Plotting with GeoJSON

Visualizing Geospatial Data in Python

Mary van Valkenburg

Data Science Program Manager, Nashville Software School

Neighborhoods GeoJSON

{ "type": "FeatureCollection",
  "features": [
    { "type":"Feature",
      "properties":{
    "name":"Historic Buena Vista"
    },"geometry":{
        "type":"MultiPolygon","coordinates":[[[[-86.79511056795417,36.17575....

neighborhoods = gpd.read_file('./data/neighborhood_boundaries.geojson')
neighborhoods.head(1)

        name             geometry
Historic Buena Vista    (POLYGON ((-86.79511056795417 36.17575964963348...)))

Geopandas dependencies

raster and vector representations

Fiona
- provides an python API for OGR
GDAL/OGR
- GDAL for translating raster data
- OGR for translating vector data

Comparing raster and vector graphics

raster image of Corfu

vector image of Corfu

Colormaps

matplotlib qualitative colormaps

https://matplotlib.org/users/colormaps.html

Plotting with color

school_districts.head(3)

first_name     last_name    position    district      geometry
Sharon         Gentry       Member       1    (POLYGON ((-86.771 36.383)...))
Jill           Speering     Vice-Chair   3    (POLYGON ((-86.753 36.404)...))
Jo Ann         Brannon      Member       2    (POLYGON ((-86.766 36.083)...))

comparing color maps

council_dists.plot(
                   column='district', 
                   cmap='Set3', 
                   legend=True)
plt.title('Council Districts')
plt.show();

council district plot with long legend

leg_kwds={'title':'District Number', 
          'loc': 'upper left', 
          'bbox_to_anchor':(1, 1.03), 
          'ncol':3}
council_dists.plot(column='district', 
                   cmap='Set3',
                   legend=True, 
             legend_kwds=leg_kwds)
plt.title('Council Districts')
plt.show();

council district plot with multicolumn legend

Let's practice!

Visualizing Geospatial Data in Python