chi-squared-selectkbest-notebook.ipynb

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    "colab": {
      "name": "chi_square.ipynb",
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      "name": "python3",
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      "metadata": {
        "id": "crjmfQnrkgtQ",
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      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from google.colab import drive\n",
        "from scipy import stats\n",
        "from sklearn.feature_selection import SelectKBest, chi2"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9zoxWpi6k9EK",
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        "outputId": "d2a24e08-6b1e-43c0-b8d9-8ac0927df48a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "source": [
        "drive.mount('/content/drive')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SChziqvDmNSv",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "file_path = '/content/drive/My Drive/accident.xlsx'"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W3PKpDZ5mWUo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_excel(file_path)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5m-IZo5JmZNc",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>is_adult</th>\n",
              "      <th>is_male</th>\n",
              "      <th>accident</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
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            ],
            "text/plain": [
              "   is_adult  is_male  accident\n",
              "0         1        0         1\n",
              "1         1        1         1\n",
              "2         1        1         0\n",
              "3         1        1         0\n",
              "4         1        0         0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 140
        }
      },
      "source": [
        "adult_accident_crosstab = pd.crosstab(df['is_adult'], df['accident'], \n",
        "                                      margins=True)\n",
        "adult_accident_crosstab"
      ],
      "execution_count": 0,
      "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>accident</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>All</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>is_adult</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>781</td>\n",
              "      <td>146</td>\n",
              "      <td>927</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>All</th>\n",
              "      <td>781</td>\n",
              "      <td>146</td>\n",
              "      <td>927</td>\n",
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            ],
            "text/plain": [
              "accident    0    1  All\n",
              "is_adult               \n",
              "1         781  146  927\n",
              "All       781  146  927"
            ]
          },
          "metadata": {
            "tags": []
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          "execution_count": 87
        }
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        }
      },
      "source": [
        "gender_accident_crosstab = pd.crosstab(df['is_male'], df['accident'], \n",
        "                                       margins=True)\n",
        "gender_accident_crosstab"
      ],
      "execution_count": 0,
      "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>accident</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>All</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>is_male</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>154</td>\n",
              "      <td>47</td>\n",
              "      <td>201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>627</td>\n",
              "      <td>99</td>\n",
              "      <td>726</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>All</th>\n",
              "      <td>781</td>\n",
              "      <td>146</td>\n",
              "      <td>927</td>\n",
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            "text/plain": [
              "accident    0    1  All\n",
              "is_male                \n",
              "0         154   47  201\n",
              "1         627   99  726\n",
              "All       781  146  927"
            ]
          },
          "metadata": {
            "tags": []
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          "execution_count": 88
        }
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      "metadata": {
        "id": "TbfBeRiMxU12",
        "colab_type": "code",
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      "source": [
        "def check_categorical_dependency(crosstab_table, confidence_interval):\n",
        "    stat, p, dof, expected = stats.chi2_contingency(crosstab_table)\n",
        "    print (\"Chi-Square Statistic value = {}\".format(stat))\n",
        "    print (\"P - Value = {}\".format(p))\n",
        "    alpha = 1.0 - confidence_interval\n",
        "    if p <= alpha:\n",
        "        print('Dependent (reject H0)')\n",
        "    else:\n",
        "\t      print('Independent (fail to reject H0)')\n",
        "    return expected"
      ],
      "execution_count": 0,
      "outputs": []
    },
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          "base_uri": "https://localhost:8080/",
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        }
      },
      "source": [
        "exp_table_1 = check_categorical_dependency(adult_accident_crosstab, 0.95)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Chi-Square Statistic value = 0.0\n",
            "P - Value = 1.0\n",
            "Independent (fail to reject H0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
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      "metadata": {
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 110
        }
      },
      "source": [
        "pd.DataFrame(exp_table_1)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>0</th>\n",
              "      <td>781.0</td>\n",
              "      <td>146.0</td>\n",
              "      <td>927.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>781.0</td>\n",
              "      <td>146.0</td>\n",
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            "text/plain": [
              "       0      1      2\n",
              "0  781.0  146.0  927.0\n",
              "1  781.0  146.0  927.0"
            ]
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          "metadata": {
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          "execution_count": 91
        }
      ]
    },
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        "colab_type": "code",
        "outputId": "448dc752-ef2f-4ba4-fc8c-3594353021f5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        }
      },
      "source": [
        "exp_table_2 = check_categorical_dependency(gender_accident_crosstab, 0.95)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Chi-Square Statistic value = 11.270043347013548\n",
            "P - Value = 0.023691007358727482\n",
            "Dependent (reject H0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
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      "cell_type": "code",
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        "id": "508WshnhynCL",
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        }
      },
      "source": [
        "pd.DataFrame(exp_table_2)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>169.343042</td>\n",
              "      <td>31.656958</td>\n",
              "      <td>201.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>611.656958</td>\n",
              "      <td>114.343042</td>\n",
              "      <td>726.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>781.000000</td>\n",
              "      <td>146.000000</td>\n",
              "      <td>927.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            "text/plain": [
              "            0           1      2\n",
              "0  169.343042   31.656958  201.0\n",
              "1  611.656958  114.343042  726.0\n",
              "2  781.000000  146.000000  927.0"
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        }
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "42REqLNZzJRj",
        "colab_type": "text"
      },
      "source": [
        "# **Feature Selection using Chi-Square**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qwu9pDZ3n-Jb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X = df[[\"is_adult\",\t\"is_male\"]]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HyDELW6YoNeC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "y = df[[\"accident\"]]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hKajjuY9oPmg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X_new = SelectKBest(chi2, k=1).fit_transform(X, y)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aiQ4IAtxoV_6",
        "colab_type": "code",
        "outputId": "7272d55c-7f23-4812-e04a-a985ee681dbd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "X_new.shape"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(927, 1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AsGHxlXFofax",
        "colab_type": "code",
        "outputId": "690b2fcc-f6f5-4ff3-9c0a-f0583d80d1ad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 140
        }
      },
      "source": [
        "pd.crosstab(np.squeeze(X_new), np.squeeze(y))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>accident</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>row_0</th>\n",
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              "      <th>0</th>\n",
              "      <td>154</td>\n",
              "      <td>47</td>\n",
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              "      <th>1</th>\n",
              "      <td>627</td>\n",
              "      <td>99</td>\n",
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            "text/plain": [
              "accident    0   1\n",
              "row_0            \n",
              "0         154  47\n",
              "1         627  99"
            ]
          },
          "metadata": {
            "tags": []
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          "execution_count": 98
        }
      ]
    },
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      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}