10.2: Data_normalization_with_scikit.ipynb

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      "name": "python3",
      "display_name": "Python 3"
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    "colab": {
      "name": "10.2: Data_normalization_with_scikit.ipynb",
      "provenance": []
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "OiIYnjRMiJS9"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import scipy.stats as stats"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uUzx_G0BiJTF"
      },
      "source": [
        "# disable chained assignments, to remove the error of SettingWithCopyWarning .\n",
        "pd.options.mode.chained_assignment = None "
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9aPDO7CTiJTG"
      },
      "source": [
        "marketing_df = pd.read_csv('https://raw.githubusercontent.com/gulabpatel/Statistics/master/Dataset/marketing_cva_f.csv')"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OiAVopd1iJTG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 222
        },
        "outputId": "37bfc5bd-1e62-4867-f732-8b6c4c74f80e"
      },
      "source": [
        "marketing_df.head()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Customer</th>\n",
              "      <th>State</th>\n",
              "      <th>CLV</th>\n",
              "      <th>Coverage</th>\n",
              "      <th>Income</th>\n",
              "      <th>loc_type</th>\n",
              "      <th>monthly_premium</th>\n",
              "      <th>months_last_claim</th>\n",
              "      <th>Months_Since_Policy_Inception</th>\n",
              "      <th>Total_Claim_Amount</th>\n",
              "      <th>Vehicle_Class</th>\n",
              "      <th>avg_vehicle_age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>BU79786</td>\n",
              "      <td>Washington</td>\n",
              "      <td>2763.519279</td>\n",
              "      <td>Basic</td>\n",
              "      <td>56274</td>\n",
              "      <td>Suburban</td>\n",
              "      <td>69</td>\n",
              "      <td>32</td>\n",
              "      <td>5</td>\n",
              "      <td>384.811147</td>\n",
              "      <td>Two-Door Car</td>\n",
              "      <td>40.696695</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AI49188</td>\n",
              "      <td>Nevada</td>\n",
              "      <td>12887.431650</td>\n",
              "      <td>Premium</td>\n",
              "      <td>48767</td>\n",
              "      <td>Suburban</td>\n",
              "      <td>108</td>\n",
              "      <td>18</td>\n",
              "      <td>38</td>\n",
              "      <td>566.472247</td>\n",
              "      <td>Two-Door Car</td>\n",
              "      <td>48.755298</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>HB64268</td>\n",
              "      <td>Washington</td>\n",
              "      <td>2813.692575</td>\n",
              "      <td>Basic</td>\n",
              "      <td>43836</td>\n",
              "      <td>Rural</td>\n",
              "      <td>73</td>\n",
              "      <td>12</td>\n",
              "      <td>44</td>\n",
              "      <td>138.130879</td>\n",
              "      <td>Four-Door Car</td>\n",
              "      <td>70.394474</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>OC83172</td>\n",
              "      <td>Oregon</td>\n",
              "      <td>8256.297800</td>\n",
              "      <td>Basic</td>\n",
              "      <td>62902</td>\n",
              "      <td>Rural</td>\n",
              "      <td>69</td>\n",
              "      <td>14</td>\n",
              "      <td>94</td>\n",
              "      <td>159.383042</td>\n",
              "      <td>Two-Door Car</td>\n",
              "      <td>53.460212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>XZ87318</td>\n",
              "      <td>Oregon</td>\n",
              "      <td>5380.898636</td>\n",
              "      <td>Basic</td>\n",
              "      <td>55350</td>\n",
              "      <td>Suburban</td>\n",
              "      <td>67</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>321.600000</td>\n",
              "      <td>Four-Door Car</td>\n",
              "      <td>32.811507</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Customer       State  ...  Vehicle_Class avg_vehicle_age\n",
              "0  BU79786  Washington  ...   Two-Door Car       40.696695\n",
              "1  AI49188      Nevada  ...   Two-Door Car       48.755298\n",
              "2  HB64268  Washington  ...  Four-Door Car       70.394474\n",
              "3  OC83172      Oregon  ...   Two-Door Car       53.460212\n",
              "4  XZ87318      Oregon  ...  Four-Door Car       32.811507\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hNE6cKx9iJTH"
      },
      "source": [
        "from sklearn.preprocessing import FunctionTransformer, PowerTransformer\n",
        "\n",
        "### Note that FunctionTransformer and power transfomer when fit returns an array.so lets not mess up.\n",
        "### we need to change it back."
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a88Qya39iJTI"
      },
      "source": [
        "### lets plot the histogram and QQ-side by side\n",
        "# histogram and Q-Q plots\n",
        "\n",
        "def check_normality(df, column_name):  \n",
        "    plt.figure(figsize=(15,6))\n",
        "    #sub_plot 1 for histogram\n",
        "    plt.subplot(1, 2, 1)\n",
        "    df[column_name].hist(bins=25)\n",
        "    #sub_plot 2 for qq plot from scipy stat\n",
        "    plt.subplot(1, 2, 2)\n",
        "    stats.probplot(df[column_name], dist=\"norm\", plot=plt)\n",
        "    plt.show()"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TpLN12LviJTI"
      },
      "source": [
        "marketing_numeric=marketing_df.select_dtypes(include=np.number)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WgtehClJiJTI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 314
        },
        "outputId": "0a9158ac-9df9-4cf2-cbdf-e1e3bd6e27ca"
      },
      "source": [
        "marketing_numeric.describe()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>CLV</th>\n",
              "      <th>Income</th>\n",
              "      <th>monthly_premium</th>\n",
              "      <th>months_last_claim</th>\n",
              "      <th>Months_Since_Policy_Inception</th>\n",
              "      <th>Total_Claim_Amount</th>\n",
              "      <th>avg_vehicle_age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>6817.000000</td>\n",
              "      <td>6817.000000</td>\n",
              "      <td>6817.000000</td>\n",
              "      <td>6817.000000</td>\n",
              "      <td>6817.000000</td>\n",
              "      <td>6817.000000</td>\n",
              "      <td>6817.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>8130.229340</td>\n",
              "      <td>50456.580461</td>\n",
              "      <td>92.963034</td>\n",
              "      <td>15.046941</td>\n",
              "      <td>47.832624</td>\n",
              "      <td>377.840789</td>\n",
              "      <td>50.126257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>6949.067972</td>\n",
              "      <td>24305.956566</td>\n",
              "      <td>34.615160</td>\n",
              "      <td>10.064762</td>\n",
              "      <td>27.895350</td>\n",
              "      <td>252.648952</td>\n",
              "      <td>9.919767</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>2119.894333</td>\n",
              "      <td>10037.000000</td>\n",
              "      <td>61.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.099007</td>\n",
              "      <td>11.875974</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>4090.750678</td>\n",
              "      <td>28432.000000</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>210.100003</td>\n",
              "      <td>43.449925</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>5810.630529</td>\n",
              "      <td>48081.000000</td>\n",
              "      <td>83.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>48.000000</td>\n",
              "      <td>340.800000</td>\n",
              "      <td>50.100924</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>9075.768214</td>\n",
              "      <td>70187.000000</td>\n",
              "      <td>109.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>498.612632</td>\n",
              "      <td>56.877234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>83325.381190</td>\n",
              "      <td>99981.000000</td>\n",
              "      <td>297.000000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>99.000000</td>\n",
              "      <td>2893.239678</td>\n",
              "      <td>83.387485</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                CLV        Income  ...  Total_Claim_Amount  avg_vehicle_age\n",
              "count   6817.000000   6817.000000  ...         6817.000000      6817.000000\n",
              "mean    8130.229340  50456.580461  ...          377.840789        50.126257\n",
              "std     6949.067972  24305.956566  ...          252.648952         9.919767\n",
              "min     2119.894333  10037.000000  ...            0.099007        11.875974\n",
              "25%     4090.750678  28432.000000  ...          210.100003        43.449925\n",
              "50%     5810.630529  48081.000000  ...          340.800000        50.100924\n",
              "75%     9075.768214  70187.000000  ...          498.612632        56.877234\n",
              "max    83325.381190  99981.000000  ...         2893.239678        83.387485\n",
              "\n",
              "[8 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aFOgfqVCiJTJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c1a84af3-0c07-4101-b68e-6e073da43c04"
      },
      "source": [
        "marketing_numeric.columns"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['CLV', 'Income', 'monthly_premium', 'months_last_claim',\n",
              "       'Months_Since_Policy_Inception', 'Total_Claim_Amount',\n",
              "       'avg_vehicle_age'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Npqz4oppiJTJ"
      },
      "source": [
        "# lets define various function transformer\n",
        "log_transformer = FunctionTransformer(np.log, validate=True)\n",
        "reciprocal_transformer = FunctionTransformer(lambda x: 1/x, validate=True)\n",
        "sqrt_transformer = FunctionTransformer(lambda x: x**(1/2), validate=True)\n",
        "exp_transformer = FunctionTransformer(lambda x: x**(1/1.2), validate=True)  # randomly 1.2..."
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bk_-XiAPiJTK"
      },
      "source": [
        "# lets define power transformer - Boxcox and Yeojohnson\n",
        "boxcox_transformer = PowerTransformer(method='box-cox', standardize=False)\n",
        "yeojohn_transformer = PowerTransformer(method='yeo-johnson', standardize=False)\n"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fNrLFqRAiJTK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ea1bad0e-0c50-4d8b-9ee7-6f46af583091"
      },
      "source": [
        "cols=marketing_numeric.columns\n",
        "cols"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['CLV', 'Income', 'monthly_premium', 'months_last_claim',\n",
              "       'Months_Since_Policy_Inception', 'Total_Claim_Amount',\n",
              "       'avg_vehicle_age'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cRhXi8QciJTK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 685
        },
        "outputId": "c48965e3-c2d4-48ba-d825-504864e96d5c"
      },
      "source": [
        "marketing_numeric.hist(figsize=(15,15))  ## \n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 9 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ek34nQV3iJTL"
      },
      "source": [
        "### function Transformer\n",
        "cols=['Income']\n",
        "### logarithmic\n",
        "transformed_log = log_transformer.transform(marketing_numeric[cols])  ## array.\n",
        "marketing_numeric['transformed_log'] =transformed_log  ## lets add back to the dataframe\n",
        "\n",
        "### reciprocal\n",
        "transformed_reciprocal = reciprocal_transformer.transform(marketing_numeric[cols])  ## array.\n",
        "marketing_numeric['transformed_reciprocal'] =transformed_reciprocal  ## lets add back to the dataframe\n",
        "\n",
        "## squareroot\n",
        "transformed_sqrt = sqrt_transformer.transform(marketing_numeric[cols])  ## array.\n",
        "marketing_numeric['transformed_sqrt'] =transformed_sqrt  ## lets add back to the dataframe\n",
        "\n",
        "# exponential\n",
        "transformed_exp = exp_transformer.transform(marketing_numeric[cols])  ## array.\n",
        "marketing_numeric['transformed_exp'] =transformed_exp  ## lets add back to the dataframe"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AlErJjq0iJTL"
      },
      "source": [
        "## power Transformer, After definition you need to fit and transform.\n",
        "cols=['Income']\n",
        "boxcox_transformer.fit(marketing_numeric[cols])\n",
        "transformed_boxcox = boxcox_transformer.transform(marketing_numeric[cols])  ## array.\n",
        "marketing_numeric['transformed_boxcox'] =transformed_boxcox  ## lets add back to the dataframe\n",
        "\n",
        "yeojohn_transformer.fit(marketing_numeric[cols])\n",
        "transformed_yeoj = yeojohn_transformer.transform(marketing_numeric[cols])  ## array.\n",
        "marketing_numeric['transformed_yeoj'] =transformed_yeoj  ## lets add back to the dataframe"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t8nqVpX2iJTM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8a4f3a8a-2ead-4742-fa81-00ca16786df2"
      },
      "source": [
        "yeojohn_transformer.lambdas_"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.44436579])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qyLYcSlKiJTM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ffa38816-1be8-4fb1-87f3-a159af60b9d4"
      },
      "source": [
        "boxcox_transformer.lambdas_"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.44437538])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qb3iIjVRiJTN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 222
        },
        "outputId": "148b1f91-6c80-41a1-e8ab-378e24a998cf"
      },
      "source": [
        "marketing_numeric.head(5)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>CLV</th>\n",
              "      <th>Income</th>\n",
              "      <th>monthly_premium</th>\n",
              "      <th>months_last_claim</th>\n",
              "      <th>Months_Since_Policy_Inception</th>\n",
              "      <th>Total_Claim_Amount</th>\n",
              "      <th>avg_vehicle_age</th>\n",
              "      <th>transformed_log</th>\n",
              "      <th>transformed_reciprocal</th>\n",
              "      <th>transformed_sqrt</th>\n",
              "      <th>transformed_exp</th>\n",
              "      <th>transformed_boxcox</th>\n",
              "      <th>transformed_yeoj</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2763.519279</td>\n",
              "      <td>56274</td>\n",
              "      <td>69</td>\n",
              "      <td>32</td>\n",
              "      <td>5</td>\n",
              "      <td>384.811147</td>\n",
              "      <td>40.696695</td>\n",
              "      <td>10.937988</td>\n",
              "      <td>0.000018</td>\n",
              "      <td>237.221416</td>\n",
              "      <td>9090.542925</td>\n",
              "      <td>288.265512</td>\n",
              "      <td>288.243543</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>12887.431650</td>\n",
              "      <td>48767</td>\n",
              "      <td>108</td>\n",
              "      <td>18</td>\n",
              "      <td>38</td>\n",
              "      <td>566.472247</td>\n",
              "      <td>48.755298</td>\n",
              "      <td>10.794809</td>\n",
              "      <td>0.000021</td>\n",
              "      <td>220.832516</td>\n",
              "      <td>8068.107942</td>\n",
              "      <td>270.357157</td>\n",
              "      <td>270.337246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2813.692575</td>\n",
              "      <td>43836</td>\n",
              "      <td>73</td>\n",
              "      <td>12</td>\n",
              "      <td>44</td>\n",
              "      <td>138.130879</td>\n",
              "      <td>70.394474</td>\n",
              "      <td>10.688211</td>\n",
              "      <td>0.000023</td>\n",
              "      <td>209.370485</td>\n",
              "      <td>7382.312611</td>\n",
              "      <td>257.744892</td>\n",
              "      <td>257.726431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8256.297800</td>\n",
              "      <td>62902</td>\n",
              "      <td>69</td>\n",
              "      <td>14</td>\n",
              "      <td>94</td>\n",
              "      <td>159.383042</td>\n",
              "      <td>53.460212</td>\n",
              "      <td>11.049333</td>\n",
              "      <td>0.000016</td>\n",
              "      <td>250.802711</td>\n",
              "      <td>9974.406078</td>\n",
              "      <td>303.001540</td>\n",
              "      <td>302.977880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5380.898636</td>\n",
              "      <td>55350</td>\n",
              "      <td>67</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>321.600000</td>\n",
              "      <td>32.811507</td>\n",
              "      <td>10.921432</td>\n",
              "      <td>0.000018</td>\n",
              "      <td>235.265807</td>\n",
              "      <td>8965.985269</td>\n",
              "      <td>286.136012</td>\n",
              "      <td>286.114288</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            CLV  Income  ...  transformed_boxcox  transformed_yeoj\n",
              "0   2763.519279   56274  ...          288.265512        288.243543\n",
              "1  12887.431650   48767  ...          270.357157        270.337246\n",
              "2   2813.692575   43836  ...          257.744892        257.726431\n",
              "3   8256.297800   62902  ...          303.001540        302.977880\n",
              "4   5380.898636   55350  ...          286.136012        286.114288\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Fxk8Zz2iJTO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1438eb85-3ebe-4caa-b7a8-3eee9cf78ff9"
      },
      "source": [
        "transfomed_cols =[x for x in marketing_numeric.columns if 'transformed' in x]\n",
        "transfomed_cols"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['transformed_log',\n",
              " 'transformed_reciprocal',\n",
              " 'transformed_sqrt',\n",
              " 'transformed_exp',\n",
              " 'transformed_boxcox',\n",
              " 'transformed_yeoj']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lfx4aQ-jiJTO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "acf865eb-0fb7-4d4a-a283-47173630e238"
      },
      "source": [
        "for each_col in transfomed_cols:\n",
        "    print(\"**********************\")\n",
        "    print(each_col)\n",
        "    check_normality(marketing_numeric,each_col)\n",
        "    print()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "**********************\n",
            "transformed_log\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "**********************\n",
            "transformed_reciprocal\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "**********************\n",
            "transformed_sqrt\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "**********************\n",
            "transformed_exp\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "**********************\n",
            "transformed_boxcox\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "**********************\n",
            "transformed_yeoj\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4KN1CjJElcmX"
      },
      "source": [
        "---------------------------------"
      ]
    }
  ]
}