train_valid_test_split.ipynb

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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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        "<a href=\"https://colab.research.google.com/github/utkarshkant/25-short-code-snippets_Python/blob/master/train_valid_test_split.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# install fast_ml library\n",
        "! pip install fast_ml --quiet"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8MzFW6yjC80u",
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            "\u001b[?25h"
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      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "CgwUK50sC5TF"
      },
      "outputs": [],
      "source": [
        "# imports\n",
        "import pandas as pd\n",
        "from fast_ml.model_development import train_valid_test_split"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# load data\n",
        "df = pd.read_csv('https://raw.githubusercontent.com/utkarshkant/Datasets-Helper-Functions/main/WA_Fn-UseC_-Telco-Customer-Churn.csv')"
      ],
      "metadata": {
        "id": "j3VwYXJaDHVW"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# preview data\n",
        "df.head()"
      ],
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          "height": 386
        },
        "id": "Ys8Qo7S6DKcu",
        "outputId": "548c8e1f-b364-42a1-888d-5cd2d2fa139d"
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      "outputs": [
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              "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
              "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
              "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
              "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
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              "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
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              "2                No             DSL            Yes  ...               No   \n",
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              "4                No     Fiber optic             No  ...               No   \n",
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              "4          No          No              No  Month-to-month              Yes   \n",
              "\n",
              "               PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
              "0           Electronic check          29.85         29.85    No  \n",
              "1               Mailed check          56.95        1889.5    No  \n",
              "2               Mailed check          53.85        108.15   Yes  \n",
              "3  Bank transfer (automatic)          42.30       1840.75    No  \n",
              "4           Electronic check          70.70        151.65   Yes  \n",
              "\n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "# train, test, validation split\n",
        "X_train, y_train, X_valid, y_valid, X_test, y_test = train_valid_test_split(df, \n",
        "                                                                            target = 'Churn', \n",
        "                                                                            train_size=0.6, \n",
        "                                                                            valid_size=0.2, \n",
        "                                                                            test_size=0.2)\n",
        "\n",
        "# reset index\n",
        "for data in [X_train, y_train, X_valid, y_valid, X_test, y_test]:\n",
        "    data.reset_index(drop=True, inplace=True)"
      ],
      "metadata": {
        "id": "ph5sY54DDL3k"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "- The split datasets retain their original index and resetting it is an optional step."
      ],
      "metadata": {
        "id": "kyZ3mXl9Do7x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# split dataset size\n",
        "print(X_train.shape, y_train.shape)\n",
        "print(X_valid.shape, y_valid.shape)\n",
        "print(X_test.shape, y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WlPqaf1TDUTx",
        "outputId": "4f728ce4-ac9d-4a4a-fe8e-05b9139c7564"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(4225, 20) (4225,)\n",
            "(1409, 20) (1409,)\n",
            "(1409, 20) (1409,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train.head(3)"
      ],
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          "height": 260
        },
        "id": "ZluMFDI-D5um",
        "outputId": "ad24f0b1-4cde-40e6-85c6-2237161e4da2"
      },
      "execution_count": 11,
      "outputs": [
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              "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
              "0  6281-FKEWS  Female              0      No         No      44           No   \n",
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              "2               No          No          No             Yes  Month-to-month   \n",
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              "  PaperlessBilling              PaymentMethod  MonthlyCharges TotalCharges  \n",
              "0              Yes           Electronic check           49.05         2265  \n",
              "1              Yes  Bank transfer (automatic)           94.40       2638.1  \n",
              "2              Yes           Electronic check           86.55       1066.9  "
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              "      <td>94.40</td>\n",
              "      <td>2638.1</td>\n",
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              "    <tr>\n",
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              "      <td>86.55</td>\n",
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              "0    No\n",
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              "2    No\n",
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              "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
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              "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>7876-DNYAP</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>69</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Two year</td>\n",
              "      <td>No</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>19.80</td>\n",
              "      <td>1436.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6145-NNPNO</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>44.15</td>\n",
              "      <td>44.15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bfd62e5f-38f9-4c95-9378-bea6c78ac0ba')\"\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",
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              "    <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",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bfd62e5f-38f9-4c95-9378-bea6c78ac0ba 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-bfd62e5f-38f9-4c95-9378-bea6c78ac0ba');\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": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_test.head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TquU6B1kEGdb",
        "outputId": "f48a3e78-b563-45dd-bfb9-25a68d4fad2e"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    No\n",
              "1    No\n",
              "2    No\n",
              "Name: Churn, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    }
  ]
}