chi-square.ipynb

chi-square.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled22.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNq4JS7c3DV/g1N9S4HcMvG",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/nogawanogawa/fc08dc0f791b159bc3cc08af22b5b0a0/untitled22.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YiM4e4zNeZmW"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from scipy import stats"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sK3N0plNkiqQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "outputId": "92171d95-7034-40a9-cb69-386664b6cb19"
      },
      "source": [
        "data = pd.DataFrame({\n",
        "  \"true\":[291, 527],\n",
        "  \"false\":[120, 387],\n",
        "},\n",
        "index=['man', 'woman']\n",
        ")\n",
        "data"
      ],
      "execution_count": 2,
      "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>true</th>\n",
              "      <th>false</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>man</th>\n",
              "      <td>291</td>\n",
              "      <td>120</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>woman</th>\n",
              "      <td>527</td>\n",
              "      <td>387</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       true  false\n",
              "man     291    120\n",
              "woman   527    387"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KSBPKcPNf0uW",
        "outputId": "3cb53dc1-87f0-4958-b382-a1359c2d478f"
      },
      "source": [
        "res = stats.chi2_contingency(data, correction=False)\n",
        "print(res)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(20.735570925391748, 5.2727380569338135e-06, 1, array([[253.73433962, 157.26566038],\n",
            "       [564.26566038, 349.73433962]]))\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FoORrvHOjtoM"
      },
      "source": [
        ""
      ],
      "execution_count": 3,
      "outputs": []
    }
  ]
}