text_plain_output_1.png
import matplotlib.pyplot as plt

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

import seaborn as sns

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

df.shape

df.isna().sum()[df.isna().sum() > 0]

df.corr()[['SalePrice']].sort_values(by='SalePrice', ascending=False)

fig, ax = plt.subplots(figsize=(16,8))
ax= sns.heatmap(df.corr(), cmap ='bwr', linewidths=.5)

df.corr()

sns.pairplot(df.loc[:, ['OverallQual', 'GrLivArea', 'SalePrice', 'YearBuilt', 'YearRemodAdd']])
df.head()
sns.set(font_scale=1.5)
plt.tight_layout()
plt.show()