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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

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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 = ____
Edit and Run Code