Question $13$

How many houses have not been remodeled, but were over the average age of home remodels when it was sold?

Hints:

Greate a new Data Frame with the opposite fitter from Question $10,$ the remodeled age equals $0,$ meaning it has never been remodeled.

Add a new column to represent the age of the house when fit was sold by subtracting the Yearbutts column from the Vrestd column.

Fliter the DataFrame where the age of the house when it was sold is greater than the value fiom Question $11.$

Print out the resulting number of rows

Answer here

Question $14$

Write the rows of all the houses in the previous question to a CSV file named "needs$\_$a$\_$remodel.cSY$".$

Hints:

pd$.$Dataframento csv$()$ method

$[93]$ # Answer here

NameError

sipython$=$input$-93\_5$df$764655$cbd$>$ in