data_processing_0.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "A basic approach to a dataset. The only things that were done - ID dropping and one-hot encoding."
      ],
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      },
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      "id": "a1634e54",
      "metadata": {
        "colab": {
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          "height": 17
        },
        "id": "a1634e54",
        "outputId": "d253df63-7f8f-4302-c849-871e88a31ba9"
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>.container { width:80% !important; }</style>"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "from IPython.display import display, HTML\n",
        "display(HTML(\"<style>.container { width:80% !important; }</style>\"))\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt "
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive \n",
        "drive.mount('/content/gdrive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2QU7e9ZFhSes",
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      },
      "id": "2QU7e9ZFhSes",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5b988d2e",
      "metadata": {
        "id": "5b988d2e"
      },
      "outputs": [],
      "source": [
        "X_train0 = pd.read_csv('/content/gdrive/MyDrive/Data Science Pro/Projekt końcowy/input_data_train_X')\n",
        "X_test0 = pd.read_csv('/content/gdrive/MyDrive/Data Science Pro/Projekt końcowy/input_data_test_X')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train0.drop(['main_working_id'], inplace=True, axis=1)\n",
        "X_test0.drop(['main_working_id'], inplace=True, axis=1)"
      ],
      "metadata": {
        "id": "PlfxfLlz9RSZ"
      },
      "id": "PlfxfLlz9RSZ",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train0 = pd.get_dummies(X_train0, drop_first=True)\n",
        "X_test0 = pd.get_dummies(X_test0, drop_first = True)\n",
        "X_test0 = X_test0.reindex(columns = X_train0.columns, fill_value=0)"
      ],
      "metadata": {
        "id": "HbxJTBuP8emF"
      },
      "id": "HbxJTBuP8emF",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#storing variables\n",
        "X_train0.to_csv('/content/gdrive/MyDrive/Data Science Pro/Projekt końcowy/EXTRACTED DATA/X_train0', index=False)\n",
        "X_test0.to_csv('/content/gdrive/MyDrive/Data Science Pro/Projekt końcowy/EXTRACTED DATA/X_test0', index=False)"
      ],
      "metadata": {
        "id": "z_pqLMcx8sXk"
      },
      "id": "z_pqLMcx8sXk",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
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        "python": {
          "delete_cmd_postfix": "",
          "delete_cmd_prefix": "del ",
          "library": "var_list.py",
          "varRefreshCmd": "print(var_dic_list())"
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        "r": {
          "delete_cmd_postfix": ") ",
          "delete_cmd_prefix": "rm(",
          "library": "var_list.r",
          "varRefreshCmd": "cat(var_dic_list()) "
        }
      },
      "types_to_exclude": [
        "module",
        "function",
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      "window_display": false
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    "colab": {
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    "accelerator": "GPU",
    "gpuClass": "standard"
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