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 | |
|---|---|---|---|---|---|---|---|---|---|
| 26 | WEST GARFIELD PARK | 26 | 18001 | 23019 | -5018 | -21.799383 | 0 | 1 | MULTIPOLYGON (((-87.72024 41.86987, -87.72023 ... |
| 65 | ENGLEWOOD | 68 | 30654 | 40222 | -9568 | -23.787977 | 0 | 1 | MULTIPOLYGON (((-87.62826 41.78316, -87.62826 ... |
| 68 | ASHBURN | 70 | 41081 | 39584 | 1497 | 3.781831 | 1 | 0 | MULTIPOLYGON (((-87.71255 41.75734, -87.71252 ... |
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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