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56 changes: 56 additions & 0 deletions examples/gallery/maps/choropleth_map.py
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"""
Choropleth Map
==============

The :meth:`pygmt.Figure.plot` method allows us to plot geographical data such
as polygons which are stored in a :class:`geopandas.GeoDataFrame` object. Use
:func:`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
:class:`geopandas.GeoDataFrame` as an argument to the ``data`` parameter of
:meth:`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.
"""

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()