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In this example, we’ll determine the bounding box of Kenya using the public domain Natural Earth dataset and the Cartopy library.

Rendering just the bounding box of Kenya (with the actual country being highlighted in green) looks like this:

How to get the bounding box

First we use Cartopy’s cartopy.io.shapereader.natural_earth() function that will automatically download Natural Earth data (if it has already been downloaded, the cached data will be used):

shpfilename = shpreader.natural_earth(resolution='10m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)

Now we can filter for Kenya just like we did in our previous post on How to highlight a specific country using Cartopy:

kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

and get the bounding box using kenya.bounds:

lon_min, lat_min, lon_max, lat_max = kenya.bounds

Complete example code

This code will render the image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
from cartopy.feature import ShapelyFeature
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
# Show only Africa
#ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

import cartopy.io.shapereader as shpreader
# Read shape file
shpfilename = shpreader.natural_earth(resolution='10m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)
# Filter for a specific country
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]
# Determine bounding box
lon_min, lat_min, lon_max, lat_max = kenya.bounds
ax.set_extent([lon_min, lon_max, lat_min, lat_max])

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

# Save figure as SVG
plt.savefig("Kenya-Bounding-Box-Tight.svg")

In order to display shapefile data in Cartopy, we can first use the cartopy.io.shapereader package to read the shape data and then convert the geometry we want to display to a cartopy.feature.ShapelyFeature.

In the following example, we’ll read the Natural Earth ne_110m_admin_0_countries.shp and
Note that there’s an easier way to plot Natural Earth data using shpreader.natural_earth – see How to highlight a specific country using Cartopy and we’ll use the Natural Earth dataset just as an example!

import cartopy.io.shapereader as shpreader
# Read shape file
reader = shpreader.Reader("ne_110m_admin_0_countries.shp")
# Filter for a specific country
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

Complete code example

import cartopy.crs as ccrs
import cartopy.feature as cf
from cartopy.feature import ShapelyFeature
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
# Show only Africa
ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

import cartopy.io.shapereader as shpreader
# Read shape file
reader = shpreader.Reader("ne_110m_admin_0_countries.shp")
# Filter for a specific country
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

# Save figure as SVG
plt.savefig("Africa-Highlight-Kenya.svg")

In our previous posts, e.g. How to draw Africa map using Cartopy we showed how to draw an overview map of an entire continent using Cartopy. This post provides an example of how to highlight a specific country in that map. In this example, we’ll highlight Kenya

The general approach is:

1. Use cartopy.io.shapereader.natural_earth to download Natural Earth data that contains the shape of Kenya
2. Convert it to a cartopy.feature.ShapelyFeature
3. Display said feature

Displaying Kenya’s Natural Earth shape in cartopy

First, we create a Reader for the Natural Earth data. Cartopy will automatically download the data if it has not been cached.

import cartopy.io.shapereader as shpreader

shpfilename = shpreader.natural_earth(resolution='110m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)

Now we can select Kenya by name from the records:

kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

In order to display that geometry, we use

shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

Complete example code

import cartopy.crs as ccrs
import cartopy.feature as cf
from cartopy.feature import ShapelyFeature
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
# Show only Africa
ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Read Natural Earth data
import cartopy.io.shapereader as shpreader

shpfilename = shpreader.natural_earth(resolution='110m',
                                      category='cultural',
                                      name='admin_0_countries')
reader = shpreader.Reader(shpfilename)
kenya = [country for country in reader.records() if country.attributes["NAME_LONG"] == "Kenya"][0]

# Display Kenya's shape
shape_feature = ShapelyFeature([kenya.geometry], ccrs.PlateCarree(), facecolor="lime", edgecolor='black', lw=1)
ax.add_feature(shape_feature)

# Save figure as SVG
plt.savefig("Africa-Highlight-Kenya.svg")

We can easily draw an Africa Map using Cartopy by setting the extents to [-13, 45, 30, 70]:

ax.set_extent([-13, 45, 30, 70])

Complete code example

The code above produces the image shown above:

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt

proj = ccrs.Miller()
ax = plt.axes(projection=proj)
ax.set_extent([-13, 45, 30, 70])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
ax.add_feature(cf.BORDERS)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Europe.svg")

By standard, Cartopy draws every feature with the same line width:

ax.add_feature(cf.COASTLINE)
ax.add_feature(cf.BORDERS)

We can easily increasing the line width by adding e.g. lw=2 to the ax.add_feature() call:

ax.add_feature(cf.COASTLINE, lw=2)
ax.add_feature(cf.BORDERS)

Complete code example

This example produces the image with a wider coast line line width as shown above

import cartopy.crs as ccrs
import cartopy.feature as cf
from matplotlib import pyplot as plt

proj = ccrs.PlateCarree()
ax = plt.axes(projection=proj)
ax.set_extent([-23, 55, -35, 40])
ax.stock_img()

ax.add_feature(cf.COASTLINE, lw=2)
ax.add_feature(cf.BORDERS)
# Make figure larger
plt.gcf().set_size_inches(20, 10)

# Save figure as SVG
plt.savefig("Africa-Standard.svg")