Impacts of Black-White Segregation by Sex
seaborn lets us plot two variables conditioned on a third variable. The two variables will be dissimilarity and unemployment, and we will condition the scatterplot on a third variable, sex, by changing the color of the points and regression line based on the sex being reported. But first we have to turn msa_black_emp into a "tidy" DataFrame.
msa_black_emp has been loaded, with columns "pct_male_unemp" and "pct_female_unemp" as calculated in the last exercise.
pandas and seaborn have been loaded using the usual aliases.
This exercise is part of the course
Analyzing US Census Data in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Restrict DataFrame to columns of interest, rename columns
tidy_black_emp = msa_black_emp[____]
tidy_black_emp.columns = ____