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


data = {
    'City': ['London', 'Paris', 'Berlin', 'Madrid', 'Rome', 'Vienna', 'Warsaw', 'Amsterdam'],
    'Country': ['United Kingdom', 'France', 'Germany', 'Spain', 'Italy', 'Austria', 'Poland', 'Netherlands'],
    'Latitude': [51.5074, 48.8566, 52.5200, 40.4168, 41.9028, 48.2082, 52.2297, 52.3676],
    'Longitude': [-0.1278, 2.3522, 13.4050, -3.7038, 12.4964, 16.3738, 21.0122, 4.9041]
}
cities = gpd.GeoDataFrame(
    data,
    geometry=gpd.points_from_xy(data['Longitude'], data['Latitude']),
    crs="EPSG:4326",
)

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=10), global_extent=True)
This web page was generated from a Jupyter notebook and not all interactivity will work on this website.
Show Source