Identifying Gentrifiable Tracts

In this exercise, you will identify and map the tracts that were gentrifiable in 2000. The criteria are:

Low median household income (MHI), determined as tract MHI less than the MHI for the New York metro area.
A low level of recent housing construction, determined as those tracts with a percentage of housing built in the previous 20 years (since 1980) less than the percentage for the New York metro area.

The GeoDataFrame bk_2000, with data for Brooklyn Census tracts in 2000, has been loaded for you.

This exercise is part of the course

Analyzing US Census Data in Python

View Course

Exercise instructions

Calculate a boolean column low_mhi by checking to see whether mhi is less than mhi_msa
Calculate a boolean column low_recent_build by checking to see whether the percentage of homes built in the 20 years prior to 2000 (pct_recent_build) is less than pct_recent_build_msa
Use the & operator to classify the neighborhood as gentrifiable if both low_mhi and low_recent_build are true; the columns must be surrounded by parenthesis
Map the gentrifiable tracts using the YlGn colormap

Hands-on interactive exercise

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

# Median income below MSA median income
bk_2000["low_mhi"] = ____

# Recent construction below MSA
bk_2000["low_recent_build"] = ____

# Identify gentrifiable tracts
bk_2000["gentrifiable"] = (____) & (____)

# Plot gentrifiable tracts
bk_2000.plot(column = ____, cmap = ____)
plt.show()

Edit and Run Code