Bivariate Map of Broadband Access

Sometimes we want to map two variables at once, a so-called bivariate map. One way to do this is by combining a choropleth map and a proportional symbol map. You will use the geo_state GeoDataFrame again to create a choropleth of the percentage of internet households with broadband access, and overaly a proportional symbol map of the count of households with internet access.

You will set an alpha transparency on the proportional symbol marker so as to not completely obscure the underlying choropleth.

geopandas is imported using the usual alias, and the sqrt function has been imported from numpy.

The geo_state GeoDataFrame has been loaded.

This exercise is part of the course

Analyzing US Census Data in Python

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Exercise instructions

Use the broadband and internet columns to calculate the percentage of internet households with broadband
Create a choropleth basemap of the new pct_broadband column using a yellow-green-blue colormap
Set the markersize of the centroid points to the square root of the number of households with internet access divided by 5; make the markers partially transparent by setting the alpha parameter to 0.7

Hands-on interactive exercise

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

# Create point GeoDataFrame at centroid of states
geo_state_pt = geo_state.copy()
geo_state_pt["geometry"] = geo_state_pt.centroid

# Calculate percentage of internet households with broadband
geo_state["pct_broadband"] = ____

# Set choropleth basemap
basemap = ____

# Plot transparent proportional symbols on top of basemap
geo_state_pt.plot(ax = basemap, ____, color = "lightgray", edgecolor = "darkgray", ____)
plt.show()

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