geoplot.kdeplot¶

geoplot.kdeplot(df, projection=None, extent=None, figsize=(8, 6), ax=None, clip=None, **kwargs)¶

Geographic kernel density estimate plot.

Parameters:	df (GeoDataFrame) – The data being plotted. projection (geoplot.crs object instance, optional) – A geographic projection. Must be an instance of an object in the geoplot.crs module, e.g. geoplot.crs.PlateCarree(). This parameter is optional: if left unspecified, a pure unprojected matplotlib object will be returned. For more information refer to the tutorial page on projections. clip (None or iterable or GeoSeries, optional) – An iterable of geometries that the KDE plot will be clipped to. This is a visual parameter useful for “cleaning up” the plot. This feature has not yet actually been implemented! figsize (tuple, optional) – An (x, y) tuple passed to matplotlib.figure which sets the size, in inches, of the resultant plot. Defaults to (8, 6), the matplotlib default global. extent (None or (minx, maxx, miny, maxy), optional) – If this parameter is set to None (default) this method will calculate its own cartographic display region. If an extrema tuple is passed—useful if you want to focus on a particular area, for example, or exclude certain outliers—that input will be used instead. clip – If this argument is specified, kdeplot output will be clipped so that the heatmap only appears when it is inside the boundaries of the given geometries. extent – If this parameter is unset geoplot will calculate the plot limits. If an extrema tuple is passed, that input will be used instead. figsize – An (x, y) tuple passed to matplotlib.figure which sets the size, in inches, of the resultant plot. Defaults to (8, 6), the matplotlib default global. ax (AxesSubplot or GeoAxesSubplot instance, optional) – A matplotlib.axes.AxesSubplot or cartopy.mpl.geoaxes.GeoAxesSubplot instance onto which this plot will be graphed. If this parameter is left undefined a new axis will be created and used instead. kwargs (dict, optional) – Keyword arguments to be passed to the sns.kdeplot method doing the plotting (ref).
Returns:	The axis object with the plot on it.
Return type:	AxesSubplot or GeoAxesSubplot instance

Examples

Give it a dataset containing a geometry of shapely Point observations, and kdeplot will return a geospatial kernel density estimate plot showing where they are.

A basic kdeplot specified data and, optionally, a projection.

import geoplot as gplt
import geoplot.crs as gcrs
gplt.kdeplot(collisions, projection=gcrs.AlbersEqualArea())

However, kdeplots need additional geospatial context to be interpretable. In this case (and for the remainder of the examples) we will provide this by overlaying borough geometry.

ax = gplt.kdeplot(collisions, projection=gcrs.AlbersEqualArea())
gplt.polyplot(boroughs, projection=gcrs.AlbersEqualArea(), ax=ax)

Most of the rest of the parameters to kdeplot are parameters inherited from the seaborn method by the same name, on which this plot type is based. For example, specifying shade=True provides a filled KDE instead of a contour one:

ax = gplt.kdeplot(collisions, projection=gcrs.AlbersEqualArea(),
                  shade=True)
gplt.polyplot(boroughs, projection=gcrs.AlbersEqualArea(), ax=ax)

Use n_levels to specify the number of contour levels.

ax = gplt.kdeplot(collisions, projection=gcrs.AlbersEqualArea(),
                  n_levels=30)
gplt.polyplot(boroughs, projection=gcrs.AlbersEqualArea(), ax=ax)

Or specify cmap to change the colormap.

ax = gplt.kdeplot(collisions, projection=gcrs.AlbersEqualArea(),
     cmap='Purples')
gplt.polyplot(boroughs, projection=gcrs.AlbersEqualArea(), ax=ax)

Oftentimes given the geometry of the location, a “regular” continuous KDEPlot doesn’t make sense. We can specify a clip of iterable geometries, which will be used to trim the kdeplot (note: if you have set shade=True as a parameter you may need to additionally specify shade_lowest=False to avoid inversion at the edges).

gplt.kdeplot(collisions, projection=gcrs.AlbersEqualArea(),
             shade=True, clip=boroughs)