Predicting the price of a house

This section will deal with building a simple linear model to predict house prices using all the features in the current dataframe. We will then evaluate the model and try to improve the accuracy by using a more complex model in the latter half of the section.

Getting ready

Visit the following links to understand how linear regression works and how to use the linear regression model in the Scikit Learn library:https://en.wikipedia.org/wiki/Linear_regression

http://www.stat.yale.edu/Courses/1997-98/101/linreg.htm

https://newonlinecourses.science.psu.edu/stat501/node/251/

http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html

http://scikit-learn.org/stable/modules/linear_model.html

How to do it...

1. Drop the Price column from the x_df dataframe and save it into a new dataframe named x_df2 using the following script:

 x_df2 = x_df.drop(['price'], axis = 1)

2. Declare a variable named reg and equate it to the LinearRegression() function from...