Predicting_Customer_Behaviour.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "#                **PREDICTING CUSTOMER BEHAVIOR**\n",
        "\n",
        "\n",
        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)\n"
      ],
      "metadata": {
        "id": "0H58E_oPVa_P"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Understanding the Data**\n",
        "\n",
        "The data is customer dataset which consists of;\n",
        "*   UserID: This is a unique id generated for each customers that made purchase.\n",
        "*   Gender: The gender of the customers to know whether they are male or female\n",
        "*   EstimatedSalary: This consists of each customers estimated salary\n",
        "*   age: This is the age of the customers\n",
        "*   Purchased: This consists of binary values 0's and 1's where 0 indicates not-purchased and 1 indicates pucshased\n",
        "\n"
      ],
      "metadata": {
        "id": "nzz6iB0e2QP-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Importing the necessary libraries**"
      ],
      "metadata": {
        "id": "TZZdQExh1ED5"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "jtSGmQe3icnG"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "import plotly.io as pio\n",
        "import itertools"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Load the dataset***"
      ],
      "metadata": {
        "id": "omIhPZeI1y0D"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cb = pd.read_csv(\"/content/drive/MyDrive/Customer_Behaviour.csv\")\n",
        "print(cb.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BFnrZxS31TZn",
        "outputId": "f5daec04-a491-4fb5-8f30-9e1f87de49c1"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    User ID  Gender  Age  EstimatedSalary  Purchased\n",
            "0  15624510    Male   19            19000          0\n",
            "1  15810944    Male   35            20000          0\n",
            "2  15668575  Female   26            43000          0\n",
            "3  15603246  Female   27            57000          0\n",
            "4  15804002    Male   19            76000          0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cb.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "49wCjln61xnm",
        "outputId": "cb184909-7e70-43dd-925e-e25ad049d6ba"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 400 entries, 0 to 399\n",
            "Data columns (total 5 columns):\n",
            " #   Column           Non-Null Count  Dtype \n",
            "---  ------           --------------  ----- \n",
            " 0   User ID          400 non-null    int64 \n",
            " 1   Gender           400 non-null    object\n",
            " 2   Age              400 non-null    int64 \n",
            " 3   EstimatedSalary  400 non-null    int64 \n",
            " 4   Purchased        400 non-null    int64 \n",
            "dtypes: int64(4), object(1)\n",
            "memory usage: 15.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cb.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "XJfniuql19Cy",
        "outputId": "ca63f5d6-4eea-4114-f11b-e62e663ed8ae"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            User ID         Age  EstimatedSalary   Purchased\n",
              "count  4.000000e+02  400.000000       400.000000  400.000000\n",
              "mean   1.569154e+07   37.655000     69742.500000    0.357500\n",
              "std    7.165832e+04   10.482877     34096.960282    0.479864\n",
              "min    1.556669e+07   18.000000     15000.000000    0.000000\n",
              "25%    1.562676e+07   29.750000     43000.000000    0.000000\n",
              "50%    1.569434e+07   37.000000     70000.000000    0.000000\n",
              "75%    1.575036e+07   46.000000     88000.000000    1.000000\n",
              "max    1.581524e+07   60.000000    150000.000000    1.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3a9a27ef-6db7-49bc-8661-a402def4923f\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User ID</th>\n",
              "      <th>Age</th>\n",
              "      <th>EstimatedSalary</th>\n",
              "      <th>Purchased</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>4.000000e+02</td>\n",
              "      <td>400.000000</td>\n",
              "      <td>400.000000</td>\n",
              "      <td>400.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.569154e+07</td>\n",
              "      <td>37.655000</td>\n",
              "      <td>69742.500000</td>\n",
              "      <td>0.357500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>7.165832e+04</td>\n",
              "      <td>10.482877</td>\n",
              "      <td>34096.960282</td>\n",
              "      <td>0.479864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.556669e+07</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>15000.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.562676e+07</td>\n",
              "      <td>29.750000</td>\n",
              "      <td>43000.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.569434e+07</td>\n",
              "      <td>37.000000</td>\n",
              "      <td>70000.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.575036e+07</td>\n",
              "      <td>46.000000</td>\n",
              "      <td>88000.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.581524e+07</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>150000.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3a9a27ef-6db7-49bc-8661-a402def4923f')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-3a9a27ef-6db7-49bc-8661-a402def4923f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-3a9a27ef-6db7-49bc-8661-a402def4923f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-827b8259-3b27-4703-b5b5-5e98a8156559\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-827b8259-3b27-4703-b5b5-5e98a8156559')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    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-827b8259-3b27-4703-b5b5-5e98a8156559 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Interpretation of the Descriptive Statistics\n",
        "- The descriptive statistics shows that each feature of the datasets consists of 400 entries. Which indicates that there are no missing values.\n",
        "- Also, the age features shows that the minimum customer age is 18 while the maximum customer age is 60 and average age is 37.\n",
        "- The minimum expected salary is 15,000 while the maximum salary is 150,000 and the average expected salary of the customer is 70,000.  "
      ],
      "metadata": {
        "id": "BxlgXi0IBEoZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Checking whether the dataset has empty or missing values\n",
        "\n",
        "cb.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XPPWY2niBCEh",
        "outputId": "950ca14d-b7a2-4834-c132-56c2f66bc7bc"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "User ID            0\n",
              "Gender             0\n",
              "Age                0\n",
              "EstimatedSalary    0\n",
              "Purchased          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "As shown in the result, the dataset is balanced. Meaning there are no missing values."
      ],
      "metadata": {
        "id": "_E7ZWBMIClVl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# checking duplicate values\n",
        "\n",
        "cb.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gqT3s06iCgip",
        "outputId": "124a5676-da53-4fe2-bf8b-7f352555d2b0"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.histplot(data=cb, x='Age', kde=True, hue='Purchased');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "wlgnDyLgC329",
        "outputId": "a71d7ac2-3fcb-46a1-ee00-98230efd33c9"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.histplot(data=cb, x='EstimatedSalary', kde=True, hue='Purchased')"
      ],
      "metadata": {
        "id": "wWlugXoYG9zl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "outputId": "8e78c37e-2771-4fe8-9559-e15ad69ff0f1"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='EstimatedSalary', ylabel='Count'>"
            ]
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(data=cb, x='Purchased', palette=['red', 'blue']);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 536
        },
        "id": "WHBY4gVDImPB",
        "outputId": "9139fac7-e901-4854-ebfb-25134ff2f752"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-9-52295a7730c9>:1: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.countplot(data=cb, x='Purchased', palette=['red', 'blue']);\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# fig, axes = plt.subplots(figsize=(10,8))\n",
        "slices = cb.Purchased.value_counts().values\n",
        "chart = ['Not Purchaesd(0)', 'Purchased(1)']\n",
        "plt.pie(slices, labels=chart, colors=['red', 'blue'],  autopct='%1.1f%%', shadow=True);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "Wk2meJIbdQCX",
        "outputId": "0ca9eaa4-b212-4b7b-9abc-1029f8770171"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Data Preprocessing**"
      ],
      "metadata": {
        "id": "TARGIUC3fshY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# dropping the userID column since its not so important in the dataset\n",
        "\n",
        "cb.drop('User ID', axis=1, inplace=True)\n",
        "cb"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "NAa-HzvVesID",
        "outputId": "05c92aef-ba84-433c-fbe7-31285061d3a4"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Gender  Age  EstimatedSalary  Purchased\n",
              "0      Male   19            19000          0\n",
              "1      Male   35            20000          0\n",
              "2    Female   26            43000          0\n",
              "3    Female   27            57000          0\n",
              "4      Male   19            76000          0\n",
              "..      ...  ...              ...        ...\n",
              "395  Female   46            41000          1\n",
              "396    Male   51            23000          1\n",
              "397  Female   50            20000          1\n",
              "398    Male   36            33000          0\n",
              "399  Female   49            36000          1\n",
              "\n",
              "[400 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-50aa8f29-eda5-43fc-97fc-e8ea684fb53e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Gender</th>\n",
              "      <th>Age</th>\n",
              "      <th>EstimatedSalary</th>\n",
              "      <th>Purchased</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Male</td>\n",
              "      <td>19</td>\n",
              "      <td>19000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>35</td>\n",
              "      <td>20000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Female</td>\n",
              "      <td>26</td>\n",
              "      <td>43000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Female</td>\n",
              "      <td>27</td>\n",
              "      <td>57000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Male</td>\n",
              "      <td>19</td>\n",
              "      <td>76000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>395</th>\n",
              "      <td>Female</td>\n",
              "      <td>46</td>\n",
              "      <td>41000</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>396</th>\n",
              "      <td>Male</td>\n",
              "      <td>51</td>\n",
              "      <td>23000</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>397</th>\n",
              "      <td>Female</td>\n",
              "      <td>50</td>\n",
              "      <td>20000</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>398</th>\n",
              "      <td>Male</td>\n",
              "      <td>36</td>\n",
              "      <td>33000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>399</th>\n",
              "      <td>Female</td>\n",
              "      <td>49</td>\n",
              "      <td>36000</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>400 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-50aa8f29-eda5-43fc-97fc-e8ea684fb53e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-50aa8f29-eda5-43fc-97fc-e8ea684fb53e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-50aa8f29-eda5-43fc-97fc-e8ea684fb53e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-0e880e20-b154-404f-8aa8-9c279a349fe3\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0e880e20-b154-404f-8aa8-9c279a349fe3')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    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-0e880e20-b154-404f-8aa8-9c279a349fe3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Creating New Features"
      ],
      "metadata": {
        "id": "7GXyml-WgisG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "## The below features will be created to enhance the predictive power of the model:\n",
        "*   Age group\n",
        "*   Income level\n",
        "*   Gender Encoding\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "aH7i4oYHg54x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Age Group\n",
        "bins = [18, 30, 45, 60]\n",
        "labels = ['18-30', '31-45', '46-60']\n",
        "\n",
        "cb['Age_Group']=pd.cut(cb['Age'], bins=bins, labels=labels, right=False)\n",
        "cb.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "hd493trRgIXu",
        "outputId": "066aac7a-4167-4b02-a22d-6b7bea47c9b4"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Gender  Age  EstimatedSalary  Purchased Age_Group\n",
              "0    Male   19            19000          0     18-30\n",
              "1    Male   35            20000          0     31-45\n",
              "2  Female   26            43000          0     18-30\n",
              "3  Female   27            57000          0     18-30\n",
              "4    Male   19            76000          0     18-30"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-84354652-c77f-4b97-aef2-cc76aaa3cdc6\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Gender</th>\n",
              "      <th>Age</th>\n",
              "      <th>EstimatedSalary</th>\n",
              "      <th>Purchased</th>\n",
              "      <th>Age_Group</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Male</td>\n",
              "      <td>19</td>\n",
              "      <td>19000</td>\n",
              "      <td>0</td>\n",
              "      <td>18-30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>35</td>\n",
              "      <td>20000</td>\n",
              "      <td>0</td>\n",
              "      <td>31-45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Female</td>\n",
              "      <td>26</td>\n",
              "      <td>43000</td>\n",
              "      <td>0</td>\n",
              "      <td>18-30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Female</td>\n",
              "      <td>27</td>\n",
              "      <td>57000</td>\n",
              "      <td>0</td>\n",
              "      <td>18-30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Male</td>\n",
              "      <td>19</td>\n",
              "      <td>76000</td>\n",
              "      <td>0</td>\n",
              "      <td>18-30</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-84354652-c77f-4b97-aef2-cc76aaa3cdc6 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-84354652-c77f-4b97-aef2-cc76aaa3cdc6');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f5342a6a-6885-4cdc-a2c9-90ef02d6f671\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f5342a6a-6885-4cdc-a2c9-90ef02d6f671')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    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-f5342a6a-6885-4cdc-a2c9-90ef02d6f671 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(8,6))\n",
        "sns.countplot(x='Age_Group', data=cb, hue='Age_Group')\n",
        "plt.title('Distribution of Age Group')\n",
        "plt.xlabel('Age Group')\n",
        "plt.ylabel('Frequency')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "6KSdOqPFjdx2",
        "outputId": "82830a54-b280-453c-b377-ba3f7148980e"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "slices = cb['Age_Group'].value_counts().values\n",
        "chart = ['Young Adult (18-30)', 'Middle Age (31-45)', 'Senior Adult (46-60)']\n",
        "assert len(slices) == len(chart), \"Length mismatch between slices and labels\"\n",
        "plt.pie(slices, labels=chart, colors=['red', 'blue', 'green'],  autopct='%1.1f%%', shadow=True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "PlosFhSokhYf",
        "outputId": "cf68b028-cfdd-4db2-bf7e-23ef145b0fe1"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Income level feature"
      ],
      "metadata": {
        "id": "GKmqcSc1ZIEQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bins = [15000, 30000, 60000, 90000, 120000, 150000]\n",
        "income_labels = ['Very Low', 'Low', 'Medium', 'High', 'Very High']\n",
        "cb['Income_Level'] = pd.cut(cb['EstimatedSalary'], bins=bins, labels=income_labels, right=False)\n",
        "cb.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "6yuqKexDmUdw",
        "outputId": "b0ed1eb4-1186-4231-a283-4fe3fa50ac66"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Gender  Age  EstimatedSalary  Purchased Age_Group Income_Level\n",
              "0    Male   19            19000          0     18-30     Very Low\n",
              "1    Male   35            20000          0     31-45     Very Low\n",
              "2  Female   26            43000          0     18-30          Low\n",
              "3  Female   27            57000          0     18-30          Low\n",
              "4    Male   19            76000          0     18-30       Medium"
            ],
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              "          + ' to learn more about interactive tables.';\n",
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              "\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "slices = cb['Income_Level'].value_counts().values\n",
        "income_labels = ['Very Low', 'Low', 'Medium', 'High', 'Very High']\n",
        "plt.pie(slices, labels=income_labels, colors=['red', 'blue', 'green', 'yellow', 'purple'], autopct='%1.1f%%', shadow=True);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "9W_nJ_ZLVCHX",
        "outputId": "616f1fac-232e-4888-d0f9-a04124d7244a"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Encoding the Income level\n",
        "\n",
        "Since income level is a categorical variable, we will need to encode it using ordinal encoder.\n"
      ],
      "metadata": {
        "id": "juJrHGAfK4JB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install category_encoders"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VMlhY1yahUsD",
        "outputId": "0c65442c-dbc5-4ab9-ce26-d0ab2ac75734"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting category_encoders\n",
            "  Downloading category_encoders-2.6.3-py2.py3-none-any.whl (81 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/81.9 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━\u001b[0m \u001b[32m71.7/81.9 kB\u001b[0m \u001b[31m2.0 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m81.9/81.9 kB\u001b[0m \u001b[31m1.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.14.0 in /usr/local/lib/python3.10/dist-packages (from category_encoders) (1.25.2)\n",
            "Requirement already satisfied: scikit-learn>=0.20.0 in /usr/local/lib/python3.10/dist-packages (from category_encoders) (1.2.2)\n",
            "Requirement already satisfied: scipy>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from category_encoders) (1.11.4)\n",
            "Requirement already satisfied: statsmodels>=0.9.0 in /usr/local/lib/python3.10/dist-packages (from category_encoders) (0.14.1)\n",
            "Requirement already satisfied: pandas>=1.0.5 in /usr/local/lib/python3.10/dist-packages (from category_encoders) (1.5.3)\n",
            "Requirement already satisfied: patsy>=0.5.1 in /usr/local/lib/python3.10/dist-packages (from category_encoders) (0.5.6)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.0.5->category_encoders) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.0.5->category_encoders) (2023.4)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from patsy>=0.5.1->category_encoders) (1.16.0)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.20.0->category_encoders) (1.3.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.20.0->category_encoders) (3.2.0)\n",
            "Requirement already satisfied: packaging>=21.3 in /usr/local/lib/python3.10/dist-packages (from statsmodels>=0.9.0->category_encoders) (23.2)\n",
            "Installing collected packages: category_encoders\n",
            "Successfully installed category_encoders-2.6.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import category_encoders as ce\n",
        "\n",
        "ordinal_encoder = ce.OrdinalEncoder(\n",
        "    cols=['Income_Level'],\n",
        "    mapping=[{'col': 'Income_Level', 'mapping':{'Very Low':0, 'Low':1, 'Medium':2, 'High':3, 'Very High':4}}])\n",
        "cb['Income_Level'] = ordinal_encoder.fit_transform(cb['Income_Level'])"
      ],
      "metadata": {
        "id": "KiJPL3oMK3hu"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Encoding the categporical feature['Gender'] to binary values"
      ],
      "metadata": {
        "id": "vR8NoddiZASv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cb['Gender'] = cb['Gender'].map({'Female':0, 'Male':1})\n",
        "cb.sample()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "rfKZ9_w6WH_r",
        "outputId": "7c95c21c-1fd9-4bb3-d682-ee55ecd649cf"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Gender  Age  EstimatedSalary  Purchased Age_Group  Income_Level\n",
              "284       1   48           141000          0     46-60           4.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5d48c0d3-d2bc-42a8-a82e-7d2fa233530a\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Gender</th>\n",
              "      <th>Age</th>\n",
              "      <th>EstimatedSalary</th>\n",
              "      <th>Purchased</th>\n",
              "      <th>Age_Group</th>\n",
              "      <th>Income_Level</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>284</th>\n",
              "      <td>1</td>\n",
              "      <td>48</td>\n",
              "      <td>141000</td>\n",
              "      <td>0</td>\n",
              "      <td>46-60</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5d48c0d3-d2bc-42a8-a82e-7d2fa233530a')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5d48c0d3-d2bc-42a8-a82e-7d2fa233530a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-5d48c0d3-d2bc-42a8-a82e-7d2fa233530a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "slices = cb['Gender'].value_counts().values\n",
        "gender = ['Male(1)', 'Female(0)']\n",
        "plt.pie(slices, labels=gender, colors=['red', 'blue'], autopct='%2.0f%%', shadow=True);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "ml7nexNqXw5H",
        "outputId": "19f64521-c6ed-4ec8-bafd-b457ea681c0f"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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BVsAFnDhP3dH9swSRjRvhscfMThE0VApnsG/jRna+9x7XHjtGekWF2XGkDz8G1gHFwEd4FoatwFe7H68EdvLFyGFP98/1vfyuX+AZGRR2/zwbWAnsBn7f/bMEmfvvh88+MztFUIg0O0Agqy4pYf1LLzG6uppJn35qdhw5jeN4CqAOSAfmAFu6vwf4b+DBk55/affX54BlJ92/F88i886T7luCZ8poLjAW+Gt/Bhf/6OyEO+6Ajz+GqCiz0wQ0LTT3obO9ndf/4z+o3byZr69dS4zdbnYkEblQ998Pv/iF2SkCmqaPemEYBh+99hrFO3Zwy549KgSRUPGrX8Enn5idIqCpFHpxYMsWtq9ezeXV1WRqHxWR0OFyeTbO0we9PqkUTlFXVsb6l15ikN3O9K1bzY4jIv3twAGd7XwaKoWTdHV08MELL1BXVsaCAweI0gVzRELT734HH3xgdoqApFLoZhgGW/72Nw5v3UqhzcaIffvMjiQiA8UwYPlyaG42O0nAUSl0O/7552x/5x1S09OZtWaN2XFEZKCVlsIPfmB2ioCjUgCcDgebV66ks72dGUePkqzN7kTCw/PP62ikU6gUgM82bKBo505GZGQwad06s+OIiD/98z+bnSCghH0pNNfV8ckbb2CLi+PiDRt0jQSRcLN+Pbz5ptkpAkZYl4JhGGx7+21qSkuZYBjk6UpqIuHpJz/xnMMg4V0KZQcPsvuDD0jNymLGu++aHUdEzLJ/P/zxj2anCAhhWwonFpc72tq4qKiIlOpqsyOJiJl+/nNoazM7henCthT2b9rE0U8/JTcjg8m6kpqIVFbCo4+ancJ0YVkKrQ0NfPzGG0TFxDDzo4904RwR8Xj0UaiqMjuFqcKyFLatWkV1cTH5CQnk7dpldhwRCRStrZ5ppDAWdqVQfugQu95/n5TsbCZu2UKELichIif74x89m+aFqbAqBZfTyeaVK7G3tJAZE0Pe7t1mRxKRQON0hvUuqmFVCp9v3szhHTvIyMtj/JYtWHVcsoj05m9/g40bzU5hirApBUdXFztWr8YaGcmgiAhGbd9udiQRCWRhuv1F2JTCkR07KD98mLThwxmzdau2sxCR09uyBcLwcPWwKAWXy8XuNWuwWCzEWq2M/fhjsyOJSDB47DGzE/hdWJRCyZ49lOzdS9rw4Yz89FNi2tvNjiQiweCtt+DQIbNT+FXIl4JhGOxaswa3y0VsbCzjNm82O5KIBAvDgN/+1uwUfhXypVB24ABFO3eSOnQouXv3ktDYaHYkEQkm//M/0NBgdgq/CelSMAyD3R9+SKfdTnxSEuM3bTI7kogEm7Y2eOops1P4TUiXQk1pKYc++YTU7GyGHDyonVBF5Pz8/veek9rCQEiXwt5162hvaiIhNZUCjRJE5HyVlcHf/252Cr8I2VJoqKxk34YNJGVmklpRQUZpqdmRRCSYhckUUsiWwmcbNtBcW0tSRgb5O3eaHUdEgt0//gFFRWanGHAhWQqtDQ3s+fBDBqWlEeF2k7t3r9mRRCTYGQY8/bTZKQZcSJbC/o8+oqGykpSsLIYeOkSM3W52JBEJBc89Bw6H2SkGVMiVgqOzk90ffEBcYiIRVqsuoiMi/aeqCl5/3ewUAyrkSqF03z7qyspIyc7G1t7OkIMHzY4kIqHk2WfNTjCgQq4UDm/ditvpJCo6mhF792J1u82OJCKh5MMPIYR3RgipUmhtaODw9u0kpqcDMEJXVhOR/uZwwKpVZqcYMCFVCsW7d9NcW8ugtDTiGhtJKyszO5KIhKI33jA7wYAJmVIwDIPPt2wh0mbDarWSs2+f2ZFEJFS98w6E6IW6QqYUao8d4/j+/SRlZgKoFERk4LS0wAcfmJ1iQIRMKRTv3k17czPxSUnENTVp6khEBlaITiGFRCm43W4OfvIJ0fHxWCwWjRJEZOC9+abnLOcQExKlUF1SQnVxMUndRx3lfPaZyYlEJOSVl8PWrWan6HchUQrH9u2jo7WV2EGDiGltZbCmjkTEH0JwCinoS8HtdnPw44+xdU8dpZeUYDE7lIiEB5VC4Dl16iijpMTkRCISNj77DA4fNjtFvwr6Uji2bx/27qkjQBfTERH/CrHRQlCXgmEYHNm+nei4OCwWC1F2O0m6DrOI+JNKIXC0NTZSe+wY8cnJgGeUEBGCh4iJSADbtAnq681O0W+CuhSqS0poa24mLikJgHStJ4iIv7nd8MknZqfoN0FfCm6nk8ioKEDrCSJikm3bzE7Qb4K6FI7t20dUTAwA1q4uUisqTE4kImFJpWC+9pYWqouLiT8xdXTsGBG6oI6ImEGlYL6akhLampqIO7HIrPUEETFLWRlUVpqdol8EbSlUl5TgcjiIstkASNd6goiYKURGC0FbCmWff05kdyFEOJ3a70hEzKVSME+n3U754cPeQ1EHl5UR6XSanEpEwppKwTw1paW0NzV5T1pLP3bM3EAiItu3m52gXwRnKZSU4OjsJCo6GoCkmhqTE4lI2KushOPHzU5xwYKyFMoPHcIaGYnF4tkkO6GhweREIiKExBRS0JWCo7OT459/7l1PAEgIoX1HRCSIqRT8r66sjNaGBm8pRHZ1EdvWZnIqERFUCmZoqqmhy24nOi4O0ChBRAJICCw2B10ptDY0YLFYvOsJg1QKIhIoams9tyAWdKXQfMpfuBaZRSSglJebneCCBF0p1JeVeXdGBU0fiUiACfLdmoOqFNxuN/UVFdhOKoVBGimISCDRSMF/7C0tdLa1YYuN9d6nkYKIBBSVgv+01NfTabd7SyHC5SKuudnkVCIiJ1Ep+E9rfT1dHR3eNYX4hgYiDMPkVCIiJ9Gagv+0dq8fRER4Yms9QUQCjkYK/tNSVwcnjQy0niAiAUel4D/15eXeC+sAWk8QkcBTWdnjw2uwCZpSMAyDuvLyHkceRXZ1mZhIRKQXDkdQn9UcNKXQ2d6Ovbm5RylYdbU1EQlEQTyFFDSl0FJf79kI7+SRgsNhYiIRkT6oFAZee1MTXZ2dPba4sKoURCQQBfFhqUFTCk6HA7fLRYTV6r1P00ciEpBUCgPP5XCAYXi3zAZNH4lIgAriC38FTSk4HQ44qRBA00ciEqCC+L0paErB5XD0GCWASkFEAlQQT20HTyn08pes6SMRCUgqhYHncjgwTjlLUAvNIhKQgvgDa9CUgtPhwHLKfRopiEhACuIPrEFTCi6Hg1N3E9GagogEpCAuhUizA5ytU9cUIpxOn5GDyAn2iBiqYrKpsWVQF5VBXWQa9dbBNESk0mBJoZFkmowkmt2JNLsG0eKMx2kEzT8HCSBulxu320VyRob3PKpFSQ4eNDnX+QqafwVdnZ06RyGMdFhsVMdkU2vLoC4qndoTb+rWE2/qKTQaSTS5k2hxDaLFmUCLI55WRxxtnbE4nFHQjucm4g9NX3w75RLzYlyooCkFR0cHloigme0Ke12WKKqjM6m1ZVAblU59VDp13Z/U6y2pNFqSaTKSaXIn0uz2vKm3OuJp7YqnrSuWTocN7HhuIkEmMmjeWX0FTfSujg7vFdcAnFFRJqYJfU4iqDnxpn7i07o17YvpF583dc8UTEtXPG2dsXQ6oqEDz00kzKgU/MDZ2dlj3yN3ZCSuiAisbreJqQKXG6iNzqTa5nljr4tMoz4yjfpT39SNRJrdiTQ5B3k+qTs8b+odXTaMzgjoNPtPIhJ8gvkza9CUgqOz02f6yGWzYe0IzY+ibqDOlk5tdCa1UemeKRjrYOqtg2m0pHje2I0Ti6WDaO7+pH5i+sXeFa03dRGTaKTgB26322ebC4fNhi2AS6E+KtU7BeP9pG4dTJ0llUZLCk0k0ej2HAHT4kqgxZFAqyOO1q442jtjMLoiQBeXEwk6KgU/sMXE4Ha5etw30OsKTZFJ1ERndh/WmE6d9dTDGpM8n9RdXxzW2NqVQGtXLO2dMbgdVtBBUiJh56TLvgSdoCmF6NhY31Kw2U77mhZrQvcRMJ4pmBOf1OsjPJ/UvW/q7kSanIndR8DE0dYVR1tnDC5nJDiB4N0FV0RMkJVldoLzFzSlYIuL8ymF32T9jINRI046AenEYY2e6ReHS8eqi4j/ZWebneD8BU0pRMfG4j7lSKMPOy5ja2mBSYlERHoXzCOFoDkbLCo62ue+xDjN64hI4NFIwQ8ibTbsHS4qKhro7HTQ0emkvbXS7FgiIj6CeaQQNKVwrKaT9w9Zcew/jkEEBhaqmmrNjiUi0kNqKvQysRE0gqYU0kaOI3nEOEaMyCA62oYtxsbBQ6Mp+5vZyUREvhDMU0cQRKUQHx9NbEI86VmDvSexJSTozC4RCSzBXgpBs9AcFxdNVJQVp/OLw1Lj4wP3bGYRCU8qBT+Jj48hKioSh+OLUkhNbQWf67GJiJhHpeAnJ0YKDscXV2Cz2ZwkJurMNBEJHCoFP/GUQs+RAkB6elMfrxAR8T+Vgp/Extqw2SLp6up5rea0tGaTEomI+FIp+ElERASZmcnY7T2PONJIQUQCyZAhZie4MEFTCgC5uel0dPQsBY0URCRQJCRAfr7ZKS5MUJVCRkYyxikHG2mkICKBYsoUiAiqd1VfQRU/PT0JoMduqXFxXcTF6XwFETHftGlmJ7hwQVUKaWmJxMVF096udQURCTwqBT9LT08kPj6a9vaeIwOtK4hIIFAp+FlsbDTp6Ym0tXX2uF8jBRExW0wMFITANb+CqhQAcnLSfQ5L1UhBRMw2eTJEBs0Wo30LulLIzk71uSynRgoiYrZQmDqCICyFE0cgGScdm5qYaCc6Wttoi4h5VAomSUtLJCbG5jOFlJNTY1IiERGVgmnS008cltpzsTkvr8qkRCIS7qKiYNIks1P0j6ArhYSEWFJSEmhr63lYal5epUmJRCTcTZgANpvZKfpH0JWCxWIhNzfDZ6SQmdmoM5tFxBTTp5udoP8EXSkA5OVl4nC4eyw2WyyaQhIRc8yYYXaC/hOUpZCfn0lMTJTPjqmaQhIRMyxcaHaC/hOUpZCbm0FqagINDW097tdIQUT8beJEyM01O0X/CcpSiImxUVCQQ2Njz1JITW0lKanVpFQiEo4WLzY7Qf8KylIAGDt2KC5Xz3UF0GhBRPxr0SKzE/SvoC2F/PxM4uKifQ5Nzc/XuoKI+EdaGsyaZXaK/hW0pTB8eDrp6YlaVxAR01xzTfBfae1UQfvHiYy0MnFiLk1NPUshIaGD9PRGc0KJSFgJtakjCOJSABg9egiAz66pGi2IyECLioIFC8xO0f+CuhTy87NISIilpcXe4/5RoypMSiQi4WLuXEhKMjtF/wvqUsjOTiErK4WGhp6HoebnV2jLCxEZUKE4dQRBXgoRERFMnjyC1taeBWC1GkycWGJSKhEJB6F2fsIJQV0KAKNGZWOxWHC5XD3unzKlyKREIhLqxoyBUaPMTjEwgr4U8vOzSEqK9zk0dciQeh2FJCIDIlSnjiAESmHw4EFMmDCcmppmn8cmTy72fyARCXm33WZ2goET9KVgsViYOXMMLpcbp7PnFNLkyUVYLO4+Xikicu6mTQutrbJPFfSlADB58ggyMpKoqWnqcX9iop0RI6pNSiUioehb3zI7wcAKiVIYNCiOGTNGU1fX4vOYFpxFpL8MGgRLl5qdYmCFRCkATJ8+kshIK3Z7zwvvjB9fis3mMCmViISS22+HhASzUwyskCmFceOGMXx4GlVVjT3ut9lcjB9/zJxQIhJSvvMdsxMMvJApBZstii99aTzNze0+11iYPFlTSCJyYWbNgsmTzU4x8EKmFACmTs1j0KBYmpvbe9yfl1dFYmJbH68SETmzUF9gPiGkSmHEiExGjx7iM4VkseicBRE5fykpcOutZqfwj5AqBYvFwiWXjKOz0+mznfaMGQexWl19vFJEpG933gmxsWan8I+QKgWAKVPySE0d5HN4amKinSlTjpqUSkSC2be/bXYC/wm5UkhLS2Tq1Dyqq5t8HpszZ5/OcBaRc3LppTBunNkp/CfkSgFg5swxWCwWurp6np+QktLGpEnaUltEzl44jRIgREth0qRcRozI5PjxOp/H5sz5DDB8XyQicoqcHLj5ZrNT+FdIlkJMjI3586fS3t6Jw+Hs8Vh6erNOZhORs/LAA2CzmZ3Cv0KyFABmzRrL8OHplJXV+zw2d+5nJiQSkWAyejTcdZfZKfwvZEshISGW+fMLaW5u97kqW3Z2A6NGlZuUTESCwYMPQmSk2Sn8L2RLAeBLXxrHsGFplJc3+Dym0YKI9GXy5NC+kM7phHQpJCXFc+WVk2loaPU5mS0np4bc3CqTkolIIPvFLzw7IYSjkC4FgLlzJ5CVlUxFhUYLInJmF18M119vdgrzhHwppKYOYt68ydTVtfiMFkaOrGTIEN/DVkUkfD38sNkJzBXypQBw2WUTSUtL7PUs58su22NCIhEJRPPmwZVXmp3CXGFRChkZyVx++USqqpp8rrUwZky5jkQSEUCjBAiTUgC47LJJDB6cQE1Ns89j11yzTTuoioS5RYvgkkvMTmG+sCmFoUMHM3t2AZWVDT6jhdTUVmbP3mdSMhExm8Vi8NBDZqcIDGFTCgDz5k0iOTme2lrf0cKcOftITm41IZWImO0rX7EwZYrZKQJDWJXCiBGZzJs3mfLyBp+znKOiXFxzzTaTkomIWZKSDB57zOwUgSOsSgFg0aIZjBiRQUlJjc9jY8aUM2bMcRNSiYhZHnnEwpAhZqcIHGFXCikpCdxwwyw6Ohy0tXX4PH7NNduJjHT28koRCTXz5hl84xtmpwgsYVcKALNnj2f69FEcPVrls+icnNzGnDladBYJdTExbv74xzDdy+I0wrIUIiOt3HTTJSQlxVFT43tC2+zZ+0hNbenllSISKh56CPLzzU4ReMKyFABGjx7C1VdPpaKiEaez56JzZKRbi84iIayw0MGPfhS2b3+nFdZ/K9deexH5+ZkUF1f7PDZqVAXjx5eakEpEBlJUlJu//CWKiLB+9+tbWP+1JCXFc8MNs3A4XLS2+i46L1iwA5vNYUIyERko991nUFBgdorAFdalAJ4L8cyYMYqiIt9F56SkdhYv/sSkZNL//h2wAD886b4jwI1AOpAIfAU4+TobncAd3Y+NAd4/5Xc+AnxvYOJKvxs3zsH991vNjhHQwr4UrFYrN930JZKT46mqavR5fOLEEgoLD/s/mPSzrcBTwOST7msD5uMpig+ATUAXsBg4sc3608B2YDPwTWApcOLDQxHwDKBd1IJBRITBCy9EERVldpLAFvalAJCfn8X8+YVUVTX5LDqD59yFjIxG/weTftIK3I7nDTzlpPs3AcXA88Ck7tv/ANvwlATAfuB6YAJwD1AD1HY/9h3g13hGERLofvhDNxddZHaKwKdS6HbNNdMZPTqbo0d9L9EZFeViyZKNREVpfSE43QNcB1x1yv2deEYJ0SfdF4Pnn8XG7p+ndH9vB94FsoE04MXu5944YKml/+TlOXnoIU0bnQ2VQrfExDhuvXUukZERvV6MJz29mWuv1WGqwedlYAfwq14emwXEA/8KtOOZTvox4AIqup+zAk8xFOCZJnoFaAAeAH4H3A+MAhYAZQP1h5ALEBPj4u9/jyQ21uwkwUGlcJJp00ayaNFMqqoasNs7fR6fOrWIKVOOmpBMzs8x4Ad88an+VOnAq8DfgQQgCWgEpvHFP40o4L/wrB9sBeYA/wR8H/gU+BuwC0/BfH9A/hRyYZ591s2ECWanCB4qhZNYLBa+/OWLmTlzLIcOVfpc0xng2mu3kpbmO5KQQLQdqMbzJh/ZfVsHPNH9vQvPQvOR7ufVAi/g+cTf16muHwKfAd8F1gLX4hltfKX7Zwkkd9/dxNKlWlk+FyqFU0RHR3HHHZczfPjgXtcXbDbP+oI2zQsGVwJ7gJ0n3S7Cs+i8Ezh5jjkNSMazwFyNZ3H5VB141iee6n6tCzixzuTo/lkCxeTJ9Tz1lA4COFcqhV4MGTKYpUsvA+j1gjyZmU0sWLDD37HknA0CJp5yiwcGd38P8BywBc9o4S/ALcCPgLG9/L5f4BkZFHb/PBtYCewGft/9swSClJRW3norFqtVG96dK5VCH2bOHMO1106nvLyejo4un8cvuugwEyaUmJBM+tcB4AZgPPD/Af8GPNrL8/biWWR+8KT7luA5qmkunmL4z4EMKmcpKsrB//6vg+HDtbJ8PizGqafxipfd3snjj7/J9u2HmTBhOBGnbJbS2RnJ009fQ339IJMSisipfvnLSu67L8vsGEFLI4XTiI2N5s4755GdnUpRke+medHRTm67bR0xMb5HKomI/91wQ7kK4QKpFM5g2LA0li69FJfLTV2d7zUW0tObWbp0nRaeRUw2dmwtL7+caXaMoKdSOAuXXDKOhQunUVZWR2en71nNw4fXsmTJJiwW30NYRWTgJSe3snp1HNHROmv5QqkUzoLFYmHJktkUFuZz8GB5r+cvjB1bph1VRUwQGengxRcdjBgRZ3aUkKBSOEtxcdHcddeVDB06mIMHK3y22QYoLDzKFVfs9H84kTAVEeHi0UerufbalDM/Wc6KSuEc5OSk881vLiApKY6jRyt7fc7cufuYOfOAn5OJhCM39957hO9/f4jZQUKKSuEcTZyYy4oVV2G1Wjl2rLbX5yxcuF3nMIgMsKVL9/KrX43EYtEJav1JpXAeLr54LHfcMQ+7vavXC/NYLHDjjZvJy+t9NCEiF+aqq7bzhz+MJDJSC8v9TaVwnq64YjJf+coc6upaqK/3PVTVanVz663rycqqNyGdSOiaOfNT/vjH4SQlxZsdJSSpFM6TxWLh+utnsnjxTMrL62lubvd5TnS0k9tvX0tKim9piMi5mzp1Fy+8kEFubobZUUKWSuECREREcNttc7nqqqkUF1fT3u57ZnNCQgdf+9qHDBrkWxoicvYmT/6UF15IZsyYoWZHCWkqhQsUFRXJXXddwezZ4zl0qKLXk9tSU1tZvvw9kpNbTUgoEvwmTtzOn/40iIkTc82OEvJUCv0gNjaar399PtOm5XPgQBlOp++++ikpbaxY8R7p6Y3+DygSxAoKtvHf/x3L9OmjzI4SFlQK/SQpKZ5vfWsh48YNY//+472e9TxokJ1ly9aQnV1nQkKR4DN+/DaeeCKK2bMLzI4SNlQK/SgjI5lvf/sacnPT2b//OC6XbzHExXVy111ryM31vaqbiJxgMGXKJp54IpIrrphsdpiwolLoZzk56fyf/3MtOTnp7N9/rNeppBNHJY0eXWZCQpHAZrU6mTv3bR59NJ4rr5yik9P8TBfZGSAlJdX84Q+rOHSonPHjhxEVFenzHLfbwttvz2DHDs2VigDExrZx2WVv8E//VKBCMIlKYQBVVNTzhz+sYu/eUsaNG0p0dFSvz1u/fgIffjjFz+lEAktKSi2XXfY699wzQ4VgIpXCAKupaeLJJ9/h00+PMnbsEGJibL0+b9euPN58cyZut07bl/CTnV3E5Ze/w913z+aKKyarEEykUvCDhoZWnn76XbZsOcDIkZkkJPR+QfGjRzN55ZW5dHb2XhwioWjkyO1cffVWVqy4khkzRpsdJ+ypFPyktdXOc8+tYe3aPQwbNpiUlIRen1ddncQrr8ylri7RzwlF/MticTNp0vssXFjON74xn1GjtAV2IFAp+FFnp4OXX17P229vIzU1gays3i8M0tUVyVtvzWDPnjw/JxTxD5uti2nTXmfx4gi+/vWrychINjuSdFMp+JnL5eKtt7by6qubiIqykpOT3uf86Y4d+bzzzkU4nb5HLokEq4SEFmbNeoWbbsrmjjvm9TmdKuZQKZjAMAzWr/+MP//5A9rbOxk9OpuIiN5PGamuTuLVV+dQW5vk55Qi/S8r6xizZv2dr351MjfeOKvXQ7XFXCoFE+3ceZRnn32P8vI6Ro/u+8ikri4rq1bNYNeufD8nFOkfVquLSZPWU1i4h6997TLmzdMRRoFKpWCyY8dq+POfP2T79sMMHZrK4MF9LzDv3JnHqlUzcDj06UqCR2ZmPZMnv8b48QYrVlzNlClaKwtkKoUA0N7eycqVm3nnnW1ERFjIy8vsczqppiaRV1+dQ01Nsn9Dipwji8XNzJl7ycxcxaRJw/jGN+br4jhBQKUQIAzDYMuWA7z44joqKuoZPTq7z+kkh8PKqlUXsXPnSD+nFDk7ycktXHrpe0RGfs6sWeO4++6rSU0dZHYsOQsqhQBz/Hgtf/7zh2zbdoghQ1JJS+t7Omn37hG8/fYMurp63z5DxAyTJx9m5Mi/k5RkYdGimVx33UV9fsCRwKNSCEB2eyevv76ZVau2A5Cf3/d0UnNzLP/4xzQ++0xXpBJzxcV1cPnl67DZtlNQMJylSy9jwoQcs2PJOVIpBCjDMPjkk4O8+OI6ysrqGDUqm9jYvj9tHTmSxTvvXKQzocUUo0cfZ+LEN4mNtTN//lRuuukSBg2KMzuWnAeVQoArK6vjhRc+YOvWw2RlJZOe3vf5Ci5XBB99NI716yfqhDfxi9jYDmbP3kpCwgby8zO57bZLueiiUTrcNIipFIJAR0cXf/vbFt5+exsul5u8vIzTnvTT2BjP6tXTOXBgmB9TSjixWl3MmHGAvLy1uFytXHrpBG69de5p18AkOKgUgoRhGGzbdpj/9/82cehQORkZSWRmJp/2E9nBg0N4552LaGzsffM9kfNRUFDK7NkfU1t7iOzsFG65ZQ5z5xZgtWrb91CgUggyLS3trF69g9Wrd9DY2EZeXiYJCTF9Pt/hsLJxYwGbNhXgcukfrZy/oUNrufrqHURGHqChoY2LLx7D0qWXMXToYLOjST9SKQSpoqJKXnvtI7ZuPUxUlJURIzKIjOz7Tb+ubhDvvDOdI0e0PbGcm8TENq68che5ufsoLa0hJSWeG264hPnzp2Kz6XDoUKNSCGIul4vNmw/w+uubOXq0iuxsz0L0maaU1q+fSFlZmh+TSjCy2RzMmfMZU6fuoaysEosFLr54LNdfP5P8/Cyz48kAUSmEgKamNlat2sZ77+2kudlOfn4mcXHRp33N0aOZrF8/kZKSTD+llGBhsbgpLDzK3LmfUl9/jPb2LiZOzOH66y9m6tS8Ps+ZkdCgUgghhw6Vs3LlR2zffoSYmChyc9PPuPhXWprGhg0TOXxY00rhzmJxM378MebO3YvbXURtbTO5uRksXjyD2bMLiI7WVFE4UCmEGKfTxcaN+3jjjY8pLq7ybpVxpuPGKypS2LBhAvv3Dwd0jHk4iY7uorDwCBdffAC3u4rjx+tIS0tk/vxCrr56KklJ8WZHFD9SKYSo+voW3nprK2vX7qGxsY3MzGQyMk6/3gCei/ps3FjA3r25GIamCUJZSkoLM2cepLDwCE5nK8XF1cTG2pg9u4BFi2boqKIwpVIIcaWlNXzwwW42btxHXV1L9/kNSWecF66vT2DjxgJ2787ToawhJienmlmzPmfcuOM4HE6Ki6txudwUFuZx/fUXM378cJ2RHMZUCmGivLyOdev2snbtXqqrm0hLG0RWVgpW6+nLobk5lm3bRrN7dx5NTZpGCFYRES4mTDjGrFmfM2RIPe3tnRw/XovD4WLUqGwWL57JzJljTntYs4QHlUKYqa5uZN26vXz44R4qKxtITo5nyJDUM74ZGAYUF2ewe3ce+/blaLvuIBET08n06YeZOfMggwa109DQSkVFA5GRVsaOHcq8eZOZMWP0GY9Wk/ChUghT9fUtbNjwGWvW7Ob48VoSE+MYOjT1rC6k7nBY2b9/OLt25VFUlKm1hwATGelk1KgKCgpKGTfuOFarg6qqJmpqmklMjGXq1Hwuv3wiEyfmamQgPlQKYa6pqY2PPvqcf/zjU0pLa4iPj2bo0MFnffhhc3Msu3ePYNeufGpr+97BVQbWyUUwZkwZ0dFOuroclJfX09xsJz09iTlzCpgzZzwjRmRqzUD6pFIQAFpb7Wze/DnvvbeT4uJqDMMgPT2RwYMTz7jucEJ5eSq7duWxd28u7e1978ck/SMy0sno0eUUFBxjzJgybDYnAK2tHZSV1eF0usjJSeeKKyYza9ZYBg/WDqZyZioF6aGjo4u9e0vYtu0wO3Ycoa6uGZstiqysZBIT487qE6bLZaGoKIsjR7IoKsqiqioZnfvQP74ogtLuInAB4Ha7qatroaqqCZstkvHjhzFv3mSmTx9JbKzWC+TsqRSkT3V1zezaVcSWLQc4cKCM5uZ2kpLiyMxMOe1V4E7V1hZNUVEWR49mUlSUpa28z1FiYhs5OTWMG3ec0aO/KAKXy01DQys1Nc04nS5SUxOYMiWPyy6bSEHBcG1lLedFpSBnZBgGJSXV7NxZxEcf7ae0tAan08XgwYNIT08658XK+voEiooyOXo0i6KiTOx2TTWdYLG4ycpqZPjwmu5bLUlJ7d7HXS439fUt1Na24HK5SElJoKBgONOmjWLChBxd5EYumEpBzonD4WT//mNs336ErVsPUV3dRESEhYyMJJKT48+5IAwDKitTvCVRVjaYjo7wme6Iieli2LBabwEMHVrrHQmccKIIamqacbvdpKQMYsKE4UybNpKCAhWB9C+Vgpy35uZ29uwpZsuWA3z++XEaG9swDIP4+BhSUhJITIw9rx01W1piqK1NoqYmiZqaxO6vSUG/eB0V5SQ5uZUhQ+oZNqyWnJwa0tOb6G2ZprcimDgxh8LCfCZMyNGisQwYlYJcMMMwqK9v4ejRKo4cqWD37mIqKuppabFjsVhITIwjJSWe+PiYCzoUsr3d5i2Impokams9hdHSEtePf5rzFxHhJimpjeTkNpKTW0lJaSU5uc37NSGho8/XOhxOmpvtNDe309bWAVhISUlQEYjfqRSk37ndbiorGzh6tIpDh8rZs6eYmppm2ts7sVojSEmJJzk54ZwWq0+nszOSpqZ4Ojps2O02OjpsdHREnfS9rdfvHY6+TtQziIgwiIhwY7M5u28ObDYn0dGe76OjHSQmtp/0pt9KYqKdiIgz/3MyDAO7vYvm5naamtrp6nJitUaQmBhHdnYK48cPZ8SIDMaOHaoiEL9TKciAczpdHDtWw9GjVRw4UMa+faXU17fS2enAao0gPj6auDjPLTbW5reLuLhcEXR1WbsL4Isi6O/zutxuNy0tdpqa2mlpseN2G8TE2EhOjiM/P4sxY4aSk5PO8OFppKQk6MQyMZVKQfyuo6OL4uJqioqqOHasluLiKurqWmhv78Ru7wTAYokgLs7WXRgxxMX5ryzOh9vtprPTSUdHFx0dXdjtXXR0OHC53FgsFgYNimHw4ETGjx9GXl4mOTnpDBuWRkxM/4yWRPqLSkFMZxgG7e2d1NR49uepqWmioqKBkpIqqqs9007t7SfKAmJjbURHRxEZaSUqykpk5Mm3iAEpD8Mw6Oo68abv6H7T78LpdAEWLBaw2aKIjY0iNjaa9PREsrJSychIIjs7hZycdDIzkwO62ERApSABzm7v9BZFTU0TVVWNlJRUU1fXSleXA6fTjdPp7P7qwuFwAQaeM6i/+F/7RGlERFgwDM+bvOcG4Pnqdhu4XO5TXn9iKscgKiqS2FgbMTE2UlMHkZWVTFZWCsnJ8aSkJHi/JiXF6cQxCVoqBQlKhmHgcDi9n9hPTNd88f0XX9vaOmlttdPSYveuY3huVqxWi/f7yMgIYmM96xo2WyQ2W1T310iio6NISorzvvnbbNo6XEKTSkFERLw0wSkiIl4qBRER8VIpiIiIl0pBJAiNGDGC3/72t+f8uksvvZS//vWvZ/38ffv2MWzYMNra2s75vyXBSaUgcgbLli3DYrH43A4fPmx2tHPy5ptvUlVVxW233ea9r6Ojg3vuuYfBgweTkJDAzTffTFVVlffxgoICZs2axWOPPWZGZDGBSkHkLCxcuJCKiooet7y8PLNjnZMnnniC5cuX9ziB7kc/+hF///vfefXVV1m3bh3l5eXcdNNNPV63fPlynnzySZxOp78jiwlUCiJnITo6mqysrB43q9XKG2+8wbRp04iJiSE/P58HH3ywx5unxWLhqaeeYtGiRcTFxTF+/Hg2b97M4cOHufzyy4mPj+dLX/oSR44c8b7myJEjfPnLXyYzM5OEhARmzJjB+++/f9p8jY2NfP3rXyc9PZ3ExESuuOIKdu3a5X28pqaGDz74gMWLF3vva2pq4tlnn+Wxxx7jiiuuYPr06Tz33HN89NFHbNmyxfu8q6++mvr6etatW9cff5US4FQKIudpw4YN3HnnnfzgBz9g3759PPXUUzz//PM8/PDDPZ73i1/8gjvvvJOdO3cybtw4li5dyre+9S3uu+8+tm3bhmEYfPe73/U+v7W1lWuvvZY1a9bw6aefsnDhQhYvXkxpaWmfWW655Raqq6t555132L59O9OmTePKK6+kvr4egI0bN3pL6YTt27fjcDi46qqrvPeNGzeOnJwcNm/e7L3PZrMxdepUNmzYcMF/ZxIEDBE5rbvuusuwWq1GfHy897ZkyRLjyiuvNH75y1/2eO4LL7xgZGdne38GjPvvv9/78+bNmw3AePbZZ733vfTSS0ZMTMxpM0yYMMH43e9+5/05NzfXePzxxw3DMIwNGzYYiYmJRkdHR4/XjBw50njqqacMwzCMxx9/3MjPz+/x+IsvvmjYbDaf/9aMGTOMf/mXf+lx34033mgsW7bstBklNPS1obyInGTevHk8+eST3p/j4+OZPHkymzZt6jEycLlcdHR00N7eTlyc5+I/kydP9j6emZkJwKRJk3rc19HRQXNzM4mJibS2tvLzn/+ct99+m4qKCpxOJ3a7vc+Rwq5du2htbWXw4ME97rfb7d5pKbvdTkzM+V+5LjY2lvb29jM/UYKeSkHkLMTHxzNq1Kge97W2tvLggw/6LMwCPd6Ao6K+2CfpxLUServP7XYD8OMf/5j33nuPRx99lFGjRhEbG8uSJUvo6urqNVtrayvZ2dmsXbvW57Hk5GQA0tLSaGho6PFYVlYWXV1dNDY2ep8HUFVVRVZWVo/n1tfXM3LkyF7/+xJaVAoi52natGkcOHDApywu1KZNm1i2bBk33ngj4HnTLy4uPm2OyspKIiMjGTFiRK/PKSwspLKykoaGBlJSUgCYPn06UVFRrFmzhptvvhmAAwcOUFpayiWXXNLj9Xv37mXJkiUX/oeTgKdSEDlPDzzwAIsWLSInJ4clS5YQERHBrl272Lt3Lw899NB5/97Ro0ezcuVKFi9ejMVi4Wc/+5l3FNGbq666iksuuYQbbriB3/zmN4wZM4by8nLefvttbrzxRi666CIKCwtJS0tj06ZNLFq0CICkpCTuvvtu7r33XlJTU0lMTOR73/sel1xyCbNmzfL+/uLiYsrKynosSEvo0tFHIudpwYIFvPXWW/zjH/9gxowZzJo1i8cff5zc3NwL+r2PPfYYKSkpfOlLX2Lx4sUsWLCAadOm9fl8i8XCqlWruPTSS1m+fDljxozhtttuo6SkxLuGYbVaWb58OS+++GKP1z7++OMsWrSIm2++mUsvvZSsrCxWrlzZ4zkvvfQS8+fPv+A/lwQHbZ0tEiYqKyuZMGECO3bsOOs3+K6uLkaPHs1f//pXZs+ePcAJJRBopCASJrKysnj22WdPe77DqUpLS/npT3+qQggjGimIiIiXRgoiIuKlUhARES+VgoiIeKkURETES6UgIiJeKgUREfFSKYiIiJdKQUREvFQKIiLipVIQEREvlYKIiHipFERExEulICIiXioFERHxUimIiIiXSkFERLxUCiIi4qVSEBERL5WCiIh4qRRERMRLpSAiIl4qBRER8VIpiIiIl0pBRES8/n9yS5pS/yfWEgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Bivariate Analysis"
      ],
      "metadata": {
        "id": "ZGLL-QUwGFgV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## count of purchased based on their gender"
      ],
      "metadata": {
        "id": "dRA-1Ft0GM5k"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ax = sns.countplot(data=cb, x='Purchased', hue='Gender')\n",
        "# for container in ax.containers:\n",
        "#   ax.bar_label(container)\n",
        "# plt.title('Count of Purchased Based on Gender', fontdict=font, pad=15)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "zdxWSKwkGWPj",
        "outputId": "08614ab3-c813-4a06-9658-ba9a03a8f554"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr = cb.corr()\n",
        "sns.heatmap(corr, cmap='Blues', annot=True);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 590
        },
        "id": "vMRRVdCbIrd0",
        "outputId": "a6955573-366f-4989-aee3-d4384d39dac2"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-21-672aed57e764>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  corr = cb.corr()\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Corelation Interpretation\n",
        "\n",
        "According to the displayed visual(correlation), There are both possitive and negative correlations with some features with a very weak correlation, some with moderate correlation and some with very high correlation.\n",
        "\n",
        "- EstimatedSalary and Income level has a high possitive correlation(0.91) which shows theres a huge relationship between the two features\n",
        "- Age and Puchased have a positive moderate correlation(0.62)\n",
        "- Income level and gender have a very low negative correlation, this indicates that they have a strong negative relationships."
      ],
      "metadata": {
        "id": "JYoMfoV2z_UC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.scatterplot(data=cb, x='Income_Level', y='EstimatedSalary')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "-8JBtSHR2igt",
        "outputId": "bb60f699-091e-41b4-af1e-5861a1b796e3"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Income_Level', ylabel='EstimatedSalary'>"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "-FHpTUTr2ib0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(data=cb, x='Gender', y='EstimatedSalary', color='Blue')\n",
        "plt.title('Boxplot of Estimated Salary by Gender')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "iL5VBCR8JN91",
        "outputId": "d0b57031-4937-449f-a57d-222d68020a20"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cb['Gender'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hWZ90PPUWt7Q",
        "outputId": "d81dfc11-997c-4547-d629-279d7c31eba7"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    204\n",
              "1    196\n",
              "Name: Gender, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cb['Purchased'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "td4TxP3tW577",
        "outputId": "9dcb3446-d07f-44b7-dd9b-59a7ec88d17e"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    257\n",
              "1    143\n",
              "Name: Purchased, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(data=cb, x='Purchased', y='EstimatedSalary', color='Blue')\n",
        "plt.title('Boxplot of Estimated Salary by Purchased')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "myheFPu3JN1u",
        "outputId": "dc92d907-5f44-4c3f-854f-e7fd24cc6067"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.violinplot(data=cb, x='Purchased', y='EstimatedSalary');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "ZLSzJAslWIRt",
        "outputId": "42dca3e0-31a6-42eb-ebdc-382268f9334d"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Univariate Analysis"
      ],
      "metadata": {
        "id": "XKIHgjDoKGbC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cb.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Do7RLDDCKs85",
        "outputId": "bc62e472-8332-4dd0-d679-11d6583fd588"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 400 entries, 0 to 399\n",
            "Data columns (total 6 columns):\n",
            " #   Column           Non-Null Count  Dtype   \n",
            "---  ------           --------------  -----   \n",
            " 0   Gender           400 non-null    int64   \n",
            " 1   Age              400 non-null    int64   \n",
            " 2   EstimatedSalary  400 non-null    int64   \n",
            " 3   Purchased        400 non-null    int64   \n",
            " 4   Age_Group        393 non-null    category\n",
            " 5   Income_Level     400 non-null    float64 \n",
            "dtypes: category(1), float64(1), int64(4)\n",
            "memory usage: 16.3 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.scatterplot(data=cb, x='Age', y='EstimatedSalary', hue='Purchased');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "H0pKmjy5XdZc",
        "outputId": "3c4d007b-cf68-4562-d2b5-625ed9af2117"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Plotting a 3D scatter plot to give a better view"
      ],
      "metadata": {
        "id": "JAFCHbrQYltN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fig = px.scatter_3d(\n",
        "        data_frame=cb,\n",
        "        x='Age',\n",
        "        y='EstimatedSalary',\n",
        "        z='Gender',\n",
        "        color='Purchased',\n",
        "        template='ggplot2',\n",
        "        opacity=0.6,\n",
        "        height=700,\n",
        "        title=f'3d scatter based on Age, EstimatedSalary, Gender and Purchased'\n",
        ")\n",
        "\n",
        "pio.show(fig)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 717
        },
        "id": "11jhnb41XdW1",
        "outputId": "9d7ccee0-2329-4ea0-81b4-4d5536cf4090"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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    {
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      "source": [
        "## Observations to the data exploration:\n",
        "\n",
        "According to the exploratory analysis, we observed that ages with lower estimated salary have less opportunity to make purchases compare to ages with higher salaries."
      ],
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        "cb.info()"
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      "execution_count": 31,
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          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 400 entries, 0 to 399\n",
            "Data columns (total 6 columns):\n",
            " #   Column           Non-Null Count  Dtype   \n",
            "---  ------           --------------  -----   \n",
            " 0   Gender           400 non-null    int64   \n",
            " 1   Age              400 non-null    int64   \n",
            " 2   EstimatedSalary  400 non-null    int64   \n",
            " 3   Purchased        400 non-null    int64   \n",
            " 4   Age_Group        393 non-null    category\n",
            " 5   Income_Level     400 non-null    float64 \n",
            "dtypes: category(1), float64(1), int64(4)\n",
            "memory usage: 16.3 KB\n"
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      "cell_type": "code",
      "source": [
        "cb['Age_Group'].isna().sum()"
      ],
      "metadata": {
        "id": "Mxs7GYznamY6",
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "outputId": "c29807f7-739b-451b-bf93-f89ee217c4f0"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cb.dropna(inplace=True)"
      ],
      "metadata": {
        "id": "IK2jbVUahgyf"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cb.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AkmIJTNbiBnv",
        "outputId": "58fe2832-58a2-4ff5-e525-a938f942400d"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 393 entries, 0 to 399\n",
            "Data columns (total 6 columns):\n",
            " #   Column           Non-Null Count  Dtype   \n",
            "---  ------           --------------  -----   \n",
            " 0   Gender           393 non-null    int64   \n",
            " 1   Age              393 non-null    int64   \n",
            " 2   EstimatedSalary  393 non-null    int64   \n",
            " 3   Purchased        393 non-null    int64   \n",
            " 4   Age_Group        393 non-null    category\n",
            " 5   Income_Level     393 non-null    float64 \n",
            "dtypes: category(1), float64(1), int64(4)\n",
            "memory usage: 18.9 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Scaling the Data\n",
        "\n",
        "Since our datset comprises of categorical and numerical features, we need to consider three scaling approach\n",
        "- MinMax Scaling: This is mostly used to scale data to a fixed range usually 0's and 1's. $X_{scaled} = (X-X_{min}) / (X_{max} - X_{min})$\n",
        "\n",
        "- Standard Scaling (Z-score normalization): This method scales the data so that it has a mean of 0 and a standard deviation of 1. It's useful when your data has outliers\n",
        "X_scaled =\n",
        "σ\n",
        "X−μ\n",
        "​\n",
        "\n",
        "Firsly, we will apply standardscler to the dataset to see if the mean is close to 0 and standard deviation is close to one. The reason for this approach is to check if standardizing the dataset using standard scalar or no. If the mean is not close to 0 and the standard deviation is not close to one then we will need to apply another approach.\n"
      ],
      "metadata": {
        "id": "hLQ23wYQpJrm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import StandardScaler\n",
        "scaler = StandardScaler()\n",
        "scaled_data = scaler.fit_transform(cb[['Age', 'EstimatedSalary']])\n",
        "\n",
        "scaled_df = pd.DataFrame(scaled_data, columns=['Scaled_Age', 'Scaled_EstimatedSalary'])\n",
        "\n",
        "mean_values = scaled_df.mean()\n",
        "std_values = scaled_df.std()\n",
        "\n",
        "print(\"Mean values after scaling:\")\n",
        "print(mean_values)\n",
        "print(\"\\nStandard deviation values after scaling:\")\n",
        "print(std_values)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4kFD6fcuigzL",
        "outputId": "f99b426f-be6b-45fa-8c3d-190b43afff1e"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mean values after scaling:\n",
            "Scaled_Age               -7.231987e-17\n",
            "Scaled_EstimatedSalary    9.039984e-17\n",
            "dtype: float64\n",
            "\n",
            "Standard deviation values after scaling:\n",
            "Scaled_Age                1.001275\n",
            "Scaled_EstimatedSalary    1.001275\n",
            "dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "pCD1fBFmo7EF"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}