Gender_Classification_by_Name.ipynb

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      "name": "Gender Classification by Name.ipynb",
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      "cell_type": "markdown",
      "source": [
        "## Import libraries"
      ],
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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# ML Packages\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from sklearn.feature_extraction import DictVectorizer\n",
        "from sklearn.model_selection import train_test_split\n",
        "#from sklearn.feature_extraction.text import TfidfVectorizer"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Load dataset"
      ],
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        "id": "y2EdgbnUCfHj"
      }
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      "source": [
        "df = pd.read_csv('name_gender_dataset.csv')\n",
        "df.head()"
      ],
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              "      Name Gender    Count  Probability\n",
              "0    James      M  5304407     0.014517\n",
              "1     John      M  5260831     0.014398\n",
              "2   Robert      M  4970386     0.013603\n",
              "3  Michael      M  4579950     0.012534\n",
              "4  William      M  4226608     0.011567"
            ],
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              "          Name Gender  Count   Probability\n",
              "147264  Zylenn      M      1  2.736740e-09\n",
              "147265  Zymeon      M      1  2.736740e-09\n",
              "147266  Zyndel      M      1  2.736740e-09\n",
              "147267  Zyshan      M      1  2.736740e-09\n",
              "147268   Zyton      M      1  2.736740e-09"
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          "data": {
            "text/plain": [
              "Name            object\n",
              "Gender          object\n",
              "Count            int64\n",
              "Probability    float64\n",
              "dtype: object"
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          "metadata": {},
          "execution_count": 5
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        "sns.countplot(x=df['Gender'], data=df)\n",
        "plt.show()"
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              "<Figure size 432x288 with 1 Axes>"
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            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Drop irrelevant columns"
      ],
      "metadata": {
        "id": "LK2H0yVdCoWz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop(['Count', 'Probability'], axis=1)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "E57Y3OuYCA3a",
        "outputId": "5683cacf-3024-4f80-ca1e-c60ce6723aca"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Name Gender\n",
              "0    James      M\n",
              "1     John      M\n",
              "2   Robert      M\n",
              "3  Michael      M\n",
              "4  William      M"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b21de4ae-8477-4167-b847-4fb69af50017\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Name</th>\n",
              "      <th>Gender</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>James</td>\n",
              "      <td>M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>John</td>\n",
              "      <td>M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Robert</td>\n",
              "      <td>M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Michael</td>\n",
              "      <td>M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>William</td>\n",
              "      <td>M</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b21de4ae-8477-4167-b847-4fb69af50017')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b21de4ae-8477-4167-b847-4fb69af50017 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b21de4ae-8477-4167-b847-4fb69af50017');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Gender'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yhWi9KHSCM6q",
        "outputId": "49ef1949-452a-4c81-db6a-b8b49d41e550"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "F    89749\n",
              "M    57520\n",
              "Name: Gender, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Check null values"
      ],
      "metadata": {
        "id": "HJznDrQMCl1L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KFHImOI5CQ_2",
        "outputId": "8bd49bc5-aa68-4835-9070-0107ef827916"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name      0\n",
              "Gender    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Replace categorical sex values to numerical\n",
        "- M: 0\n",
        "- F: 1"
      ],
      "metadata": {
        "id": "E6Pex7iSCv0h"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "gender_map = {'M':0,'F':1}\n",
        "df['Gender'].replace(gender_map, inplace=True)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "hfjb3oL_C8ec",
        "outputId": "772615de-a22f-4636-e87e-dbb122849c4f"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Name  Gender\n",
              "0    James       0\n",
              "1     John       0\n",
              "2   Robert       0\n",
              "3  Michael       0\n",
              "4  William       0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-02acca68-77ff-45ea-83ec-2e7054ba249e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Name</th>\n",
              "      <th>Gender</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>James</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>John</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Robert</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Michael</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>William</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-02acca68-77ff-45ea-83ec-2e7054ba249e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-02acca68-77ff-45ea-83ec-2e7054ba249e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-02acca68-77ff-45ea-83ec-2e7054ba249e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Gender'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sK9zi1g9DVCB",
        "outputId": "0edc961e-bc41-4139-b4e0-c90c276459a1"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1    89749\n",
              "0    57520\n",
              "Name: Gender, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = df['Name']"
      ],
      "metadata": {
        "id": "D3mgw08xDtx2"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Feature extraction"
      ],
      "metadata": {
        "id": "ghtYIQp0DzEZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cv = CountVectorizer()\n",
        "X = cv.fit_transform(X)"
      ],
      "metadata": {
        "id": "P9hiaa-AD004"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cv.get_feature_names()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9T9r2QZLEkUJ",
        "outputId": "da24129e-cd5d-4813-edea-b5f5fb320eb3"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              " 'aashray',\n",
              " 'aashrita',\n",
              " 'aashrith',\n",
              " 'aashritha',\n",
              " 'aashriya',\n",
              " 'aashu',\n",
              " 'aashvi',\n",
              " 'aashwath',\n",
              " 'aasia',\n",
              " 'aasiah',\n",
              " 'aasif',\n",
              " 'aasil',\n",
              " 'aasim',\n",
              " 'aasin',\n",
              " 'aasini',\n",
              " 'aasir',\n",
              " 'aasish',\n",
              " 'aasiya',\n",
              " 'aasiyah',\n",
              " 'aasma',\n",
              " 'aasmin',\n",
              " 'aason',\n",
              " 'aasra',\n",
              " 'aasta',\n",
              " 'aastha',\n",
              " 'aasto',\n",
              " 'aasu',\n",
              " 'aatam',\n",
              " 'aateka',\n",
              " 'aathan',\n",
              " 'aathithya',\n",
              " 'aathmika',\n",
              " 'aatif',\n",
              " 'aatikun',\n",
              " 'aatir',\n",
              " 'aatish',\n",
              " 'aava',\n",
              " 'aavah',\n",
              " 'aavan',\n",
              " 'aavash',\n",
              " 'aaveer',\n",
              " 'aaven',\n",
              " 'aavesh',\n",
              " 'aavi',\n",
              " 'aavin',\n",
              " 'aavion',\n",
              " 'aavir',\n",
              " 'aavish',\n",
              " 'aavya',\n",
              " 'aavyan',\n",
              " 'aavyn',\n",
              " 'aaxon',\n",
              " 'aaya',\n",
              " 'aayaan',\n",
              " 'aayah',\n",
              " 'aayam',\n",
              " 'aayan',\n",
              " 'aayana',\n",
              " 'aayanah',\n",
              " 'aayanna',\n",
              " 'aayansh',\n",
              " 'aayat',\n",
              " 'aaydan',\n",
              " 'aayden',\n",
              " 'aayesha',\n",
              " 'aayetan',\n",
              " 'aayla',\n",
              " 'aaylah',\n",
              " 'aayliah',\n",
              " 'aaymaan',\n",
              " 'aayon',\n",
              " 'aayra',\n",
              " 'aaysha',\n",
              " 'aayu',\n",
              " 'aayush',\n",
              " 'aayusha',\n",
              " 'aayushi',\n",
              " 'aazaan',\n",
              " 'aazad',\n",
              " 'aazadi',\n",
              " 'aazan',\n",
              " 'aazeen',\n",
              " 'aazil',\n",
              " 'aazim',\n",
              " 'aaziyah',\n",
              " 'aazra',\n",
              " 'aazulah',\n",
              " 'ab',\n",
              " 'aba',\n",
              " 'abaan',\n",
              " 'abaas',\n",
              " 'abad',\n",
              " 'abagael',\n",
              " 'abagail',\n",
              " 'abagaile',\n",
              " 'abagale',\n",
              " 'abagayle',\n",
              " 'abahyjot',\n",
              " 'abaigael',\n",
              " 'abaigail',\n",
              " 'abaigeal',\n",
              " 'abak',\n",
              " 'abalazs',\n",
              " 'aban',\n",
              " 'abang',\n",
              " 'abanoub',\n",
              " 'abany',\n",
              " 'abas',\n",
              " 'abash',\n",
              " 'abasi',\n",
              " 'abass',\n",
              " 'abayo',\n",
              " 'abayomi',\n",
              " 'abaz',\n",
              " 'abb',\n",
              " 'abba',\n",
              " 'abbaas',\n",
              " 'abbagail',\n",
              " 'abbagale',\n",
              " 'abbagayle',\n",
              " 'abbal',\n",
              " 'abbas',\n",
              " 'abbe',\n",
              " 'abbee',\n",
              " 'abbegael',\n",
              " 'abbegail',\n",
              " 'abbegale',\n",
              " 'abbegayle',\n",
              " 'abbergale',\n",
              " 'abbey',\n",
              " 'abbeygail',\n",
              " 'abbeygale',\n",
              " 'abbi',\n",
              " 'abbie',\n",
              " 'abbiegail',\n",
              " 'abbiegale',\n",
              " 'abbiegayle',\n",
              " 'abbigael',\n",
              " 'abbigail',\n",
              " 'abbigaile',\n",
              " 'abbigal',\n",
              " 'abbigale',\n",
              " 'abbigayl',\n",
              " 'abbigayle',\n",
              " 'abbilyn',\n",
              " 'abbimarie',\n",
              " 'abbir',\n",
              " 'abbiyana',\n",
              " 'abbiygale',\n",
              " 'abbot',\n",
              " 'abbott',\n",
              " 'abbra',\n",
              " 'abbriella',\n",
              " 'abbrielle',\n",
              " 'abby',\n",
              " 'abbye',\n",
              " 'abbygael',\n",
              " 'abbygail',\n",
              " 'abbygaile',\n",
              " 'abbygale',\n",
              " 'abbygayl',\n",
              " 'abbygayle',\n",
              " 'abbylynn',\n",
              " 'abcde',\n",
              " 'abd',\n",
              " 'abdal',\n",
              " 'abdala',\n",
              " 'abdalah',\n",
              " 'abdalhay',\n",
              " 'abdalla',\n",
              " 'abdallah',\n",
              " 'abdalrahman',\n",
              " 'abdalrhman',\n",
              " 'abdel',\n",
              " 'abdelaziz',\n",
              " 'abdelgader',\n",
              " 'abdelhadi',\n",
              " 'abdelhamid',\n",
              " 'abdelkader',\n",
              " 'abdelkareem',\n",
              " 'abdelkarim',\n",
              " 'abdellah',\n",
              " 'abdelmajid',\n",
              " 'abdelrahman',\n",
              " 'abdelrhman',\n",
              " 'abderrahman',\n",
              " 'abdi',\n",
              " 'abdia',\n",
              " 'abdias',\n",
              " 'abdiasis',\n",
              " 'abdiaziz',\n",
              " 'abdiel',\n",
              " 'abdifatah',\n",
              " 'abdihafid',\n",
              " 'abdihakim',\n",
              " 'abdihamid',\n",
              " 'abdijabar',\n",
              " 'abdikadir',\n",
              " 'abdikani',\n",
              " 'abdikarim',\n",
              " 'abdikhaliq',\n",
              " 'abdiladhif',\n",
              " 'abdilahi',\n",
              " 'abdimalik',\n",
              " 'abdinajib',\n",
              " 'abdinasir',\n",
              " 'abdiqadir',\n",
              " 'abdiqani',\n",
              " 'abdirahim',\n",
              " 'abdirahin',\n",
              " 'abdirahman',\n",
              " 'abdirashid',\n",
              " 'abdirazaq',\n",
              " 'abdirisak',\n",
              " 'abdirisaq',\n",
              " 'abdirizak',\n",
              " 'abdirizaq',\n",
              " 'abdisalam',\n",
              " 'abdisalan',\n",
              " 'abdisamad',\n",
              " 'abdisamat',\n",
              " 'abdishakur',\n",
              " 'abdiwahab',\n",
              " 'abdiwali',\n",
              " 'abdlsalem',\n",
              " 'abdo',\n",
              " 'abdollah',\n",
              " 'abdon',\n",
              " 'abdou',\n",
              " 'abdoul',\n",
              " 'abdoulaye',\n",
              " 'abdoulaziz',\n",
              " 'abdoulie',\n",
              " 'abdourahman',\n",
              " 'abdourahmane',\n",
              " 'abdrahman',\n",
              " 'abdrew',\n",
              " 'abdriel',\n",
              " 'abdu',\n",
              " 'abdual',\n",
              " 'abduallah',\n",
              " 'abduel',\n",
              " 'abdujilil',\n",
              " 'abdul',\n",
              " 'abdula',\n",
              " 'abdulah',\n",
              " 'abdulahad',\n",
              " 'abdulahi',\n",
              " 'abdulai',\n",
              " 'abdulallah',\n",
              " 'abdulaye',\n",
              " 'abdulazeem',\n",
              " 'abdulazeez',\n",
              " 'abdulazim',\n",
              " 'abdulaziz',\n",
              " 'abdulbari',\n",
              " 'abdulbasit',\n",
              " 'abdule',\n",
              " 'abdulelaah',\n",
              " 'abdulelah',\n",
              " 'abdulgader',\n",
              " 'abdulghani',\n",
              " 'abdulhaadi',\n",
              " 'abdulhadi',\n",
              " 'abdulhakeem',\n",
              " 'abdulhakim',\n",
              " 'abdulhaleem',\n",
              " 'abdulhalim',\n",
              " 'abdulhameed',\n",
              " 'abdulhamid',\n",
              " 'abdulhamied',\n",
              " 'abduljabbar',\n",
              " 'abduljaleel',\n",
              " 'abduljalil',\n",
              " 'abdulkader',\n",
              " 'abdulkadir',\n",
              " 'abdulkareem',\n",
              " 'abdulkarim',\n",
              " 'abdulkhaliq',\n",
              " 'abdull',\n",
              " 'abdulla',\n",
              " 'abdullah',\n",
              " 'abdullahi',\n",
              " 'abdullatif',\n",
              " 'abdulloh',\n",
              " 'abdulmajeed',\n",
              " 'abdulmajid',\n",
              " 'abdulmalek',\n",
              " 'abdulmalik',\n",
              " 'abdulmannan',\n",
              " 'abdulmohsen',\n",
              " 'abdulnasir',\n",
              " 'abdulqader',\n",
              " 'abdulqadir',\n",
              " 'abdulraheem',\n",
              " 'abdulrahiem',\n",
              " 'abdulrahim',\n",
              " 'abdulrahman',\n",
              " 'abdulrazaq',\n",
              " 'abdulrehman',\n",
              " 'abdulrhman',\n",
              " 'abdulsalam',\n",
              " 'abdulsamad',\n",
              " 'abdulwadud',\n",
              " 'abdulwahab',\n",
              " 'abdulwahid',\n",
              " 'abdulwali',\n",
              " 'abdur',\n",
              " 'abdurahim',\n",
              " 'abdurahman',\n",
              " 'abdurahmon',\n",
              " 'abdurraheem',\n",
              " 'abdurrahim',\n",
              " 'abdurrahmaan',\n",
              " 'abdurrahman',\n",
              " 'abdurrehman',\n",
              " 'abdussamad',\n",
              " 'abe',\n",
              " 'abeal',\n",
              " 'abeba',\n",
              " 'abed',\n",
              " 'abedallah',\n",
              " 'abedalrahman',\n",
              " 'abedghani',\n",
              " 'abednego',\n",
              " 'abeeha',\n",
              " 'abeel',\n",
              " 'abeemelek',\n",
              " 'abeer',\n",
              " 'abeera',\n",
              " 'abegail',\n",
              " 'abegale',\n",
              " 'abegayle',\n",
              " 'abeir',\n",
              " 'abel',\n",
              " 'abela',\n",
              " 'abelardo',\n",
              " 'abele',\n",
              " 'abelina',\n",
              " 'abelino',\n",
              " 'abell',\n",
              " 'abella',\n",
              " 'abem',\n",
              " 'abema',\n",
              " 'aben',\n",
              " 'abena',\n",
              " 'abenazer',\n",
              " 'abeneezer',\n",
              " 'abenezer',\n",
              " 'abeni',\n",
              " 'abeny',\n",
              " 'aber',\n",
              " 'aberdeen',\n",
              " 'abergail',\n",
              " 'aberham',\n",
              " 'abernathy',\n",
              " 'abert',\n",
              " 'abery',\n",
              " 'abey',\n",
              " 'abgail',\n",
              " 'abha',\n",
              " 'abhai',\n",
              " 'abhaki',\n",
              " 'abhash',\n",
              " 'abhay',\n",
              " 'abhaya',\n",
              " 'abhaypratap',\n",
              " 'abhaysingh',\n",
              " 'abhayveer',\n",
              " 'abheek',\n",
              " 'abhi',\n",
              " 'abhidyu',\n",
              " 'abhigna',\n",
              " 'abhignya',\n",
              " 'abhijay',\n",
              " 'abhijeet',\n",
              " 'abhijit',\n",
              " 'abhijot',\n",
              " 'abhik',\n",
              " 'abhikirat',\n",
              " 'abhilash',\n",
              " 'abhilasha',\n",
              " 'abhimanu',\n",
              " 'abhimanyu',\n",
              " 'abhinandan',\n",
              " 'abhinash',\n",
              " 'abhinav',\n",
              " 'abhinay',\n",
              " 'abhinaya',\n",
              " 'abhinniti',\n",
              " 'abhinoor',\n",
              " 'abhinwav',\n",
              " 'abhir',\n",
              " 'abhiraam',\n",
              " 'abhiraj',\n",
              " 'abhiram',\n",
              " 'abhirami',\n",
              " 'abhireet',\n",
              " 'abhirup',\n",
              " 'abhisek',\n",
              " 'abhisekh',\n",
              " 'abhishak',\n",
              " 'abhishek',\n",
              " 'abhishekh',\n",
              " 'abhishiek',\n",
              " 'abhishik',\n",
              " 'abhishikth',\n",
              " 'abhitaj',\n",
              " 'abhyuday',\n",
              " 'abi',\n",
              " 'abia',\n",
              " 'abiagael',\n",
              " 'abiageal',\n",
              " 'abiah',\n",
              " 'abian',\n",
              " 'abianna',\n",
              " 'abiar',\n",
              " 'abibail',\n",
              " 'abid',\n",
              " 'abida',\n",
              " 'abidah',\n",
              " 'abidan',\n",
              " 'abidin',\n",
              " 'abie',\n",
              " 'abiebatu',\n",
              " 'abiegail',\n",
              " 'abiei',\n",
              " 'abiel',\n",
              " 'abiela',\n",
              " 'abiella',\n",
              " 'abiezer',\n",
              " 'abigael',\n",
              " 'abigaelle',\n",
              " 'abigahil',\n",
              " 'abigai',\n",
              " 'abigail',\n",
              " 'abigaile',\n",
              " 'abigailgrace',\n",
              " 'abigaille',\n",
              " 'abigailmarie',\n",
              " 'abigailrose',\n",
              " 'abigal',\n",
              " 'abigale',\n",
              " 'abigayil',\n",
              " 'abigayl',\n",
              " 'abigayle',\n",
              " 'abigeal',\n",
              " 'abigel',\n",
              " 'abigial',\n",
              " 'abiha',\n",
              " 'abihail',\n",
              " 'abijah',\n",
              " 'abijai',\n",
              " 'abijot',\n",
              " 'abileigh',\n",
              " 'abilene',\n",
              " 'abilgail',\n",
              " 'abilio',\n",
              " 'abilyn',\n",
              " 'abilynn',\n",
              " 'abimael',\n",
              " 'abimbola',\n",
              " 'abimelec',\n",
              " 'abimelech',\n",
              " 'abin',\n",
              " 'abinadab',\n",
              " 'abinadi',\n",
              " 'abinav',\n",
              " 'abinaya',\n",
              " 'abiodun',\n",
              " 'abiol',\n",
              " 'abiola',\n",
              " 'abiona',\n",
              " 'abir',\n",
              " 'abira',\n",
              " 'abiral',\n",
              " 'abiram',\n",
              " 'abirami',\n",
              " 'abisag',\n",
              " 'abisai',\n",
              " 'abisaid',\n",
              " 'abiselom',\n",
              " 'abish',\n",
              " 'abisha',\n",
              " 'abishai',\n",
              " 'abishak',\n",
              " 'abishek',\n",
              " 'abishkka',\n",
              " 'abisola',\n",
              " 'abit',\n",
              " 'abiud',\n",
              " 'abiy',\n",
              " 'abiya',\n",
              " 'abiyah',\n",
              " 'abla',\n",
              " 'ablakat',\n",
              " 'ablavi',\n",
              " 'able',\n",
              " 'ablett',\n",
              " 'abnel',\n",
              " 'abner',\n",
              " 'abney',\n",
              " 'abniel',\n",
              " 'abolfaz',\n",
              " 'abolfazi',\n",
              " 'abolfazl',\n",
              " 'abolhasan',\n",
              " 'aboma',\n",
              " 'abony',\n",
              " 'abot',\n",
              " 'abou',\n",
              " 'aboubacar',\n",
              " 'aboubakar',\n",
              " 'aboung',\n",
              " 'abra',\n",
              " 'abraam',\n",
              " 'abraar',\n",
              " 'abrah',\n",
              " 'abraham',\n",
              " 'abrahan',\n",
              " 'abraheem',\n",
              " 'abrahem',\n",
              " 'abrahim',\n",
              " ...]"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X, y = X, df['Gender']"
      ],
      "metadata": {
        "id": "b3nWCziEEskA"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X,y, test_size=0.33, random_state=42)\n",
        "X_train.shape, y_train.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lBHXAY29FGPP",
        "outputId": "4ce13b54-64e9-43b0-e647-febbbfea9e87"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((98670, 126918), (98670,))"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_test.shape, y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4wgO9SZjFYJr",
        "outputId": "0a8d8dda-8872-4156-b719-87bedc8147dc"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((48599, 126918), (48599,))"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Training the model"
      ],
      "metadata": {
        "id": "Yvbncfj9FyZ9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Printing predicted gender by names helper method\n",
        "\n"
      ],
      "metadata": {
        "id": "JGwoMdZkJbdZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def print_pred(names, predictions):\n",
        "  for i in range(len(names)):\n",
        "    if predictions[i] == 0:\n",
        "      print(names[i], \": Male\")\n",
        "    else:\n",
        "      print(names[i], \": Female\")"
      ],
      "metadata": {
        "id": "qRdmi2qmJ0li"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Naive Bayes MultinomialNB"
      ],
      "metadata": {
        "id": "8k5JD269F6TX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.naive_bayes import MultinomialNB"
      ],
      "metadata": {
        "id": "IAceqT4DF1Gv"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "clf = MultinomialNB()\n",
        "clf.fit(X_train, y_train)\n",
        "clf.score(X_test, y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PqJRMEuWF5ip",
        "outputId": "16221032-f7e8-4785-ef06-47766c1177a3"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.5682009917899545"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Accuracy: \",clf.score(X_train, y_train), \"%\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2EXGxJH6JI0M",
        "outputId": "a6e56ecb-1e67-4e31-f7e6-a089261dc585"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy:  0.9339008817269687 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Multi-NB Prediction"
      ],
      "metadata": {
        "id": "Irsbx42sGjR4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "s_name = ['Mart Anthony', 'Andrea', 'Myka', 'Monica', 'Mark', 'John', 'Johhny', 'Marie']\n",
        "vector = cv.transform(s_name).toarray()"
      ],
      "metadata": {
        "id": "wi5CcKRjGknI"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "prediction = clf.predict(vector)\n",
        "print_pred(s_name, prediction)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "blMGyDzmG45h",
        "outputId": "f226476f-d78a-4e81-d18c-c379b2685a72"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mart Anthony : Male\n",
            "Andrea : Female\n",
            "Myka : Female\n",
            "Monica : Female\n",
            "Mark : Male\n",
            "John : Male\n",
            "Johhny : Male\n",
            "Marie : Female\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Save the model and vectorizer"
      ],
      "metadata": {
        "id": "zLlxckTrNZGO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pickle"
      ],
      "metadata": {
        "id": "tbdu8tggNauK"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pickle.dump(clf, open('gender_classifier.pkl', 'wb'))\n",
        "pickle.dump(cv, open('vectorizer.pkl', 'wb'))"
      ],
      "metadata": {
        "id": "szpkH8iFNd3w"
      },
      "execution_count": 25,
      "outputs": []
    }
  ]
}