Extracting Text to New Features

Garages are an important consideration for houses in Minnesota where most people own a car and the snow is annoying to clear off a car parked outside. The type of garage is also important, can you get to your car without braving the cold or not? Let's look at creating a feature has_attached_garage that captures whether the garage is attached to the house or not.

Import the needed function when() from pyspark.sql.functions.
Create a string matching condition using like() to look for for the string pattern Attached Garage in df['GARAGEDESCRIPTION'] and use wildcards % so it will match anywhere in the field.
Similarly, create another condition using like() to find the string pattern Detached Garage in df['GARAGEDESCRIPTION'] and use wildcards % so it will match anywhere in the field.
Create a new column has_attached_garage using when() to assign the value 1 if it has an attached garage, zero if detached and use otherwise() to assign null with None if it is neither.

Exercise

Extracting Text to New Features

Instructions