{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from happypred import whdata_to_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_csv, y_train_csv, X_test_csv, y_test_csv = whdata_to_csv('WHR20_DataForTable2.1.xls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'X_train.csv'"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_df = pd.read_csv(X_train_csv)\n",
    "y_train_df = pd.read_csv(y_train_csv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Log GDP per capita</th>\n",
       "      <th>Social support</th>\n",
       "      <th>Healthy life expectancy at birth</th>\n",
       "      <th>Freedom to make life choices</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Perceptions of corruption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.144916</td>\n",
       "      <td>0.450662</td>\n",
       "      <td>50.799999</td>\n",
       "      <td>0.718114</td>\n",
       "      <td>0.178993</td>\n",
       "      <td>0.881686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.314788</td>\n",
       "      <td>0.552308</td>\n",
       "      <td>51.200001</td>\n",
       "      <td>0.678896</td>\n",
       "      <td>0.201228</td>\n",
       "      <td>0.850035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.421525</td>\n",
       "      <td>0.539075</td>\n",
       "      <td>51.599998</td>\n",
       "      <td>0.600127</td>\n",
       "      <td>0.131578</td>\n",
       "      <td>0.706766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.394349</td>\n",
       "      <td>0.521104</td>\n",
       "      <td>51.919998</td>\n",
       "      <td>0.495901</td>\n",
       "      <td>0.173452</td>\n",
       "      <td>0.731109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.480296</td>\n",
       "      <td>0.520637</td>\n",
       "      <td>52.240002</td>\n",
       "      <td>0.530935</td>\n",
       "      <td>0.246943</td>\n",
       "      <td>0.775620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1504</th>\n",
       "      <td>7.826639</td>\n",
       "      <td>0.765839</td>\n",
       "      <td>52.380001</td>\n",
       "      <td>0.642034</td>\n",
       "      <td>-0.067743</td>\n",
       "      <td>0.820217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1505</th>\n",
       "      <td>7.827643</td>\n",
       "      <td>0.735800</td>\n",
       "      <td>53.799999</td>\n",
       "      <td>0.667193</td>\n",
       "      <td>-0.117035</td>\n",
       "      <td>0.810457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1506</th>\n",
       "      <td>7.819675</td>\n",
       "      <td>0.768425</td>\n",
       "      <td>54.400002</td>\n",
       "      <td>0.732971</td>\n",
       "      <td>-0.088488</td>\n",
       "      <td>0.723612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507</th>\n",
       "      <td>7.851042</td>\n",
       "      <td>0.754147</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>0.752826</td>\n",
       "      <td>-0.091540</td>\n",
       "      <td>0.751208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1508</th>\n",
       "      <td>7.896704</td>\n",
       "      <td>0.775388</td>\n",
       "      <td>55.599998</td>\n",
       "      <td>0.762675</td>\n",
       "      <td>-0.063282</td>\n",
       "      <td>0.844209</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1509 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Log GDP per capita  Social support  Healthy life expectancy at birth  \\\n",
       "0               7.144916        0.450662                         50.799999   \n",
       "1               7.314788        0.552308                         51.200001   \n",
       "2               7.421525        0.539075                         51.599998   \n",
       "3               7.394349        0.521104                         51.919998   \n",
       "4               7.480296        0.520637                         52.240002   \n",
       "...                  ...             ...                               ...   \n",
       "1504            7.826639        0.765839                         52.380001   \n",
       "1505            7.827643        0.735800                         53.799999   \n",
       "1506            7.819675        0.768425                         54.400002   \n",
       "1507            7.851042        0.754147                         55.000000   \n",
       "1508            7.896704        0.775388                         55.599998   \n",
       "\n",
       "      Freedom to make life choices  Generosity  Perceptions of corruption  \n",
       "0                         0.718114    0.178993                   0.881686  \n",
       "1                         0.678896    0.201228                   0.850035  \n",
       "2                         0.600127    0.131578                   0.706766  \n",
       "3                         0.495901    0.173452                   0.731109  \n",
       "4                         0.530935    0.246943                   0.775620  \n",
       "...                            ...         ...                        ...  \n",
       "1504                      0.642034   -0.067743                   0.820217  \n",
       "1505                      0.667193   -0.117035                   0.810457  \n",
       "1506                      0.732971   -0.088488                   0.723612  \n",
       "1507                      0.752826   -0.091540                   0.751208  \n",
       "1508                      0.762675   -0.063282                   0.844209  \n",
       "\n",
       "[1509 rows x 6 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python [conda env:.conda-happy38]",
   "language": "python",
   "name": "conda-env-.conda-happy38-py"
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  "language_info": {
   "codemirror_mode": {
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