Exploring and visualizing spatial data and its attributes

Working with Geospatial Data in Python

Joris Van den Bossche

Open source software developer and teacher, GeoPandas maintainer

Filtering data

countries.head()

          name      continent       gdp                            geometry
0  Afghanistan           Asia   64080.0  POLYGON ((61.21 35.65, 62.23 35...
1       Angola         Africa  189000.0  MULTIPOLYGON (((23.90 -11.72, 2...
...

countries['continent'] == 'Africa'

0      False
1       True
         ...  
175     True
176     True
Name: continent, Length: 177, dtype: bool

Filtering data

countries_africa = countries[countries['continent'] == 'Africa']

countries_africa.plot()

Visualizing spatial data

countries.plot()

Adjusting the color: uniform color

countries.plot(color="red")

Adjusting the color: based on attribute values

countries.plot(column='gdp_per_cap')

Multi-layered plot

fig, ax = plt.subplots(figsize=(12, 6))
countries.plot(ax=ax)
cities.plot(ax=ax, color='red', markersize=10)
ax.set_axis_off()

Let's practice!

Working with Geospatial Data in Python