Polygons#
import hvplot.pandas # noqa
Using hvplot with geopandas is as simple as loading a geopandas dataframe and calling hvplot on it with geo=True.
import geodatasets
import geopandas as gpd
chicago = gpd.read_file(geodatasets.get_path("geoda.chicago_commpop"))
chicago.sample(3)
Downloading file 'chicago_commpop.zip' from 'https://geodacenter.github.io/data-and-lab//data/chicago_commpop.zip' to '/home/runner/.cache/geodatasets'.
Extracting 'chicago_commpop/chicago_commpop.geojson' from '/home/runner/.cache/geodatasets/chicago_commpop.zip' to '/home/runner/.cache/geodatasets/chicago_commpop.zip.unzip'
| community | NID | POP2010 | POP2000 | POPCH | POPPERCH | popplus | popneg | geometry | |
|---|---|---|---|---|---|---|---|---|---|
| 46 | PULLMAN | 50 | 7325 | 8921 | -1596 | -17.890371 | 0 | 1 | MULTIPOLYGON (((-87.60157 41.68621, -87.60168 ... |
| 28 | NEAR WEST SIDE | 28 | 54881 | 46419 | 8462 | 18.229604 | 1 | 0 | MULTIPOLYGON (((-87.63759 41.88623, -87.63765 ... |
| 5 | LINCOLN SQUARE | 4 | 39493 | 44574 | -5081 | -11.399022 | 0 | 1 | MULTIPOLYGON (((-87.67441 41.9761, -87.6744 41... |
chicago.hvplot(geo=True)
Control the color of the elements using the c option.
chicago.hvplot.polygons(geo=True, c='POP2010', hover_cols='all')
You can even color by another series, such as population density:
chicago.hvplot.polygons(
geo=True,
c=chicago.POP2010/chicago.to_crs('EPSG:32616').area,
clabel='pop density',
)
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