Filling continuous missing values
In the last lesson, you dealt with different methods of removing data missing values and filling in missing values with a fixed string. These approaches are valid in many cases, particularly when dealing with categorical columns but have limited use when working with continuous values. In these cases, it may be most valid to fill the missing values in the column with a value calculated from the entries present in the column.
This exercise is part of the course
Feature Engineering for Machine Learning in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Print the first five rows of StackOverflowJobsRecommend column
print(____)