import pandas as pd
import os
from sklearn.model_selection import train_test_split

CUTOFF = int(os.environ['CUTOFF'])

wines = pd.read_csv('data/winemag-data_first150k.csv', engine='python', encoding='ISO-8859-1', sep=',')

wines = wines.dropna()

wines = wines.sample(100)

X, Y = wines, wines

# SPLIT BETWEEN DEV, TRAINS, AND TEST
wines_train, wines_temp, wines_train, wines_temp = train_test_split(X, Y, test_size=0.2, random_state=1)
wines_dev, wines_test, wines_dev, wines_test = train_test_split(wines_temp, wines_temp, test_size=0.2)

wines_train.to_csv('wines_train.csv', index=False)
wines_dev.to_csv('wines_dev.csv', index=False)
wines_test.to_csv('wines_test.csv', index=False)