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 | |
|---|---|---|---|---|---|---|---|---|---|
| 5 | LINCOLN SQUARE | 4 | 39493 | 44574 | -5081 | -11.399022 | 0 | 1 | MULTIPOLYGON (((-87.67441 41.9761, -87.6744 41... |
| 54 | BRIGHTON PARK | 58 | 45368 | 44912 | 456 | 1.015319 | 1 | 0 | MULTIPOLYGON (((-87.68424 41.823, -87.68423 41... |
| 48 | EAST SIDE | 52 | 23042 | 23653 | -611 | -2.583182 | 0 | 1 | MULTIPOLYGON (((-87.52462 41.6918, -87.52501 4... |
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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