Note
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Choropleth map
The pygmt.Figure.plot
method allows us to plot geographical data such
as polygons which are stored in a geopandas.GeoDataFrame
object. Use
geopandas.read_file
to load data from any supported OGR format such as
a shapefile (.shp), GeoJSON (.geojson), geopackage (.gpkg), etc. You can also
use a full URL pointing to your desired data source. Then, pass the
geopandas.GeoDataFrame
as an argument to the data
parameter of
pygmt.Figure.plot
, and style the geometry using the pen
parameter.
To fill the polygons based on a corresponding column you need to set
fill="+z"
as well as select the appropriate column using the aspatial
parameter as shown in the example below.
![choropleth map](../../_images/sphx_glr_choropleth_map_001.png)
import geopandas as gpd
import pygmt
# Read polygon data using geopandas
gdf = gpd.read_file("https://geodacenter.github.io/data-and-lab/data/airbnb.zip")
fig = pygmt.Figure()
fig.basemap(
region=gdf.total_bounds[[0, 2, 1, 3]],
projection="M6c",
frame="+tPopulation of Chicago",
)
# The dataset contains different attributes, here we select
# the "population" column to plot.
# First, we define the colormap to fill the polygons based on
# the "population" column.
pygmt.makecpt(
cmap="acton",
series=[gdf["population"].min(), gdf["population"].max(), 10],
continuous=True,
reverse=True,
)
# Next, we plot the polygons and fill them using the defined colormap.
# The target column is defined by the aspatial parameter.
fig.plot(
data=gdf,
pen="0.3p,gray10",
fill="+z",
cmap=True,
aspatial="Z=population",
)
# Add colorbar legend
fig.colorbar(frame="x+lPopulation", position="jML+o-0.5c+w3.5c/0.2c")
fig.show()
Total running time of the script: (0 minutes 0.782 seconds)