import numpy as np
import holoviews as hv
hv.extension('matplotlib')

normal = np.random.randn(1000)
hv.Distribution(normal)

hv.NdOverlay({bw: hv.Distribution(normal).opts(alpha=1, bandwidth=bw, filled=False)
              for bw in [0.05, 0.1, 0.5, 1]}, 'Bandwidth')

points = hv.Points(np.random.randn(100,2))
points2 = hv.Points(np.random.randn(100,2)*2+1)

xdist, ydist = ((hv.Distribution(points2, kdims=[dim]) *
                 hv.Distribution(points, kdims=[dim]))
                for dim in 'xy')
((points2 * points) << ydist << xdist).redim.range(x=(-5, 5), y=(-5, 5))

from holoviews.operation.stats import univariate_kde
dist = hv.Distribution(normal)
kde = univariate_kde(dist, bin_range=(-4, 4), bw_method='silverman', n_samples=20)
kde