import cartopy.crs as ccrs
import holoviews as hv
import geoviews as gv
import geoviews.feature as gf

hv.extension('bokeh', 'matplotlib')

%%opts Points [width=600 height=500] (size=6)

nyc     = (-74.0, 40.7, 'NYC')
london  = (  0.1, 51.5, 'London')
beijing = (116.4, 39.9, 'Beijing')

points = gv.Points([nyc, london, beijing], vdims=['City'], extents=(-180, -90, 180, 90))
print('Default projection:', points.crs.__class__.__name__)
points * gf.borders * gf.coastline

%%opts Points [projection=ccrs.Robinson() width=800 height=400 global_extent=True]
points * gf.borders * gf.coastline

projected = gv.operation.project(points)
print('New projection:', projected.crs.__class__.__name__)
projected.dframe().set_index('City')

import geoviews.tile_sources as gts

gv.Layout([ts.relabel(name) for name, ts in gts.tile_sources.items()]).options(
    'WMTS', xaxis=None, yaxis=None, width=225, height=225
).cols(4)

%%opts Feature [width=600 height=500 global_extent=True]
import cartopy.feature as cf
graticules = cf.NaturalEarthFeature(
    category='physical',
    name='graticules_30',
    scale='110m')
gf.ocean * gf.land * gf.coastline * gv.Feature(graticules, group='Lines')

import geopandas as gpd
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
world.head()

%%opts Polygons [width=600 height=500 tools=['hover']] (cmap='viridis')
gv.Polygons(world, vdims=['gdp_md_est', 'continent', 'name']).redim.range(Latitude=(-60, 90))

usa = world[world.name=='United States'].geometry.iloc[0]
gv.Shape(usa)