Exploring and visualizing spatial data and its attributes

Lavorare con i dati geospaziali 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!

Lavorare con i dati geospaziali in Python