text_html_output_1.png
import pandas as pd

train_path = '../input/train.csv'
test_path = '../input/test.csv'
train_df = pd.read_csv(train_path)
test_df = pd.read_csv(test_path)

train_df.shape

missing_data = train_df.isnull().sum()
percent_missing = round(missing_data / train_df.isnull().count() * 100, 2)
missing_df = pd.concat([missing_data.sort_values(ascending=False), percent_missing.sort_values(ascending=False)], axis=1, keys=['Total', 'Percent'])
missing_df.head(5)