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import matplotlib.pyplot as plt

import missingno as msno

import numpy as np

import numpy as np # linear algebra

import pandas as pd

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

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])

target = np.log(train['SalePrice'])
target.skew()
plt.hist(target, color='turquoise')