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Points#

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)
/tmp/ipykernel_2286/4227810846.py:3: FutureWarning: The geopandas.dataset module is deprecated and will be removed in GeoPandas 1.0. You can get the original 'naturalearth_cities' data from https://www.naturalearthdata.com/downloads/110m-cultural-vectors/.
  cities = gpd.read_file(gpd.datasets.get_path('naturalearth_cities'))
name geometry
11 Tarawa POINT (173.01757 1.33819)
153 Warsaw POINT (21.00535 52.23087)
200 ?saka POINT (135.50375 34.69110)
198 Ürümqi POINT (87.57306 43.80696)
232 Shanghai POINT (121.43456 31.21840)
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)