51 lines (50 with data), 1.2 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"D:/Studia/Semestr 4/WB/project/data/data.csv\")\n",
    "learning_data, validation_data = train_test_split(df, test_size=0.3, random_state=42)\n",
    "\n",
    "learning_data.to_csv(\"D:/Studia/Semestr 4/WB/project/data/learning_data.csv\", index=False)\n",
    "validation_data.to_csv(\"D:/Studia/Semestr 4/WB/project/validation_data/validation_data.csv\", index=False)"
   ]
  }
 ],
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   "display_name": "DataFrames",
   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
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 "nbformat": 4,
 "nbformat_minor": 2
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