10.1: Data_normalization_without_sklearn.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "colab": {
      "name": "10.1: Data_normalization_without_sklearn.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "U0g8Y_UfhiRG"
      },
      "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": "K5-FToithiRP"
      },
      "source": [
        "marketing_df = pd.read_csv('https://raw.githubusercontent.com/gulabpatel/Statistics/master/Dataset/marketing_cva_f.csv')"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e-l4bnPGhiRP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 222
        },
        "outputId": "fa344b12-3815-4dfa-da69-5aa4899e576b"
      },
      "source": [
        "marketing_df.head()"
      ],
      "execution_count": 3,
      "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>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": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fVpYZnKihiRQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3865d461-1355-4ec6-c0d0-4a594b9cb4d0"
      },
      "source": [
        "marketing_df.info()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 6817 entries, 0 to 6816\n",
            "Data columns (total 12 columns):\n",
            " #   Column                         Non-Null Count  Dtype  \n",
            "---  ------                         --------------  -----  \n",
            " 0   Customer                       6817 non-null   object \n",
            " 1   State                          6817 non-null   object \n",
            " 2   CLV                            6817 non-null   float64\n",
            " 3   Coverage                       6817 non-null   object \n",
            " 4   Income                         6817 non-null   int64  \n",
            " 5   loc_type                       6817 non-null   object \n",
            " 6   monthly_premium                6817 non-null   int64  \n",
            " 7   months_last_claim              6817 non-null   int64  \n",
            " 8   Months_Since_Policy_Inception  6817 non-null   int64  \n",
            " 9   Total_Claim_Amount             6817 non-null   float64\n",
            " 10  Vehicle_Class                  6817 non-null   object \n",
            " 11  avg_vehicle_age                6817 non-null   float64\n",
            "dtypes: float64(3), int64(4), object(5)\n",
            "memory usage: 639.2+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l8jmFjPIhiRR"
      },
      "source": [
        "### lets do only for numerical columns.\n",
        "marketing_numeric=marketing_df.select_dtypes(include=np.number)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FgCtrCquhiRS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 685
        },
        "outputId": "0300f99d-ccd9-451e-9e49-b546a3493813"
      },
      "source": [
        "marketing_numeric.hist(figsize=(15,15))  ## even if you give original df also , hist will any way plot for numeric only.\n",
        "plt.show()"
      ],
      "execution_count": 6,
      "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": "XSWzGQtKhiRT"
      },
      "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": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MUATFxw6hiRU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f4b30222-08e2-4a7a-afea-ab440c873fb5"
      },
      "source": [
        "marketing_numeric.columns"
      ],
      "execution_count": 8,
      "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": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k-_0vVdohiRU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "d43a1753-e4f3-4b7b-f0bc-ad62acd8270d"
      },
      "source": [
        "#example \n",
        "\n",
        "check_normality(marketing_numeric, 'Income')"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "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"
          }
        }
      ]
    },
    {
      "cell_type": "raw",
      "metadata": {
        "id": "UyEmGGPAhiRV"
      },
      "source": [
        "You can do one of the below Transformations for converting the above..lets check each one\n",
        "1) without sklearn 2) with sklearn later.\n",
        "\n",
        "Logarithmic transformation - np.log(X)\n",
        "Reciprocal transformation - 1 / X\n",
        "Square root transformation - X**(1/2)\n",
        "Exponential transformation (more general, you can use any exponent)\n",
        "Box-Cox transformation\n",
        "Yeo-Johnson transformation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "36PxLmDnhiRV"
      },
      "source": [
        "## logarithmic - without sklearn"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xSXLUrb8hiRV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e4bab577-187b-489d-8166-76af1d6fdd38"
      },
      "source": [
        "marketing_numeric.loc[:,'Income_log']=np.log(marketing_numeric['Income'])"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1596: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self.obj[key] = _infer_fill_value(value)\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1743: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(ilocs[0], value)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HMYcBXs9hiRW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 130
        },
        "outputId": "52765690-d8ad-4675-886b-e8ed185412ae"
      },
      "source": [
        "marketing_numeric.head(2)  # new column"
      ],
      "execution_count": 11,
      "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>Income_log</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",
              "    </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",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            CLV  Income  ...  avg_vehicle_age  Income_log\n",
              "0   2763.519279   56274  ...        40.696695   10.937988\n",
              "1  12887.431650   48767  ...        48.755298   10.794809\n",
              "\n",
              "[2 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uksi-vCWhiRW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "85cf53d4-9d57-4b6a-9da1-068777dbd4f8"
      },
      "source": [
        "check_normality(marketing_numeric, 'Income_log')  ### not much has been done."
      ],
      "execution_count": 12,
      "outputs": [
        {
          "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"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uxjrGpb4hiRW"
      },
      "source": [
        "### Reciprocal transformation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QT2ZIRlMhiRW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e773799f-1f6f-44ac-df92-4730ddda76ce"
      },
      "source": [
        "marketing_numeric.loc[:,'Income_reciprocal']= 1 /marketing_numeric['Income']"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1596: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self.obj[key] = _infer_fill_value(value)\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1743: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(ilocs[0], value)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dbYUuZkWhiRX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 130
        },
        "outputId": "b31ff4c5-a974-4498-c3d2-fb56e016868b"
      },
      "source": [
        "marketing_numeric.head(2)"
      ],
      "execution_count": 14,
      "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>Income_log</th>\n",
              "      <th>Income_reciprocal</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",
              "    </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",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            CLV  Income  ...  Income_log  Income_reciprocal\n",
              "0   2763.519279   56274  ...   10.937988           0.000018\n",
              "1  12887.431650   48767  ...   10.794809           0.000021\n",
              "\n",
              "[2 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S0FnL0n2hiRX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "outputId": "9837ffdb-82e5-4507-e05b-bb3bdbb92092"
      },
      "source": [
        "check_normality(marketing_numeric, 'Income_reciprocal')  ### vey bad...see here."
      ],
      "execution_count": 15,
      "outputs": [
        {
          "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"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dseqJmbqhiRX"
      },
      "source": [
        "## Square root transformation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9dNmWd1HhiRY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e98fbf2e-ba70-440b-8815-bd2ba4d9f7a4"
      },
      "source": [
        "marketing_numeric.loc[:,'Income_sqrt']= marketing_numeric['Income']**(1/1.5)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1596: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self.obj[key] = _infer_fill_value(value)\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1743: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(ilocs[0], value)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fzewZ3ojhiRY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "46fdfd48-c0ae-464d-fb4a-a11076ec7526"
      },
      "source": [
        "check_normality(marketing_numeric, 'Income_sqrt')  ### not good.. this is also bad.."
      ],
      "execution_count": 17,
      "outputs": [
        {
          "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"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1Rnhvv0vhiRY"
      },
      "source": [
        "## Box-Cox transformation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zR2egNXChiRY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 568
        },
        "outputId": "e4b8489e-5197-4568-b866-b327089c7cf6"
      },
      "source": [
        "marketing_numeric.loc[:,'Income_boxcox'], param = stats.boxcox(marketing_numeric['Income']) \n",
        "print('Optimal λ: ', param)\n",
        "\n",
        "\n",
        "check_normality(marketing_numeric, 'Income_boxcox')"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1596: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self.obj[key] = _infer_fill_value(value)\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1743: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(ilocs[0], value)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Optimal λ:  0.44437538279540056\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"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZB0r-Lp4hiRZ"
      },
      "source": [
        "### Yeo-Johnson"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HuOJ7tXuhiRZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "701a21b2-8c20-4ec4-b5eb-168ddc7d822b"
      },
      "source": [
        "marketing_numeric.loc[:,'Income_yeojohnson'], param = stats.yeojohnson(marketing_numeric['Income']) \n",
        "print('Optimal λ: ', param)\n"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Optimal λ:  0.44436578851948233\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VJo2BTNehiRZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "a32a671f-0410-4cd3-c7d0-51680e7f520d"
      },
      "source": [
        "check_normality(marketing_numeric, 'Income_yeojohnson')"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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FAw+El16Cm2+Gffapd0UNx/lISZIkSdVx7bUwdmzpurXf/MaGrZds2iRJkiT1r7aEyMMOg/e8B+bPNyGyD2zaJEmSJPWfVavg+OPhrLNKTdutt8Kb31zvqhqaTZskSZKk/rF8OYwbV4r0/8IX4Cc/MdK/HxhEIkmSJKnvFi8uNWwmRPY7mzZJkiRJfWNCZFW5PFKSJElS75kQWXU2bZIkSZJ6zoTImrFpkyRJktQz5QmRhx5qQmSV2bRJktQHETE0In4fEXOK7bdFxPyIWBgRP42I1xXjry+2FxbPj6pn3ZLUa+0TImfONCGyymzaJEnqm9OAP5Rtnw9cmJnvAJ4FjivGjwOeLcYvLPaTpMayeDHstRfcdlspIfK//guG2FJUm2dYkqReiohtgHHA94rtAD4EXFPsMh04uHh8ULFN8fw+xf6S1Bh++1vYYw9YsqSUEGmkf83YtEmS1HvfAs4CXi22NweWZebqYnsJMLJ4PBJ4DKB4fnmx/3oiYmJELIiIBU899VS1apekyl133dqEyDvvNCGyxmzaJEnqhYgYDzyZmXf392tn5rTMHJOZY7bccsv+fnlJqlwmXHBBKWykLSFyhx3qXVXT8cu1JUnqnb2AAyPiAOANwBuBi4BNI2KDYjZtG2Bpsf9SYFtgSURsALwJeLr2ZUtShVatgpNPLgWOHHYYTJ9u4EidONMmSVIvZOYXMnObzBwFHAHcmplHAbcBhxa7HQPcUDyeVWxTPH9rZmYNS5akyi1fDuPHmxA5QDjTJklS/zobmBkRXwV+D1xRjF8B/CgiFgLPUGr0JGngWby4FOn/pz+VEiINHKk7mzZJkvooM1uB1uLxn4HdO9jnJeCwmhYmST31u9/BhAnw0kulhEgDRwYEm7ZBbtTkufUuQeo3fp4lSaqi666Do4+Glha49VYDRwYQr2mTJEmSmpkJkQOeTZskSZLUrFatguOPh89/vtS03XorvPnN9a5K7di0SZIkSc3IhMiG4TVtkiRJUrMpT4j83vfguOPqXZG6YNMmSZIkNRMTIhuOyyMlSZKkZnHddfDBD5aWQd55pw1bg7BpkyRJkga78oTId78b7rrLhMgGYtMmSZIkDWarVsEJJ6xNiLztttJ3salhdNu0RcQbIuK3EXFfRDwUEf9RjL8tIuZHxMKI+GlEvK4Yf32xvbB4flR1fwRJkiRJHWpLiPzOd2Dy5AGXEDljBgwfDhF9uw0dWrrfYIN177fYonQbMmTdx6NGwYknlu7btmfMWFtTR+Od1V/pvn1RSRDJy8CHMnNFRGwI3BERNwFnAhdm5syIuBw4Dpha3D+bme+IiCOA84HDq1O+JEmSpA4tXlxq2P74x5okRM6YAZ/+NLzySlXfpkOvvlq6X7Nm3funn167T/njxYth6tR1tydOhF//GqZPh5Ur1x0HOOqodd9zxozSc5Xs21fdNm2ZmcCKYnPD4pbAh4B/K8anA1+m1LQdVDwGuAa4NCKieB2pYY2aPLdXxy06b1w/VyJJktSNKiRE7rgjPPxwP9Q2QK1cWfrKuraGr3z8nHPWb8TOOWdtw9bdvn1VUeR/RAwF7gbeAXwb+D9gWWauLnZZAowsHo8EHgPIzNURsRzYHPh7P9Yt9Vpvm6/BzHMiSdIgcv31pa6hpQVuvbXbwJF994V582pU2wDXvmFr8+ijlY11Nd4XFTVtmbkG2DkiNgWuB97Z1zeOiInARICWlhZaW1v7+pJVt2LFioaos9yk0au736mftAyr7fv19r9FLWuEtXUO5M9Prc9JR2r9+amWav43HsifIUnSAJAJU6bAWWfB7rvDDTesFzjyuteVcknUsaFDO27cttuu47HFiyvbt6969OXambksIm4D3gtsGhEbFLNt2wBLi92WAtsCSyJiA+BNwNMdvNY0YBrAmDFjcuzYsb3+IWqltbWVRqiz3LE1nEGZNHo1Ux6o3fe1LzpqbK+Oq+U5gbV1DuTPT63PSUdq/fmplt5+LisxkD9DkqQ6W70aTj65FDhy2GGlC7OGDbNJ64GNNoJjjln3mra28XPPXX//c89d95q2rvbtq0rSI7csZtiIiGHAh4E/ALcBhxa7HQPcUDyeVWxTPH+r17NJkiRJVfLcc+skRA7575nERsOIaJ6GbUjR1Qwduu795puXbhHrPn7rW0vfgvDWt67dnjYNLrusdN9+vKNr1I46qvJ9+6qSf9beCpheXNc2BLg6M+dExMPAzIj4KvB74Ipi/yuAH0XEQuAZ4Ij+L1uSJElSW0Lkqgf/yPF8j++fV92EyGqJgOOPLzVN9XbUUZU3Xj3Zty8qSY+8H9ilg/E/A7t3MP4ScFi/VCdJkiRpPfvuC8vn/Y7ZTOANvMSh3MQ89q13Wes44YSB0YQNBo1/AYkkSZLUJCJK9wdzPbM4iido4UPcyh/oOiGyvw0dWrr2qxazTKrgmjZJkiRJ9TNjRqlZKzVsySQu4Fo+xv28mz25q98btq23LgVRdnVbvdqGrZacaZMkSZIGqLaZNYChrOZSTuZ4vsN/cyif5EpeYlifXt8ljI3Bpk2S+lFvv6h80Xnj+rkSSVKjmjEDjj563bFNeI6r+Tj78XO+xmTO4VyyF4vm9tkHfvnLfipUNWPTJkmSJA0A5bNq5bblUeYyjnfyR47je3yfniVEXnWVSxkbnU2bJEmSVEedNWsAu7GA2UxgGC+yfw8SIp1RG1xs2iRJkqQ6GDoUXn218+cP5npmFAmR+zCv28CRzH4uUAOGTZs0iPT2eirVXyX/7SaNXs2x7fbzWjhJakxdza5Bcibf5Bt8nt+yOwdxA0/S0uGeO+wADz1UlRI1gNi0SZIkSTXSdbNWeUKks2rNxe9pkyRJkqpsxIjuG7ZNeI45jOd4vsPXmMzh/HS9hu2qq2zYmpEzbVKVtS1762hpW2dc8iZJ0uDRXbMGpYTIOYznXfyBz/BdruAz6zxvo9bcnGmTJEmSqiCisoZtNxYwnz14K4vZn5tea9h22KHUrNmwyZk2SZIkqZ9V0qzB2oTIJ3kz+/JLHmZHhg2DlSurW58aizNtkiRJUj/ZccdKG7bkTKZwLR/jft7NHsznYXYk04ZN67NpkyRJkvpBBDz8cPf7DWU1UzmBKXyOa/kYe3MbHzuhxWWQ6pTLI6UByO9bU6V6+1kx7EaS+lelyyE34Tmu5uPsx885j7P5Iv/Fq+k8irrmJ0SSJEnqpRkzKm/YtuVR7uB97MM8PsN3mZzn2bCpIs60qWE5GyX1Xm/+/3F2TpLWNWIELFtW2b67sYDZTGAjVnLYxjfxsxX7Vrc4DSq29pIkSVIPRVTesB3Ez7idD/Ayr+dND95pw6Yes2mTJEmSKlTpd6+VlBIir+OjPBijGfW3+aV4SamHbNokSZKkClTerJUSIi/jRKbwOYZ87KPsvuI2aGmpXnEa1GzaJEmSpG70pGHbhOeYw3hO4HI4+2y4+mrYaKPqFadBzyASSZIkqRM9adaglBA5h/HswMPw3e/CZz5TncLUVGzaJEmSpA70tGFrS4jc6o0r4dqbYV8DR9Q/XB4pSZIklRkxoucNW1tC5FZvfT3ceacNm/qVTZskSZJU6EmUf0lyBt/kOj7KRruPhvkmRKr/2bRJkiRJ9Hx2rS0h8ptMYsjHPgq3mRCp6rBpkyRJUtPracNmQqRqySASSZLKRMQQYHhmPlfvWiTVRm8SIucyntFDH4ap0+Df/706hUkFZ9okSU0vIn4cEW+MiI2BB4GHI+Lz9a5LUvX1JiHy0bfsweg3Loabb7ZhU01027RFxLYRcVtEPBwRD0XEacX4lyNiaUTcW9wOKDvmCxGxMCL+FBEfqeYPIElSP9ihmFk7GLgJeBvwifqWJKmaZszoXULkgmEfgNebEKnaqmR55GpgUmbeExGbAHdHxC3Fcxdm5gXlO0fEDsARwI7A1sAvI+IfM3NNfxYuSVI/2jAiNqTUtF2amasiIutdlKTqmDEDjj66J0ckOeVC+NznYPQ/w6xZBo6oprpt2jLzceDx4vHzEfEHYGQXhxwEzMzMl4G/RMRCYHfgN/1QryRJ1fAdYBFwH3B7RLwV8Jo2aRAaMaJnkf5DWc3q40+BSZfDxz4GV15p4IhqrkfXtEXEKGAXYH4xdHJE3B8R34+IEcXYSOCxssOW0HWTJ0lSXWXmxZk5MjMPyJLFwN71rktS/3rd63rWsG3Cc6zebwJcfjmcdZYJkaqbitMjI2I4cC1wemY+FxFTga8AWdxPAT7dg9ebCEwEaGlpobW1tQdl18eKFSsaos5yk0avrtl7tQyr7fs1Gs9P1zw/3av3OWq0P/96IiJagP8Cts7M/Yul/u8FrqhvZZL6y4knwqpVle+/LY/y6OjxcMvDMM2ESNVXRU1bsc7/WmBGZl4HkJlPlD3/XWBOsbkU2Lbs8G2KsXVk5jRgGsCYMWNy7NixvSi/tlpbW2mEOssdO3luzd5r0ujVTHnAb5HojOena56f7tX7HC06amzd3rsGfgj8ADin2P5f4KfYtEmDxtSple+7K3dz91vGw+KVcNNN8OEPV68wqQKVpEcGpV9af8jMb5aNb1W22yGUIpIBZgFHRMTrI+JtwPbAb/uvZEmS+t0WmXk18CpAZq4GDNCSBomepEQeyA3cvVFZQqQNmwaASv7Jdi9KsccPRMS9xdgXgSMjYmdKyyMXAZ8FyMyHIuJq4GFKyZMnmRwpSRrgXoiIzSn9TiMi9gSW17ckSf2h8oYt+e9/uZBDf/M52MmESA0slaRH3gF09HG/sYtjzgXO7UNdkiTV0pmUVoq8PSJ+DWwJHFrfkiT1xYknVr4kciiruXXHU/nAnVNNiNSA5AUkkqSmV3wX6QeBf6L0D5V/ysxuIwsi4g3A7cDrKf1OvSYzv1RcHjAT2By4G/hEZr4SEa8HrgR2A54GDs/MRdX4maRmtu++MG9eZftuwnM8t9/hcPPNpYTIr30NhvQoYF2qOps2SVLTi4hPthvaNSLIzCu7OfRl4EOZuaII7bojIm6iNHN3YWbOjIjLgeOAqcX9s5n5jog4AjgfOLx/fxqpufXk+rVteIy5jDMhUgOe/4wgSRL8c9nt/cCXgQO7O6j4TrcVxeaGxS2BDwHXFOPTgYOLxwcV2xTP71MEfknqBz35v2lX7mY+e/DuNy4uJUTasGkAc6ZNktT0MvOU8u2I2JTS8sZuRcRQSksg3wF8G/g/YFmRQAmwBBhZPB4JPFa85+qIWE5pCeXf273ma99lut122/XiJ5KaT08TIn/Mv7HxW7eEubfAjjtWrzCpHzjTJknS+l4A3lbJjpm5JjN3pvS9pLsD7+zrm2fmtMwck5ljttxyy76+nDTo9SQh8nQu5HoOYePdd4L5823Y1BCcaZMkNb2ImE0R90/pHzR3AK7uyWtk5rKIuA14L7BpRGxQzLZtAywtdlsKbAssiYgNgDdRCiSR1EuVNmxDWc3FnMqJmBCpxmPTJkkSXFD2eDWwODOXdHdQRGwJrCoatmHAhymFi9xG6SsDZgLHADcUh8wqtn9TPH9rZuZ6LyypIpU2bJvwHD/lcPbHhEg1Jps2SVLTy8xf9fLQrYDpxXVtQ4CrM3NORDwMzIyIrwK/B64o9r8C+FFELASeAY7oY+lS06q0YWtLiHz30IdhqgmRakw2bZKkphURz7N2WeQ6T1EKh3xjV8dn5v3ALh2M/5nS9W3tx18CDutdtZLaVNqw7crdzGYCW7/xBbjmJvjwh6tbmFQlNm2SpKaVmZvUuwZJPVNpw2ZCpAYTF/NKklSIiDdHxHZtt3rXI2ldlTVsZQmR/7wj3HWXDZsank2bJKnpRcSBEfEI8BfgV8Ai4Ka6FiVpHSNHdr/PUFbzbU7iQs5kyMc+Cq2t8Ja3VL02qdps2iRJgq8AewL/m5lvA/YB7qpvSZLK/fWvXT+/Cc8xmwmlSP+zzoKrrzbSX4OGTZskSaXY/qeBIRExJDNvA8bUuyhJJd0ti9yGx7iD9/FhboFp0+D8843016BiEIkkSbAsIoYDtwMzIuJJ4IU61ySJ7hu2toTIjXmBDX5hQqQGJ/8JQpLUtCLisIh4A3AQsBI4A7gZ+D9gQj1rk9R9w3YgN3A7H+AVXsebHvi1DUUcRZcAACAASURBVJsGLZs2SVIz+zfgUeByYD9K3802PTMvLpZLSqqTrhu2tQmRD7Ejox6/C3baqValSTVn0yZJalqZeQjwDuCXwCnAkoi4PCI+WN/KpObWVcM2lNVcyslcyJlczyF8eINWEyI16Nm0SZKaWmY+V8yu7Q/sBPweuDgiHqtzaZLa2YTnmMWBnMRlfJ3Pcxj/zfJVJkRq8DOIRJIkICJGAB8FDgc2A66pb0VSc+pslm0bHmMu49iBh5nId/guE8msbW1Svdi0SZKaVpEYeQhwJLALMIvSd7a1ZvrXQanWOmvYyhMiD+BGbuFfbdjUVGzaJEnNbBGltMjLgJ9n5qr6liM1r6FDOx4/kBv4Mf/GU2zJv/ILHmInGzY1HZs2SVIz2zYzX6x3EZLg1VfbjySncRHf5EwWMIYDmcUTvMWGTU3JIBJJUtOyYZMGhvbLItsSIr/FGVzPIYyllSd4C1tvXZ/6pHqzaZMkSVLdtG/YOkqIfJFSQuTSpXUoUBoAXB4pSZKkAWEbHmMO49mRh15LiGzjskg1M5s2SVLTiojZQKd/FczMA2tYjtR0ymfZOkqIbGPDpmZn0yZJamYXFPcfBd4CXFVsHwk8UZeKpCZR3rBNYBY/4Uj+zhbsxa95iJ1ee26ffepQnDTA2LRJkppWZv4KICKmZOaYsqdmR8SCOpUlDXprG7aOEyLL/fKXNS9PGnAMIpEkCTaOiH9o24iItwEb17EeadDaqJQp0mlCZDmXRUol3TZtEbFtRNwWEQ9HxEMRcVoxvllE3BIRjxT3I4rxiIiLI2JhRNwfEbtW+4eQJKmPzgBaI6I1In4F3AacXueapEHpxRdhOM93mhDZZtiwOhUoDUCVLI9cDUzKzHsiYhPg7oi4BTgWmJeZ50XEZGAycDawP7B9cdsDmFrcS5I0IGXmzRGxPfDOYuiPmflyPWuSBqOIrhMiy61cWePipAGs25m2zHw8M+8pHj8P/AEYCRwETC92mw4cXDw+CLgyS+4CNo2Irfq9ckmS+klEbAR8Hjg5M+8DtouI8XUuSxpURoyAXbiH+ezBKBZxADd22rC5LFJaV4+CSCJiFLALMB9oyczHi6f+BrQUj0cCj5UdtqQYe7xsjIiYCKX/U1taWmhtbe1Z5XWwYsWKhqiz3KTRq2v2Xi3Davt+jcbz0zXPT/fqfY4a7c+/HvoBcDfw3mJ7KfDfwJy6VSQNMu9f1nlCZDkbNml9FTdtETEcuBY4PTOfi7Kc1szMiOjR/2KZOQ2YBjBmzJgcO3ZsTw6vi9bWVhqhznLHTp5bs/eaNHo1Ux4wkLQznp+ueX66V+9ztOiosXV77xp4e2YeHhFHAmTmyij/RSep9zI5fchF/KyLhMiyXSV1oKL0yIjYkFLDNiMzryuGn2hb9ljcP1mMLwW2LTt8m2JMkqSB6pWIGEbxRdsR8XbAa9qkvlq9mkuHnMK3OIOfcXCHCZFtDB6ROldJemQAVwB/yMxvlj01CzimeHwMcEPZ+CeLFMk9geVlyyglSRqIvgTcDGwbETOAecBZ9S1JanDPP8+NGx7IyXybb/A5DuWa9RIiyxk8InWuknU2ewGfAB6IiHuLsS8C5wFXR8RxwGLg48VzNwIHAAuBlcCn+rViSZL6UUQMAUYAHwX2BAI4LTP/XtfCpEb22GPct914/rWbhMg2LouUutZt05aZd1D6BdaRfTrYP4GT+liXJEk1kZmvRsRZmXk1ULsLgaXB6p57+Otu43kbKziAG7mFf+1y9623rlFdUgOr6Jo2SZIGuV9GxOciYtuI2KztVu+ipIYzaxa8//2sYkP+hTu7bdiGDIGlJh9I3TKqTZIkOLy4L18pksA/1KEWqfFkwsUXwxln8LvcjQnM7jRwpNyaNTWoTRoEbNokSU0vM99W7xqkhrV6NZx+Onz721zHIRzNVV0GjrTxOjapci6PlCQ1vYjYKCL+X0RMK7a3j4jx9a5LGvCefx4OPBC+XVlCZBsbNqlnbNokSYIfAK8A/1JsLwW+Wr9ypAawZAm8733wi1/wWS7nLL5BVvBXSxs2qedcHilJErw9Mw+PiCMBMnNl8T2lkjpyzz0wfjysWMFH1szlF3yk3hVJg5ozbZIkwSsRMYxS+AgR8Xbg5fqWJA1Qs2fD+98PG27ITs/f2aOGzVk2qXds2iRJgi8BNwPbRsQMYB5wVn1LkgaYTLjoIjjoINhhB97y6HweYqceHS6pd1weKUlqepl5S0TcA+wJBHBaZv69zmVJA0dZQiSHHAJXXcUTG3cfONLGhk3qG5s2SVLTiohd2w09XtxvFxHbZeY9ta5JGnCefx6OOAJuvBE+9zk4/3xiaOWLtWzYpL6zaZMkNbMpxf0bgDHAfZRm2t4NLADeW6e6pIFhyZJS4MiDD8Lll8NnP0tPInps2KT+YdMmSWpambk3QERcB+yamQ8U2zsBX65jaVL9lSVEMncufOQjNmxSnRhEIkkS/FNbwwaQmQ8C76pjPVJ9lSVEcuedNmxSndm0SZIED0TE9yJibHH7LnB/vYuSaq5dQiTz58NOOzFjRuUvsfXW1StPalY2bZIkwbHAQ8Bpxe1h4FP1LEiqudWr4dRTSymRBx8Mv/oVvOUtABx9dGUvMWQILF1axRqlJuU1bZKkphYRQ4GbiuvbLqx3PVJddJAQyZDSv+33ZFnkmjVVqk9qcjZtkqSmlplrIuLViHhTZi6vdz1SzXWQENnG69ikgcGmTZIkWEHpurZbgBfaBjPz1PqVJNXAPffAhAmlmbYiIbKNDZs0cNi0SZIE1xU3qXnMnl1aErnFFvDrX8Po0QDsuy/Mm1f5y9iwSdVn0yZJEvwUeEfxeGFmvlTPYqSqu/jiUuDIbruVmrcicKQns2sAJ5xQhdokrcf0SElS04qIDSLi68ASYDpwJfBYRHw9Ijasb3VSFaxeDaecAqedtl5CZE8btq23hssuq0KNktZj0yZJambfADYD3paZu2XmrsDbgU2BC+pamdTfnn++9P1rl15aSoi85hrYaCOg5w0bGO0v1ZLLIyVJzWw88I+Za6/KycznIuIE4I+UvrNNanzlCZFTp8Lxx7/2VG8aNq9jk2rLpk2S1MyyvGErG1wTEf61VINDJwmRvWnWwIZNqgeXR0qSmtnDEfHJ9oMRcTSlmTapsc2eDe9/P2ywQSkh0oZNakjOtEmSmtlJwHUR8Wng7mJsDDAMOKRuVUn9oTwhctYsRuywFcuW9e6lbNak+rJpkyQ1rcxcCuwRER8CdiyGb8zMHnxLlTTArF4NZ5xRChw55BD40Y+I4Rv3+uVs2KT6s2mTJDW9zLwVuLWnx0XEtpS+JqAFSGBaZl4UEZtR+u63UcAi4OOZ+WxEBHARcACwEjg2M+/plx9CgtJ1a0ccATfeCJMmMXTK+bw6fGivX86GTRoYvKZNkqTeWw1MyswdgD2BkyJiB2AyMC8ztwfmFdsA+wPbF7eJwNTal6xBa8mS0vVrP/85TJ1KTLmAV7FhkwYDmzZJknopMx9vmynLzOeBPwAjgYMofVk3xf3BxeODgCuz5C5g04jYqsZlazC65x7YYw/4859h7lzihOO7P6YLNmzSwNJt0xYR34+IJyPiwbKxL0fE0oi4t7gdUPbcFyJiYUT8KSI+Uq3CJUkaSCJiFLALMB9oyczHi6f+Rmn5JJQausfKDltSjLV/rYkRsSAiFjz11FNVq1mDxOzZ8IEP8NjjQxn9/K+J/Xr/169MGzZpIKpkpu2HwH4djF+YmTsXtxsBiiUhR1C6mHs/4LKI6P28vCRJDSAihgPXAqdn5nPlzxXfA9ejvwZn5rTMHJOZY7bccst+rFSDzsUXw8EH87sX3sXuOZ8HGd2rl9l0U5s1aSDrtmnLzNuBZyp8vYOAmZn5cmb+BVgI7N6H+iRJGtAiYkNKDduMzLyuGH6ibdljcf9kMb4U2Lbs8G2KMalnVq+GU06B007julcPYiyt/I2er7Rtm1l79tkq1Cip3/QlPfLk4gtJF1C6CPtZSks87irbp8NlH1Ba+kHpImxaWlpobW3tQym1sWLFioaos9yk0atr9l4tw2r7fo3G89M1z0/36n2OGu3Pv1oo0iCvAP6Qmd8se2oWcAxwXnF/Q9n4yRExE9gDWF62jFKqzPPPM+eNRzKeuVzAJM7m/F4FjjizJjWO3jZtU4GvUFru8RVgCvDpnrxAZk4DpgGMGTMmx44d28tSaqe1tZVGqLPcsZPn1uy9Jo1ezZQH/BaJznh+uub56V69z9Gio8bW7b0HsL2ATwAPRMS9xdgXKTVrV0fEccBi4OPFczdSivtfSCny/1O1LVeNbptYwhzGsx8PcjxT+Q49DxyxWZMaT69++2fmE22PI+K7wJxi02UfkqSmkZl3ANHJ0/t0sH8CJ1W1KA1KEbAzv2c+49mE5xnHXH5BzwNHbNikxtSryP928cSHAG3JkrOAIyLi9RHxNkrfQ/PbvpUoSZLUnEaMKDVs45nN//B+1jCUvfh1jxs2UyGlxtbtTFtE/AQYC2wREUuALwFjI2JnSssjFwGfBcjMhyLiauBhSl84elJmrqlO6ZIkSYNTlM3fnsLFXMgZ3MOuHMisHgWO2KhJg0O3TVtmHtnB8BVd7H8ucG5fipIkSWpGJ54IU6eWHg9hDRdyBqdyCddzMEdzFSvZuOLXsmGTBg+v+pckSaqzaHdl5HCe5yf0LiHSZk0afHp1TZskSZL6bt9912/YRrKE/+H97MfNHM9UPs8FFTVsXrcmDV7OtEmSJNXBRhvBiy+uO7Yzv2dODxMibdSkwc+ZNkmSpBp73evWb9h6mhDpzJrUPJxpaxCjavgl2ZIkqXraL4eEtQmRv2cXJjC7y4RIGzWp+TjTJkmSVCPtG7YhrOEiTuViTmMWB/JBftVhw7bPPs6sSc3MmTZJkqQaaN+wbcwKZnJEtwmRNmqSnGmTJEmqote9rucJkSec4MyapLWcaZMkSaqSjq5fK0+IHM8cfs5+6zxvoyapPWfaJEmS+llH378GMI456yRE2rBJqoQzbZIkSf1oxAhYtmz98e4SIm3YJHXGmTZJkqR+ErF+w1ZJQqQNm6Su2LRJkiT1g46WQ27MCn7GwZzKJVzAJA7lGlay8WvPb721DZuk7rk8UpIkqY86athGsoTZTGA0D3ACl3E5J6zzvM2apErZtEmSJPWBCZGSqs3lkZIkSb3U04TIYcNs2CT1nE2bJElSL3TUsJ3CxdzAQfyRd7IH83mQ0a89lwkrV9awQEmDhssja2zU5Ln1LkGSJPXBiSfC1Knrjg1hDRdyBqdyCT/jII5ixjqBI86uSeoLZ9okSZIqMGNGaXatfcNWnhA5hTP5GNe+1rCZDimpPzjTJkmS1I3OvjB7a5Yyh/EdJkTusw/88pc1LFLSoGXTJkmS1ImNNoIXX+z4ufdwL3MYzxt5br2EyE03tWGT1H+avmnryTVmk0av5thi/0XnjatWSZIkqc46um6t3DjmMJMjeIbNeB938ADvfu25HXaAhx6qQZGSmobXtEmSpKbXdr1a262rhu1kLlknIdKGTVK1Nf1MmyRJam6dXa/WXncJkTZskqrFpk2SJDWdHXeEhx+ufP+NWcFPOJIJzGEKZ3IWX+dVhgKw4YbwyitVKlSSsGmTJElNZN99Yd68nh2zNUuZzQTew33rJUQa5y+pFrymTZIkDSozZsAGG6x7jVrbracN23u4l/nswfY8wnjmvNaw7bCDDZuk2rFpkyRJDW/ffdc2ZkcfDWvW9P01xzGHO3gfrzKEvfg1N7M/V11Vata8dk1SLbk8UpIkNazeLHesxMlcwrc4nd+zCxOYzUubbkU+2//vI0mVcKZNkiQ1nLaI/v5u2Iawhos4lUs4laEHTWDMil/xeG7FszZskuqo26YtIr4fEU9GxINlY5tFxC0R8UhxP6IYj4i4OCIWRsT9EbFrNYuXJEmD24wZMHz4+temHX10/7/XxqzgZxzMqVwCZ54J114LG2/c/YGSVGWVzLT9ENiv3dhkYF5mbg/MK7YB9ge2L24TgS6+mlKSJDWbGTNgiy06Dgnp6Hb00fDCC9Wva/InlrJilw8wYciNcNllMGUKDB1a/TeWpAp027Rl5u3AM+2GDwKmF4+nAweXjV+ZJXcBm0bEVv1VrCRJqo4ZM2DUKBgypHQ/Y0bH4yeeuHZ7iy1Kt/LHEWuTG4cM6bgJe/rpuv2Y6znhBMjf38vXbt0DHnkE5swpDUrSABJZQV5tRIwC5mTmTsX2sszctHgcwLOZuWlEzAHOy8w7iufmAWdn5oIOXnMipdk4Wlpadps5c2b//EQ99MDS5RXv2zIMnnix9Hj0yDdV/f0aTfn50fo8P13z/HSv3ueot3/utbf33nvfnZlj+uXFmsCYMWNywYL1fo1WZMYMOOccePRR2G47OPdcOOqojvebOBFWrlw7ttFGcMwxMH36uuON6IQTSpNnHZo7Fw4/HEaMKD1+97trWpsktYmITn8/9jk9MjMzInr8TSWZOQ2YBqVfSGPHju1rKb1y7OS5Fe87afRqpjxQOmWLjhpb9fdrNOXnR+vz/HTN89O9ep+j3v65p/po34gtXlzahvUbt3POWb8xW7kSpk3rn+j8WuuySSt3ySVw+umw884wezZsvXXVa5Ok3uhteuQTbcsei/sni/GlwLZl+21TjEmSpBrqrBE755z193300Y5fo9EatrYvvO62YVuzBk47DU49FSZMgNtvt2GTNKD1tmmbBRxTPD4GuKFs/JNFiuSewPLMfLyPNUqSpB7qrBHraHy77Tret1FyOIYPh6uuqvALr1esgIMPhosvNiFSUsOoJPL/J8BvgH+KiCURcRxwHvDhiHgE2LfYBrgR+DOwEPgucGJVqpYkSV3qrBHraPzcc0vXsJXbaKPScsr24/W0+eal5ixz3dvzz3d8rd56li6FD3wAbjQhUlJj6fbiiMw8spOn9ulg3wRO6mtRkiSpb849t+NwkXPPXX/ftoano9CSvfZad/yAA0o9z6OPwmablY575pm1j59+utQHrVlTSovsKO9s883hoosqbLT6y733wvjxsHx5KSFy//1r+OaS1Dde9S9J0iDUVSPW2f4dPdfZeEMpT4i84w54z3vqXZEk9YhNmyRJg9SgaLj66tJLS6EjJkRKamC9DSKRJEkauNoSIk85xYRISQ3Ppk2SJA0uK1bAIYeUEiLPOMOESEkNz+WRkiRp8Fi6tDSzdt998O1vw4kGWUtqfDZtkiRpcDAhUtIg5fJISZLU+ObOhfe9r/Q9A3fcYcMmaVBxpq2XRk2eW+8SJEkSmBApadBzpk2SJDWm8oTI8eNNiJQ0aNm0SZKkxtM+IfK660yIlDRouTxSkiQ1FhMiJTUZmzZJktQ47rsPxo0zIVJSU3F5pCRJagw33mhCpKSmZNMmSZIGvksvLS2J/Md/hPnz4T3vqXdFklQzNm2SJGngWrMGTj/dhEhJTc2mTZKkXoqI70fEkxHxYNnYZhFxS0Q8UtyPKMYjIi6OiIURcX9E7Fq/yhtEW0LkRReZECmpqdm0SZLUez8E9ms3NhmYl5nbA/OKbYD9ge2L20Rgao1qbEx//St84AMwd24pIfKb34ShQ+tdlSTVhU2bJEm9lJm3A8+0Gz4ImF48ng4cXDZ+ZZbcBWwaEVvVptIGc999sMce8MgjMHu2kf6Smp5NmyRJ/aslMx8vHv8NaCkejwQeK9tvSTG2noiYGBELImLBU089Vb1KB6K2hEgoJUQecEB965GkAcCmTZKkKsnMBLIXx03LzDGZOWbLLbesQmUD1Le/bUKkJHXApk2SpP71RNuyx+L+yWJ8KbBt2X7bFGNqS4g8+WQTIiWpAzZtkiT1r1nAMcXjY4AbysY/WaRI7gksL1tG2bzKEyJPP92ESEnqwAb1LkCSpEYVET8BxgJbRMQS4EvAecDVEXEcsBj4eLH7jcABwEJgJfCpmhc80Pz1r6WZtfvuKy2NNHBEkjo0aJq2UZPn1rsESVKTycwjO3lqnw72TeCk6lbUQO67r9SwLVtWSog0cESSOuXySEmSVFsmREpSj9i0SZKk2mlLiNx+exMiJalCNm2SJKn6yhMix40zIVKSesCmTZIkVVf7hMjrr4fhw+tdlSQ1jEETRCJJkgag8oTISy+Fk8xikaSesmmTJEnVYUKkJPWLPi2PjIhFEfFARNwbEQuKsc0i4paIeKS4H9E/pUqSpIbRlhCZaUKkJPVRf1zTtndm7pyZY4rtycC8zNwemFdsS5KkZmFCpCT1q2oEkRwETC8eTwcOrsJ7SJKkgWbNGjjjjHUTIkeOrHdVktTwIjN7f3DEX4BngQS+k5nTImJZZm5aPB/As23b7Y6dCEwEaGlp2W3mzJm9rgPggaXL+3R8JVqGwRMvVv1tGpbnp2uen655frpX73M0euSb+uV19t5777vLVmeoG2PGjMkFCxbUu4zurVgBRx0Fs2aVEiIvuACGDq13VZLUMCKi09+PfQ0ieV9mLo2INwO3RMQfy5/MzIyIDrvCzJwGTIPSL6SxY8f2qZBjJ8/t0/GVmDR6NVMeMLulM56frnl+uub56V69z9Gio8bW7b01wP31r6XlkPfea0KkJFVBn377Z+bS4v7JiLge2B14IiK2yszHI2Ir4Ml+qFOSJA1EJkRKUtX1+pq2iNg4IjZpewz8K/AgMAs4ptjtGOCGvhYpSZIGIBMiJakm+jLT1gJcX7psjQ2AH2fmzRHxO+DqiDgOWAx8vO9lSpKkAeWyy+CUU0rJkLNnGzgiSVXU66YtM/8MrJfhm5lPA/v0pShJkjRArVkDn/scfOtbpevYfvxjGD683lVJ0qBWjch/SZI0GK1YAR/9aKlhO+00uP56GzZJqgGj2iRJUvdMiJSkurFpkyRJXTMhUpLqyuWRkiSpczfdZEKkJNWZTZskSerYZZeVZti23x7mzy8lRUqSas6mTZIkrWvNGjjjjNJ1a+PGwe23G+kvSXXkNW2SJGmtF16Af/s3mDWrlBA5ZQoMHVrvqiSpqdm0SZKkkvKEyEsugZNPrndFkiRs2iRJEsD995eWQi5bVpplGzeu3hVJkgpe0yZJUrO76SbYa6+1CZE2bJI0oNi0SZLUzEyIlKQBz6ZNkqRmtGYNnHmmCZGS1AC8pk2SpGZjQqQkNRSbNkmSmokJkZLUcGzaJElqFiZESlJD8po2SZKaQXlC5P/8jw2bJDUQmzZJkga7qVPXTYjceed6VyRJ6gGbNkmSBqtMmDQJTjzRhEhJamA2bZIkDVYRsMkmpYTI66+H4cPrXZEkqRcMIpEkaTD70pdKzZskqWE506b/v737D5arrO84/v40QKCIWIUyqUkJQ2OY1EKkEBFHh2K18ccQUCxhKAVNi3aMQzvWFnTG1lpaCq2pgmgB0wTNEJFqm6FpAwQcmCIQgQRJICUVKKSBtFZQaw1N+PSP89xkc7m7dy9m95zd+3nN7NxznvPrm2+e3XOefZ5zNiIihlkabBERAy+NtoiIiIiIiAZLoy0iIiIiIqLB0miLiIiIiIhosDTaIiIiIiIiGiyNtoiIiIiIiAZLoy0iIiIiIqLB0miLiIiIiIhosDTaIiIiIiIiGqxnjTZJ8yVtlrRF0kW9Ok5ERERERMQw60mjTdIU4HPA24E5wNmS5vTiWBEREREREcOsVz1t84Attr9j+3lgJbCgR8eKiIiIiIgYWr1qtL0aeLJl/qlSFhERERERERMg2/t+p9KZwHzbv1XmzwVeb3txyzoXABeU2dnA5n0eyL53GPBfdQfRYMlPZ8lPZ8nP+IYlR0faPrzuIAaFpP8EnmgpGtR6MKhxw+DGPqhxQ2Kvw6DGDYMb++i4254f9+tRAFuBGS3z00vZbravBq7u0fF7QtK3bJ9QdxxNlfx0lvx0lvyMLzmanEafwAe1Hgxq3DC4sQ9q3JDY6zCoccPgxj6RuHs1PHIdMEvSUZIOABYCq3p0rIiIiIiIiKHVk5422zslLQbWAFOApbY39uJYERERERERw6xXwyOxvRpY3av912SghnPWIPnpLPnpLPkZX3IUMLj1YFDjhsGNfVDjhsReh0GNGwY39q7j7smDSCIiIiIiImLf6NU9bREREREREbEPpNHWQtJSSdslPdRS9seStkpaX17vaFl2saQtkjZL+rV6ou4fSTMk3S5pk6SNki4s5a+UdIukR8vfnynlkvTZkqMHJR1f77+gtzrkJ3UIkHSgpHslbSj5+WQpP0rSPSUPXykPL0LS1DK/pSyfWWf8vdYhP8skPdZSf+aW8kn1/oqxSfqIJEs6rO5YuiHpU6W+rpd0s6Sfqzumbkm6XNIjJf6vS3pF3TF1Q9J7y2fKC5Ia/3Q9SfPLOXGLpIvqjqdbY11DDop21y9N1+68OSgkTZH0gKSbulk/jba9LQPmj1G+xPbc8loNIGkO1VMxf7Fsc5WkKX2LtB47gY/YngOcBHyo5OEiYK3tWcDaMg/wdmBWeV0AfL7/IfdVu/xA6hDADuBU28cBc4H5kk4C/oIqP78AfA9YVNZfBHyvlC8p6w2zdvkB+GhL/Vlfyibb+ytGkTQDeBvw73XHMgGX2z7W9lzgJuATdQc0AbcAr7V9LPCvwMU1x9Oth4B3A3fUHch4yjnwc1Sfb3OAs1vOo023jLGvIQdBp+uXJut03hwEFwIPd7tyGm0tbN8B/HeXqy8AVtreYfsxYAswr2fBNYDtbbbvL9M/oKpor6bKxfKy2nLg9DK9ALjOlbuBV0ia1uew+6ZDftqZVHWo1IMfltn9y8vAqcCNpXx0/RmpVzcCb5GkPoXbdx3y086ken/FmJYAf0DnetIotr/fMnswgxX7zbZ3ltm7qX6DtvFsP2x7c91xdGkesMX2d2w/D6yk+qxrvAleQzbKS7h+aYSXcN5sDEnTgXcC13a7TRpt0BTo2QAAB+RJREFU3VlchkMsHRn6R1WZn2xZ5ykGoILvK2Wo2uuAe4AjbG8ri54GjijTkzZHo/IDqUPA7qEA64HtVN9a/xvwbMuFUGsOduenLH8OeFV/I+6v0fmxPVJ/Lin1Z4mkqaVs0tWf2EPSAmCr7Q11xzJRki6R9CRwDoPV09bq/cA/1R3EEMrnWs3GuH5ptA7nzab7a6ov3V7odoM02sb3eeBoqm7XbcBf1RtO/SS9DPg74HdHfWuKq8eRDsS3HL0yRn5Shwrbu8qwqOlU36geU3NIjTI6P5JeSzUE6xjgROCVwB/WGGL0kaRbJT00xmsB8DEa2uAZJ25sf9z2DGAFsLjeaPc2XuxlnY9TDSdbUV+ke+sm7ojxdLq+a6o2581Gk/QuYLvt+yayXc9+p21Y2H5mZFrSNVRj8AG2AjNaVp1eyoaapP2p3tArbH+tFD8jaZrtbWV41vZSPulyNFZ+UodezPazkm4H3kA1rG+/0pvWmoOR/DwlaT/gUOC7tQTcZy35mW/7L0vxDkl/C/x+mZ+09WeysP2rY5VL+iXgKGBDGTE8Hbhf0jzbT/cxxDG1i3sMK6h+z/WPehjOhIwXu6TzgXcBb3GDfjNpAjlvunyu1aTN9d3AaD1vUt3H2WRvBE5T9WC6A4GXS/qy7d/otFF62sYx6h6RM9hTEVYBC1U94e4oqocB3Nvv+Pqp3E/0ReBh259uWbQKOK9Mnwf8Q0v5b6pyEvBcyzDKodMuP6lDFUmHqzxtTdJBwFupxs3fDpxZVhtdf0bq1ZnAbU26SNrX2uTnkZH6U+rX6exdfybN+yv2sP1t2z9re6btmVRDyI5vQoNtPJJmtcwuAB6pK5aJkjSfajjTabZ/VHc8Q2odMEvVU4UPoHpY16qaYxp6Ha7vGq3debPeqMZn+2Lb08vn90Kq65uODTZIT9teJF0PnAIcJukpqm//TlH1iG0DjwMfALC9UdINwCaqYRIfsr2rjrj76I3AucC3y/hhqIboXArcIGkR8ATw62XZauAdVA/Y+BHwvv6G23ft8nN26hAA04Dlqp4O9lPADbZvkrQJWCnpT4EHqE4clL9fkrSF6ubuhXUE3Uft8nObpMMBAeuBD5b1J9v7K4bDpZJmU93H8QR76vMguBKYCtxSejjvtt34+CWdAVwBHA78o6T1thv5EzO2d0paDKwBpgBLbW+sOayujHUNafuLnbdqjDGvX0aedt1gY543a46pZzTEX1xHREREREQMvAyPjIiIiIiIaLA02iIiIiIiIhosjbaIiIiIiIgGS6MtIiIiIiKiwdJoi4iIiIiIaLA02iIiIiIGmKRXSVpfXk9L2lqmny0/q9LPWE6XNKdl/k8kTfjHvyXNlFTbjyRL+tio+bvK31rjiskrjbaIiIiIAWb7u7bn2p4LfAFYUqbnUv0m3j4lqdPv/J4O7G602f6E7Vv3dQx9sFejzfbJdQUSAWm0RURERAyzKZKukbRR0s2SDgKQdLSkf5Z0n6Q7JR1TymdKuk3Sg5LWSvr5Ur5M0hck3QNcNtb2kk4GTgMuLz19R5ftziz7OFHSXZI2SLpX0iHleHdKur+8OjaOVLlS0mZJt0pa3bL/xyUdVqZPkPSNMj1P0jclPVCOP7uUny/pa+Xf8aiky0r5pcBB5d+wopT9cIxYpki6XNK6kq8PlPJpku4o2z8k6U0/4f9hBJ2+KYmIiIiIwTYLONv2b0u6AXgP8GXgauCDth+V9HrgKuBU4Apgue3lkt4PfJaq9wxgOnCy7V2S1o7e3vapklYBN9m+EUAS5e8BwFeAs2yvk/Ry4H+B7cBbbf9Y0izgeuCEDv+eM4DZVL15RwCbgKXj5OAR4E22d5ahmn9W8gBVb+TrgB3AZklX2L5I0uLSW9nJIuA52ydKmgr8i6SbgXcDa2xfImkK8NPj7CdiXGm0RURERAyvx2yvL9P3ATMlvQw4GfjqSKMKmFr+voGq0QHwJeCyln19tTTYOm3fzmxgm+11ALa/DyDpYOBKSXOBXcBrxtnPm4Hrbe8C/kPSbeOsD3AosLw0Cg3s37Jsre3nSiybgCOBJ7vYJ8DbgGNHevrKcWYB64ClkvYH/r4l/xEvWRptEREREcNrR8v0LuAgqttjnu2iJ2m0/yl/X+r2Y/k94BnguLLfH/8E+9rJnlt/Dmwp/xRwu+0zJM0EvtGybHR+JnJtLODDtte8aIH0ZuCdwDJJn7Z93QT2G/EiuactIiIiYhIpvVyPSXov7L5P7Liy+C5gYZk+B7hzgtv/ADhkjMNuBqZJOrFsc0h5oMmhVD1wLwDnAlPGCf8O4KxyP9k04Fdalj0O/HKZfk9L+aHA1jJ9/jj7H/F/paeskzXA74ysJ+k1kg6WdCTwjO1rgGuB47s8ZkRbabRFRERETD7nAIskbQA2AgtK+YeB90l6kKoRdeEEt18JfLQ89OPokZVtPw+cBVxRtrmFqjfsKuC8UnYMe3rz2vk68CjVvWzXAd9sWfZJ4DOSvkXVazbiMuDPJT1A9z1pVwMPjjyIpI1rSxz3q/oZgL8p+z8F2FCOdxbwmS6PGdGWbNcdQ0RERETEhElaRsuDTyKGVXraIiIiIiIiGiw9bREREREREQ2WnraIiIiIiIgGS6MtIiIiIiKiwdJoi4iIiIiIaLA02iIiIiIiIhosjbaIiIiIiIgGS6MtIiIiIiKiwf4fCJDTwA70Bn8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1080x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h1ImvcaIkSHf"
      },
      "source": [
        "---------------------"
      ]
    }
  ]
}