How to use geoplot - 10 common examples

import numpy as np
import geopandas as gpd
from shapely.geometry import Polygon
from matplotlib.colors import Normalize
import matplotlib.pyplot as plt

from geoplot import utils
from geoplot import (
    pointplot, voronoi, kdeplot, polyplot, webmap, choropleth, cartogram, quadtree,
    sankey
)
from geoplot.crs import AlbersEqualArea, WebMercator


np.random.seed(42)
p_srs = gpd.GeoSeries(utils.gaussian_points(n=100))
p_df = gpd.GeoDataFrame(geometry=p_srs)
p_df = p_df.assign(var=p_df.geometry.map(lambda p: abs(p.y) + abs(p.x)))
p_df = p_df.assign(var_cat=np.floor(p_df['var'] // (p_df['var'].max() / 5)).astype(str))

poly_df = gpd.GeoDataFrame(geometry=utils.gaussian_polygons(p_srs.geometry, n=10))
poly_df = poly_df.assign(
    var=poly_df.geometry.centroid.x.abs() + poly_df.geometry.centroid.y.abs()
)

ls_df = gpd.GeoDataFrame(geometry=utils.gaussian_linestrings(p_srs.geometry))
ls_df = ls_df.assign(var=ls_df.geometry.centroid.x.abs() + ls_df.geometry.centroid.y.abs())

clip_geom = gpd.GeoSeries(Polygon([[-10, -10], [10, -10], [10, 10], [-10, 10]]))
non_clip_geom = gpd.GeoSeries(Polygon([[-30, -30], [30, -30], [30, 30], [-30, 30]]))

def identity_scale(minval, maxval):

)
from geoplot.crs import AlbersEqualArea, WebMercator


np.random.seed(42)
p_srs = gpd.GeoSeries(utils.gaussian_points(n=100))
p_df = gpd.GeoDataFrame(geometry=p_srs)
p_df = p_df.assign(var=p_df.geometry.map(lambda p: abs(p.y) + abs(p.x)))
p_df = p_df.assign(var_cat=np.floor(p_df['var'] // (p_df['var'].max() / 5)).astype(str))

poly_df = gpd.GeoDataFrame(geometry=utils.gaussian_polygons(p_srs.geometry, n=10))
poly_df = poly_df.assign(
    var=poly_df.geometry.centroid.x.abs() + poly_df.geometry.centroid.y.abs()
)

ls_df = gpd.GeoDataFrame(geometry=utils.gaussian_linestrings(p_srs.geometry))
ls_df = ls_df.assign(var=ls_df.geometry.centroid.x.abs() + ls_df.geometry.centroid.y.abs())

clip_geom = gpd.GeoSeries(Polygon([[-10, -10], [10, -10], [10, 10], [-10, 10]]))
non_clip_geom = gpd.GeoSeries(Polygon([[-30, -30], [30, -30], [30, 30], [-30, 30]]))

def identity_scale(minval, maxval):
    def scalar(val):
        return 10
    return scalar


def axis_initializer(f):
    def wrapped(_self):
        try:
            f(_self)
        finally:

from geoplot import utils
from geoplot import (
    pointplot, voronoi, kdeplot, polyplot, webmap, choropleth, cartogram, quadtree,
    sankey
)
from geoplot.crs import AlbersEqualArea, WebMercator


np.random.seed(42)
p_srs = gpd.GeoSeries(utils.gaussian_points(n=100))
p_df = gpd.GeoDataFrame(geometry=p_srs)
p_df = p_df.assign(var=p_df.geometry.map(lambda p: abs(p.y) + abs(p.x)))
p_df = p_df.assign(var_cat=np.floor(p_df['var'] // (p_df['var'].max() / 5)).astype(str))

poly_df = gpd.GeoDataFrame(geometry=utils.gaussian_polygons(p_srs.geometry, n=10))
poly_df = poly_df.assign(
    var=poly_df.geometry.centroid.x.abs() + poly_df.geometry.centroid.y.abs()
)

ls_df = gpd.GeoDataFrame(geometry=utils.gaussian_linestrings(p_srs.geometry))
ls_df = ls_df.assign(var=ls_df.geometry.centroid.x.abs() + ls_df.geometry.centroid.y.abs())

clip_geom = gpd.GeoSeries(Polygon([[-10, -10], [10, -10], [10, 10], [-10, 10]]))
non_clip_geom = gpd.GeoSeries(Polygon([[-30, -30], [30, -30], [30, 30], [-30, 30]]))

def identity_scale(minval, maxval):
    def scalar(val):
        return 10
    return scalar

def test_base_init(self):
        """Test the base init all plotters pass to Plot."""
        plot = Plot(self.gdf, **self.kwargs)
        assert plot.figsize == (8, 6)
        assert isinstance(plot.ax, SubplotBase)  # SO 11690597
        assert plot.extent == None
        assert plot.projection == None

        plot = Plot(self.gdf, **{**self.kwargs, **{'projection': gcrs.PlateCarree()}})
        assert plot.figsize == (8, 6)
        assert isinstance(plot.ax, GeoAxesSubplot)
        assert plot.extent == None
        assert isinstance(plot.projection, ccrs.PlateCarree)

    pytest.param(gcrs.TransverseMercator(central_longitude=45), marks=pytest.mark.xfail),
    pytest.param(gcrs.TransverseMercator(central_latitude=45), marks=pytest.mark.xfail),
    pytest.param(gcrs.LambertAzimuthalEqualArea(central_longitude=45), marks=pytest.mark.xfail),
    gcrs.LambertAzimuthalEqualArea(central_latitude=45),
])
def test_partially_parameterized_global_projections(proj, countries):
    gplt.polyplot(countries, proj)
    ax = plt.gca()
    ax.set_global()
    return plt.gcf()

    gcrs.LambertConformal(central_longitude=45, central_latitude=45),
    gcrs.Orthographic(central_longitude=45, central_latitude=45),
    gcrs.Stereographic(central_longitude=45, central_latitude=45),
    pytest.param(
        gcrs.TransverseMercator(central_longitude=45, central_latitude=45),
        marks=pytest.mark.xfail
    ),
    gcrs.LambertAzimuthalEqualArea(central_longitude=45, central_latitude=45),
])
def test_fully_parameterized_global_projections(proj, countries):
    gplt.polyplot(countries, proj)
    ax = plt.gca()
    ax.set_global()
    return plt.gcf()

    gcrs.Orthographic(),
    gcrs.Stereographic(),
    pytest.param(gcrs.TransverseMercator(), marks=pytest.mark.xfail),
    gcrs.LambertAzimuthalEqualArea(),
    gcrs.WebMercator()
])
def test_basic_global_projections(proj, countries):
    gplt.polyplot(countries, proj)
    ax = plt.gca()
    ax.set_global()
    return plt.gcf()

    gcrs.OSGB(),
])
def test_basic_non_global_projections(proj, countries):
    with warnings.catch_warnings():
        warnings.simplefilter("ignore")
        gplt.polyplot(countries, proj)
    return plt.gcf()

    pytest.param(gcrs.Orthographic(), marks=pytest.mark.xfail),
    gcrs.Stereographic(),
    pytest.param(gcrs.TransverseMercator(), marks=pytest.mark.xfail),
    gcrs.LambertAzimuthalEqualArea(),
    gcrs.WebMercator()
])
def test_subplots_global_projections(proj, countries):
    gplt.polyplot(countries, proj, ax=plt.subplot(2, 1, 1, projection=proj)).set_global()
    gplt.polyplot(countries, proj, ax=plt.subplot(2, 1, 2, projection=proj)).set_global()
    return plt.gcf()

def test_fully_parameterized_global_projections(proj, countries):
    gplt.polyplot(countries, proj)
    ax = plt.gca()
    ax.set_global()
    return plt.gcf()