_duration         0.189493\n",
            "mean_cqi_voice_pcnt_poor_duration    0.245270\n",
            "avg_days_bw_rchg_and_expiry          0.259295\n",
            "Name: recharge_delay, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Normalizing the continuous values\n",
        "# Create an instance of the scaler\n",
        "scaler = MinMaxScaler()\n",
        "\n",
        "# Select only the continuous features from the DataFrame\n",
        "continuous_features = data.select_dtypes(include=['float64','int64'])\n",
        "\n",
        "# Scale the continuous features\n",
        "data[continuous_features.columns] = scaler.fit_transform(continuous_features)"
      ],
      "metadata": {
        "id": "TPLwD0izrbBS"
      },
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Showing the balance existing in majority and minority classes of churn**"
      ],
      "metadata": {
        "id": "ay5ZjuH92HHx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Get the counts of the binary classes in the target variable\n",
        "counts = data['churn'].value_counts()\n",
        "\n",
        "# Create a bar plot\n",
        "sns.barplot(x=counts.index, y=counts.values)\n",
        "\n",
        "# Label the axes\n",
        "plt.xlabel('Class')\n",
        "plt.ylabel('Count')\n",
        "\n",
        "# Show the plot\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "c3BuKaln2aH5",
        "outputId": "ba12836b-1d44-46f4-bd2e-ce70be0fe9f5"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Applying upsampling of the minority class\n",
        "from imblearn.over_sampling import SMOTE\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "# Split data into features (X) and target (y)\n",
        "X = data.drop('churn', axis=1)\n",
        "y = data['churn']\n",
        "\n",
        "# Split data into train and test sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Apply SMOTE to the training data\n",
        "sm = SMOTE(random_state=42)\n",
        "X_train_resampled, y_train_resampled = sm.fit_resample(X_train, y_train)"
      ],
      "metadata": {
        "id": "ppoI8TbwKnh1"
      },
      "execution_count": 82,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Applying PCA after oversampling to reduce noise"
      ],
      "metadata": {
        "id": "hvYme5bBLQxf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.decomposition import PCA\n",
        "\n",
        "# Initialize PCA object\n",
        "pca = PCA(n_components=0.95)\n",
        "\n",
        "# Fit and transform data\n",
        "X_reduced = pca.fit_transform(X)"
      ],
      "metadata": {
        "id": "A-jpsewdLX2N"
      },
      "execution_count": 83,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Models**\n",
        "##Logistic Regression"
      ],
      "metadata": {
        "id": "rCtuwpvBpx1y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import confusion_matrix, classification_report\n",
        "\n",
        "# split the data into training and test sets\n",
        "X = data.drop('churn', axis=1)\n",
        "y = data['churn']\n",
        "# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# initialize the model\n",
        "logistic_regression = LogisticRegression()\n",
        "\n",
        "# fit the model to the training data\n",
        "logistic_regression.fit(X_train, y_train)\n",
        "\n",
        "# make predictions on the test set\n",
        "y_pred = logistic_regression.predict(X_test)\n",
        "\n",
        "# Get the confusion matrix and classification report\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "\n",
        "# Print the evaluation metrics\n",
        "print('Confusion Matrix:')\n",
        "print(cm)\n",
        "print('Classification Report:')\n",
        "print(cr)\n",
        "auc = roc_auc_score(y_test, y_pred)\n",
        "print(\"AUC-ROC:\", auc)\n",
        "plt.plot(fpr, tpr)\n",
        "plt.title('ROC Curve')\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 538
        },
        "id": "eNwHJP8frm_-",
        "outputId": "2f4108b9-bd29-4cba-b21f-23bb4180e10a"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confusion Matrix:\n",
            "[[145   6]\n",
            " [ 33  16]]\n",
            "Classification Report:\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.81      0.96      0.88       151\n",
            "         1.0       0.73      0.33      0.45        49\n",
            "\n",
            "    accuracy                           0.81       200\n",
            "   macro avg       0.77      0.64      0.67       200\n",
            "weighted avg       0.79      0.81      0.78       200\n",
            "\n",
            "AUC-ROC: 0.6433977564535749\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Adaboost Algorithmn"
      ],
      "metadata": {
        "id": "QwaeH_61vnm1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import AdaBoostClassifier\n",
        "from sklearn.metrics import confusion_matrix, classification_report\n",
        "from sklearn.metrics import roc_auc_score\n",
        "\n",
        "X = data.drop('churn', axis=1)\n",
        "y = data['churn']\n",
        "\n",
        "# Split the data into training and testing sets\n",
        "from sklearn.model_selection import train_test_split\n",
        "# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Create an AdaBoost classifier\n",
        "ada = AdaBoostClassifier()\n",
        "\n",
        "# Train the classifier on the training data\n",
        "ada.fit(X_train, y_train)\n",
        "\n",
        "# Make predictions on the test data\n",
        "y_pred = ada.predict(X_test)\n",
        "\n",
        "# Get the confusion matrix and classification report\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "\n",
        "# Print the evaluation metrics\n",
        "print('Confusion Matrix:')\n",
        "print(cm)\n",
        "print('Classification Report:')\n",
        "print(cr)\n",
        "auc = roc_auc_score(y_test, y_pred)\n",
        "print(\"AUC-ROC:\", auc)\n",
        "\n",
        "plt.plot(fpr, tpr)\n",
        "plt.title('ROC Curve')\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "dOSYPHxAup5m",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 538
        },
        "outputId": "404dbf1f-c9b5-470e-eaaf-8a9365332a90"
      },
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confusion Matrix:\n",
            "[[145   6]\n",
            " [ 19  30]]\n",
            "Classification Report:\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.88      0.96      0.92       151\n",
            "         1.0       0.83      0.61      0.71        49\n",
            "\n",
            "    accuracy                           0.88       200\n",
            "   macro avg       0.86      0.79      0.81       200\n",
            "weighted avg       0.87      0.88      0.87       200\n",
            "\n",
            "AUC-ROC: 0.7862548993107177\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "JIS7wGoYVI2V"
      },
      "execution_count": 85,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Random Forest"
      ],
      "metadata": {
        "id": "st1LJ6_lxXay"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import roc_auc_score\n",
        "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
        "\n",
        "# Split data into training and test sets\n",
        "X = data.drop('churn', axis=1)\n",
        "y = data['churn']\n",
        "\n",
        "\n",
        "# Build the model\n",
        "clf = RandomForestClassifier(random_state=42)\n",
        "clf.fit(X_train, y_train)\n",
        "\n",
        "# Make predictions on the test set\n",
        "y_pred = clf.predict(X_test)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "\n",
        "# Print the evaluation metrics\n",
        "print('Confusion Matrix:')\n",
        "print(cm)\n",
        "print('Classification Report:')\n",
        "print(cr)\n",
        "auc = roc_auc_score(y_test, y_pred)\n",
        "print(\"AUC-ROC:\", auc)\n",
        "\n",
        "fpr, tpr, thresholds = roc_curve(y_test, y_pred)\n",
        "\n",
        "plt.plot(fpr, tpr)\n",
        "plt.title('ROC Curve')\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.show()\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "taItIBpmWa4I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 538
        },
        "outputId": "e3c0d37a-db9e-4fb4-b289-f6e02850a789"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confusion Matrix:\n",
            "[[147   4]\n",
            " [ 16  33]]\n",
            "Classification Report:\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.90      0.97      0.94       151\n",
            "         1.0       0.89      0.67      0.77        49\n",
            "\n",
            "    accuracy                           0.90       200\n",
            "   macro avg       0.90      0.82      0.85       200\n",
            "weighted avg       0.90      0.90      0.89       200\n",
            "\n",
            "AUC-ROC: 0.8234896607649683\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Decision Tree"
      ],
      "metadata": {
        "id": "rUYT4PrRMr8n"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import roc_auc_score\n",
        "# Split data into features (X) and target (y)\n",
        "X = data.drop('churn', axis=1)\n",
        "y = data['churn']\n",
        "\n",
        "# Split data into train and test sets\n",
        "# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Initialize the decision tree classifier\n",
        "clf = DecisionTreeClassifier(random_state=42)\n",
        "\n",
        "# Train the classifier on the training data\n",
        "clf.fit(X_train, y_train)\n",
        "\n",
        "# Make predictions on the test set\n",
        "y_pred = clf.predict(X_test)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "\n",
        "# Print the evaluation metrics\n",
        "print('Confusion Matrix:')\n",
        "print(cm)\n",
        "print('Classification Report:')\n",
        "print(cr)\n",
        "auc = roc_auc_score(y_test, y_pred)\n",
        "print(\"AUC-ROC:\", auc)\n",
        "fpr, tpr, thresholds = roc_curve(y_test, y_pred)\n",
        "\n",
        "plt.plot(fpr, tpr)\n",
        "plt.title('ROC Curve')\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "q6ptHV2r09e-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 538
        },
        "outputId": "c4877325-23c8-4fd3-f221-93a53a246837"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confusion Matrix:\n",
            "[[134  17]\n",
            " [ 22  27]]\n",
            "Classification Report:\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.86      0.89      0.87       151\n",
            "         1.0       0.61      0.55      0.58        49\n",
            "\n",
            "    accuracy                           0.81       200\n",
            "   macro avg       0.74      0.72      0.73       200\n",
            "weighted avg       0.80      0.81      0.80       200\n",
            "\n",
            "AUC-ROC: 0.7192188133531557\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Neural Network"
      ],
      "metadata": {
        "id": "wGn4JlJBNyvk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.neural_network import MLPClassifier\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import roc_auc_score\n",
        "# Split data into features (X) and target (y)\n",
        "X = data.drop('churn', axis=1)\n",
        "y = data['churn']\n",
        "\n",
        "# Split data into train and test sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Initialize the neural network\n",
        "clf = MLPClassifier(hidden_layer_sizes=(100,), max_iter=1000, alpha=1e-4,\n",
        "                    solver='sgd', verbose=10, tol=1e-4, random_state=1,\n",
        "                    learning_rate_init=.1)\n",
        "\n",
        "# Train the neural network on the training data\n",
        "clf.fit(X_train, y_train)\n",
        "\n",
        "y_pred = clf.predict(X_test)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "\n",
        "# Print the evaluation metrics\n",
        "print('Confusion Matrix:')\n",
        "print(cm)\n",
        "print('Classification Report:')\n",
        "print(cr)\n",
        "auc = roc_auc_score(y_test, y_pred)\n",
        "print(\"AUC-ROC:\", auc)\n",
        "\n",
        "fpr, tpr, thresholds = roc_curve(y_test, y_pred)\n",
        "\n",
        "plt.plot(fpr, tpr)\n",
        "plt.title('ROC Curve')\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "YUhUI3mN40gw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 8818
        },
        "outputId": "833e5d27-39b8-4f66-b393-00835c367a6a"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Iteration 1, loss = 0.61099110\n",
            "Iteration 2, loss = 0.58010085\n",
            "Iteration 3, loss = 0.55250785\n",
            "Iteration 4, loss = 0.53860269\n",
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            "Iteration 10, loss = 0.47328213\n",
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            "Iteration 422, loss = 0.01202344\n",
            "Iteration 423, loss = 0.01194301\n",
            "Iteration 424, loss = 0.01176232\n",
            "Iteration 425, loss = 0.01172990\n",
            "Iteration 426, loss = 0.01166660\n",
            "Iteration 427, loss = 0.01157088\n",
            "Iteration 428, loss = 0.01208671\n",
            "Iteration 429, loss = 0.01165418\n",
            "Iteration 430, loss = 0.01156793\n",
            "Iteration 431, loss = 0.01155988\n",
            "Iteration 432, loss = 0.01151690\n",
            "Iteration 433, loss = 0.01138105\n",
            "Iteration 434, loss = 0.01137746\n",
            "Iteration 435, loss = 0.01141792\n",
            "Iteration 436, loss = 0.01121485\n",
            "Iteration 437, loss = 0.01110871\n",
            "Iteration 438, loss = 0.01122401\n",
            "Iteration 439, loss = 0.01098623\n",
            "Iteration 440, loss = 0.01104653\n",
            "Iteration 441, loss = 0.01099673\n",
            "Iteration 442, loss = 0.01085891\n",
            "Iteration 443, loss = 0.01083179\n",
            "Iteration 444, loss = 0.01076585\n",
            "Iteration 445, loss = 0.01076017\n",
            "Iteration 446, loss = 0.01071101\n",
            "Iteration 447, loss = 0.01062765\n",
            "Iteration 448, loss = 0.01063810\n",
            "Iteration 449, loss = 0.01115260\n",
            "Iteration 450, loss = 0.01085262\n",
            "Iteration 451, loss = 0.01052024\n",
            "Iteration 452, loss = 0.01078626\n",
            "Iteration 453, loss = 0.01041547\n",
            "Iteration 454, loss = 0.01069137\n",
            "Iteration 455, loss = 0.01036015\n",
            "Iteration 456, loss = 0.01026186\n",
            "Iteration 457, loss = 0.01026811\n",
            "Iteration 458, loss = 0.01042848\n",
            "Iteration 459, loss = 0.01028172\n",
            "Iteration 460, loss = 0.01004404\n",
            "Iteration 461, loss = 0.01017535\n",
            "Iteration 462, loss = 0.00996122\n",
            "Iteration 463, loss = 0.01001381\n",
            "Iteration 464, loss = 0.01000527\n",
            "Iteration 465, loss = 0.00982673\n",
            "Iteration 466, loss = 0.00984721\n",
            "Iteration 467, loss = 0.00977793\n",
            "Iteration 468, loss = 0.00987653\n",
            "Iteration 469, loss = 0.00967838\n",
            "Iteration 470, loss = 0.00966865\n",
            "Iteration 471, loss = 0.00960188\n",
            "Iteration 472, loss = 0.00961552\n",
            "Iteration 473, loss = 0.00958651\n",
            "Iteration 474, loss = 0.00950788\n",
            "Iteration 475, loss = 0.00946383\n",
            "Iteration 476, loss = 0.00946746\n",
            "Training loss did not improve more than tol=0.000100 for 10 consecutive epochs. Stopping.\n",
            "Confusion Matrix:\n",
            "[[133  18]\n",
            " [ 27  22]]\n",
            "Classification Report:\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.83      0.88      0.86       151\n",
            "         1.0       0.55      0.45      0.49        49\n",
            "\n",
            "    accuracy                           0.78       200\n",
            "   macro avg       0.69      0.66      0.67       200\n",
            "weighted avg       0.76      0.78      0.77       200\n",
            "\n",
            "AUC-ROC: 0.6648871469117449\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "keAUMK-OQqB7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Naive Bayes Algorithm"
      ],
      "metadata": {
        "id": "xkAIohQlPafb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.naive_bayes import GaussianNB\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "# Split data into features (X) and target (y)\n",
        "X = data.drop('churn', axis=1)\n",
        "y = data['churn']\n",
        "\n",
        "# Split data into train and test sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Initialize the Gaussian Naive Bayes classifier\n",
        "clf = GaussianNB()\n",
        "\n",
        "# Train the classifier on the training data\n",
        "clf.fit(X_train, y_train)\n",
        "\n",
        "y_pred = clf.predict(X_test)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "\n",
        "# Print the evaluation metrics\n",
        "print('Confusion Matrix:')\n",
        "print(cm)\n",
        "print('Classification Report:')\n",
        "print(cr)\n",
        "\n",
        "auc = roc_auc_score(y_test, y_pred)\n",
        "print(\"AUC-ROC:\", auc)\n",
        "\n",
        "fpr, tpr, thresholds = roc_curve(y_test, y_pred)\n",
        "\n",
        "plt.plot(fpr, tpr)\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "IsHFnqB-tyXM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "outputId": "66081511-5cb2-4bb7-b755-b9239a37d291"
      },
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confusion Matrix:\n",
            "[[97 54]\n",
            " [18 31]]\n",
            "Classification Report:\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.84      0.64      0.73       151\n",
            "         1.0       0.36      0.63      0.46        49\n",
            "\n",
            "    accuracy                           0.64       200\n",
            "   macro avg       0.60      0.64      0.60       200\n",
            "weighted avg       0.73      0.64      0.66       200\n",
            "\n",
            "AUC-ROC: 0.6375185835923773\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "zJ9_PLMIPioU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Summary\n",
        "The random forest model gives the best the best AUC-ROC value. This metric is well preferred because of the imbalance that still exist in the two classes of churn[0 and 1] even after sampling of the minority class"
      ],
      "metadata": {
        "id": "R5lNBFSqP7iu"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Gu9kjCmTQCUp"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}