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import numpy as np # linear algebra

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

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

"""
Checking for missing data
"""
missing_values_count = X_full.isnull().sum()
print('Total missing values %d' % missing_values_count.sum())
total_cells = np.product(X_full.shape)
total_missing = missing_values_count.sum()
percent_missing = total_missing / total_cells * 100
print('Percent missing values %f' % percent_missing)