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from sklearn.model_selection import train_test_split

import numpy as np # linear algebra

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

from sklearn.model_selection import train_test_split
seed = 5
np.random.seed(seed)
data_train = pd.read_csv('../input/train.csv')
X = data_train.drop('label', axis=1)
y = data_train['label']
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=seed)
print('There are %d train entries and %d test entries' % (len(X_train), len(y_test)))