Customer Churn Prediction using PySpark.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O1eOogPqix4i"
      },
      "source": [
        "### **Task 1 - Loading our data**\n",
        "\n",
        "Installing the pyspark using pip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pYfUECtFisDa",
        "outputId": "dbada48a-18de-4735-94c4-a045b3a87689"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pyspark in /usr/local/lib/python3.10/dist-packages (3.5.1)\n",
            "Requirement already satisfied: py4j==0.10.9.7 in /usr/local/lib/python3.10/dist-packages (from pyspark) (0.10.9.7)\n"
          ]
        }
      ],
      "source": [
        "!pip install pyspark"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cr4LlOxmvUmW"
      },
      "source": [
        "Importing Modules"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tiE8RPAHvWHD"
      },
      "outputs": [],
      "source": [
        "# importing spark session\n",
        "from pyspark.sql import SparkSession\n",
        "\n",
        "# data visualization modules\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "\n",
        "# pandas module\n",
        "import pandas as pd\n",
        "\n",
        "# pyspark SQL functions\n",
        "from pyspark.sql.functions import col, when, count, udf\n",
        "\n",
        "# pyspark data preprocessing modules\n",
        "from pyspark.ml.feature import Imputer, StringIndexer, VectorAssembler, StandardScaler, OneHotEncoder\n",
        "\n",
        "# pyspark data modeling and model evaluation modules\n",
        "from pyspark.ml.classification import DecisionTreeClassifier\n",
        "from pyspark.ml.evaluation import BinaryClassificationEvaluator\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W-_0aGYvj6sI"
      },
      "source": [
        "Building our Spark Session"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 216
        },
        "id": "qQgz_0Zgiilu",
        "outputId": "63392a63-e3ae-43ec-9786-5d31e1e7e735"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pyspark.sql.session.SparkSession at 0x797dd49f0190>"
            ],
            "text/html": [
              "\n",
              "            <div>\n",
              "                <p><b>SparkSession - in-memory</b></p>\n",
              "                \n",
              "        <div>\n",
              "            <p><b>SparkContext</b></p>\n",
              "\n",
              "            <p><a href=\"http://e60abab24a7f:4040\">Spark UI</a></p>\n",
              "\n",
              "            <dl>\n",
              "              <dt>Version</dt>\n",
              "                <dd><code>v3.5.1</code></dd>\n",
              "              <dt>Master</dt>\n",
              "                <dd><code>local[*]</code></dd>\n",
              "              <dt>AppName</dt>\n",
              "                <dd><code>Customer_Churn_Prediction</code></dd>\n",
              "            </dl>\n",
              "        </div>\n",
              "        \n",
              "            </div>\n",
              "        "
            ]
          },
          "metadata": {},
          "execution_count": 135
        }
      ],
      "source": [
        "spark = SparkSession.builder.appName(\"Customer_Churn_Prediction\").getOrCreate()\n",
        "spark"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B1aneLUYvh71"
      },
      "source": [
        "Loading our data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J3Y1melCvqN5",
        "outputId": "b08320bb-1bb9-4efc-c4f6-cc1eca2a2aab"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+--------------+------------+----------------+-----------+-----------+---------------+--------------+----------------+--------------------+--------------+------------+-----+\n",
            "|customerID|gender|SeniorCitizen|Partner|Dependents|tenure|PhoneService|   MultipleLines|InternetService|OnlineSecurity|OnlineBackup|DeviceProtection|TechSupport|StreamingTV|StreamingMovies|      Contract|PaperlessBilling|       PaymentMethod|MonthlyCharges|TotalCharges|Churn|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+--------------+------------+----------------+-----------+-----------+---------------+--------------+----------------+--------------------+--------------+------------+-----+\n",
            "|7590-VHVEG|Female|           No|    Yes|        No|     1|          No|No phone service|            DSL|            No|         Yes|              No|         No|         No|             No|Month-to-month|             Yes|    Electronic check|         29.85|       29.85|   No|\n",
            "|5575-GNVDE|  Male|           No|     No|        No|    34|         Yes|              No|            DSL|           Yes|          No|             Yes|         No|         No|             No|      One year|              No|        Mailed check|         56.95|      1889.5|   No|\n",
            "|3668-QPYBK|  Male|           No|     No|        No|     2|         Yes|              No|            DSL|           Yes|         Yes|              No|         No|         No|             No|Month-to-month|             Yes|        Mailed check|         53.85|      108.15|  Yes|\n",
            "|7795-CFOCW|  Male|           No|     No|        No|    45|          No|No phone service|            DSL|           Yes|          No|             Yes|        Yes|         No|             No|      One year|              No|Bank transfer (au...|          42.3|     1840.75|   No|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+--------------+------------+----------------+-----------+-----------+---------------+--------------+----------------+--------------------+--------------+------------+-----+\n",
            "only showing top 4 rows\n",
            "\n"
          ]
        }
      ],
      "source": [
        "data = spark.read.format(\"csv\").option(\"inferSchema\", True).option(\"header\", True).load(\"dataset.csv\")\n",
        "data.show(4)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TeY_Znoi4WQA"
      },
      "source": [
        "Print the data schema to check out the data types"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6yopaRXr4Ufr",
        "outputId": "70d1cc2d-591a-4a44-d8a2-935e6511f869"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "root\n",
            " |-- customerID: string (nullable = true)\n",
            " |-- gender: string (nullable = true)\n",
            " |-- SeniorCitizen: string (nullable = true)\n",
            " |-- Partner: string (nullable = true)\n",
            " |-- Dependents: string (nullable = true)\n",
            " |-- tenure: integer (nullable = true)\n",
            " |-- PhoneService: string (nullable = true)\n",
            " |-- MultipleLines: string (nullable = true)\n",
            " |-- InternetService: string (nullable = true)\n",
            " |-- OnlineSecurity: string (nullable = true)\n",
            " |-- OnlineBackup: string (nullable = true)\n",
            " |-- DeviceProtection: string (nullable = true)\n",
            " |-- TechSupport: string (nullable = true)\n",
            " |-- StreamingTV: string (nullable = true)\n",
            " |-- StreamingMovies: string (nullable = true)\n",
            " |-- Contract: string (nullable = true)\n",
            " |-- PaperlessBilling: string (nullable = true)\n",
            " |-- PaymentMethod: string (nullable = true)\n",
            " |-- MonthlyCharges: double (nullable = true)\n",
            " |-- TotalCharges: double (nullable = true)\n",
            " |-- Churn: string (nullable = true)\n",
            "\n"
          ]
        }
      ],
      "source": [
        "data.printSchema()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Od0SPukD3kPI"
      },
      "source": [
        "Get the data dimension"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EW0B267Wv0tm",
        "outputId": "88c9f0a4-9dd3-4591-ba63-0c0cd7e2f306"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "21"
            ]
          },
          "metadata": {},
          "execution_count": 138
        }
      ],
      "source": [
        "len(data.columns)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4xbTCX5cuG2f",
        "outputId": "bb4e1837-b8d0-4818-abdc-f222460a13ce"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7043"
            ]
          },
          "metadata": {},
          "execution_count": 139
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oZzDBEKT2H9P"
      },
      "source": [
        "### **Task 2 - Exploratory Data Analysis**\n",
        "- Distribution Analysis\n",
        "- Correlation Analysis\n",
        "- Univariate Analysis\n",
        "- Finding Missing values"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VUWEEw9VTVor"
      },
      "source": [
        "Let's define some lists to store different column names with different data types."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "60DqvLYRwR6R",
        "outputId": "98297b6e-4982-47ad-85df-58991b711552"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('customerID', 'string'),\n",
              " ('gender', 'string'),\n",
              " ('SeniorCitizen', 'string'),\n",
              " ('Partner', 'string'),\n",
              " ('Dependents', 'string'),\n",
              " ('tenure', 'int'),\n",
              " ('PhoneService', 'string'),\n",
              " ('MultipleLines', 'string'),\n",
              " ('InternetService', 'string'),\n",
              " ('OnlineSecurity', 'string'),\n",
              " ('OnlineBackup', 'string'),\n",
              " ('DeviceProtection', 'string'),\n",
              " ('TechSupport', 'string'),\n",
              " ('StreamingTV', 'string'),\n",
              " ('StreamingMovies', 'string'),\n",
              " ('Contract', 'string'),\n",
              " ('PaperlessBilling', 'string'),\n",
              " ('PaymentMethod', 'string'),\n",
              " ('MonthlyCharges', 'double'),\n",
              " ('TotalCharges', 'double'),\n",
              " ('Churn', 'string')]"
            ]
          },
          "metadata": {},
          "execution_count": 140
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "H4cJoyG-Ubel"
      },
      "outputs": [],
      "source": [
        "\n",
        "numerical_columns = [name for name,typ in data.dtypes if typ == \"double\" or typ == \"int\"]\n",
        "categorical_columns = [name for name,typ in data.dtypes if typ == \"string\"]\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DYoYREY75vfo"
      },
      "source": [
        "Let's get all the numerical features and store them into a pandas dataframe."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
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          "height": 204
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        "id": "CWYeP2xp45Ot",
        "outputId": "dead7934-4655-4a51-8433-02223407e565"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "   tenure  MonthlyCharges  TotalCharges\n",
              "0       1           29.85         29.85\n",
              "1      34           56.95       1889.50\n",
              "2       2           53.85        108.15\n",
              "3      45           42.30       1840.75\n",
              "4       2           70.70        151.65"
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8f956e7b-d17c-4d88-ba36-b137c51e4aa3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 7043,\n  \"fields\": [\n    {\n      \"column\": \"tenure\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 74,\n        \"samples\": [\n          8,\n          53,\n          12\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"MonthlyCharges\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.090047097678493,\n        \"min\": 18.25,\n        \"max\": 118.75,\n        \"num_unique_values\": 1585,\n        \"samples\": [\n          48.85,\n          20.05,\n          36.85\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"TotalCharges\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2266.771361883145,\n        \"min\": 18.8,\n        \"max\": 8684.8,\n        \"num_unique_values\": 6530,\n        \"samples\": [\n          5594.0,\n          6840.95,\n          6148.45\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 142
        }
      ],
      "source": [
        "df = data.select(numerical_columns).toPandas()\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PZgNnbgnNtTe"
      },
      "source": [
        "Let's create histograms to analyse the distribution of our numerical columns."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "gizkvQ3oNsuo",
        "outputId": "d639f0a3-822a-4332-ce34-cef730fd897f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-143-e273f7e70916>:3: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared.\n",
            "  df.hist(ax = ax, bins = 20)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    7043.000000\n",
              "mean       32.435752\n",
              "std        25.075228\n",
              "min         0.000000\n",
              "25%         9.000000\n",
              "50%        29.000000\n",
              "75%        55.000000\n",
              "max       458.000000\n",
              "Name: tenure, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 143
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1000 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "fig = plt.figure(figsize=(15, 10))\n",
        "ax = fig.gca()\n",
        "df.hist(ax = ax, bins = 20)\n",
        "df.tenure.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9qjCcR72ru2_"
      },
      "source": [
        "Let's generate the correlation matrix"
      ]
    },
    {
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      "execution_count": null,
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        },
        "id": "ldNx2GuVrvAR",
        "outputId": "ace95db6-8821-47bc-b8b4-429bbba92cde"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  tenure  MonthlyCharges  TotalCharges\n",
              "tenure          1.000000        0.243703      0.806530\n",
              "MonthlyCharges  0.243703        1.000000      0.651065\n",
              "TotalCharges    0.806530        0.651065      1.000000"
            ],
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              "      <td>0.806530</td>\n",
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              "      <th>MonthlyCharges</th>\n",
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              "      <td>0.651065</td>\n",
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              "      <th>TotalCharges</th>\n",
              "      <td>0.806530</td>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"tenure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3928928759172614,\n        \"min\": 0.2437034941648647,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1.0,\n          0.2437034941648647,\n          0.8065302035568778\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"MonthlyCharges\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3785241983471621,\n        \"min\": 0.2437034941648647,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.2437034941648647,\n          1.0,\n          0.6510648032262017\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"TotalCharges\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.17481219655356328,\n        \"min\": 0.6510648032262017,\n        \"max\": 1.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.8065302035568778,\n          0.6510648032262017,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 144
        }
      ],
      "source": [
        "df.corr()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vbBRqQQJhmqg"
      },
      "source": [
        "Let's check the unique value count per each categorical variables"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pgXj3fjJb0th",
        "outputId": "9fdbc21a-d662-4133-85b1-a470a87df0d9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+-----+\n",
            "|customerID|count|\n",
            "+----------+-----+\n",
            "|3668-QPYBK|    1|\n",
            "|6234-RAAPL|    1|\n",
            "|1894-IGFSG|    1|\n",
            "|6982-SSHFK|    1|\n",
            "|5859-HZYLF|    1|\n",
            "|6479-OAUSD|    1|\n",
            "|2592-YKDIF|    1|\n",
            "|6718-BDGHG|    1|\n",
            "|3195-TQDZX|    1|\n",
            "|4248-QPAVC|    1|\n",
            "|5668-MEISB|    1|\n",
            "|5802-ADBRC|    1|\n",
            "|2712-SYWAY|    1|\n",
            "|2011-TRQYE|    1|\n",
            "|7244-KXYZN|    1|\n",
            "|0953-LGOVU|    1|\n",
            "|3623-FQBOX|    1|\n",
            "|3692-JHONH|    1|\n",
            "|3528-HFRIQ|    1|\n",
            "|7661-CPURM|    1|\n",
            "+----------+-----+\n",
            "only showing top 20 rows\n",
            "\n",
            "+------+-----+\n",
            "|gender|count|\n",
            "+------+-----+\n",
            "|Female| 3488|\n",
            "|  Male| 3555|\n",
            "+------+-----+\n",
            "\n",
            "+-------------+-----+\n",
            "|SeniorCitizen|count|\n",
            "+-------------+-----+\n",
            "|           No| 5901|\n",
            "|          Yes| 1142|\n",
            "+-------------+-----+\n",
            "\n",
            "+-------+-----+\n",
            "|Partner|count|\n",
            "+-------+-----+\n",
            "|     No| 3641|\n",
            "|    Yes| 3402|\n",
            "+-------+-----+\n",
            "\n",
            "+----------+-----+\n",
            "|Dependents|count|\n",
            "+----------+-----+\n",
            "|        No| 4933|\n",
            "|       Yes| 2110|\n",
            "+----------+-----+\n",
            "\n",
            "+------------+-----+\n",
            "|PhoneService|count|\n",
            "+------------+-----+\n",
            "|          No|  682|\n",
            "|         Yes| 6361|\n",
            "+------------+-----+\n",
            "\n",
            "+----------------+-----+\n",
            "|   MultipleLines|count|\n",
            "+----------------+-----+\n",
            "|No phone service|  682|\n",
            "|              No| 3390|\n",
            "|             Yes| 2971|\n",
            "+----------------+-----+\n",
            "\n",
            "+---------------+-----+\n",
            "|InternetService|count|\n",
            "+---------------+-----+\n",
            "|    Fiber optic| 3096|\n",
            "|             No| 1526|\n",
            "|            DSL| 2421|\n",
            "+---------------+-----+\n",
            "\n",
            "+-------------------+-----+\n",
            "|     OnlineSecurity|count|\n",
            "+-------------------+-----+\n",
            "|                 No| 3498|\n",
            "|                Yes| 2019|\n",
            "|No internet service| 1526|\n",
            "+-------------------+-----+\n",
            "\n",
            "+-------------------+-----+\n",
            "|       OnlineBackup|count|\n",
            "+-------------------+-----+\n",
            "|                 No| 3088|\n",
            "|                Yes| 2429|\n",
            "|No internet service| 1526|\n",
            "+-------------------+-----+\n",
            "\n",
            "+-------------------+-----+\n",
            "|   DeviceProtection|count|\n",
            "+-------------------+-----+\n",
            "|                 No| 3095|\n",
            "|                Yes| 2422|\n",
            "|No internet service| 1526|\n",
            "+-------------------+-----+\n",
            "\n",
            "+-------------------+-----+\n",
            "|        TechSupport|count|\n",
            "+-------------------+-----+\n",
            "|                 No| 3473|\n",
            "|                Yes| 2044|\n",
            "|No internet service| 1526|\n",
            "+-------------------+-----+\n",
            "\n",
            "+-------------------+-----+\n",
            "|        StreamingTV|count|\n",
            "+-------------------+-----+\n",
            "|                 No| 2810|\n",
            "|                Yes| 2707|\n",
            "|No internet service| 1526|\n",
            "+-------------------+-----+\n",
            "\n",
            "+-------------------+-----+\n",
            "|    StreamingMovies|count|\n",
            "+-------------------+-----+\n",
            "|                 No| 2785|\n",
            "|                Yes| 2732|\n",
            "|No internet service| 1526|\n",
            "+-------------------+-----+\n",
            "\n",
            "+--------------+-----+\n",
            "|      Contract|count|\n",
            "+--------------+-----+\n",
            "|Month-to-month| 3875|\n",
            "|      One year| 1473|\n",
            "|      Two year| 1695|\n",
            "+--------------+-----+\n",
            "\n",
            "+----------------+-----+\n",
            "|PaperlessBilling|count|\n",
            "+----------------+-----+\n",
            "|              No| 2872|\n",
            "|             Yes| 4171|\n",
            "+----------------+-----+\n",
            "\n",
            "+--------------------+-----+\n",
            "|       PaymentMethod|count|\n",
            "+--------------------+-----+\n",
            "|Credit card (auto...| 1522|\n",
            "|        Mailed check| 1612|\n",
            "|Bank transfer (au...| 1544|\n",
            "|    Electronic check| 2365|\n",
            "+--------------------+-----+\n",
            "\n",
            "+-----+-----+\n",
            "|Churn|count|\n",
            "+-----+-----+\n",
            "|   No| 5174|\n",
            "|  Yes| 1869|\n",
            "+-----+-----+\n",
            "\n"
          ]
        }
      ],
      "source": [
        "for column in categorical_columns:\n",
        "  data.groupby(column).count().show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "p4jhFIepJN_t"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mgmiBcimTw5z"
      },
      "source": [
        "Let's find number of null values in all of our dataframe columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-vlBo7LWT1kB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cea0c45c-499c-46d3-a311-21bc39f0336e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+\n",
            "|customerID|\n",
            "+----------+\n",
            "|         0|\n",
            "+----------+\n",
            "\n",
            "+------+\n",
            "|gender|\n",
            "+------+\n",
            "|     0|\n",
            "+------+\n",
            "\n",
            "+-------------+\n",
            "|SeniorCitizen|\n",
            "+-------------+\n",
            "|            0|\n",
            "+-------------+\n",
            "\n",
            "+-------+\n",
            "|Partner|\n",
            "+-------+\n",
            "|      0|\n",
            "+-------+\n",
            "\n",
            "+----------+\n",
            "|Dependents|\n",
            "+----------+\n",
            "|         0|\n",
            "+----------+\n",
            "\n",
            "+------+\n",
            "|tenure|\n",
            "+------+\n",
            "|     0|\n",
            "+------+\n",
            "\n",
            "+------------+\n",
            "|PhoneService|\n",
            "+------------+\n",
            "|           0|\n",
            "+------------+\n",
            "\n",
            "+-------------+\n",
            "|MultipleLines|\n",
            "+-------------+\n",
            "|            0|\n",
            "+-------------+\n",
            "\n",
            "+---------------+\n",
            "|InternetService|\n",
            "+---------------+\n",
            "|              0|\n",
            "+---------------+\n",
            "\n",
            "+--------------+\n",
            "|OnlineSecurity|\n",
            "+--------------+\n",
            "|             0|\n",
            "+--------------+\n",
            "\n",
            "+------------+\n",
            "|OnlineBackup|\n",
            "+------------+\n",
            "|           0|\n",
            "+------------+\n",
            "\n",
            "+----------------+\n",
            "|DeviceProtection|\n",
            "+----------------+\n",
            "|               0|\n",
            "+----------------+\n",
            "\n",
            "+-----------+\n",
            "|TechSupport|\n",
            "+-----------+\n",
            "|          0|\n",
            "+-----------+\n",
            "\n",
            "+-----------+\n",
            "|StreamingTV|\n",
            "+-----------+\n",
            "|          0|\n",
            "+-----------+\n",
            "\n",
            "+---------------+\n",
            "|StreamingMovies|\n",
            "+---------------+\n",
            "|              0|\n",
            "+---------------+\n",
            "\n",
            "+--------+\n",
            "|Contract|\n",
            "+--------+\n",
            "|       0|\n",
            "+--------+\n",
            "\n",
            "+----------------+\n",
            "|PaperlessBilling|\n",
            "+----------------+\n",
            "|               0|\n",
            "+----------------+\n",
            "\n",
            "+-------------+\n",
            "|PaymentMethod|\n",
            "+-------------+\n",
            "|            0|\n",
            "+-------------+\n",
            "\n",
            "+--------------+\n",
            "|MonthlyCharges|\n",
            "+--------------+\n",
            "|             0|\n",
            "+--------------+\n",
            "\n",
            "+------------+\n",
            "|TotalCharges|\n",
            "+------------+\n",
            "|          11|\n",
            "+------------+\n",
            "\n",
            "+-----+\n",
            "|Churn|\n",
            "+-----+\n",
            "|    0|\n",
            "+-----+\n",
            "\n"
          ]
        }
      ],
      "source": [
        "for column in data.columns:\n",
        "  data.select(count(when(col(column).isNull(),column)).alias(column)).show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WcTLE0ZdS-so"
      },
      "source": [
        "### **Task 3 - Data Preprocessing**\n",
        "- Handling the missing values\n",
        "- Removing the outliers"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bDKvkUiwzt_H"
      },
      "source": [
        "**Handling the missing values** <br>\n",
        "Let's create a list of column names with missing values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ABZfAKxRS3CN"
      },
      "outputs": [],
      "source": [
        "columns_with_missing_values = [\"TotalCharges\"]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ny4cfwKYzzJN"
      },
      "source": [
        "Creating our Imputer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lqBhbzyNzyFs"
      },
      "outputs": [],
      "source": [
        "imputer = Imputer(inputCols = columns_with_missing_values, outputCols= columns_with_missing_values).setStrategy(\"mean\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2XgghJUpz6wv"
      },
      "source": [
        "Use Imputer to fill the missing values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LmMfG-Gqz4m4"
      },
      "outputs": [],
      "source": [
        "imputer = imputer.fit(data)\n",
        "data = imputer.transform(data)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8fKFfw2G0A4j"
      },
      "source": [
        "Let's check the missing value counts again"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LscLsydL0Dg_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b0dcfdab-2087-430b-f143-a3e64e453f69"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+------------+\n",
            "|TotalCharges|\n",
            "+------------+\n",
            "|           0|\n",
            "+------------+\n",
            "\n"
          ]
        }
      ],
      "source": [
        "data.select(count(when(col(\"TotalCharges\").isNull(),\"TotalCharges\")).alias(\"TotalCharges\")).show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g9JJoI4_1Ao5"
      },
      "source": [
        "**Removing the outliers** <br>\n",
        "Let's find the customer with the tenure higher than 100"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GuUgYzfM1ICN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "65768ec6-b279-49c7-dfba-f28084e8f636"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------+-------------+-------+----------+------+------------+-------------+---------------+--------------+------------+----------------+-----------+-----------+---------------+--------------+----------------+----------------+--------------+------------+-----+\n",
            "|customerID|gender|SeniorCitizen|Partner|Dependents|tenure|PhoneService|MultipleLines|InternetService|OnlineSecurity|OnlineBackup|DeviceProtection|TechSupport|StreamingTV|StreamingMovies|      Contract|PaperlessBilling|   PaymentMethod|MonthlyCharges|TotalCharges|Churn|\n",
            "+----------+------+-------------+-------+----------+------+------------+-------------+---------------+--------------+------------+----------------+-----------+-----------+---------------+--------------+----------------+----------------+--------------+------------+-----+\n",
            "|5122-CYFXA|Female|           No|     No|        No|   458|         Yes|           No|            DSL|            No|         Yes|              No|        Yes|        Yes|            Yes|Month-to-month|             Yes|Electronic check|          75.3|       244.1|   No|\n",
            "+----------+------+-------------+-------+----------+------+------------+-------------+---------------+--------------+------------+----------------+-----------+-----------+---------------+--------------+----------------+----------------+--------------+------------+-----+\n",
            "\n"
          ]
        }
      ],
      "source": [
        "data.select(\"*\").where(data.tenure > 100).show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YcaebVkh2CoU"
      },
      "source": [
        "Let's drop the outlier row"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ANT7iLlB2Et5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5763e2ea-a678-4b42-ff0b-3daa5a06f571"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Before removing the outlier 7043\n",
            "After removing the outlier 7042\n"
          ]
        }
      ],
      "source": [
        "print(\"Before removing the outlier\", data.count())\n",
        "data = data.filter(data.tenure < 100)\n",
        "print(\"After removing the outlier\", data.count())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CQMD4VIuPDen"
      },
      "source": [
        "### **Task 4 - Feature Preparation**\n",
        "- Numerical Features\n",
        "    - Vector Assembling\n",
        "    - Numerical Scaling\n",
        "- Categorical Features\n",
        "    - String Indexing\n",
        "    - Vector Assembling\n",
        "\n",
        "- Combining the numerical and categorical feature vectors\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "**Feature Preparation - Numerical Features** <br>\n",
        "\n",
        "`Vector Assembling --> Standard Scaling` <br>\n",
        "\n",
        "**Vector Assembling** <br>\n",
        "To apply our machine learning model we need to combine all of our numerical and categorical features into vectors. For now let's create a feature vector for our numerical columns.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7_g7Hu3HPC9Q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "60511d6d-442d-4074-9adc-28094d295a41"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+\n",
            "|customerID|gender|SeniorCitizen|Partner|Dependents|tenure|PhoneService|   MultipleLines|InternetService|     OnlineSecurity|       OnlineBackup|   DeviceProtection|        TechSupport|        StreamingTV|    StreamingMovies|      Contract|PaperlessBilling|       PaymentMethod|MonthlyCharges|TotalCharges|Churn|numerical_features_vector|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+\n",
            "|7590-VHVEG|Female|           No|    Yes|        No|     1|          No|No phone service|            DSL|                 No|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|         29.85|       29.85|   No|        [1.0,29.85,29.85]|\n",
            "|5575-GNVDE|  Male|           No|     No|        No|    34|         Yes|              No|            DSL|                Yes|                 No|                Yes|                 No|                 No|                 No|      One year|              No|        Mailed check|         56.95|      1889.5|   No|      [34.0,56.95,1889.5]|\n",
            "|3668-QPYBK|  Male|           No|     No|        No|     2|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         53.85|      108.15|  Yes|       [2.0,53.85,108.15]|\n",
            "|7795-CFOCW|  Male|           No|     No|        No|    45|          No|No phone service|            DSL|                Yes|                 No|                Yes|                Yes|                 No|                 No|      One year|              No|Bank transfer (au...|          42.3|     1840.75|   No|      [45.0,42.3,1840.75]|\n",
            "|9237-HQITU|Female|           No|     No|        No|     2|         Yes|              No|    Fiber optic|                 No|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|          70.7|      151.65|  Yes|        [2.0,70.7,151.65]|\n",
            "|9305-CDSKC|Female|           No|     No|        No|     8|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         99.65|       820.5|  Yes|        [8.0,99.65,820.5]|\n",
            "|1452-KIOVK|  Male|           No|     No|       Yes|    22|         Yes|             Yes|    Fiber optic|                 No|                Yes|                 No|                 No|                Yes|                 No|Month-to-month|             Yes|Credit card (auto...|          89.1|      1949.4|   No|       [22.0,89.1,1949.4]|\n",
            "|6713-OKOMC|Female|           No|     No|        No|    10|          No|No phone service|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|              No|        Mailed check|         29.75|       301.9|   No|       [10.0,29.75,301.9]|\n",
            "|7892-POOKP|Female|           No|    Yes|        No|    28|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         104.8|     3046.05|  Yes|     [28.0,104.8,3046.05]|\n",
            "|6388-TABGU|  Male|           No|     No|       Yes|    62|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|      One year|              No|Bank transfer (au...|         56.15|     3487.95|   No|     [62.0,56.15,3487.95]|\n",
            "|9763-GRSKD|  Male|           No|    Yes|       Yes|    13|         Yes|              No|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         49.95|      587.45|   No|      [13.0,49.95,587.45]|\n",
            "|7469-LKBCI|  Male|           No|     No|        No|    16|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      Two year|              No|Credit card (auto...|         18.95|       326.8|   No|       [16.0,18.95,326.8]|\n",
            "|8091-TTVAX|  Male|           No|    Yes|        No|    58|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|      One year|              No|Credit card (auto...|        100.35|      5681.1|   No|     [58.0,100.35,5681.1]|\n",
            "|0280-XJGEX|  Male|           No|     No|        No|    49|         Yes|             Yes|    Fiber optic|                 No|                Yes|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|Bank transfer (au...|         103.7|      5036.3|  Yes|      [49.0,103.7,5036.3]|\n",
            "|5129-JLPIS|  Male|           No|     No|        No|    25|         Yes|              No|    Fiber optic|                Yes|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         105.5|     2686.05|   No|     [25.0,105.5,2686.05]|\n",
            "|3655-SNQYZ|Female|           No|    Yes|       Yes|    69|         Yes|             Yes|    Fiber optic|                Yes|                Yes|                Yes|                Yes|                Yes|                Yes|      Two year|              No|Credit card (auto...|        113.25|     7895.15|   No|     [69.0,113.25,7895...|\n",
            "|8191-XWSZG|Female|           No|     No|        No|    52|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      One year|              No|        Mailed check|         20.65|     1022.95|   No|     [52.0,20.65,1022.95]|\n",
            "|9959-WOFKT|  Male|           No|     No|       Yes|    71|         Yes|             Yes|    Fiber optic|                Yes|                 No|                Yes|                 No|                Yes|                Yes|      Two year|              No|Bank transfer (au...|         106.7|     7382.25|   No|     [71.0,106.7,7382.25]|\n",
            "|4190-MFLUW|Female|           No|    Yes|       Yes|    10|         Yes|              No|            DSL|                 No|                 No|                Yes|                Yes|                 No|                 No|Month-to-month|              No|Credit card (auto...|          55.2|      528.35|  Yes|       [10.0,55.2,528.35]|\n",
            "|4183-MYFRB|Female|           No|     No|        No|    21|         Yes|              No|    Fiber optic|                 No|                Yes|                Yes|                 No|                 No|                Yes|Month-to-month|             Yes|    Electronic check|         90.05|      1862.9|   No|      [21.0,90.05,1862.9]|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ],
      "source": [
        "numerical_vector_assembler = VectorAssembler(inputCols= numerical_columns, outputCol= \"numerical_features_vector\")\n",
        "data = numerical_vector_assembler.transform(data)\n",
        "data.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U39MK-kfYnpc"
      },
      "source": [
        "**Numerical Scaling** <br>\n",
        "Let's standardize all of our numerical features."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RqvD874WSQEs"
      },
      "outputs": [],
      "source": [
        "scaler = StandardScaler(inputCol=\"numerical_features_vector\", outputCol=\"numerical_features_scaled\", withStd=True, withMean=True)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = scaler.fit(data).transform(data)\n",
        "data.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VFOowXqldi0k",
        "outputId": "e1f58f75-6471-4c7f-a3fa-d5b8f0fcd937"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+\n",
            "|customerID|gender|SeniorCitizen|Partner|Dependents|tenure|PhoneService|   MultipleLines|InternetService|     OnlineSecurity|       OnlineBackup|   DeviceProtection|        TechSupport|        StreamingTV|    StreamingMovies|      Contract|PaperlessBilling|       PaymentMethod|MonthlyCharges|TotalCharges|Churn|numerical_features_vector|numerical_features_scaled|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+\n",
            "|7590-VHVEG|Female|           No|    Yes|        No|     1|          No|No phone service|            DSL|                 No|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|         29.85|       29.85|   No|        [1.0,29.85,29.85]|     [-1.2775627682208...|\n",
            "|5575-GNVDE|  Male|           No|     No|        No|    34|         Yes|              No|            DSL|                Yes|                 No|                Yes|                 No|                 No|                 No|      One year|              No|        Mailed check|         56.95|      1889.5|   No|      [34.0,56.95,1889.5]|     [0.06615490566075...|\n",
            "|3668-QPYBK|  Male|           No|     No|        No|     2|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         53.85|      108.15|  Yes|       [2.0,53.85,108.15]|     [-1.2368440508304...|\n",
            "|7795-CFOCW|  Male|           No|     No|        No|    45|          No|No phone service|            DSL|                Yes|                 No|                Yes|                Yes|                 No|                 No|      One year|              No|Bank transfer (au...|          42.3|     1840.75|   No|      [45.0,42.3,1840.75]|     [0.51406079695460...|\n",
            "|9237-HQITU|Female|           No|     No|        No|     2|         Yes|              No|    Fiber optic|                 No|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|          70.7|      151.65|  Yes|        [2.0,70.7,151.65]|     [-1.2368440508304...|\n",
            "|9305-CDSKC|Female|           No|     No|        No|     8|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         99.65|       820.5|  Yes|        [8.0,99.65,820.5]|     [-0.9925317464883...|\n",
            "|1452-KIOVK|  Male|           No|     No|       Yes|    22|         Yes|             Yes|    Fiber optic|                 No|                Yes|                 No|                 No|                Yes|                 No|Month-to-month|             Yes|Credit card (auto...|          89.1|      1949.4|   No|       [22.0,89.1,1949.4]|     [-0.4224697030234...|\n",
            "|6713-OKOMC|Female|           No|     No|        No|    10|          No|No phone service|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|              No|        Mailed check|         29.75|       301.9|   No|       [10.0,29.75,301.9]|     [-0.9110943117076...|\n",
            "|7892-POOKP|Female|           No|    Yes|        No|    28|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         104.8|     3046.05|  Yes|     [28.0,104.8,3046.05]|     [-0.1781573986813...|\n",
            "|6388-TABGU|  Male|           No|     No|       Yes|    62|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|      One year|              No|Bank transfer (au...|         56.15|     3487.95|   No|     [62.0,56.15,3487.95]|     [1.20627899259056...|\n",
            "|9763-GRSKD|  Male|           No|    Yes|       Yes|    13|         Yes|              No|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         49.95|      587.45|   No|      [13.0,49.95,587.45]|     [-0.7889381595366...|\n",
            "|7469-LKBCI|  Male|           No|     No|        No|    16|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      Two year|              No|Credit card (auto...|         18.95|       326.8|   No|       [16.0,18.95,326.8]|     [-0.6667820073655...|\n",
            "|8091-TTVAX|  Male|           No|    Yes|        No|    58|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|      One year|              No|Credit card (auto...|        100.35|      5681.1|   No|     [58.0,100.35,5681.1]|     [1.04340412302915...|\n",
            "|0280-XJGEX|  Male|           No|     No|        No|    49|         Yes|             Yes|    Fiber optic|                 No|                Yes|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|Bank transfer (au...|         103.7|      5036.3|  Yes|      [49.0,103.7,5036.3]|     [0.67693566651600...|\n",
            "|5129-JLPIS|  Male|           No|     No|        No|    25|         Yes|              No|    Fiber optic|                Yes|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         105.5|     2686.05|   No|     [25.0,105.5,2686.05]|     [-0.3003135508523...|\n",
            "|3655-SNQYZ|Female|           No|    Yes|       Yes|    69|         Yes|             Yes|    Fiber optic|                Yes|                Yes|                Yes|                Yes|                Yes|                Yes|      Two year|              No|Credit card (auto...|        113.25|     7895.15|   No|     [69.0,113.25,7895...|     [1.49131001432301...|\n",
            "|8191-XWSZG|Female|           No|     No|        No|    52|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      One year|              No|        Mailed check|         20.65|     1022.95|   No|     [52.0,20.65,1022.95]|     [0.79909181868705...|\n",
            "|9959-WOFKT|  Male|           No|     No|       Yes|    71|         Yes|             Yes|    Fiber optic|                Yes|                 No|                Yes|                 No|                Yes|                Yes|      Two year|              No|Bank transfer (au...|         106.7|     7382.25|   No|     [71.0,106.7,7382.25]|     [1.57274744910371...|\n",
            "|4190-MFLUW|Female|           No|    Yes|       Yes|    10|         Yes|              No|            DSL|                 No|                 No|                Yes|                Yes|                 No|                 No|Month-to-month|              No|Credit card (auto...|          55.2|      528.35|  Yes|       [10.0,55.2,528.35]|     [-0.9110943117076...|\n",
            "|4183-MYFRB|Female|           No|     No|        No|    21|         Yes|              No|    Fiber optic|                 No|                Yes|                Yes|                 No|                 No|                Yes|Month-to-month|             Yes|    Electronic check|         90.05|      1862.9|   No|      [21.0,90.05,1862.9]|     [-0.4631884204138...|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KfbVsiv6Z1SM"
      },
      "source": [
        "**Feature Preperation - Categorical Features** <br>\n",
        "\n",
        "`String Indexing --> Vector Assembling` <br>\n",
        "\n",
        "**String Indexing** <br>\n",
        "We need to convert all the string columns to numeric columns."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "U7xmubmpZ1zo",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d48760f2-b4e3-4621-9e42-8b0ab5b6c709"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+\n",
            "|customerID|gender|SeniorCitizen|Partner|Dependents|tenure|PhoneService|   MultipleLines|InternetService|     OnlineSecurity|       OnlineBackup|   DeviceProtection|        TechSupport|        StreamingTV|    StreamingMovies|      Contract|PaperlessBilling|       PaymentMethod|MonthlyCharges|TotalCharges|Churn|numerical_features_vector|numerical_features_scaled|customerID_Indexed|gender_Indexed|SeniorCitizen_Indexed|Partner_Indexed|Dependents_Indexed|PhoneService_Indexed|MultipleLines_Indexed|InternetService_Indexed|OnlineSecurity_Indexed|OnlineBackup_Indexed|DeviceProtection_Indexed|TechSupport_Indexed|StreamingTV_Indexed|StreamingMovies_Indexed|Contract_Indexed|PaperlessBilling_Indexed|PaymentMethod_Indexed|Churn_Indexed|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+\n",
            "|7590-VHVEG|Female|           No|    Yes|        No|     1|          No|No phone service|            DSL|                 No|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|         29.85|       29.85|   No|        [1.0,29.85,29.85]|     [-1.2775627682208...|            5374.0|           1.0|                  0.0|            1.0|               0.0|                 1.0|                  2.0|                    1.0|                   0.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  0.0|          0.0|\n",
            "|5575-GNVDE|  Male|           No|     No|        No|    34|         Yes|              No|            DSL|                Yes|                 No|                Yes|                 No|                 No|                 No|      One year|              No|        Mailed check|         56.95|      1889.5|   No|      [34.0,56.95,1889.5]|     [0.06615490566075...|            3961.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    1.0|                   1.0|                 0.0|                     1.0|                0.0|                0.0|                    0.0|             2.0|                     1.0|                  1.0|          0.0|\n",
            "|3668-QPYBK|  Male|           No|     No|        No|     2|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         53.85|      108.15|  Yes|       [2.0,53.85,108.15]|     [-1.2368440508304...|            2564.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    1.0|                   1.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  1.0|          1.0|\n",
            "|7795-CFOCW|  Male|           No|     No|        No|    45|          No|No phone service|            DSL|                Yes|                 No|                Yes|                Yes|                 No|                 No|      One year|              No|Bank transfer (au...|          42.3|     1840.75|   No|      [45.0,42.3,1840.75]|     [0.51406079695460...|            5534.0|           0.0|                  0.0|            0.0|               0.0|                 1.0|                  2.0|                    1.0|                   1.0|                 0.0|                     1.0|                1.0|                0.0|                    0.0|             2.0|                     1.0|                  2.0|          0.0|\n",
            "|9237-HQITU|Female|           No|     No|        No|     2|         Yes|              No|    Fiber optic|                 No|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|          70.7|      151.65|  Yes|        [2.0,70.7,151.65]|     [-1.2368440508304...|            6510.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   0.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  0.0|          1.0|\n",
            "|9305-CDSKC|Female|           No|     No|        No|     8|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         99.65|       820.5|  Yes|        [8.0,99.65,820.5]|     [-0.9925317464883...|            6550.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          1.0|\n",
            "|1452-KIOVK|  Male|           No|     No|       Yes|    22|         Yes|             Yes|    Fiber optic|                 No|                Yes|                 No|                 No|                Yes|                 No|Month-to-month|             Yes|Credit card (auto...|          89.1|      1949.4|   No|       [22.0,89.1,1949.4]|     [-0.4224697030234...|            1002.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  1.0|                    0.0|                   0.0|                 1.0|                     0.0|                0.0|                1.0|                    0.0|             0.0|                     0.0|                  3.0|          0.0|\n",
            "|6713-OKOMC|Female|           No|     No|        No|    10|          No|No phone service|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|              No|        Mailed check|         29.75|       301.9|   No|       [10.0,29.75,301.9]|     [-0.9110943117076...|            4769.0|           1.0|                  0.0|            0.0|               0.0|                 1.0|                  2.0|                    1.0|                   1.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     1.0|                  1.0|          0.0|\n",
            "|7892-POOKP|Female|           No|    Yes|        No|    28|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         104.8|     3046.05|  Yes|     [28.0,104.8,3046.05]|     [-0.1781573986813...|            5603.0|           1.0|                  0.0|            1.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                1.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          1.0|\n",
            "|6388-TABGU|  Male|           No|     No|       Yes|    62|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|      One year|              No|Bank transfer (au...|         56.15|     3487.95|   No|     [62.0,56.15,3487.95]|     [1.20627899259056...|            4533.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  0.0|                    1.0|                   1.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             2.0|                     1.0|                  2.0|          0.0|\n",
            "|9763-GRSKD|  Male|           No|    Yes|       Yes|    13|         Yes|              No|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         49.95|      587.45|   No|      [13.0,49.95,587.45]|     [-0.7889381595366...|            6870.0|           0.0|                  0.0|            1.0|               1.0|                 0.0|                  0.0|                    1.0|                   1.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  1.0|          0.0|\n",
            "|7469-LKBCI|  Male|           No|     No|        No|    16|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      Two year|              No|Credit card (auto...|         18.95|       326.8|   No|       [16.0,18.95,326.8]|     [-0.6667820073655...|            5287.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    2.0|                   2.0|                 2.0|                     2.0|                2.0|                2.0|                    2.0|             1.0|                     1.0|                  3.0|          0.0|\n",
            "|8091-TTVAX|  Male|           No|    Yes|        No|    58|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|      One year|              No|Credit card (auto...|        100.35|      5681.1|   No|     [58.0,100.35,5681.1]|     [1.04340412302915...|            5750.0|           0.0|                  0.0|            1.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             2.0|                     1.0|                  3.0|          0.0|\n",
            "|0280-XJGEX|  Male|           No|     No|        No|    49|         Yes|             Yes|    Fiber optic|                 No|                Yes|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|Bank transfer (au...|         103.7|      5036.3|  Yes|      [49.0,103.7,5036.3]|     [0.67693566651600...|             174.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 1.0|                     1.0|                0.0|                1.0|                    1.0|             0.0|                     0.0|                  2.0|          1.0|\n",
            "|5129-JLPIS|  Male|           No|     No|        No|    25|         Yes|              No|    Fiber optic|                Yes|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         105.5|     2686.05|   No|     [25.0,105.5,2686.05]|     [-0.3003135508523...|            3614.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   1.0|                 0.0|                     1.0|                1.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          0.0|\n",
            "|3655-SNQYZ|Female|           No|    Yes|       Yes|    69|         Yes|             Yes|    Fiber optic|                Yes|                Yes|                Yes|                Yes|                Yes|                Yes|      Two year|              No|Credit card (auto...|        113.25|     7895.15|   No|     [69.0,113.25,7895...|     [1.49131001432301...|            2556.0|           1.0|                  0.0|            1.0|               1.0|                 0.0|                  1.0|                    0.0|                   1.0|                 1.0|                     1.0|                1.0|                1.0|                    1.0|             1.0|                     1.0|                  3.0|          0.0|\n",
            "|8191-XWSZG|Female|           No|     No|        No|    52|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      One year|              No|        Mailed check|         20.65|     1022.95|   No|     [52.0,20.65,1022.95]|     [0.79909181868705...|            5819.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    2.0|                   2.0|                 2.0|                     2.0|                2.0|                2.0|                    2.0|             2.0|                     1.0|                  1.0|          0.0|\n",
            "|9959-WOFKT|  Male|           No|     No|       Yes|    71|         Yes|             Yes|    Fiber optic|                Yes|                 No|                Yes|                 No|                Yes|                Yes|      Two year|              No|Bank transfer (au...|         106.7|     7382.25|   No|     [71.0,106.7,7382.25]|     [1.57274744910371...|            7018.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  1.0|                    0.0|                   1.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             1.0|                     1.0|                  2.0|          0.0|\n",
            "|4190-MFLUW|Female|           No|    Yes|       Yes|    10|         Yes|              No|            DSL|                 No|                 No|                Yes|                Yes|                 No|                 No|Month-to-month|              No|Credit card (auto...|          55.2|      528.35|  Yes|       [10.0,55.2,528.35]|     [-0.9110943117076...|            2937.0|           1.0|                  0.0|            1.0|               1.0|                 0.0|                  0.0|                    1.0|                   0.0|                 0.0|                     1.0|                1.0|                0.0|                    0.0|             0.0|                     1.0|                  3.0|          1.0|\n",
            "|4183-MYFRB|Female|           No|     No|        No|    21|         Yes|              No|    Fiber optic|                 No|                Yes|                Yes|                 No|                 No|                Yes|Month-to-month|             Yes|    Electronic check|         90.05|      1862.9|   No|      [21.0,90.05,1862.9]|     [-0.4631884204138...|            2928.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   0.0|                 1.0|                     1.0|                0.0|                0.0|                    1.0|             0.0|                     0.0|                  0.0|          0.0|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ],
      "source": [
        "categorical_columns_indexed = [name + \"_Indexed\" for name in categorical_columns]\n",
        "\n",
        "indexer = StringIndexer(inputCols=categorical_columns, outputCols=categorical_columns_indexed)\n",
        "data = indexer.fit(data).transform(data)\n",
        "data.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "566hiGhl_1m0"
      },
      "source": [
        "Let's combine all of our categorifal features in to one feature vector."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Uh0qcHDb6q8t"
      },
      "outputs": [],
      "source": [
        "categorical_columns_indexed.remove(\"customerID_Indexed\")\n",
        "categorical_columns_indexed.remove(\"Churn_Indexed\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "categorical_vector_assembler = VectorAssembler(inputCols=categorical_columns_indexed, outputCol=\"categorical_features_vector\")\n",
        "data = categorical_vector_assembler.transform(data)\n",
        "data.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eJqOW1iFf2tD",
        "outputId": "fdb434d4-70d6-4338-fe63-614bfd68e3e6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+---------------------------+\n",
            "|customerID|gender|SeniorCitizen|Partner|Dependents|tenure|PhoneService|   MultipleLines|InternetService|     OnlineSecurity|       OnlineBackup|   DeviceProtection|        TechSupport|        StreamingTV|    StreamingMovies|      Contract|PaperlessBilling|       PaymentMethod|MonthlyCharges|TotalCharges|Churn|numerical_features_vector|numerical_features_scaled|customerID_Indexed|gender_Indexed|SeniorCitizen_Indexed|Partner_Indexed|Dependents_Indexed|PhoneService_Indexed|MultipleLines_Indexed|InternetService_Indexed|OnlineSecurity_Indexed|OnlineBackup_Indexed|DeviceProtection_Indexed|TechSupport_Indexed|StreamingTV_Indexed|StreamingMovies_Indexed|Contract_Indexed|PaperlessBilling_Indexed|PaymentMethod_Indexed|Churn_Indexed|categorical_features_vector|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+---------------------------+\n",
            "|7590-VHVEG|Female|           No|    Yes|        No|     1|          No|No phone service|            DSL|                 No|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|         29.85|       29.85|   No|        [1.0,29.85,29.85]|     [-1.2775627682208...|            5374.0|           1.0|                  0.0|            1.0|               0.0|                 1.0|                  2.0|                    1.0|                   0.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  0.0|          0.0|       (16,[0,2,4,5,6,8]...|\n",
            "|5575-GNVDE|  Male|           No|     No|        No|    34|         Yes|              No|            DSL|                Yes|                 No|                Yes|                 No|                 No|                 No|      One year|              No|        Mailed check|         56.95|      1889.5|   No|      [34.0,56.95,1889.5]|     [0.06615490566075...|            3961.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    1.0|                   1.0|                 0.0|                     1.0|                0.0|                0.0|                    0.0|             2.0|                     1.0|                  1.0|          0.0|       (16,[6,7,9,13,14,...|\n",
            "|3668-QPYBK|  Male|           No|     No|        No|     2|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         53.85|      108.15|  Yes|       [2.0,53.85,108.15]|     [-1.2368440508304...|            2564.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    1.0|                   1.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  1.0|          1.0|       (16,[6,7,8,15],[1...|\n",
            "|7795-CFOCW|  Male|           No|     No|        No|    45|          No|No phone service|            DSL|                Yes|                 No|                Yes|                Yes|                 No|                 No|      One year|              No|Bank transfer (au...|          42.3|     1840.75|   No|      [45.0,42.3,1840.75]|     [0.51406079695460...|            5534.0|           0.0|                  0.0|            0.0|               0.0|                 1.0|                  2.0|                    1.0|                   1.0|                 0.0|                     1.0|                1.0|                0.0|                    0.0|             2.0|                     1.0|                  2.0|          0.0|       (16,[4,5,6,7,9,10...|\n",
            "|9237-HQITU|Female|           No|     No|        No|     2|         Yes|              No|    Fiber optic|                 No|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|          70.7|      151.65|  Yes|        [2.0,70.7,151.65]|     [-1.2368440508304...|            6510.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   0.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  0.0|          1.0|             (16,[0],[1.0])|\n",
            "|9305-CDSKC|Female|           No|     No|        No|     8|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         99.65|       820.5|  Yes|        [8.0,99.65,820.5]|     [-0.9925317464883...|            6550.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          1.0|       (16,[0,5,9,11,12]...|\n",
            "|1452-KIOVK|  Male|           No|     No|       Yes|    22|         Yes|             Yes|    Fiber optic|                 No|                Yes|                 No|                 No|                Yes|                 No|Month-to-month|             Yes|Credit card (auto...|          89.1|      1949.4|   No|       [22.0,89.1,1949.4]|     [-0.4224697030234...|            1002.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  1.0|                    0.0|                   0.0|                 1.0|                     0.0|                0.0|                1.0|                    0.0|             0.0|                     0.0|                  3.0|          0.0|       (16,[3,5,8,11,15]...|\n",
            "|6713-OKOMC|Female|           No|     No|        No|    10|          No|No phone service|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|              No|        Mailed check|         29.75|       301.9|   No|       [10.0,29.75,301.9]|     [-0.9110943117076...|            4769.0|           1.0|                  0.0|            0.0|               0.0|                 1.0|                  2.0|                    1.0|                   1.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     1.0|                  1.0|          0.0|       (16,[0,4,5,6,7,14...|\n",
            "|7892-POOKP|Female|           No|    Yes|        No|    28|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         104.8|     3046.05|  Yes|     [28.0,104.8,3046.05]|     [-0.1781573986813...|            5603.0|           1.0|                  0.0|            1.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                1.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          1.0|       (16,[0,2,5,9,10,1...|\n",
            "|6388-TABGU|  Male|           No|     No|       Yes|    62|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|      One year|              No|Bank transfer (au...|         56.15|     3487.95|   No|     [62.0,56.15,3487.95]|     [1.20627899259056...|            4533.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  0.0|                    1.0|                   1.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             2.0|                     1.0|                  2.0|          0.0|       (16,[3,6,7,8,13,1...|\n",
            "|9763-GRSKD|  Male|           No|    Yes|       Yes|    13|         Yes|              No|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         49.95|      587.45|   No|      [13.0,49.95,587.45]|     [-0.7889381595366...|            6870.0|           0.0|                  0.0|            1.0|               1.0|                 0.0|                  0.0|                    1.0|                   1.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  1.0|          0.0|       (16,[2,3,6,7,15],...|\n",
            "|7469-LKBCI|  Male|           No|     No|        No|    16|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      Two year|              No|Credit card (auto...|         18.95|       326.8|   No|       [16.0,18.95,326.8]|     [-0.6667820073655...|            5287.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    2.0|                   2.0|                 2.0|                     2.0|                2.0|                2.0|                    2.0|             1.0|                     1.0|                  3.0|          0.0|       [0.0,0.0,0.0,0.0,...|\n",
            "|8091-TTVAX|  Male|           No|    Yes|        No|    58|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|      One year|              No|Credit card (auto...|        100.35|      5681.1|   No|     [58.0,100.35,5681.1]|     [1.04340412302915...|            5750.0|           0.0|                  0.0|            1.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             2.0|                     1.0|                  3.0|          0.0|       (16,[2,5,9,11,12,...|\n",
            "|0280-XJGEX|  Male|           No|     No|        No|    49|         Yes|             Yes|    Fiber optic|                 No|                Yes|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|Bank transfer (au...|         103.7|      5036.3|  Yes|      [49.0,103.7,5036.3]|     [0.67693566651600...|             174.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 1.0|                     1.0|                0.0|                1.0|                    1.0|             0.0|                     0.0|                  2.0|          1.0|       (16,[5,8,9,11,12,...|\n",
            "|5129-JLPIS|  Male|           No|     No|        No|    25|         Yes|              No|    Fiber optic|                Yes|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         105.5|     2686.05|   No|     [25.0,105.5,2686.05]|     [-0.3003135508523...|            3614.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   1.0|                 0.0|                     1.0|                1.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          0.0|       (16,[7,9,10,11,12...|\n",
            "|3655-SNQYZ|Female|           No|    Yes|       Yes|    69|         Yes|             Yes|    Fiber optic|                Yes|                Yes|                Yes|                Yes|                Yes|                Yes|      Two year|              No|Credit card (auto...|        113.25|     7895.15|   No|     [69.0,113.25,7895...|     [1.49131001432301...|            2556.0|           1.0|                  0.0|            1.0|               1.0|                 0.0|                  1.0|                    0.0|                   1.0|                 1.0|                     1.0|                1.0|                1.0|                    1.0|             1.0|                     1.0|                  3.0|          0.0|       [1.0,0.0,1.0,1.0,...|\n",
            "|8191-XWSZG|Female|           No|     No|        No|    52|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      One year|              No|        Mailed check|         20.65|     1022.95|   No|     [52.0,20.65,1022.95]|     [0.79909181868705...|            5819.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    2.0|                   2.0|                 2.0|                     2.0|                2.0|                2.0|                    2.0|             2.0|                     1.0|                  1.0|          0.0|       [1.0,0.0,0.0,0.0,...|\n",
            "|9959-WOFKT|  Male|           No|     No|       Yes|    71|         Yes|             Yes|    Fiber optic|                Yes|                 No|                Yes|                 No|                Yes|                Yes|      Two year|              No|Bank transfer (au...|         106.7|     7382.25|   No|     [71.0,106.7,7382.25]|     [1.57274744910371...|            7018.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  1.0|                    0.0|                   1.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             1.0|                     1.0|                  2.0|          0.0|       (16,[3,5,7,9,11,1...|\n",
            "|4190-MFLUW|Female|           No|    Yes|       Yes|    10|         Yes|              No|            DSL|                 No|                 No|                Yes|                Yes|                 No|                 No|Month-to-month|              No|Credit card (auto...|          55.2|      528.35|  Yes|       [10.0,55.2,528.35]|     [-0.9110943117076...|            2937.0|           1.0|                  0.0|            1.0|               1.0|                 0.0|                  0.0|                    1.0|                   0.0|                 0.0|                     1.0|                1.0|                0.0|                    0.0|             0.0|                     1.0|                  3.0|          1.0|       (16,[0,2,3,6,9,10...|\n",
            "|4183-MYFRB|Female|           No|     No|        No|    21|         Yes|              No|    Fiber optic|                 No|                Yes|                Yes|                 No|                 No|                Yes|Month-to-month|             Yes|    Electronic check|         90.05|      1862.9|   No|      [21.0,90.05,1862.9]|     [-0.4631884204138...|            2928.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   0.0|                 1.0|                     1.0|                0.0|                0.0|                    1.0|             0.0|                     0.0|                  0.0|          0.0|       (16,[0,8,9,12],[1...|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+---------------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4G0bVH-vALJt"
      },
      "source": [
        "Now let's combine categorical and numerical feature vectors."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "UrsFk-CZZgrV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fc4a443f-5584-4285-f88c-8b0759bbcc4e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+---------------------------+---------------------+\n",
            "|customerID|gender|SeniorCitizen|Partner|Dependents|tenure|PhoneService|   MultipleLines|InternetService|     OnlineSecurity|       OnlineBackup|   DeviceProtection|        TechSupport|        StreamingTV|    StreamingMovies|      Contract|PaperlessBilling|       PaymentMethod|MonthlyCharges|TotalCharges|Churn|numerical_features_vector|numerical_features_scaled|customerID_Indexed|gender_Indexed|SeniorCitizen_Indexed|Partner_Indexed|Dependents_Indexed|PhoneService_Indexed|MultipleLines_Indexed|InternetService_Indexed|OnlineSecurity_Indexed|OnlineBackup_Indexed|DeviceProtection_Indexed|TechSupport_Indexed|StreamingTV_Indexed|StreamingMovies_Indexed|Contract_Indexed|PaperlessBilling_Indexed|PaymentMethod_Indexed|Churn_Indexed|categorical_features_vector|final_features_vector|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+---------------------------+---------------------+\n",
            "|7590-VHVEG|Female|           No|    Yes|        No|     1|          No|No phone service|            DSL|                 No|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|         29.85|       29.85|   No|        [1.0,29.85,29.85]|     [-1.2775627682208...|            5374.0|           1.0|                  0.0|            1.0|               0.0|                 1.0|                  2.0|                    1.0|                   0.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  0.0|          0.0|       (16,[0,2,4,5,6,8]...| (19,[0,2,4,5,6,8,...|\n",
            "|5575-GNVDE|  Male|           No|     No|        No|    34|         Yes|              No|            DSL|                Yes|                 No|                Yes|                 No|                 No|                 No|      One year|              No|        Mailed check|         56.95|      1889.5|   No|      [34.0,56.95,1889.5]|     [0.06615490566075...|            3961.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    1.0|                   1.0|                 0.0|                     1.0|                0.0|                0.0|                    0.0|             2.0|                     1.0|                  1.0|          0.0|       (16,[6,7,9,13,14,...| (19,[6,7,9,13,14,...|\n",
            "|3668-QPYBK|  Male|           No|     No|        No|     2|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         53.85|      108.15|  Yes|       [2.0,53.85,108.15]|     [-1.2368440508304...|            2564.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    1.0|                   1.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  1.0|          1.0|       (16,[6,7,8,15],[1...| (19,[6,7,8,15,16,...|\n",
            "|7795-CFOCW|  Male|           No|     No|        No|    45|          No|No phone service|            DSL|                Yes|                 No|                Yes|                Yes|                 No|                 No|      One year|              No|Bank transfer (au...|          42.3|     1840.75|   No|      [45.0,42.3,1840.75]|     [0.51406079695460...|            5534.0|           0.0|                  0.0|            0.0|               0.0|                 1.0|                  2.0|                    1.0|                   1.0|                 0.0|                     1.0|                1.0|                0.0|                    0.0|             2.0|                     1.0|                  2.0|          0.0|       (16,[4,5,6,7,9,10...| [0.0,0.0,0.0,0.0,...|\n",
            "|9237-HQITU|Female|           No|     No|        No|     2|         Yes|              No|    Fiber optic|                 No|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|    Electronic check|          70.7|      151.65|  Yes|        [2.0,70.7,151.65]|     [-1.2368440508304...|            6510.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   0.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  0.0|          1.0|             (16,[0],[1.0])| (19,[0,16,17,18],...|\n",
            "|9305-CDSKC|Female|           No|     No|        No|     8|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         99.65|       820.5|  Yes|        [8.0,99.65,820.5]|     [-0.9925317464883...|            6550.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          1.0|       (16,[0,5,9,11,12]...| (19,[0,5,9,11,12,...|\n",
            "|1452-KIOVK|  Male|           No|     No|       Yes|    22|         Yes|             Yes|    Fiber optic|                 No|                Yes|                 No|                 No|                Yes|                 No|Month-to-month|             Yes|Credit card (auto...|          89.1|      1949.4|   No|       [22.0,89.1,1949.4]|     [-0.4224697030234...|            1002.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  1.0|                    0.0|                   0.0|                 1.0|                     0.0|                0.0|                1.0|                    0.0|             0.0|                     0.0|                  3.0|          0.0|       (16,[3,5,8,11,15]...| (19,[3,5,8,11,15,...|\n",
            "|6713-OKOMC|Female|           No|     No|        No|    10|          No|No phone service|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|              No|        Mailed check|         29.75|       301.9|   No|       [10.0,29.75,301.9]|     [-0.9110943117076...|            4769.0|           1.0|                  0.0|            0.0|               0.0|                 1.0|                  2.0|                    1.0|                   1.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     1.0|                  1.0|          0.0|       (16,[0,4,5,6,7,14...| (19,[0,4,5,6,7,14...|\n",
            "|7892-POOKP|Female|           No|    Yes|        No|    28|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         104.8|     3046.05|  Yes|     [28.0,104.8,3046.05]|     [-0.1781573986813...|            5603.0|           1.0|                  0.0|            1.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                1.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          1.0|       (16,[0,2,5,9,10,1...| (19,[0,2,5,9,10,1...|\n",
            "|6388-TABGU|  Male|           No|     No|       Yes|    62|         Yes|              No|            DSL|                Yes|                Yes|                 No|                 No|                 No|                 No|      One year|              No|Bank transfer (au...|         56.15|     3487.95|   No|     [62.0,56.15,3487.95]|     [1.20627899259056...|            4533.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  0.0|                    1.0|                   1.0|                 1.0|                     0.0|                0.0|                0.0|                    0.0|             2.0|                     1.0|                  2.0|          0.0|       (16,[3,6,7,8,13,1...| (19,[3,6,7,8,13,1...|\n",
            "|9763-GRSKD|  Male|           No|    Yes|       Yes|    13|         Yes|              No|            DSL|                Yes|                 No|                 No|                 No|                 No|                 No|Month-to-month|             Yes|        Mailed check|         49.95|      587.45|   No|      [13.0,49.95,587.45]|     [-0.7889381595366...|            6870.0|           0.0|                  0.0|            1.0|               1.0|                 0.0|                  0.0|                    1.0|                   1.0|                 0.0|                     0.0|                0.0|                0.0|                    0.0|             0.0|                     0.0|                  1.0|          0.0|       (16,[2,3,6,7,15],...| (19,[2,3,6,7,15,1...|\n",
            "|7469-LKBCI|  Male|           No|     No|        No|    16|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      Two year|              No|Credit card (auto...|         18.95|       326.8|   No|       [16.0,18.95,326.8]|     [-0.6667820073655...|            5287.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    2.0|                   2.0|                 2.0|                     2.0|                2.0|                2.0|                    2.0|             1.0|                     1.0|                  3.0|          0.0|       [0.0,0.0,0.0,0.0,...| [0.0,0.0,0.0,0.0,...|\n",
            "|8091-TTVAX|  Male|           No|    Yes|        No|    58|         Yes|             Yes|    Fiber optic|                 No|                 No|                Yes|                 No|                Yes|                Yes|      One year|              No|Credit card (auto...|        100.35|      5681.1|   No|     [58.0,100.35,5681.1]|     [1.04340412302915...|            5750.0|           0.0|                  0.0|            1.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             2.0|                     1.0|                  3.0|          0.0|       (16,[2,5,9,11,12,...| (19,[2,5,9,11,12,...|\n",
            "|0280-XJGEX|  Male|           No|     No|        No|    49|         Yes|             Yes|    Fiber optic|                 No|                Yes|                Yes|                 No|                Yes|                Yes|Month-to-month|             Yes|Bank transfer (au...|         103.7|      5036.3|  Yes|      [49.0,103.7,5036.3]|     [0.67693566651600...|             174.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  1.0|                    0.0|                   0.0|                 1.0|                     1.0|                0.0|                1.0|                    1.0|             0.0|                     0.0|                  2.0|          1.0|       (16,[5,8,9,11,12,...| (19,[5,8,9,11,12,...|\n",
            "|5129-JLPIS|  Male|           No|     No|        No|    25|         Yes|              No|    Fiber optic|                Yes|                 No|                Yes|                Yes|                Yes|                Yes|Month-to-month|             Yes|    Electronic check|         105.5|     2686.05|   No|     [25.0,105.5,2686.05]|     [-0.3003135508523...|            3614.0|           0.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   1.0|                 0.0|                     1.0|                1.0|                1.0|                    1.0|             0.0|                     0.0|                  0.0|          0.0|       (16,[7,9,10,11,12...| (19,[7,9,10,11,12...|\n",
            "|3655-SNQYZ|Female|           No|    Yes|       Yes|    69|         Yes|             Yes|    Fiber optic|                Yes|                Yes|                Yes|                Yes|                Yes|                Yes|      Two year|              No|Credit card (auto...|        113.25|     7895.15|   No|     [69.0,113.25,7895...|     [1.49131001432301...|            2556.0|           1.0|                  0.0|            1.0|               1.0|                 0.0|                  1.0|                    0.0|                   1.0|                 1.0|                     1.0|                1.0|                1.0|                    1.0|             1.0|                     1.0|                  3.0|          0.0|       [1.0,0.0,1.0,1.0,...| [1.0,0.0,1.0,1.0,...|\n",
            "|8191-XWSZG|Female|           No|     No|        No|    52|         Yes|              No|             No|No internet service|No internet service|No internet service|No internet service|No internet service|No internet service|      One year|              No|        Mailed check|         20.65|     1022.95|   No|     [52.0,20.65,1022.95]|     [0.79909181868705...|            5819.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    2.0|                   2.0|                 2.0|                     2.0|                2.0|                2.0|                    2.0|             2.0|                     1.0|                  1.0|          0.0|       [1.0,0.0,0.0,0.0,...| [1.0,0.0,0.0,0.0,...|\n",
            "|9959-WOFKT|  Male|           No|     No|       Yes|    71|         Yes|             Yes|    Fiber optic|                Yes|                 No|                Yes|                 No|                Yes|                Yes|      Two year|              No|Bank transfer (au...|         106.7|     7382.25|   No|     [71.0,106.7,7382.25]|     [1.57274744910371...|            7018.0|           0.0|                  0.0|            0.0|               1.0|                 0.0|                  1.0|                    0.0|                   1.0|                 0.0|                     1.0|                0.0|                1.0|                    1.0|             1.0|                     1.0|                  2.0|          0.0|       (16,[3,5,7,9,11,1...| [0.0,0.0,0.0,1.0,...|\n",
            "|4190-MFLUW|Female|           No|    Yes|       Yes|    10|         Yes|              No|            DSL|                 No|                 No|                Yes|                Yes|                 No|                 No|Month-to-month|              No|Credit card (auto...|          55.2|      528.35|  Yes|       [10.0,55.2,528.35]|     [-0.9110943117076...|            2937.0|           1.0|                  0.0|            1.0|               1.0|                 0.0|                  0.0|                    1.0|                   0.0|                 0.0|                     1.0|                1.0|                0.0|                    0.0|             0.0|                     1.0|                  3.0|          1.0|       (16,[0,2,3,6,9,10...| (19,[0,2,3,6,9,10...|\n",
            "|4183-MYFRB|Female|           No|     No|        No|    21|         Yes|              No|    Fiber optic|                 No|                Yes|                Yes|                 No|                 No|                Yes|Month-to-month|             Yes|    Electronic check|         90.05|      1862.9|   No|      [21.0,90.05,1862.9]|     [-0.4631884204138...|            2928.0|           1.0|                  0.0|            0.0|               0.0|                 0.0|                  0.0|                    0.0|                   0.0|                 1.0|                     1.0|                0.0|                0.0|                    1.0|             0.0|                     0.0|                  0.0|          0.0|       (16,[0,8,9,12],[1...| (19,[0,8,9,12,16,...|\n",
            "+----------+------+-------------+-------+----------+------+------------+----------------+---------------+-------------------+-------------------+-------------------+-------------------+-------------------+-------------------+--------------+----------------+--------------------+--------------+------------+-----+-------------------------+-------------------------+------------------+--------------+---------------------+---------------+------------------+--------------------+---------------------+-----------------------+----------------------+--------------------+------------------------+-------------------+-------------------+-----------------------+----------------+------------------------+---------------------+-------------+---------------------------+---------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ],
      "source": [
        "final_vector_assembler = VectorAssembler(inputCols=[\"categorical_features_vector\", \"numerical_features_scaled\"], outputCol=\"final_features_vector\")\n",
        "data = final_vector_assembler.transform(data)\n",
        "\n",
        "data.show()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.select([\"final_features_vector\", \"Churn_Indexed\"]).show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xgZsjQ12hfcY",
        "outputId": "afba2349-f1de-4244-dabf-817632e01dfa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+---------------------+-------------+\n",
            "|final_features_vector|Churn_Indexed|\n",
            "+---------------------+-------------+\n",
            "| (19,[0,2,4,5,6,8,...|          0.0|\n",
            "| (19,[6,7,9,13,14,...|          0.0|\n",
            "| (19,[6,7,8,15,16,...|          1.0|\n",
            "| [0.0,0.0,0.0,0.0,...|          0.0|\n",
            "| (19,[0,16,17,18],...|          1.0|\n",
            "| (19,[0,5,9,11,12,...|          1.0|\n",
            "| (19,[3,5,8,11,15,...|          0.0|\n",
            "| (19,[0,4,5,6,7,14...|          0.0|\n",
            "| (19,[0,2,5,9,10,1...|          1.0|\n",
            "| (19,[3,6,7,8,13,1...|          0.0|\n",
            "| (19,[2,3,6,7,15,1...|          0.0|\n",
            "| [0.0,0.0,0.0,0.0,...|          0.0|\n",
            "| (19,[2,5,9,11,12,...|          0.0|\n",
            "| (19,[5,8,9,11,12,...|          1.0|\n",
            "| (19,[7,9,10,11,12...|          0.0|\n",
            "| [1.0,0.0,1.0,1.0,...|          0.0|\n",
            "| [1.0,0.0,0.0,0.0,...|          0.0|\n",
            "| [0.0,0.0,0.0,1.0,...|          0.0|\n",
            "| (19,[0,2,3,6,9,10...|          1.0|\n",
            "| (19,[0,8,9,12,16,...|          0.0|\n",
            "+---------------------+-------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_og11F0MdrYE"
      },
      "source": [
        "### **Task 5 - Model Training**\n",
        "- Train and Test data splitting\n",
        "- Creating our model\n",
        "- Training our model\n",
        "- Make initial predictions using our model\n",
        "\n",
        "In this task, we are going to start training our model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8VFwkblddkdV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ded39b58-5643-49e4-d172-868b2bc498d5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4930\n",
            "2112\n"
          ]
        }
      ],
      "source": [
        "train, test = data.randomSplit([0.7, 0.3], seed=100)\n",
        "\n",
        "print(train.count())\n",
        "print(test.count())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aiAJrl8oEKIk"
      },
      "source": [
        "Now let's create and train our desicion tree"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dt = DecisionTreeClassifier(featuresCol=\"final_features_vector\", labelCol= \"Churn_Indexed\", maxDepth=6)\n",
        "model = dt.fit(train)"
      ],
      "metadata": {
        "id": "zH7VLfHclLvU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cy_-7W2LEO9j"
      },
      "source": [
        "Let's make predictions on our test data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AqU9-y6dEOqq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "071b91db-733b-409f-b4c3-c457933dcd8a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+-----+----------+\n",
            "|Churn|prediction|\n",
            "+-----+----------+\n",
            "|  Yes|       1.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|  Yes|       1.0|\n",
            "|   No|       0.0|\n",
            "|  Yes|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|  Yes|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       1.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "|   No|       0.0|\n",
            "+-----+----------+\n",
            "only showing top 20 rows\n",
            "\n"
          ]
        }
      ],
      "source": [
        "predictions_test = model.transform(test)\n",
        "predictions_test.select([\"Churn\", \"prediction\"]).show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sZXX1rqz8hoT"
      },
      "source": [
        "### **Task 6 - Model Evaluation**\n",
        "- Calculating area under the ROC curve for the `test` set\n",
        "- Calculating area under the ROC curve for the `training` set\n",
        "- Hyper parameter tuning"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "V8Ldw-rno18o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cd9e87e6-753f-4797-a56a-756512e71e78"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.7968240892739675"
            ]
          },
          "metadata": {},
          "execution_count": 174
        }
      ],
      "source": [
        "evaluator = BinaryClassificationEvaluator(labelCol=\"Churn_Indexed\")\n",
        "auc_test = evaluator.evaluate(predictions_test, {evaluator.metricName : \"areaUnderROC\"})\n",
        "auc_test"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nXpG_p4BGEhq"
      },
      "source": [
        "Let's get the AUC for our `training` set"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LVkrmoC8GErZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "06655b63-9a3f-4b19-bba8-50f9444e3a24"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.797607974377661"
            ]
          },
          "metadata": {},
          "execution_count": 175
        }
      ],
      "source": [
        "predictions_train = model.transform(train)\n",
        "auc_train = evaluator.evaluate(predictions_train, {evaluator.metricName : \"areaUnderROC\"})\n",
        "auc_train"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HH4ZH3yFHbvS"
      },
      "source": [
        "**Hyper parameter tuning**\n",
        "\n",
        "Let's find the best `maxDepth` parameter for our DT model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CwkzV8xLHNlE"
      },
      "outputs": [],
      "source": [
        "def evaluate_dt(mode_params):\n",
        "      test_accuracies = []\n",
        "      train_accuracies = []\n",
        "\n",
        "      for maxD in mode_params:\n",
        "        # train the model based on the maxD\n",
        "        decision_tree = DecisionTreeClassifier(featuresCol = 'final_features_vector', labelCol = 'Churn_Indexed', maxDepth = maxD)\n",
        "        dtModel = decision_tree.fit(train)\n",
        "\n",
        "        # calculating test error\n",
        "        predictions_test = dtModel.transform(test)\n",
        "        evaluator = BinaryClassificationEvaluator(labelCol=\"Churn_Indexed\")\n",
        "        auc_test = evaluator.evaluate(predictions_test, {evaluator.metricName: \"areaUnderROC\"})\n",
        "        # recording the accuracy\n",
        "        test_accuracies.append(auc_test)\n",
        "\n",
        "        # calculating training error\n",
        "        predictions_training = dtModel.transform(train)\n",
        "        evaluator = BinaryClassificationEvaluator(labelCol=\"Churn_Indexed\")\n",
        "        auc_training = evaluator.evaluate(predictions_training, {evaluator.metricName: \"areaUnderROC\"})\n",
        "        train_accuracies.append(auc_training)\n",
        "\n",
        "      return(test_accuracies, train_accuracies)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "37QrYjWvcE4Z"
      },
      "source": [
        "Let's define `params` list to evaluate our model iteratively with differe maxDepth parameter.  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6rVz17-jIoVC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d6070479-8583-46f8-927a-d430c82afc72"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.7737711024910238, 0.7721112330375414, 0.6732017750857608, 0.5647403286677019, 0.797607974377661, 0.7600331160893413, 0.7616399322585649, 0.7851198149534798, 0.82591977092655, 0.8633625692715379, 0.8899907318309699, 0.9236516335825413, 0.9402616892332477, 0.9521037242780167, 0.9662424766482165, 0.9763120733848871, 0.9807472862567603, 0.9853808496196841, 0.9883361989750398]\n",
            "[0.7918744332963926, 0.7678230877272001, 0.6938514510575503, 0.5664944085244075, 0.7968240892739675, 0.7464077658395512, 0.7486976928866473, 0.7390283218461648, 0.7568262227463716, 0.7717528253693575, 0.770466222983424, 0.7493673661690539, 0.7371905724224987, 0.7208594338001293, 0.7102797812005524, 0.704298946894316, 0.7036452746549405, 0.6956814962753128, 0.6895714683623821]\n"
          ]
        }
      ],
      "source": [
        "maxDepths = [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]\n",
        "test_accs, train_accs = evaluate_dt(maxDepths)\n",
        "print(train_accs)\n",
        "print(test_accs)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3uBlqQ2-cWCm"
      },
      "source": [
        "Let's visualize our results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PqFqOfKvJATk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "01b05598-8e5f-4879-e39f-4aafe140968b"
      },
      "outputs": [
        {
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          "metadata": {}
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      ],
      "source": [
        "df = pd.DataFrame()\n",
        "df[\"maxDepth\"] = maxDepths\n",
        "df[\"trainacc\"] = train_accs\n",
        "df[\"testacc\"] = test_accs\n",
        "\n",
        "px.line(df, x = \"maxDepth\", y = [\"trainacc\", \"testacc\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "koCUPBFUKDIZ"
      },
      "source": [
        "### **7 - Model Deployment**\n",
        "- Giving Recommendations using our model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xomU5qnMUdWJ"
      },
      "source": [
        "\n",
        "\n",
        "We were asked to recommend a solution to reduce the customer churn.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1FIFIqdLsAvq",
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          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "bfb3d7ac-f87d-4415-db4c-c22931b08351"
      },
      "outputs": [
        {
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            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "feature_importance = model.featureImportances\n",
        "scores = [score for i, score in enumerate(feature_importance)]\n",
        "\n",
        "df = pd.DataFrame(scores, columns=[\"Score\"], index = categorical_columns_indexed + numerical_columns)\n",
        "px.bar(df, y=\"Score\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n_FrIiJwWuwg"
      },
      "source": [
        "Let's create a bar chart to visualize the customer churn per contract type"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "V4eObw2aK7Qp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "0e0334ce-86cd-4f04-ac3a-8edef88bb02a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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          "metadata": {}
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      ],
      "source": [
        "df = data.groupBy([\"Contract\", \"Churn\"]).count().toPandas()\n",
        "px.bar(df, x = \"Contract\", y = \"count\", color = \"Churn\")"
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      "source": [
        "The bar chart displays the number of churned customers based on their contract type. It is evident that customers with a \"Month-to-month\" contract have a higher churn rate compared to those with \"One year\" or \"Two year\" contracts. As a recommendation, the telecommunication company could consider offering incentives or discounts to encourage customers with month-to-month contracts to switch to longer-term contracts."
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