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
Exercise instructions
- Calculate a boolean column
low_mhi
by checking to see whethermhi
is less thanmhi_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 thanpct_recent_build_msa
- Use the
&
operator to classify the neighborhood as gentrifiable if bothlow_mhi
andlow_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()