text_plain_output_1.png
from sklearn.preprocessing import StandardScaler

import pandas as pd

train = pd.read_csv('../input/30-days-of-ml/train.csv')
test = pd.read_csv('../input/30-days-of-ml/test.csv')
sub = pd.read_csv('../input/30-days-of-ml/sample_submission.csv')

train = train.drop('id', axis=1)
test = test.drop('id', axis=1)

cols = test.columns

X_train = train[cols]
X_test = test.copy()
y = train['target']

ss = StandardScaler()
X_train_scaled = ss.fit_transform(X_train)
X_test_scaled = ss.fit_transform(X_test)

print('X_train data shape: ', X_train_scaled.shape)
print('X_val data shape: ', X_val_scaled.shape)
print('y_train shape: ', y_train.shape)
print('y_val shape: ', y_val.shape)