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 | |
|---|---|---|---|---|---|---|---|---|---|
| 52 | GARFIELD RIDGE | 56 | 34513 | 36101 | -1588 | -4.398770 | 0 | 1 | MULTIPOLYGON (((-87.73856 41.81871, -87.73853 ... |
| 70 | BEVERLY | 72 | 20034 | 21992 | -1958 | -8.903237 | 0 | 1 | MULTIPOLYGON (((-87.67308 41.73566, -87.66975 ... |
| 64 | WEST ENGLEWOOD | 67 | 35505 | 45282 | -9777 | -21.591361 | 0 | 1 | MULTIPOLYGON (((-87.65487 41.79417, -87.65487 ... |
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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