From 10c434ffa7c67dc1746b03c77b4df3b91346d0f5 Mon Sep 17 00:00:00 2001
From: Michael Grund <23025878+michaelgrund@users.noreply.github.com>
Date: Fri, 10 Nov 2023 04:19:29 +0100
Subject: [PATCH] Add gallery example showing usage of polygon objects from a
 geopandas.GeoDataFrame (choropleth map) (#2796)
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Co-authored-by: Yvonne Fröhlich <94163266+yvonnefroehlich@users.noreply.github.com>
Co-authored-by: Dongdong Tian <seisman.info@gmail.com>
---
 examples/gallery/maps/choropleth_map.py | 56 +++++++++++++++++++++++++
 1 file changed, 56 insertions(+)
 create mode 100644 examples/gallery/maps/choropleth_map.py

diff --git a/examples/gallery/maps/choropleth_map.py b/examples/gallery/maps/choropleth_map.py
new file mode 100644
index 00000000000..62f9fbdea9b
--- /dev/null
+++ b/examples/gallery/maps/choropleth_map.py
@@ -0,0 +1,56 @@
+"""
+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()