text_plain_output_1.png image_output_1.png
import missingno as msno

import pandas as pd

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

import seaborn as sns

pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', 20)

test = pd.read_csv('../input/house-prices-advanced-regression-techniques/test.csv')
train = pd.read_csv('../input/house-prices-advanced-regression-techniques/train.csv')

train.shape

train = train.drop(['Id'], axis=1)

missingdata_df = train.columns[train.isnull().any()].tolist()
msno.matrix(train[missingdata_df])

sns.boxplot(train['SalePrice'], color='turquoise')