Iris grouped grid¶
Download this notebook from GitHub (right-click to download).
Most examples work across multiple plotting backends, this example is also available for:
In [1]:
import holoviews as hv
from holoviews import opts
hv.extension('bokeh')
Declaring data¶
In [2]:
from bokeh.sampledata.iris import flowers
from holoviews.operation import gridmatrix
iris_ds = hv.Dataset(flowers).groupby('species').overlay()
Plot¶
In [3]:
density_grid = gridmatrix(iris_ds, diagonal_type=hv.Distribution, chart_type=hv.Bivariate)
point_grid = gridmatrix(iris_ds, chart_type=hv.Points)
(density_grid * point_grid).opts(
opts.Bivariate(bandwidth=0.5, cmap=hv.Cycle(values=['Blues', 'Reds', 'Oranges'])),
opts.Points(size=2, alpha=0.5),
opts.NdOverlay(batched=False))
Out[3]:
Download this notebook from GitHub (right-click to download).