Tract Demographics in a Segregated City

The first few rows of the tracts_cook DataFrame appear in the console. In this exercise, you will calculate the percent African-American in two time periods, examine the histogram of this variable for 2010, and then plot them against each other to see how they have changed. You will observe that tracts with a mix of Black and other races are more likely to increase their percentage of black residents over time.

pandas and seaborn are loaded using the usual aliases.

This exercise is part of the course

Analyzing US Census Data in Python

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Exercise instructions

Calculate the percent African-American of each tract in 2010 as 100 times the Black population in that year divided by the total population in that year
Call sns.distplot on the new pct_black_2010 column of the tracts_cook DataFrame; make sure to set kde to False

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Calculate percent Black in 2010
tracts_cook["pct_black_2010"] = 100 * ____ / ____

# Examine histogram of percent Black
sns.distplot(____, ____)
plt.show()

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