Points#
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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 geopandas as gpd
cities = gpd.read_file(gpd.datasets.get_path('naturalearth_cities'))
cities.sample(5)
name | geometry | |
---|---|---|
136 | Apia | POINT (-171.76860 -13.83571) |
50 | Lusaka | POINT (28.28138 -15.41470) |
144 | Hanoi | POINT (105.84807 21.03527) |
118 | Tirana | POINT (19.81888 41.32754) |
181 | Caracas | POINT (-66.91898 10.50294) |
cities.hvplot(geo=True, tiles=True)
You can easily change the tiles, add coastlines, or which fields show up in the hover text:
cities.hvplot(tiles='EsriTerrain', coastline=True, hover_cols='all')
We can also alter the projection of the data using cartopy:
import cartopy.crs as ccrs
cities.hvplot(coastline=True, projection=ccrs.Geostationary(central_longitude=-30), global_extent=True)
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Download this notebook from GitHub (right-click to download).