00: Find_data_distriution.ipynb

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  "metadata": {
    "colab": {
      "name": "Data_distriution.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "mount_file_id": "1z7lomKjO4GYAS5bg8rZPU4Rcm7hx6vQc",
      "authorship_tag": "ABX9TyMHlU/JV+rI4nipfw6Gqp5U",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/gulabpatel/Statistics/blob/main/Data_distriution.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QRArk1GX9C1S"
      },
      "source": [
        "pip install pmlb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fgyEl0ryuISO"
      },
      "source": [
        "#Import Library"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QTNtMyPjq5br"
      },
      "source": [
        "import pandas as pd\r\n",
        "import numpy as np\r\n",
        "import scipy\r\n",
        "from scipy import stats as st\r\n",
        "from datetime import datetime\r\n",
        "import matplotlib.pyplot as plt\r\n",
        "import seaborn as sns\r\n",
        "import warnings\r\n",
        "warnings.filterwarnings(\"ignore\")\r\n",
        "from pmlb import fetch_data"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y_fvvzRbuQUO"
      },
      "source": [
        "#Read Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "mwdMURSsuPvm",
        "outputId": "85c9fa6e-b380-4043-e156-750274e40acc"
      },
      "source": [
        "data = fetch_data('adult')\r\n",
        "data"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>workclass</th>\n",
              "      <th>fnlwgt</th>\n",
              "      <th>education</th>\n",
              "      <th>education-num</th>\n",
              "      <th>marital-status</th>\n",
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              "      <th>sex</th>\n",
              "      <th>capital-gain</th>\n",
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              "      <th>hours-per-week</th>\n",
              "      <th>native-country</th>\n",
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              "      <td>40.0</td>\n",
              "      <td>39</td>\n",
              "      <td>1</td>\n",
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              "      <td>9</td>\n",
              "      <td>13.0</td>\n",
              "      <td>2</td>\n",
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              "      <td>60.0</td>\n",
              "      <td>39</td>\n",
              "      <td>0</td>\n",
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              "<p>48842 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        age  workclass    fnlwgt  ...  hours-per-week  native-country  target\n",
              "0      39.0          7   77516.0  ...            40.0              39       1\n",
              "1      50.0          6   83311.0  ...            13.0              39       1\n",
              "2      38.0          4  215646.0  ...            40.0              39       1\n",
              "3      53.0          4  234721.0  ...            40.0              39       1\n",
              "4      28.0          4  338409.0  ...            40.0               5       1\n",
              "...     ...        ...       ...  ...             ...             ...     ...\n",
              "48837  39.0          4  215419.0  ...            36.0              39       1\n",
              "48838  64.0          0  321403.0  ...            40.0              39       1\n",
              "48839  38.0          4  374983.0  ...            50.0              39       1\n",
              "48840  44.0          4   83891.0  ...            40.0              39       1\n",
              "48841  35.0          5  182148.0  ...            60.0              39       0\n",
              "\n",
              "[48842 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hcNxeJi4I94w"
      },
      "source": [
        "**Check whether there is any missing value in our data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-dMnCfL8u33B",
        "outputId": "3e8ff647-36b7-4540-9321-45de9feab699"
      },
      "source": [
        "#df_placement.describe()\r\n",
        "data.isnull().any()  "
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age               False\n",
              "workclass         False\n",
              "fnlwgt            False\n",
              "education         False\n",
              "education-num     False\n",
              "marital-status    False\n",
              "occupation        False\n",
              "relationship      False\n",
              "race              False\n",
              "sex               False\n",
              "capital-gain      False\n",
              "capital-loss      False\n",
              "hours-per-week    False\n",
              "native-country    False\n",
              "target            False\n",
              "dtype: bool"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NC0TnhQwF5bc"
      },
      "source": [
        "Distribution of data?\r\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "z1-UodtIGRYC",
        "outputId": "c8085244-bcc2-4f96-864e-9dc073044cfb"
      },
      "source": [
        "#plt.figure(figsize=(10,10))\r\n",
        "features = list(data.columns)\r\n",
        "for i in enumerate(features):\r\n",
        "  plt.figure(figsize=(5,30))\r\n",
        "  plt.subplot(data.shape[1],1,i[0]+1)\r\n",
        "  sns.distplot(data.loc[:,i[1]], bins=50, color=\"g\")\r\n",
        "  plt.show()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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6j4WbFzJ301xeyn2JhHoJHC4+zO0dbqdRVNB3eTZnUVkCLfVyG+BaFx54Dtewz1dV9akK2yNxzSnaCddSHoNVNV9EGuIa+dQZeFNVR1X2XTVpzsY5AHYDKYCEh4bTt1lfemf0Zvmu5SzIX8DYuWMZN28c1190PSM7jfRolifrKxpcKkug7USk4AzvC1DnXAdWcV34YmAc0Nr9qFVmb5xNUlQSDeo2cDoUU81CQ0LJSs4iKzmLnk178kreK7y54k2mrp5Ko6hGXJZ+Gd3Sutm8owaopA1UVUNVNfYMjxhVrawKX5V14Y+o6iIqX7iuxpWeKGXB5gVWfQ8CrRJa8eyVz7JjzA7evv5tYiNjmb52Og/NeYjJKydzqPiQ0yEah53Pmkjn60zrwnc92z7uNZROrgv/s3bX2mLJ1iUcPXbUqu9BpE5YHYa1HcbRY0fZUbiDefnzWLxlMUu2LeHATwd4qPtDxNeNdzpM4wBfJlCfE5ERwAiA9PT0GvnO2RtnEyqhXNjwwhr5PlN11dkumRyTzNA2Q+nfrD8fff8RTy9+mpfzXmZcz3GM6lKrmupNDfBlH5wqrQvvCSfWhZ+zcQ5dU7tSN7xujXyfqZ0SoxIZ3mE4K+5aQXZqNmO+GEObl9qwcvdKgnyQXlDxZQL1el14H8ZUJQd/Osg3O77hiswrnA7F1BJtk9ry6dBPmTVkFoLwwjcvMDFnIjsKdzgdmqkBPqvCV3FdeEQkH4gFIkTkOlzrwq+p+D01aX7+fMq0jH4X9GPNXkdDMVVU3bNnXd3iavo168fQGUOZtWEWf1r4J3o17cU1La/x6Lutq5N/8mkbqLfrwru3ZfgyNm/M3jib6IhouqZ0tQRqfiY8NJwrml1Bdmo2M9fPZH7+fHK25xAeGs5dWXcRFuLXtxzMGdg4xPMwe+Nsemf0tunrzDlFR0QzpM0QxvUcR1pcGr/59De0+1s7vvjxC6dDM9XM/kv00I8HfuSHAz9wX5f7nA7F1JCqVvNTYlO4v+v9NI5uzJgvxnDlO1cysOVAuiR3ISk6qZqiNE6yEqiHZm2YBcCAlgMcjsT4ExHh2lbXsvqe1Tx9xdMsyF/AhAUTmLZmGkePHXU6PFNFlkA99PH3H3NRwkU0i2/mdCjGD0WGRfJg9wfZ8JsNZKdmM3fjXMbNG8fCzQtt5ic/ZlV4DxSWFDI/fz6ju452OhRTy5xvNT8pOolftvslvTN6M3X1VCavmsyC/AW0bNiSPpl9fBSl8RVLoB747IfPOFZ2jIEtBzodigkQ6XHpjLl0DMt2LmP62un0/Xtf+mb25Yk+T9A1tat1dfITlkA98P7q90mKSqJHeg+nQzEBRETolNyJtkltKT1RypOLniT7tWyuaXkN7Rq3Iy02rfIPMY6yNtBKFJYUMmvDLG66+CZCQ0KdDscEoPDQcB649AE2jt7I45c/zsLNC3l84eNMWjaJXUW7nA7PnIOVQCsxc/1Mio8XM7j1YKdDMX7K03bS6IhoHu35KPd0voehM4by5aYvyduRR6fkTlx5wZU+jtJ4wxJoJV5b/hpN45rSLa2b06GYIBFfN57rWl1Hn8w+zP5xNgu3LCR3Ry4523N4sNuD9G3W19biqiUsgZ7D6j2rmZc/j6f6PmW/sKbGxUbGcsPFN3B1i6tZsHkBS7Ytof87/cmsn8lt7W9DkJ91yLcbTTXLEug5PJ/zPJGhkdzR8Q6nQzEB7lzV/Lrhdbmq+VW8d8N7TF87nTdWvMH4+eNRlEZRjWjdqDXN45uTGZ/p0bpNpvpYAj2L/EP5vLHiDYa1HUZCvQSnwzGGyLBIhrQZwpA2Q9hyeAsPzXmIVbtXsXDzQr7c9CUAE5dOpGtqVzo07kD7xu1p37g9abFpllR9xBLoWTz65aOICON7j3c6FGN+Jj0uncszLufyjMs5XnacbQXb2HhwI2EhYeRsz+Gf6/6J4ppaN75O/Klk2r5xezo07kCrhFY2KU41sAR6BrO+n8W7q97l0cseJTU21elwjAHOXs0PCwkjo34GGfUzTrWBFpUWsWr3KlbsWuF67F7BS7kvUXy8+NQxyTHJpMWmMfiSwbRv3J52jdsRGxlbY+cTCMSXE8B7uy68e9vDuJY9PgHcp6qfn+u7srKyNDc3t8oxr9u3jktfu5TM+pl8dcdX1Ak78+rN1T0hrzG+dqLsBHuO7GFrwVa2FmxlW8E2th7eSmFp4al9msU3O1VKvSTxEjLqZ5AZn0n9OvUdjNxZIpKnqlln2uazEmhV1oUXkYtxzU5/CZAMzBGRlqp6wlfxAny64VOGzhhKeEg4H/znB2dNnsb4o9CQUJrENKFJTBO6pHQBQFUZdOEglu9a/u/S6q4VzFg747Rj4yLjSIlNoVFUIxLrJdIoqhFbDm8hJiKGmMgYYiJi+HXHX5MYlUj9OvWDpteKz0qgInIpMF5Vr3S/fhhAVZ8st8/n7n2WuBeV2wUkAmPL71t+v7N93/mWQE+UnTjVbrR672qmrZnGws0LaZXQillDZlU665KVQE0gKz5ezJ4je9h3dB/7j+4nKTqJnUU72XtkL3uO7GHPkT0cLD54xmPDQsJIrJdIYpQr0Z5Muon1EomNjCUqIoroiGiiI6KJCo86bYRfmZZRWFJIQUkBBSUFHC45TEFJAV9v+5qS4yWUnCjhWNkxLmx4IZFhkcRExBAXGUf9OvXP+oirE0dEaITXfxeOlECp2rrwKcDXFY5Nqc7ger3Zi8VbF5963aJBC/63//9yT+d7rORpgl6dsDqkx6WTHvfv5cLbJrU9bZ8TZScoKi2ioLSAwpJC1/OSAgpLCykqKaKwtJAfD/zIil0rKCotOtX+er5CJISI0AgiQyOJDI0kLDSMo8eOUny8mKLSIg4VH6p0SsCwkDBCJZQQCeGFq1/g9g63exXLzz63Wj7FIeXXhQeKRGS9t5+1gQ2Mcf+pRgnAvur8QD8QjOcMwXneNXLOZZRR7P7jrePuPwDD/2s4wxl+Poc3PdsGXybQ81kXfluFdeE9ORZVfQWotXVpEck9W9E/UAXjOUNwnncwnnNFtXVd+JnAzSISKSKZQAsgx4exGmPMeauV68K795sKrAGOA/f6+g68McacL5/2Aw12IjLC3cwQNILxnCE4zzsYz7kiS6DGGOOl4OjtaowxPmAJtBqISJqIzBORNSKyWkRGu99vICKzRWSD+2e807H6goiEishyEfnY/TpTRJaKyA8i8r77JmLAEJH6IvKBiKwTkbUicmkwXGsRecD9+/2diLwnInUC/VpXxhJo9TgOjFHVi4Fs4F73cNSxwFxVbQHMdb8ORKOBteVe/xn4i6o2Bw7iGrIbSJ4DPlPVVkA7XOce0NdaRFKA+4AsVW2N68bwyeHXgXytz8kSaDVQ1Z2qusz9vBDXP6gU4FrgLfdubwHXOROh74hIKjAAeNX9WoA+wAfuXQLqvEUkDuiJqwcJqlqqqocIgmuNq9dOXXef7XrATgL4WnvCEmg1E5EMoAOwFEhS1Z3uTbuApLMc5s/+D/g9cHIsXUPgkKoed7+u9mG4DssE9gJvuJstXhWRKAL8WqvqduAZYAuuxHkYyCOwr3WlLIFWIxGJBqYD96tqQflt7gECAdXlQUQGAntUNc/pWGpQGNAReElVOwBHqFBdD9BrHY+rlJ2Ja4a0KOAqR4OqBSyBVhMRCceVPCer6sm5wHaLSBP39ibAHqfi85HuwCARyQem4KrOPQfUd1fz4CzDcP3YNmCbqi51v/4AV0IN9Gt9BbBJVfeq6jFgBq7rH8jXulKWQKuBu93vNWCtqj5bblP5oaq/Av5Z07H5kqo+rKqpqpqB64bCl6o6FJiHa2guBNh5q+ouYKuIXOh+qy+uEXMBfa1xVd2zRaSe+/f95HkH7LX2hHWkrwYi0gP4F7CKf7cFPoKrHXQqkA5sBv5TVQ84EqSPiUhv4HeqOlBEmuEqkTYAlgPDVLXEyfiqk4i0x3XTLALYCNyOqzAS0NdaRCYAg3H1OlkO/BpXm2fAXuvKWAI1xhgvWRXeGGO8ZAnUGGO8ZAnUGGO8ZAnUGGO8ZAnUGGO8ZAnUGGO8ZAnUGGO8ZAnUBCQR+YeI5Lnnrxzhfu8OEfleRHJEZJKIPO9+P1FEpovIN+5Hd2ejN/7COtKbgCQiDVT1gIjUxbVC7JXAYlzj1guBL4FvVXWUiLwLvKiqi0QkHfhcVS9yLHjjN3y5LrwxTrpPRK53P08DbgUWnBxeKSLTgJbu7VcAF7uGeAMQKyLRqlpUkwEb/2MJ1AQc97j8K4BLVfWoiMwH1gFnK1WGANmqWlwzEZpAYW2gJhDFAQfdybMVrmVWooBeIhLvnn7thnL7fwH85uQL92QhxlTKEqgJRJ8BYSKyFngK+BrXPJX/DeTgagvNxzWrOrjX+hGRlSKyBrirxiM2fsluIpmgcbJd010C/RB4XVU/dDou47+sBGqCyXgRWQF8B2wC/uFwPMbPWQnUGGO8ZCVQY4zxkiVQY4zxkiVQY4zxkiVQY4zxkiVQY4zxkiVQY4zx0v8D7/8aqcZ0vcMAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUwAAACJCAYAAABHPAHsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAATS0lEQVR4nO3de3QW9Z3H8fc3gXALt0AEuWgCBSxeQHwqKEWQoKW0tXqUriIqHi+12lrb7aoHPD3K9qa71dM9tWdNlVOgXWvBrlgvbQUUlJuAEBEqgoCI5aoIRiDh8t0/ZoKBTfJMYuZ5JvB5nfOczMwzM8/nefLkm7n+fubuiIhIejnZDiAi0lSoYIqIRKSCKSISkQqmiEhEKpgiIhGpYIqIRNQs2wGi6Ny5sxcVFWU7hoicYJYvX77L3Qujzt8kCmZRURHLli3LdgwROcGY2Xv1mV+75CIiEalgiohEpIIpIhJRkziGKSLJVrq89JjxW8+7NUtJ4qUtTBGRiFQwRUQiUsEUEYlIBVNEJCIVTBGRiFQwRUQiUsEUEYlIBVNEJCIVTBGRiFQwRUQiUsEUEYlIBVNEJCIVTBGRiGIrmGbW0sxeN7MyM1ttZg+E04vNbImZrTezp8wsL64MIiKNKc4tzApgpLsPAAYCo81sCPAg8Ii7fwHYDdwUYwYRkUYTW8H0QHk42jx8ODASmBlOnwpcHlcGEZHGFOsxTDPLNbOVwA7gJeBd4GN3PxTOsgXoHmcGEZHGEmvBdPfD7j4Q6AGcD5wRdVkzu9XMlpnZsp07d8aWUUQkqoycJXf3j4GXgQuADmZW1TVGD+CDWpYpdfeUu6cKCyN3GywiEps4z5IXmlmHcLgVcAnwD4LCeVU42w3ArLgyiIg0pjg7QTsVmGpmuQSF+U/u/pyZrQH+aGY/AVYAT8SYQUSk0cRWMN39TeDcGqZvIDieKSLSpOhOHxGRiCIVTDP7s5l9zcxUYEXkpBW1AP4GGAesM7NfmFm/GDOJiCRSpILp7rPd/VpgELAJmG1mC83sRjNrHmdAEZGkiLyLbWadgAnAzQRnt39FUEBfiiWZiEjCRDpLbmb/C/QDpgPfcPet4VNPmdmyuMKJiCRJ1MuKfuvuL1SfYGYt3L3C3VMx5BIRSZyou+Q/qWHaosYMIiKSdHVuYZpZV4LWhFqZ2bmAhU+1A1rHnE1EJFHS7ZJ/heBETw/g4WrTPwEmxpRJRCSR6iyY7j6V4H7wK9396QxlEhFJpHS75OPd/fdAkZn98Pjn3f3hGhYTETkhpdslbxP+zI87iIhI0qXbJX8s/PlAZuKIiCRX1MY3HjKzdmbW3MzmmNlOMxufZpmeZvayma0Ju9n9fji9wMxeMrN14c+OjfFGRETiFvU6zEvdfS/wdYJ7yb8A/FuaZQ4B/+ru/YEhwB1m1h+4F5jj7n2AOeG4iEjiRS2YVbvuXwNmuPuedAu4+1Z3fyMc/oSge4ruwDcJutcFdbMrIk1I1FsjnzOzt4H9wHfMrBA4EPVFzKyIoPX1JUCXaveibwO6RE4rIpJFUZt3uxe4EEi5+0HgU4ItxbTMLB94Grgr3K2vvl4HvJbl1M2uiCRKffr0OYPgeszqy0yra4GwrcyngT+4+5/DydvN7FR332pmpwI7alrW3UuBUoBUKlVjURURyaSozbtNB3oDK4HD4WSnjoJpZkbQI+Q/jrvA/VmC7nV/gbrZFZEmJOoWZgroH+5CRzUUuA5YZWYrw2kTCQrln8zsJuA94Fv1WKeISNZELZhvAV2BrelmrOLur/FZ60bHK4m6HhGRpIhaMDsDa8zsdaCiaqK7XxZLKhGRBIpaMO+PM4SISFMQqWC6+zwzOx3o4+6zzaw1kBtvNBGRZIl6L/ktwEzgsXBSd+CZuEKJiCRR1Fsj7yA4670XwN3XAafEFUpEJImiFswKd6+sGgkvXtfF5CJyUolaMOeZ2USCztAuAWYAf4kvlohI8kQtmPcCO4FVwLeBF4D74golIpJEUc+SHzGzZ4Bn3F0tYYjISanOLUwL3G9mu4C1wNqwtfUfZyaeiEhypNsl/wHB2fEvuXuBuxcAg4GhZvaD2NOJiCRIuoJ5HXCNu2+smuDuG4DxwPVxBhMRSZp0BbO5u+86fmJ4HLN5PJFERJIp3UmfygY+d9IpXV56zPit592apSQiEpd0W5gDzGxvDY9PgLPrWtDMppjZDjN7q9o0dbErIk1WnQXT3XPdvV0Nj7bunm6X/HfA6OOmqYtdEWmyol64Xm/uPh/46LjJ6mJXRJqs2ApmLdTFrog0WZkumEfV1cUuqJtdEUmeTBfM7WHXutTVxS4E3ey6e8rdU4WFhRkLKCJSm0wXzKoudkFd7IpIExNbwTSzJ4FFQD8z2xJ2q/sL4BIzWweMCsdFRJqEqJ2g1Zu7X1PLU+piV0SapKyd9BERaWpUMEVEIlLBFJFGVXm4kj0H9nD4yOFsR2l0sR3DFJGTx7bybczbNI+y7WV8uP9Dvvfi98jPy2doz6HcMOAGrup/Fc1zm34DZyqYItJgH+3/iLtfupspK6aQm5PLmYVnMvS0oVx02kVs2L2BF9e/yLg/j2Py/Mk8OuZRRhaPzHbkz0UFU0QaZOkHS7n8qcvZXr6dkl4ljO49mrYt2gKfNW94xI8w6+1Z3D37bkZNG8XEYRO5f8T9NMtpmqVHxzBFpN5mrpnJ8N8NJy83j9dveZ2x/cceLZbV5VgOV3zxCspuK+PGgTfy01d/ysipI9lWvi0LqT8/FUwRiczd+fmrP2fsjLEM7DqQJTcvYdCpg9Iu17p5a5745hNMv2I6y7cuZ8jjQ1i9Y3UGEjcuFUwRiaTiUAUTZk1g4tyJjDt7HHNvmMspbU6p1zrGnzOe+RPmU3m4kgunXMjf3/17TGnjoYIpImnt2reLUdNHMa1sGg+MeIDfX/F7WjZr2aB1ndftPJbcvISiDkWM+cMYHlv2WCOnjY8KpojUac3ONQx+fDBLP1jKk1c+yY+H/xgz+1zr7Nm+J6/d+BqX9r6U256/jR/9/UdN4rpNFUwRqdWM1TM4/7fn82nlp7wy4RWuPuvqRlt32xZtefaaZ7njS3fwy0W/5KoZV/Fp5aeNtv44NM1z+wmw7+A+1n+0ns17NlNeWc6CzQvIy80jPy+fdi3aUXGoghbNWmQ7pkiD7D+4n/vm3sfDix9mSI8hzBw7k+7tujf66zTLacavx/yavp36ctdf7yL12xTTr5hOqluq0V+rMahgRrStfBsvb3yZORvn8MqmV3h397t1zv+z137GGZ3PYHD3wZQUl3Bx8cV0ze+aobQiDTd341y+/dy3Wf/Rem5P3c4jox8hLzcv1te8c/Cd9C/sz4RnJjDk8SFMGjaJe758D62bt471desrKwXTzEYDvwJygcfdPXHtYn584GPmbZrH3I1zmbNxDqt3BpdAdGjZgeGnD+f6AdfTr1M/ijsWk5+XzzNvP8PBwwcpryxn94HddGnThZXbV/L0P57miRVPAHBm4ZmMLB5JSXEJI4pG0L5l+2y+RZFjLHp/EQ8ueJBZa2fRu2NvZl83m5JemWuNcVSvUbx1+1vc+eKdTJ4/mdI3Spk0bBK3DLolMXtrFnStk8EXNMsF3gEuAbYAS4Fr3H1NbcukUilftmxZbJncnff3vs/C9xcefazYtoIjfoRWzVox7PRhjCwaSUmvEs7tei65Obn/bx2ly0uPGa+60+HwkcOs2LaCORvmMGfjHF7b/Br7D+0nx3JIdUtRUlzChT0vZECXAfRo1+NzH0wXqY+Nuzcya+0sZqyZwcL3F9KxZUe+P/j73D30blo1bxV5PbV9/xvq1fdeZdLcSby6+VUKWhUwtv9Yxp09jgt6XNCo96Sb2XJ3j7z/n40tzPOB9e6+AcDM/kjQ/W6tBbO+jvgRKg5VcODQgaOP/Yf28+G+D9m1bxe79u1ia/lW1n20jrW71vLOh++wp2IPAG2at2Fwj8FMGjaJkuIShvQY8rn+u+Xm5JLqliLVLcU9X76HikMVLN6ymDkbgwL60IKHOOzB2cGCVgUM6DKAXh170aNdD3q060G3tt1o36I9+Xn5Rx9t8trQLKcZuZZLjuWQYzkqtCcwd8fD/gKrNnCqj9f23KEjh/ik4hPKK8spryxn175dbNm7hc17NlO2vYwV21aw6eNNQLD388hXHuHmQTeTn5efybdXo2GnD2PehGAP74kVTzCtbBqPLX+Mls1akuqWYlDXQRR3LKa4QzGFbQopaFVAQauCel8XWl/ZKJjdgferjW8BBjfWyudtmseIqSMizXta+9Po26kv1559Lf0L+3NBzws4p8s5sd7n2qJZC4YXDWd40XAmXzyZ8spyyraVsXLbSsq2l1G2vYzn1z3P9vLtR7/4URhGjuWQm1OtiKIimmmO11jUGvJcnPoU9GFw98Hcef6dXNbvMnoX9I79NevLzCjpVUJJrxLKK8v56/q/svD9hSzasogpK6dQXll+zPxd2nRh24/iveUyG7vkVwGj3f3mcPw6YLC7f/e4+W4Fqrbr+wFrgc7ArgzGrY8kZ4Nk51O2hlG2hqme7XR3j9wtbTa2MD8AelYb7xFOO4a7lwLHHBgxs2X1Od6QSUnOBsnOp2wNo2wN83myZePC9aVAHzMrNrM84GqC7ndFRBIt41uY7n7IzL4L/I3gsqIp7t70mi0RkZNOVq7DdPcXgBcasGhp+lmyJsnZINn5lK1hlK1hGpwt4yd9RESaKjW+ISISUaILppkVmNlLZrYu/NmxhnkGmtkiM1ttZm+a2b/EnGm0ma01s/Vmdm8Nz7cws6fC55eYWVGceeqZ7Ydmtib8nOaY2elJyVZtvivNzM0so2dYo+Qzs2+Fn99qM/ufpGQzs9PM7GUzWxH+bsdkKNcUM9thZm/V8ryZ2X+Fud80s/RNs2c237VhrlVmttDMBqRdqbsn9gE8BNwbDt8LPFjDPH2BPuFwN2Ar0CGmPLnAu0AvIA8oA/ofN8/twH+Hw1cDT2Xos4qS7WKgdTj8nSRlC+drC8wHFgOpDH7Ponx2fYAVQMdw/JQEZSsFvhMO9wc2ZSjbRcAg4K1anh8DvAgYMARYkqnfacR8F1b7fX41Sr5Eb2ES3DI5NRyeClx+/Azu/o67rwuH/wnsACJfiFpPR2/rdPdKoOq2ztoyzwRKLDP3LabN5u4vu/u+cHQxwTWwmRDlcwP4d+BB4ECGclWJku8W4FF33w3g7jsSlM2BduFwe+CfmQjm7vOBj+qY5ZvANA8sBjqY2amZyAbp87n7wqrfJxH/HpJeMLu4+9ZweBvQpa6Zzex8gv/Cdbe91nA13dZ5fCOBR+dx90PAHqBTTHnqm626mwj++2dC2mzh7lpPd38+Q5mqi/LZ9QX6mtkCM1sctriVlGz3A+PNbAvB1Sffy0y0tOr7ncymSH8PWW8P08xmAzU1FDmp+oi7u5nVeko//M81HbjB3Y80bsoTi5mNB1LA8GxnATCzHOBhYEKWo9SlGcFu+QiCLZH5Zna2u3+c1VSBa4DfufsvzewCYLqZnaW/g2jM7GKCgvnldPNmvWC6+6janjOz7WZ2qrtvDQtijbtBZtYOeB6YFG76xyXKbZ1V82wxs2YEu0gfxpipPtkws1EE/4yGu3tFBnJFydYWOAt4JTx60RV41swuc/f42vWLng+CraMl7n4Q2Ghm7xAU0KUJyHYTMBrA3ReZWUuC+6UzddigNpG+k9lkZucAjwNfdff0f6eZPAjbgIO2/8GxJ30eqmGePGAOcFcG8jQDNgDFfHYA/szj5rmDY0/6/ClDn1WUbOcSHK7ok+HfY9psx83/Cpk96RPlsxsNTA2HOxPsanZKSLYXgQnh8BcJjmFahj67Imo/qfI1jj3p83omv3cR8p0GrAcujLy+TL+Ber7ZTmExXAfMBgrC6SmCltoBxgMHgZXVHgNjzDSGoAHkdwm2aAEmA5eFwy2BGeEv4nWgVwY/r3TZZgPbq31OzyYl23HzZrRgRvzsjOCwwRpgFXB1grL1BxaExXQlcGmGcj1JcFXKQYIt8JuA24Dbqn1mj4a5V2Xhd5ou3+PA7mp/D8vSrVN3+oiIRJT0s+QiIomhgikiEpEKpohIRCqYIiIRqWCKiESkgimJY2YdzOz2DLzO5WbWP+7XkROHCqYkUQeCVp8iCZsRa8h3+XKCaxhFItF1mJI4ZlbVIs9a4GXgHKAj0By4z91nhe2M/g1YApxHcHH39QQ3MuwkuBNnubv/p5n1JriAuhDYR9DyUAHwHEHjKHuAK909rkZb5ASR9XvJRWpwL3CWuw8M78dv7e57zawzsNjMqnoZ7UPQ2MpiM/sScCUwgKCwvgEsD+crJbi7Y52ZDQZ+4+4jw/U85+4zM/nmpOlSwZSkM+BnZnYRcISgebCqZv7e888aWxkKzHL3A8ABM/sLgJnlEzQUO6Nas6QtMhVeTiwqmJJ01xLsSp/n7gfNbBPB/foAn0ZYPgf42N0HxpRPTiI66SNJ9AlBk28QNI+3IyyWFwO19UO0APiGmbUMtyq/DuDuewmaYxsLR08QVfXdUv11RNJSwZTE8aBdwgVh51UDgZSZrSI4qfN2LcssBZ4F3iRoUmwVwckcCLZSbzKzMmA1n3Xx8Efg38LOw3rH9X7kxKGz5HLCMLN8dy83s9YEnand6u5vZDuXnDh0DFNOJKXhhegtCRr7VbGURqUtTBGRiHQMU0QkIhVMEZGIVDBFRCJSwRQRiUgFU0QkIhVMEZGI/g9xF2aVFydtIQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x2160 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t5sR9zCAM9Wd",
        "outputId": "6ca0599d-5b49-4d72-e722-1ce82ed57505"
      },
      "source": [
        "data.columns"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['age', 'workclass', 'fnlwgt', 'education', 'education-num',\n",
              "       'marital-status', 'occupation', 'relationship', 'race', 'sex',\n",
              "       'capital-gain', 'capital-loss', 'hours-per-week', 'native-country',\n",
              "       'target'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        },
        "id": "bVRbYogGlwmQ",
        "outputId": "c8352ee3-4771-4bcc-d41e-58389994fad5"
      },
      "source": [
        "import seaborn as sns; sns.set()\r\n",
        "plt.figure(figsize=(15,15))\r\n",
        "fig, ax = plt.subplots()\r\n",
        "sns.distplot(data.loc[:,'relationship'], bins=25, color=\"g\", ax=ax)\r\n",
        "plt.show()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x1080 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2I64v6PkpwiE"
      },
      "source": [
        "#Continuous Distribution"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FsgDnNCopM7W"
      },
      "source": [
        "def get_best_cont_distribution(data):\r\n",
        "    dist_names = ['beta','cauchy','chi','chi2','expon','gamma','gumbel_r','laplace','lognorm','norm','pareto','t','triang','uniform','weibull_min','weibull_max']\r\n",
        "    dist_results = []\r\n",
        "    params = {}\r\n",
        "    for dist_name in dist_names: \r\n",
        "        dist = getattr(st, dist_name)   ##from scipy import stats as st\r\n",
        "        param = dist.fit(data)\r\n",
        "\r\n",
        "        params[dist_name] = param\r\n",
        "        # Applying the Kolmogorov-Smirnov test\r\n",
        "        D, p = st.kstest(data, dist_name, args=param)\r\n",
        "        print(\"p value for \"+dist_name+\" = \"+str(p))\r\n",
        "        dist_results.append((dist_name, p))\r\n",
        "\r\n",
        "    # select the best fitted distribution\r\n",
        "    best_dist, best_p = (max(dist_results, key=lambda item: item[1]))\r\n",
        "    # store the name of the best fit distribution and its p value\r\n",
        "    print()\r\n",
        "    print(\"Best fitting distribution: \"+str(best_dist))\r\n",
        "    print(\"Best p value: \"+ str(best_p))\r\n",
        "    print(\"Parameters for the best fit: \"+ str(params[best_dist]))\r\n",
        "    print()\r\n",
        "    return best_dist, best_p, params[best_dist]"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xUsFj9KPpQ6U",
        "outputId": "8dc360ed-f00a-4146-d983-ade04dec9ecd"
      },
      "source": [
        "get_best_cont_distribution(data['age'])"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "p value for beta = 6.450744257941582e-60\n",
            "p value for cauchy = 0.0\n",
            "p value for chi = 0.0\n",
            "p value for chi2 = 2.102348488210109e-109\n",
            "p value for expon = 0.0\n",
            "p value for gamma = 2.0939153891306407e-109\n",
            "p value for gumbel_r = 1.079697710045403e-93\n",
            "p value for laplace = 4.56253192166453e-296\n",
            "p value for lognorm = 2.1178226743621387e-88\n",
            "p value for norm = 1.183484192842924e-169\n",
            "p value for pareto = 0.0\n",
            "p value for t = 1.6092975298433733e-169\n",
            "p value for triang = 0.0\n",
            "p value for uniform = 0.0\n",
            "p value for weibull_min = 0.0\n",
            "p value for weibull_max = 7.12163933488832e-95\n",
            "\n",
            "Best fitting distribution: beta\n",
            "Best p value: 6.450744257941582e-60\n",
            "Parameters for the best fit: (1.468250776456375, 3.7326546384194828, 16.58801810784547, 77.66290897379534)\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('beta',\n",
              " 6.450744257941582e-60,\n",
              " (1.468250776456375, 3.7326546384194828, 16.58801810784547, 77.66290897379534))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6IbP-7sP2f5J"
      },
      "source": [
        "-----------------------------"
      ]
    }
  ]
}