text_html_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

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

fig, ax = plt.subplots()
ax.scatter(x = training_dataframe['GrLivArea'], y = training_dataframe['SalePrice'])
plt.ylabel('SalePrice', fontsize=13)
plt.xlabel('GrLivArea', fontsize=13)
plt.show()

#Deleting outliers
training_dataframe= training_dataframe.drop(training_dataframe[(training_dataframe['GrLivArea']>4000) & (training_dataframe['SalePrice']<300000)].index)

#Check the scatterplot again
fig, ax = plt.subplots()
ax.scatter(training_dataframe['GrLivArea'], training_dataframe['SalePrice'])
plt.ylabel('SalePrice', fontsize=13)
plt.xlabel('GrLivArea', fontsize=13)
plt.show()

training_dataframe['SalePrice'].describe()