sklearn_split

sklearn_split.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6, 2)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame([[1,2],[3,4],[5,6],[7,8],[9,10],[11,12]], columns=['col1', 'col2'])\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   col1  col2\n",
      "2     5     6\n",
      "5    11    12\n",
      "3     7     8\n",
      "0     1     2\n",
      "   col1  col2\n",
      "4     9    10\n",
      "1     3     4\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train, test = train_test_split(df, test_size=0.3)\n",
    "train.shape, test.shape\n",
    "print(train)\n",
    "print(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   col1  col2\n",
      "0     1     2\n",
      "1     3     4\n",
      "2     5     6\n",
      "3     7     8\n",
      "   col1  col2\n",
      "4     9    10\n",
      "5    11    12\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train, test = train_test_split(df, test_size=0.3, shuffle=False)\n",
    "train.shape, test.shape\n",
    "print(train)\n",
    "print(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}