Python/Regression_Models.ipynb

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    "colab": {
      "name": "Regression_Models.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMVjl0krnj7nQOnvdLyPSfU",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/happyrabbit/IntroDataScience/blob/master/Python/Regression_Models.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SMyu1xW6Jmf3"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "from scipy import stats\n",
        "from statistics import mean\n",
        "import statsmodels.api as sm\n",
        "from sklearn.preprocessing import scale\n",
        "from statsmodels.nonparametric.smoothers_lowess import lowess\n",
        "import sklearn.model_selection as ms\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.cross_decomposition import PLSRegression, PLSSVD\n",
        "from sklearn.metrics import mean_squared_error"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wDG57VkpgELs"
      },
      "source": [
        "# Ordinary Least Square"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4kdcBtOUJ36A",
        "outputId": "494cb857-bc88-467c-e8d8-4a3a04bf0fab",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "# load data\n",
        "sim_dat = pd.read_csv(\"http://bit.ly/2P5gTw4\")\n",
        "sim_dat.head()"
      ],
      "execution_count": 262,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>gender</th>\n",
              "      <th>income</th>\n",
              "      <th>house</th>\n",
              "      <th>store_exp</th>\n",
              "      <th>online_exp</th>\n",
              "      <th>store_trans</th>\n",
              "      <th>online_trans</th>\n",
              "      <th>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>Q5</th>\n",
              "      <th>Q6</th>\n",
              "      <th>Q7</th>\n",
              "      <th>Q8</th>\n",
              "      <th>Q9</th>\n",
              "      <th>Q10</th>\n",
              "      <th>segment</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>57</td>\n",
              "      <td>Female</td>\n",
              "      <td>120963.400958</td>\n",
              "      <td>Yes</td>\n",
              "      <td>529.134363</td>\n",
              "      <td>303.512475</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>Price</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>63</td>\n",
              "      <td>Female</td>\n",
              "      <td>122008.104950</td>\n",
              "      <td>Yes</td>\n",
              "      <td>478.005781</td>\n",
              "      <td>109.529710</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>Price</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>59</td>\n",
              "      <td>Male</td>\n",
              "      <td>114202.295294</td>\n",
              "      <td>Yes</td>\n",
              "      <td>490.810731</td>\n",
              "      <td>279.249582</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>Price</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>60</td>\n",
              "      <td>Male</td>\n",
              "      <td>113616.337078</td>\n",
              "      <td>Yes</td>\n",
              "      <td>347.809004</td>\n",
              "      <td>141.669752</td>\n",
              "      <td>10</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>Price</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>51</td>\n",
              "      <td>Male</td>\n",
              "      <td>124252.552787</td>\n",
              "      <td>Yes</td>\n",
              "      <td>379.625940</td>\n",
              "      <td>112.237177</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>Price</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  gender         income house   store_exp  ...  Q7  Q8  Q9  Q10  segment\n",
              "0   57  Female  120963.400958   Yes  529.134363  ...   1   4   2    4    Price\n",
              "1   63  Female  122008.104950   Yes  478.005781  ...   1   4   1    4    Price\n",
              "2   59    Male  114202.295294   Yes  490.810731  ...   1   4   1    4    Price\n",
              "3   60    Male  113616.337078   Yes  347.809004  ...   1   4   2    4    Price\n",
              "4   51    Male  124252.552787   Yes  379.625940  ...   1   4   2    4    Price\n",
              "\n",
              "[5 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 262
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MyWrElFOJ_Ws"
      },
      "source": [
        "Before fitting the model, we need to clean the data, such as removing bad data points that are not logical (negative expense)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B2zOPqkjJ4UB"
      },
      "source": [
        "sim_dat = sim_dat[sim_dat.store_exp >0] \n",
        "sim_dat = sim_dat[sim_dat.online_exp > 0]"
      ],
      "execution_count": 263,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vcmykFdnLQp5"
      },
      "source": [
        "Use 10 survey question variables as our explanatory variables."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gl-BUy2gKJaj"
      },
      "source": [
        "dat = sim_dat.filter(regex = \"^Q\")"
      ],
      "execution_count": 264,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sdx0sqikLbQG"
      },
      "source": [
        "The response variable is the sum of in-store spending and online spending."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T8SqWzG7LjlL",
        "outputId": "a1680e07-be80-4ff4-87e3-8a13ce5d4abb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        }
      },
      "source": [
        "# total expense = in store expense + online expense\n",
        "dat['total_exp'] = sim_dat.store_exp + sim_dat.online_exp\n",
        "dat.head()"
      ],
      "execution_count": 265,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:2: 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",
            "  \n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>Q5</th>\n",
              "      <th>Q6</th>\n",
              "      <th>Q7</th>\n",
              "      <th>Q8</th>\n",
              "      <th>Q9</th>\n",
              "      <th>Q10</th>\n",
              "      <th>total_exp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>4</td>\n",
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              "      <td>4</td>\n",
              "      <td>832.646838</td>\n",
              "    </tr>\n",
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              "      <td>4</td>\n",
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              "      <td>4</td>\n",
              "      <td>587.535491</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>770.060313</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
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              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
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              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>489.478756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
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              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>491.863117</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Q1  Q2  Q3  Q4  Q5  Q6  Q7  Q8  Q9  Q10   total_exp\n",
              "0   4   2   1   2   1   4   1   4   2    4  832.646838\n",
              "1   4   1   1   2   1   4   1   4   1    4  587.535491\n",
              "2   5   2   1   2   1   4   1   4   1    4  770.060313\n",
              "3   5   2   1   3   1   4   1   4   2    4  489.478756\n",
              "4   4   1   1   3   1   4   1   4   2    4  491.863117"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 265
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KjnXTQnYLimV"
      },
      "source": [
        "To fit a linear regression model, let us first check if there are any missing values or outliers:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sfxwVMEKexNe",
        "outputId": "f2df4202-dbcb-434e-dac5-c67095439039",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "dat.info()"
      ],
      "execution_count": 266,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 999 entries, 0 to 999\n",
            "Data columns (total 11 columns):\n",
            " #   Column     Non-Null Count  Dtype  \n",
            "---  ------     --------------  -----  \n",
            " 0   Q1         999 non-null    int64  \n",
            " 1   Q2         999 non-null    int64  \n",
            " 2   Q3         999 non-null    int64  \n",
            " 3   Q4         999 non-null    int64  \n",
            " 4   Q5         999 non-null    int64  \n",
            " 5   Q6         999 non-null    int64  \n",
            " 6   Q7         999 non-null    int64  \n",
            " 7   Q8         999 non-null    int64  \n",
            " 8   Q9         999 non-null    int64  \n",
            " 9   Q10        999 non-null    int64  \n",
            " 10  total_exp  999 non-null    float64\n",
            "dtypes: float64(1), int64(10)\n",
            "memory usage: 93.7 KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TOOeEtbHabpU",
        "outputId": "7712212e-bfca-4afe-c441-f62ed53988ca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        }
      },
      "source": [
        "\n",
        "fig, axs = plt.subplots(ncols=2)\n",
        "\n",
        "fig.set_size_inches(16, 8)\n",
        "sns.set_theme(style=\"whitegrid\")\n",
        "sns.histplot(x=dat[\"total_exp\"], ax=axs[0])\n",
        "sns.boxplot(x=dat[\"total_exp\"], ax=axs[1])"
      ],
      "execution_count": 267,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9290f061d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 267
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1152x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AoeAo8hMe3UZ"
      },
      "source": [
        "There is no missing value in the response variable, but there are outliers. Outliers are usually best described by the problem to solve itself such that we know from domain knowledge that it is not possible to have such values. We can also use a statistical threshold to remove extremely large or small outlier values from the data. We use the Z-score to find and remove outliers."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "el8KpWLFB-pr"
      },
      "source": [
        "# calculate median of the absolute dispersion for total_exp\n",
        "y = dat.total_exp\n",
        "ymad = stats.median_absolute_deviation(y)\n",
        "# calculate z-score\n",
        "zs = (y - mean(y))/ymad\n",
        "dat = dat[zs <= 3.5]"
      ],
      "execution_count": 268,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vxjEUcybelB6",
        "outputId": "78cb61bb-4e10-42f1-9837-761d0ff353c3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 489
        }
      },
      "source": [
        "plt.figure(figsize=(19,8))\n",
        "cor_plot = sns.heatmap(dat.drop(columns=['total_exp']).corr(), annot = True)"
      ],
      "execution_count": 269,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1368x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Uu7PB5_cFsGP"
      },
      "source": [
        " Remove highly correlated explanatory variables with a threshold of 0.75:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "np1rZVTbISoQ"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "def find_correlation(df, thresh=0.9):\n",
        "  \"\"\"\n",
        "    Given a numeric pd.DataFrame, this will find highly correlated features,\n",
        "    and return a list of features to remove\n",
        "    params:\n",
        "    - df : pd.DataFrame\n",
        "    - thresh : correlation threshold, will remove one of pairs of features with\n",
        "               a correlation greater than this value\n",
        "    @Original python code by Scott Warchal (GitHub: https://gist.github.com/Swarchal/881976176aaeb21e8e8df486903e99d6), modified by Hui Lin\n",
        "  \"\"\"\n",
        "  corrMatrix = df.corr().abs()\n",
        "  corrMatrix.loc[:,:] =  np.tril(corrMatrix, k=-1)\n",
        "  already_in = set()\n",
        "  result = []\n",
        "\n",
        "  for col in corrMatrix:\n",
        "    perfect_corr = corrMatrix[col][corrMatrix[col] > thresh].index.tolist()\n",
        "    if perfect_corr and col not in already_in:\n",
        "      already_in.update(set(perfect_corr))\n",
        "      perfect_corr.append(col)\n",
        "      result.append(perfect_corr)\n",
        "        \n",
        "  select_nested = [f[1:] for f in result]\n",
        "  select_flat = [i for j in select_nested for i in j]\n",
        "  return select_flat"
      ],
      "execution_count": 270,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bO8RIV7VI6Rz",
        "outputId": "42a8f6cb-1df6-46a5-86aa-2ea472674e9f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        }
      },
      "source": [
        "removeCols = find_correlation(dat.drop(columns = ['total_exp']), thresh = 0.8)\n",
        "dat2 = dat.drop(columns = removeCols)\n",
        "dat2.corr()"
      ],
      "execution_count": 286,
      "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>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>Q6</th>\n",
              "      <th>Q8</th>\n",
              "      <th>total_exp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Q1</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.204073</td>\n",
              "      <td>0.211009</td>\n",
              "      <td>0.574563</td>\n",
              "      <td>0.529759</td>\n",
              "      <td>0.241402</td>\n",
              "      <td>-0.502225</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Q2</th>\n",
              "      <td>0.204073</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.491826</td>\n",
              "      <td>0.438618</td>\n",
              "      <td>0.400840</td>\n",
              "      <td>-0.058989</td>\n",
              "      <td>0.237724</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Q3</th>\n",
              "      <td>0.211009</td>\n",
              "      <td>0.491826</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.750710</td>\n",
              "      <td>-0.103039</td>\n",
              "      <td>-0.635736</td>\n",
              "      <td>0.570096</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Q4</th>\n",
              "      <td>0.574563</td>\n",
              "      <td>0.438618</td>\n",
              "      <td>0.750710</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.195380</td>\n",
              "      <td>-0.336292</td>\n",
              "      <td>0.146038</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Q6</th>\n",
              "      <td>0.529759</td>\n",
              "      <td>0.400840</td>\n",
              "      <td>-0.103039</td>\n",
              "      <td>0.195380</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.679606</td>\n",
              "      <td>-0.545836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Q8</th>\n",
              "      <td>0.241402</td>\n",
              "      <td>-0.058989</td>\n",
              "      <td>-0.635736</td>\n",
              "      <td>-0.336292</td>\n",
              "      <td>0.679606</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.719683</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_exp</th>\n",
              "      <td>-0.502225</td>\n",
              "      <td>0.237724</td>\n",
              "      <td>0.570096</td>\n",
              "      <td>0.146038</td>\n",
              "      <td>-0.545836</td>\n",
              "      <td>-0.719683</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 Q1        Q2        Q3  ...        Q6        Q8  total_exp\n",
              "Q1         1.000000  0.204073  0.211009  ...  0.529759  0.241402  -0.502225\n",
              "Q2         0.204073  1.000000  0.491826  ...  0.400840 -0.058989   0.237724\n",
              "Q3         0.211009  0.491826  1.000000  ... -0.103039 -0.635736   0.570096\n",
              "Q4         0.574563  0.438618  0.750710  ...  0.195380 -0.336292   0.146038\n",
              "Q6         0.529759  0.400840 -0.103039  ...  1.000000  0.679606  -0.545836\n",
              "Q8         0.241402 -0.058989 -0.635736  ...  0.679606  1.000000  -0.719683\n",
              "total_exp -0.502225  0.237724  0.570096  ... -0.545836 -0.719683   1.000000\n",
              "\n",
              "[7 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 286
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ctLWiKnxn4H-",
        "outputId": "6e3177d2-5aaa-4d04-fd22-f0f194ec8cbe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "x = dat2.drop(columns = ['total_exp'])\n",
        "x = sm.add_constant(x)\n",
        "y = np.log10(dat2.total_exp)\n",
        "\n",
        "lm = sm.OLS(y, x)\n",
        "lm_fit = lm.fit()\n",
        "print(lm_fit.summary())"
      ],
      "execution_count": 287,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                            OLS Regression Results                            \n",
            "==============================================================================\n",
            "Dep. Variable:              total_exp   R-squared:                       0.854\n",
            "Model:                            OLS   Adj. R-squared:                  0.853\n",
            "Method:                 Least Squares   F-statistic:                     785.2\n",
            "Date:                Mon, 09 Nov 2020   Prob (F-statistic):               0.00\n",
            "Time:                        03:32:24   Log-Likelihood:                 734.28\n",
            "No. Observations:                 811   AIC:                            -1455.\n",
            "Df Residuals:                     804   BIC:                            -1422.\n",
            "Df Model:                           6                                         \n",
            "Covariance Type:            nonrobust                                         \n",
            "==============================================================================\n",
            "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "const          3.5166      0.024    148.757      0.000       3.470       3.563\n",
            "Q1            -0.0638      0.005    -13.905      0.000      -0.073      -0.055\n",
            "Q2             0.0444      0.008      5.242      0.000       0.028       0.061\n",
            "Q3             0.1092      0.009     11.689      0.000       0.091       0.128\n",
            "Q4             0.0017      0.006      0.264      0.792      -0.011       0.014\n",
            "Q6            -0.0991      0.005    -19.535      0.000      -0.109      -0.089\n",
            "Q8            -0.0390      0.007     -5.358      0.000      -0.053      -0.025\n",
            "==============================================================================\n",
            "Omnibus:                       38.453   Durbin-Watson:                   2.039\n",
            "Prob(Omnibus):                  0.000   Jarque-Bera (JB):               49.862\n",
            "Skew:                          -0.448   Prob(JB):                     1.49e-11\n",
            "Kurtosis:                       3.821   Cond. No.                         45.0\n",
            "==============================================================================\n",
            "\n",
            "Warnings:\n",
            "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9JvmejeEW3wb"
      },
      "source": [
        "# Diagnostics for Linear Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lqwO6MnBfMir",
        "outputId": "7fa4ce9b-0a8a-486c-b329-ec68bbb07da3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 723
        }
      },
      "source": [
        "residuals = lm_fit.resid\n",
        "fitted = lm_fit.fittedvalues\n",
        "smoothed = lowess(residuals,fitted)\n",
        "top3 = abs(residuals).sort_values(ascending = False)[:3]\n",
        "\n",
        "plt.rcParams.update({'font.size': 16})\n",
        "plt.rcParams[\"figure.figsize\"] = (8,7)\n",
        "fig, ax = plt.subplots(nrows = 2, ncols = 2,  figsize=(22,12))\n",
        "\n",
        "############ residual plot\n",
        "ax[0,0].scatter(fitted, residuals, edgecolors = 'k', facecolors = 'none')\n",
        "ax[0,0].plot(smoothed[:,0],smoothed[:,1],color = 'r')\n",
        "ax[0,0].set_ylabel('Residuals')\n",
        "ax[0,0].set_xlabel('Fitted Values')\n",
        "ax[0,0].set_title('Residuals vs. Fitted')\n",
        "ax[0,0].plot([min(fitted),max(fitted)],[0,0],color = 'k',linestyle = ':', alpha = .3)\n",
        "\n",
        "for i in top3.index:\n",
        "    ax[0,0].annotate(i,xy=(fitted[i],residuals[i]))\n",
        "\n",
        "############ Q-Q plot\n",
        "sorted_student_residuals = pd.Series(lm_fit.get_influence().resid_studentized_internal)\n",
        "sorted_student_residuals.index = lm_fit.resid.index\n",
        "sorted_student_residuals = sorted_student_residuals.sort_values(ascending = True)\n",
        "df = pd.DataFrame(sorted_student_residuals)\n",
        "df.columns = ['sorted_student_residuals']\n",
        "df['theoretical_quantiles'] = stats.probplot(df['sorted_student_residuals'], dist = 'norm', fit = False)[0]\n",
        "rankings = abs(df['sorted_student_residuals']).sort_values(ascending = False)\n",
        "top3 = rankings[:3]\n",
        "\n",
        "x = df['theoretical_quantiles']\n",
        "y = df['sorted_student_residuals']\n",
        "ax[0,1].scatter(x,y, edgecolor = 'k',facecolor = 'none')\n",
        "ax[0,1].set_title('Normal Q-Q')\n",
        "ax[0,1].set_ylabel('Standardized Residuals')\n",
        "ax[0,1].set_xlabel('Theoretical Quantiles')\n",
        "ax[0,1].plot([np.min([x,y]),np.max([x,y])],[np.min([x,y]),np.max([x,y])], color = 'r', ls = '--')\n",
        "for val in top3.index:\n",
        "    ax[0,1].annotate(val,xy=(df['theoretical_quantiles'].loc[val],df['sorted_student_residuals'].loc[val]))\n",
        "\n",
        "############ student residual plot\n",
        "student_residuals = lm_fit.get_influence().resid_studentized_internal\n",
        "sqrt_student_residuals = pd.Series(np.sqrt(np.abs(student_residuals)))\n",
        "sqrt_student_residuals.index = lm_fit.resid.index\n",
        "smoothed = lowess(sqrt_student_residuals,fitted)\n",
        "top3 = abs(sqrt_student_residuals).sort_values(ascending = False)[:3]\n",
        "\n",
        "ax[1,0].scatter(fitted, sqrt_student_residuals, edgecolors = 'k', facecolors = 'none')\n",
        "ax[1,0].plot(smoothed[:,0],smoothed[:,1],color = 'r')\n",
        "ax[1,0].set_ylabel('$\\sqrt{|Studentized \\ Residuals|}$')\n",
        "ax[1,0].set_xlabel('Fitted Values')\n",
        "ax[1,0].set_title('Scale-Location')\n",
        "ax[1,0].set_ylim(0,max(sqrt_student_residuals)+0.1)\n",
        "for i in top3.index:\n",
        "    ax[1,0].annotate(i,xy=(fitted[i],sqrt_student_residuals[i]))\n",
        "\n",
        "############ Cook’s Distance\n",
        "student_residuals = pd.Series(lm_fit.get_influence().resid_studentized_internal)\n",
        "student_residuals.index = lm_fit.resid.index\n",
        "df = pd.DataFrame(student_residuals)\n",
        "df.columns = ['student_residuals']\n",
        "df['leverage'] = lm_fit.get_influence().hat_matrix_diag\n",
        "smoothed = lowess(df['student_residuals'],df['leverage'])\n",
        "sorted_student_residuals = abs(df['student_residuals']).sort_values(ascending = False)\n",
        "top3 = sorted_student_residuals[:3]\n",
        "\n",
        "x = df['leverage']\n",
        "y = df['student_residuals']\n",
        "xpos = max(x)+max(x)*0.01  \n",
        "ax[1,1].scatter(x, y, edgecolors = 'k', facecolors = 'none')\n",
        "ax[1,1].plot(smoothed[:,0],smoothed[:,1],color = 'r')\n",
        "ax[1,1].set_ylabel('Studentized Residuals')\n",
        "ax[1,1].set_xlabel('Leverage')\n",
        "ax[1,1].set_title('Residuals vs. Leverage')\n",
        "ax[1,1].set_ylim(min(y)-min(y)*0.15,max(y)+max(y)*0.15)\n",
        "ax[1,1].set_xlim(-0.01,max(x)+max(x)*0.05)\n",
        "\n",
        "for val in top3.index:\n",
        "    ax[1,1].annotate(val,xy=(x.loc[val],y.loc[val]))\n",
        "\n",
        "cooksx = np.linspace(min(x), xpos, 50)\n",
        "p = len(results.params)\n",
        "poscooks1y = np.sqrt((p*(1-cooksx))/cooksx)\n",
        "poscooks05y = np.sqrt(0.5*(p*(1-cooksx))/cooksx)\n",
        "negcooks1y = -np.sqrt((p*(1-cooksx))/cooksx)\n",
        "negcooks05y = -np.sqrt(0.5*(p*(1-cooksx))/cooksx)\n",
        "\n",
        "ax[1,1].plot(cooksx,poscooks1y,label = \"Cook's Distance\", ls = ':', color = 'r')\n",
        "ax[1,1].plot(cooksx,poscooks05y, ls = ':', color = 'r')\n",
        "ax[1,1].plot(cooksx,negcooks1y, ls = ':', color = 'r')\n",
        "ax[1,1].plot(cooksx,negcooks05y, ls = ':', color = 'r')\n",
        "ax[1,1].plot([0,0],ax[1,1].get_ylim(), ls=\":\", alpha = .3, color = 'k')\n",
        "ax[1,1].plot(ax[1,1].get_xlim(), [0,0], ls=\":\", alpha = .3, color = 'k')\n",
        "ax[1,1].annotate('1.0', xy = (xpos, poscooks1y[-1]), color = 'r')\n",
        "ax[1,1].annotate('0.5', xy = (xpos, poscooks05y[-1]), color = 'r')\n",
        "ax[1,1].annotate('1.0', xy = (xpos, negcooks1y[-1]), color = 'r')\n",
        "ax[1,1].annotate('0.5', xy = (xpos, negcooks05y[-1]), color = 'r')\n",
        "ax[1,1].legend()\n",
        "\n"
      ],
      "execution_count": 288,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f9290569470>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 288
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1584x864 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9VdEaqbmEQKo"
      },
      "source": [
        "# Principal Components Regression\n",
        "\n",
        "Let us use the 10 survey questions (`Q1`-`Q10`) as the explanatory variables and `income` as the response variable. First load the data and preprocessing the data:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9AduEDjAe5y-"
      },
      "source": [
        "# load data\n",
        "sim_dat = pd.read_csv(\"http://bit.ly/2P5gTw4\")\n",
        "sim_dat = sim_dat[sim_dat.income > 0]\n",
        "# calculate median of the absolute dispersion for income\n",
        "y = sim_dat.income\n",
        "ymad = stats.median_absolute_deviation(y)\n",
        "# calculate z-score\n",
        "zs = (y - mean(y))/ymad\n",
        "sim_dat = sim_dat[zs <= 3.5]"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bkjywMACrJfl"
      },
      "source": [
        "xtrain = sim_dat.filter(regex = \"^Q\")\n",
        "ytrain = sim_dat.income"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iinjAsn2rY4Z"
      },
      "source": [
        "pca = PCA()\n",
        "xtrain_pc = pca.fit_transform(scale(xtrain, axis = 0, with_mean = True, with_std = True))"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Is0xlk7lsi22"
      },
      "source": [
        "Let's print out the first few variables of the first few principal components:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FImQH4LPsb3H",
        "outputId": "8aa9a6c7-9860-4d5d-ab63-6d3b417b3efa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "pd.DataFrame(pca.components_.T).loc[:4,:5]"
      ],
      "execution_count": 27,
      "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>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.347528</td>\n",
              "      <td>-0.083611</td>\n",
              "      <td>0.512279</td>\n",
              "      <td>-0.172628</td>\n",
              "      <td>0.183858</td>\n",
              "      <td>0.658842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.100047</td>\n",
              "      <td>0.508312</td>\n",
              "      <td>-0.267229</td>\n",
              "      <td>-0.058849</td>\n",
              "      <td>0.210804</td>\n",
              "      <td>0.466175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.163582</td>\n",
              "      <td>0.507674</td>\n",
              "      <td>0.083695</td>\n",
              "      <td>0.020200</td>\n",
              "      <td>0.093503</td>\n",
              "      <td>0.119623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.038456</td>\n",
              "      <td>0.479928</td>\n",
              "      <td>0.431846</td>\n",
              "      <td>-0.228330</td>\n",
              "      <td>0.319326</td>\n",
              "      <td>-0.544996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.425154</td>\n",
              "      <td>-0.083809</td>\n",
              "      <td>-0.100016</td>\n",
              "      <td>0.101061</td>\n",
              "      <td>0.205063</td>\n",
              "      <td>0.093502</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          0         1         2         3         4         5\n",
              "0  0.347528 -0.083611  0.512279 -0.172628  0.183858  0.658842\n",
              "1 -0.100047  0.508312 -0.267229 -0.058849  0.210804  0.466175\n",
              "2 -0.163582  0.507674  0.083695  0.020200  0.093503  0.119623\n",
              "3  0.038456  0.479928  0.431846 -0.228330  0.319326 -0.544996\n",
              "4 -0.425154 -0.083809 -0.100016  0.101061  0.205063  0.093502"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8VvuZui3szPr"
      },
      "source": [
        "Now we'll perform 10-fold cross-validation to see how it influences the MSE:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oUOA_fgDspCT",
        "outputId": "31fe1ab3-a375-4f37-8cd6-d4ec2bdca711",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        }
      },
      "source": [
        "# 10-fold CV, with shuffle\n",
        "n = len(xtrain_pc)\n",
        "kf10 = ms.KFold( n_splits=10, shuffle = True, random_state = 100)\n",
        "\n",
        "lm = LinearRegression()\n",
        "mse = []\n",
        "\n",
        "# Calculate MSE with only the intercept (no principal components in regression)\n",
        "score = -1*ms.cross_val_score(lm, np.ones((n,1)), ytrain.ravel(), cv = kf10, scoring='neg_mean_squared_error').mean()    \n",
        "mse.append(score)\n",
        "\n",
        "# Calculate MSE using CV for the 10 principle components, adding one component at the time.\n",
        "for i in np.arange(1, 11):\n",
        "    score = -1*model_selection.cross_val_score(lm, xtrain_pc[:,:i], ytrain.ravel(), cv = kf10, scoring='neg_mean_squared_error').mean()\n",
        "    mse.append(score)\n",
        "    \n",
        "# Plot results    \n",
        "plt.plot(mse, '-v')\n",
        "plt.xlabel('Number of principal components in regression')\n",
        "plt.ylabel('MSE')\n",
        "plt.title('Principal Components Regression')\n",
        "plt.xlim(xmin=-1);"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hCo_8cXAu-zn"
      },
      "source": [
        "There is only minimum improvement in MSE after 3 components."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qHKP3nfBvVqO"
      },
      "source": [
        "# Partial Least Square\n",
        "\n",
        "Scikit-learn `PLSRegression` gives same results as the `pls` package in R when using `method='oscorespls'`.  However, the standard method used is `kernelpls`, which we will use here. Feel free to try out both."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pvoJJAsKtwpM",
        "outputId": "74a6152d-8c40-4888-83dd-373c207cac79",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        }
      },
      "source": [
        "n = len(xtrain)\n",
        "\n",
        "# 10-fold CV, with shuffle\n",
        "kf10 = model_selection.KFold(n_splits=10, shuffle = True, random_state = 100)\n",
        "\n",
        "mse = []\n",
        "\n",
        "for i in np.arange(1, 11):\n",
        "    pls = PLSRegression(n_components = i)\n",
        "    score = ms.cross_val_score(pls, scale(xtrain, axis = 0, with_mean= True, with_std=True), ytrain, cv=kf10, scoring='neg_mean_squared_error').mean()\n",
        "    mse.append(-score)\n",
        "\n",
        "# Plot results\n",
        "plt.plot(np.arange(1, 11), np.array(mse), '-v')\n",
        "plt.xlabel('Number of principal components in regression')\n",
        "plt.ylabel('MSE')\n",
        "plt.title('Salary')\n",
        "plt.xlim(xmin=-1)"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(-1.0, 10.45)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p6rLupxQwtfV"
      },
      "source": [
        "From the output, we see little difference after the model with 5 components. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jy9OwBdqtz3C"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}