Iris Grouped Grid#

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Most examples work across multiple plotting backends, this example is also available for:

import holoviews as hv
from holoviews import opts
hv.extension('bokeh')

Declaring data#

from bokeh.sampledata.iris import flowers
from holoviews.operation import gridmatrix

iris_ds = hv.Dataset(flowers).groupby('species').overlay()

Plot#

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))
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Download this notebook from GitHub (right-click to download).