{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "xvQK94SA0GW9"
      },
      "outputs": [],
      "source": [
        "import numpy as np \n",
        "import pandas as pd\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.model_selection import train_test_split\n",
        "import matplotlib.pyplot as plt \n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "id": "pUKlXCoA2hKG",
        "outputId": "f2e2a9bc-ba4d-4eaf-a321-9359e7187fc4"
      },
      "outputs": [
        {
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              "      <th></th>\n",
              "      <th>Customer ID</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Age</th>\n",
              "      <th>Married</th>\n",
              "      <th>Number of Dependents</th>\n",
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              "      <th>Latitude</th>\n",
              "      <th>Longitude</th>\n",
              "      <th>Number of Referrals</th>\n",
              "      <th>...</th>\n",
              "      <th>Payment Method</th>\n",
              "      <th>Monthly Charge</th>\n",
              "      <th>Total Charges</th>\n",
              "      <th>Total Refunds</th>\n",
              "      <th>Total Extra Data Charges</th>\n",
              "      <th>Total Long Distance Charges</th>\n",
              "      <th>Total Revenue</th>\n",
              "      <th>Customer Status</th>\n",
              "      <th>Churn Category</th>\n",
              "      <th>Churn Reason</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0002-ORFBO</td>\n",
              "      <td>Female</td>\n",
              "      <td>37</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Frazier Park</td>\n",
              "      <td>93225</td>\n",
              "      <td>34.827662</td>\n",
              "      <td>-118.999073</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>Credit Card</td>\n",
              "      <td>65.6</td>\n",
              "      <td>593.30</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>381.51</td>\n",
              "      <td>974.81</td>\n",
              "      <td>Stayed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0003-MKNFE</td>\n",
              "      <td>Male</td>\n",
              "      <td>46</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Glendale</td>\n",
              "      <td>91206</td>\n",
              "      <td>34.162515</td>\n",
              "      <td>-118.203869</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>Credit Card</td>\n",
              "      <td>-4.0</td>\n",
              "      <td>542.40</td>\n",
              "      <td>38.33</td>\n",
              "      <td>10</td>\n",
              "      <td>96.21</td>\n",
              "      <td>610.28</td>\n",
              "      <td>Stayed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0004-TLHLJ</td>\n",
              "      <td>Male</td>\n",
              "      <td>50</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Costa Mesa</td>\n",
              "      <td>92627</td>\n",
              "      <td>33.645672</td>\n",
              "      <td>-117.922613</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>Bank Withdrawal</td>\n",
              "      <td>73.9</td>\n",
              "      <td>280.85</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>134.60</td>\n",
              "      <td>415.45</td>\n",
              "      <td>Churned</td>\n",
              "      <td>Competitor</td>\n",
              "      <td>Competitor had better devices</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0011-IGKFF</td>\n",
              "      <td>Male</td>\n",
              "      <td>78</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Martinez</td>\n",
              "      <td>94553</td>\n",
              "      <td>38.014457</td>\n",
              "      <td>-122.115432</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>Bank Withdrawal</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1237.85</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>361.66</td>\n",
              "      <td>1599.51</td>\n",
              "      <td>Churned</td>\n",
              "      <td>Dissatisfaction</td>\n",
              "      <td>Product dissatisfaction</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0013-EXCHZ</td>\n",
              "      <td>Female</td>\n",
              "      <td>75</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Camarillo</td>\n",
              "      <td>93010</td>\n",
              "      <td>34.227846</td>\n",
              "      <td>-119.079903</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>Credit Card</td>\n",
              "      <td>83.9</td>\n",
              "      <td>267.40</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>22.14</td>\n",
              "      <td>289.54</td>\n",
              "      <td>Churned</td>\n",
              "      <td>Dissatisfaction</td>\n",
              "      <td>Network reliability</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 38 columns</p>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            ],
            "text/plain": [
              "  Customer ID  Gender  Age Married  Number of Dependents          City  \\\n",
              "0  0002-ORFBO  Female   37     Yes                     0  Frazier Park   \n",
              "1  0003-MKNFE    Male   46      No                     0      Glendale   \n",
              "2  0004-TLHLJ    Male   50      No                     0    Costa Mesa   \n",
              "3  0011-IGKFF    Male   78     Yes                     0      Martinez   \n",
              "4  0013-EXCHZ  Female   75     Yes                     0     Camarillo   \n",
              "\n",
              "   Zip Code   Latitude   Longitude  Number of Referrals  ...   Payment Method  \\\n",
              "0     93225  34.827662 -118.999073                    2  ...      Credit Card   \n",
              "1     91206  34.162515 -118.203869                    0  ...      Credit Card   \n",
              "2     92627  33.645672 -117.922613                    0  ...  Bank Withdrawal   \n",
              "3     94553  38.014457 -122.115432                    1  ...  Bank Withdrawal   \n",
              "4     93010  34.227846 -119.079903                    3  ...      Credit Card   \n",
              "\n",
              "  Monthly Charge Total Charges  Total Refunds Total Extra Data Charges  \\\n",
              "0           65.6        593.30           0.00                        0   \n",
              "1           -4.0        542.40          38.33                       10   \n",
              "2           73.9        280.85           0.00                        0   \n",
              "3           98.0       1237.85           0.00                        0   \n",
              "4           83.9        267.40           0.00                        0   \n",
              "\n",
              "  Total Long Distance Charges Total Revenue  Customer Status   Churn Category  \\\n",
              "0                      381.51        974.81           Stayed              NaN   \n",
              "1                       96.21        610.28           Stayed              NaN   \n",
              "2                      134.60        415.45          Churned       Competitor   \n",
              "3                      361.66       1599.51          Churned  Dissatisfaction   \n",
              "4                       22.14        289.54          Churned  Dissatisfaction   \n",
              "\n",
              "                    Churn Reason  \n",
              "0                            NaN  \n",
              "1                            NaN  \n",
              "2  Competitor had better devices  \n",
              "3        Product dissatisfaction  \n",
              "4            Network reliability  \n",
              "\n",
              "[5 rows x 38 columns]"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df = pd.read_csv('telecom_customer_churn.csv')\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9HNJtFhU2s7c",
        "outputId": "11c70966-a62e-41f6-b5d3-8326f78c88d4"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Los Angeles         293\n",
              "San Diego           285\n",
              "San Jose            112\n",
              "Sacramento          108\n",
              "San Francisco       104\n",
              "                   ... \n",
              "Johannesburg          2\n",
              "South Lake Tahoe      2\n",
              "Jacumba               2\n",
              "Holtville             2\n",
              "Eldridge              2\n",
              "Name: City, Length: 1106, dtype: int64"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df['City'].value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HxitAQaO20_h",
        "outputId": "12959a89-1da6-433b-8b9f-4c9847113d68"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Index(['Customer ID', 'Gender', 'Age', 'Married', 'Number of Dependents',\n",
              "       'City', 'Zip Code', 'Latitude', 'Longitude', 'Number of Referrals',\n",
              "       'Tenure in Months', 'Offer', 'Phone Service',\n",
              "       'Avg Monthly Long Distance Charges', 'Multiple Lines',\n",
              "       'Internet Service', 'Internet Type', 'Avg Monthly GB Download',\n",
              "       'Online Security', 'Online Backup', 'Device Protection Plan',\n",
              "       'Premium Tech Support', 'Streaming TV', 'Streaming Movies',\n",
              "       'Streaming Music', 'Unlimited Data', 'Contract', 'Paperless Billing',\n",
              "       'Payment Method', 'Monthly Charge', 'Total Charges', 'Total Refunds',\n",
              "       'Total Extra Data Charges', 'Total Long Distance Charges',\n",
              "       'Total Revenue', 'Customer Status', 'Churn Category', 'Churn Reason'],\n",
              "      dtype='object')"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df = df.replace(['Female','Male'],[0,1])\n",
        "\n",
        "\n",
        "df.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "tP3uM6u73Zbi",
        "outputId": "e9199883-90ab-4cb0-f13c-adc699fe6818"
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        {
          "data": {
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",
            "text/plain": [
              "<Figure size 1152x1728 with 38 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig = plt.figure(figsize=(16,24))\n",
        "for i in range(len(df.columns)):\n",
        "    clumn = df.columns[i]\n",
        "    sub = fig.add_subplot(4,10,i+1)\n",
        "    chart = sns.countplot(data=df,x=clumn,hue='Customer Status')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "id": "qfBXNc_A3otF",
        "outputId": "30578baa-dd59-468b-a84f-5bd673099a62"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-74f1925e-b4d6-4892-b9cb-7ca707cea01f\">\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>Age</th>\n",
              "      <th>Married</th>\n",
              "      <th>Number of Dependents</th>\n",
              "      <th>Number of Referrals</th>\n",
              "      <th>Tenure in Months</th>\n",
              "      <th>Phone Service</th>\n",
              "      <th>Multiple Lines</th>\n",
              "      <th>Internet Service</th>\n",
              "      <th>Online Security</th>\n",
              "      <th>Online Backup</th>\n",
              "      <th>...</th>\n",
              "      <th>Streaming TV</th>\n",
              "      <th>Streaming Movies</th>\n",
              "      <th>Streaming Music</th>\n",
              "      <th>Unlimited Data</th>\n",
              "      <th>Contract</th>\n",
              "      <th>Paperless Billing</th>\n",
              "      <th>Payment Method</th>\n",
              "      <th>Monthly Charge</th>\n",
              "      <th>Total Charges</th>\n",
              "      <th>Total Revenue</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>37</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>One Year</td>\n",
              "      <td>1</td>\n",
              "      <td>Credit Card</td>\n",
              "      <td>65.6</td>\n",
              "      <td>593.30</td>\n",
              "      <td>974.81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>46</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Month-to-Month</td>\n",
              "      <td>0</td>\n",
              "      <td>Credit Card</td>\n",
              "      <td>-4.0</td>\n",
              "      <td>542.40</td>\n",
              "      <td>610.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>50</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Month-to-Month</td>\n",
              "      <td>1</td>\n",
              "      <td>Bank Withdrawal</td>\n",
              "      <td>73.9</td>\n",
              "      <td>280.85</td>\n",
              "      <td>415.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>78</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Month-to-Month</td>\n",
              "      <td>1</td>\n",
              "      <td>Bank Withdrawal</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1237.85</td>\n",
              "      <td>1599.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>75</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Month-to-Month</td>\n",
              "      <td>1</td>\n",
              "      <td>Credit Card</td>\n",
              "      <td>83.9</td>\n",
              "      <td>267.40</td>\n",
              "      <td>289.54</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 22 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-74f1925e-b4d6-4892-b9cb-7ca707cea01f')\"\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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              "  </style>\n",
              "\n",
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              "\n",
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              "          const element = document.querySelector('#df-74f1925e-b4d6-4892-b9cb-7ca707cea01f');\n",
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              "            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",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   Age  Married  Number of Dependents  Number of Referrals  Tenure in Months  \\\n",
              "0   37        1                     0                    2                 9   \n",
              "1   46        0                     0                    0                 9   \n",
              "2   50        0                     0                    0                 4   \n",
              "3   78        1                     0                    1                13   \n",
              "4   75        1                     0                    3                 3   \n",
              "\n",
              "   Phone Service  Multiple Lines  Internet Service  Online Security  \\\n",
              "0              1             0.0                 1              0.0   \n",
              "1              1             1.0                 1              0.0   \n",
              "2              1             0.0                 1              0.0   \n",
              "3              1             0.0                 1              0.0   \n",
              "4              1             0.0                 1              0.0   \n",
              "\n",
              "   Online Backup  ...  Streaming TV  Streaming Movies  Streaming Music  \\\n",
              "0            1.0  ...           1.0               0.0              0.0   \n",
              "1            0.0  ...           0.0               1.0              1.0   \n",
              "2            0.0  ...           0.0               0.0              0.0   \n",
              "3            1.0  ...           1.0               1.0              0.0   \n",
              "4            0.0  ...           1.0               0.0              0.0   \n",
              "\n",
              "   Unlimited Data        Contract  Paperless Billing   Payment Method  \\\n",
              "0             1.0        One Year                  1      Credit Card   \n",
              "1             0.0  Month-to-Month                  0      Credit Card   \n",
              "2             1.0  Month-to-Month                  1  Bank Withdrawal   \n",
              "3             1.0  Month-to-Month                  1  Bank Withdrawal   \n",
              "4             1.0  Month-to-Month                  1      Credit Card   \n",
              "\n",
              "   Monthly Charge Total Charges  Total Revenue  \n",
              "0            65.6        593.30         974.81  \n",
              "1            -4.0        542.40         610.28  \n",
              "2            73.9        280.85         415.45  \n",
              "3            98.0       1237.85        1599.51  \n",
              "4            83.9        267.40         289.54  \n",
              "\n",
              "[5 rows x 22 columns]"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "X = df[['Age', 'Married', 'Number of Dependents',\n",
        "        'Number of Referrals',\n",
        "        'Tenure in Months','Phone Service',\n",
        "        'Multiple Lines',\n",
        "        'Internet Service',\n",
        "        'Online Security', 'Online Backup', 'Device Protection Plan',\n",
        "        'Premium Tech Support', 'Streaming TV', 'Streaming Movies',\n",
        "        'Streaming Music', 'Unlimited Data', 'Contract', 'Paperless Billing',\n",
        "        'Payment Method', 'Monthly Charge', 'Total Charges',\n",
        "        'Total Revenue']]\n",
        "\n",
        "X = X.replace(['Yes','No'],[1,0])\n",
        "\n",
        "Y = np.asanyarray(df[['Customer Status']])\n",
        "X.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ttzPD0hiwL9R",
        "outputId": "6e1ba5d5-c6f7-4501-8684-f39cc2c04395"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/preprocessing/_label.py:133: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
            "  y = column_or_1d(y, warn=True)\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "array([[37, 1, 0, 2, 9, 1, 0.0, 1, 0.0, 1.0, 0.0, 1.0, 1.0, 0.0, 0.0,\n",
              "        1.0, 1, 1, 1, 65.6, 593.3, 974.81],\n",
              "       [46, 0, 0, 0, 9, 1, 1.0, 1, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0,\n",
              "        0.0, 0, 0, 1, -4.0, 542.4, 610.28],\n",
              "       [50, 0, 0, 0, 4, 1, 0.0, 1, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0,\n",
              "        1.0, 0, 1, 0, 73.9, 280.85, 415.45],\n",
              "       [78, 1, 0, 1, 13, 1, 0.0, 1, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0, 0.0,\n",
              "        1.0, 0, 1, 0, 98.0, 1237.85, 1599.51],\n",
              "       [75, 1, 0, 3, 3, 1, 0.0, 1, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,\n",
              "        1.0, 0, 1, 1, 83.9, 267.4, 289.54]], dtype=object)"
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "X= np.asanyarray(X)\n",
        "from sklearn import preprocessing\n",
        "\n",
        "con_la = preprocessing.LabelEncoder()\n",
        "con_la.fit(['Month-to-Month','Two Year','One Year'])\n",
        "X[:,16] = con_la.transform(X[:,16])\n",
        "\n",
        "pay_la = preprocessing.LabelEncoder()\n",
        "pay_la.fit(['Bank Withdrawal','Credit Card','Mailed Check'])\n",
        "X[:,18] = pay_la.transform(X[:,18])\n",
        "\n",
        "y_la = preprocessing.LabelEncoder()\n",
        "y_la.fit(['Churned','Stayed','Joined'])\n",
        "Y = y_la.transform(Y)\n",
        "X[0:5]\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CG3rZ_SN56Ej",
        "outputId": "81aff30c-0832-4116-9c14-636efb6315e1"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([[-0.56777322,  1.03453023, -0.4868349 ,  0.01603903, -0.95299362,\n",
              "         0.32743831, -0.93616301,  0.52592737, -0.75972822,  1.12752165,\n",
              "        -0.88461998,  1.30350273,  1.01884714, -0.99043903, -0.90630745,\n",
              "         0.40335788,  0.28902128,  0.8297975 ,  0.83470403,  0.06422137,\n",
              "        -0.74449996, -0.71887199],\n",
              "       [-0.03043292, -0.96662231, -0.4868349 , -0.65040855, -0.95299362,\n",
              "         0.32743831,  1.06819004,  0.52592737, -0.75972822, -0.88690093,\n",
              "        -0.88461998, -0.76716372, -0.9815015 ,  1.00965326,  1.10337833,\n",
              "        -2.47918798, -0.88965671, -1.20511329,  0.83470403, -2.16636714,\n",
              "        -0.76696186, -0.84610754],\n",
              "       [ 0.20838499, -0.96662231, -0.4868349 , -0.65040855, -1.15673995,\n",
              "         0.32743831, -0.93616301,  0.52592737, -0.75972822, -0.88690093,\n",
              "         1.13042891, -0.76716372, -0.9815015 , -0.99043903, -0.90630745,\n",
              "         0.40335788, -0.88965671,  0.8297975 , -0.83351971,  0.33022546,\n",
              "        -0.88238248, -0.914111  ],\n",
              "       [ 1.88011037,  1.03453023, -0.4868349 , -0.31718476, -0.78999655,\n",
              "         0.32743831, -0.93616301,  0.52592737, -0.75972822,  1.12752165,\n",
              "         1.13042891, -0.76716372,  1.01884714,  1.00965326, -0.90630745,\n",
              "         0.40335788, -0.88965671,  0.8297975 , -0.83351971,  1.10259878,\n",
              "        -0.46006348, -0.5008267 ],\n",
              "       [ 1.70099694,  1.03453023, -0.4868349 ,  0.34926281, -1.19748922,\n",
              "         0.32743831, -0.93616301,  0.52592737, -0.75972822, -0.88690093,\n",
              "        -0.88461998,  1.30350273,  1.01884714, -0.99043903, -0.90630745,\n",
              "         0.40335788, -0.88965671,  0.8297975 ,  0.83470403,  0.65071232,\n",
              "        -0.88831789, -0.95805863]])"
            ]
          },
          "execution_count": 28,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "scaler = preprocessing.StandardScaler()\n",
        "X = scaler.fit(X).transform(X.astype(float))\n",
        "X = np.nan_to_num(X)\n",
        "\n",
        "X[0:5]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "id": "58njgDmEovxt"
      },
      "outputs": [],
      "source": [
        "x_train , x_test , y_train ,y_test = train_test_split(X,Y,test_size=0.3,random_state=4)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "id": "F6Mzmz9j2u2V",
        "outputId": "d334ac86-4556-46ae-f28b-815d94735c5f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "the best k is: 8 with accuracy: 0.7553241836251775\n"
          ]
        },
        {
          "data": {
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              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\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>k</th>\n",
              "      <th>accuracy</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>0.716517</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>0.687175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>0.744912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>0.739233</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
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              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>0.754378</td>\n",
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              "    <tr>\n",
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              "      <td>7</td>\n",
              "      <td>0.753904</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>0.755324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>0.752958</td>\n",
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              "\n",
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              "          const element = document.querySelector('#df-277e0ef3-9cbd-4325-b034-6f2169744af0');\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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              "          dataTable['output_type'] = 'display_data';\n",
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              "        }\n",
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              "  "
            ],
            "text/plain": [
              "   k  accuracy\n",
              "0  1  0.716517\n",
              "1  2  0.687175\n",
              "2  3  0.744912\n",
              "3  4  0.739233\n",
              "4  5  0.753904\n",
              "5  6  0.754378\n",
              "6  7  0.753904\n",
              "7  8  0.755324\n",
              "8  9  0.752958"
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from sklearn import metrics\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "\n",
        "#knn model for difrent ks\n",
        "ks = 10\n",
        "acc_matrix = []\n",
        "auc_matrix = []\n",
        "ks_array = []\n",
        "for k in range(1,ks):\n",
        "  neigh = KNeighborsClassifier(n_neighbors=k).fit(x_train,y_train)\n",
        "  y_hat = neigh.predict(x_test)\n",
        "  acc_matrix.append(metrics.accuracy_score(y_test,y_hat))\n",
        "  ks_array.append(k)\n",
        "\n",
        "datas = {'k':ks_array,'accuracy':acc_matrix}\n",
        "k_df = pd.DataFrame(datas)\n",
        "\n",
        "acc_np = np.asanyarray(acc_matrix)\n",
        "print('the best k is: {} with accuracy: {}'.format(acc_np.argmax()+1,acc_np.max()))\n",
        "\n",
        "k_df\n",
        "\n",
        "\n",
        "  \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
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          "height": 193
        },
        "id": "0fZjudvJl4r4",
        "outputId": "c9330901-32f2-443c-c15e-7cb10c051ada"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "best model is  logestic_regression with accuracy : 80.64363464268813%\n"
          ]
        },
        {
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              "      <th>accuracy</th>\n",
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              "  </thead>\n",
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              "      <th>0</th>\n",
              "      <td>logestic reg</td>\n",
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              "      <th>3</th>\n",
              "      <td>KNN</td>\n",
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            "text/plain": [
              "          model  accuracy\n",
              "0  logestic reg  0.806436\n",
              "1           svm  0.805017\n",
              "2  decisiontree  0.787506\n",
              "3           KNN  0.755324"
            ]
          },
          "execution_count": 31,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "my_models = [\n",
        "    LogisticRegression(solver = 'liblinear'),\n",
        "    SVC(),\n",
        "    DecisionTreeClassifier(),\n",
        "    KNeighborsClassifier(n_neighbors=8)\n",
        "]\n",
        "model_list = ['logestic reg','svm','decisiontree','KNN']\n",
        "acc_list = []\n",
        "auc_list = []\n",
        "\n",
        "for model in my_models:\n",
        "  model.fit(x_train,y_train)\n",
        "  y_hat = model.predict(x_test)\n",
        "  acc_list.append(metrics.accuracy_score(y_test,y_hat))\n",
        "\n",
        "datas = {'model':model_list,'accuracy':acc_list}\n",
        "model_df = pd.DataFrame(datas)\n",
        "model_np = np.asanyarray(model_df)\n",
        "print('best model is  logestic_regression with accuracy : {}%'.format(model_np[:,1].max()*100 ))\n",
        "model_df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xLg3AhftYtWL"
      },
      "source": [
        "made by alireza rezaei\n",
        "<a href='alirezarezaei.pythonanywhere.com' style='color:\"red\";'>\n",
        "```\n",
        "alireza rezaei \n",
        "```\n",
        "</a>\n"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "telecom_churn.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
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    "language_info": {
      "name": "python"
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  "nbformat_minor": 0
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