Pointplot of US cities by population

This example, taken from the User Guide, plots cities in the contiguous United States by their population. It demonstrates some of the range of styling options available in geoplot.

../_images/sphx_glr_plot_largest_cities_usa_001.png
import geopandas as gpd
import geoplot as gplt
import geoplot.crs as gcrs
import matplotlib.pyplot as plt
import mapclassify as mc

continental_usa_cities = gpd.read_file(gplt.datasets.get_path('usa_cities'))
continental_usa_cities = continental_usa_cities.query('STATE not in ["AK", "HI", "PR"]')
contiguous_usa = gpd.read_file(gplt.datasets.get_path('contiguous_usa'))
scheme = mc.Quantiles(continental_usa_cities['POP_2010'], k=5)

ax = gplt.polyplot(
    contiguous_usa,
    zorder=-1,
    linewidth=1,
    projection=gcrs.AlbersEqualArea(),
    edgecolor='white',
    facecolor='lightgray',
    figsize=(8, 12)
)
gplt.pointplot(
    continental_usa_cities,
    scale='POP_2010',
    limits=(2, 30),
    hue='POP_2010',
    cmap='Blues',
    scheme=scheme,
    legend=True,
    legend_var='scale',
    legend_values=[8000000, 2000000, 1000000, 100000],
    legend_labels=['8 million', '2 million', '1 million', '100 thousand'],
    legend_kwargs={'frameon': False, 'loc': 'lower right'},
    ax=ax
)


plt.title("Large cities in the contiguous United States, 2010")
plt.savefig("largest-cities-usa.png", bbox_inches='tight', pad_inches=0.1)

Total running time of the script: ( 0 minutes 3.728 seconds)

Gallery generated by Sphinx-Gallery