<jupyter_start><jupyter_text>Most examples work across multiple plotting backends, this example is also available for:* [Bokeh - iris_grouped_grid](../bokeh/iris_grouped_grid.ipynb)<jupyter_code>import holoviews as hv
hv.extension('matplotlib')<jupyter_output><empty_output><jupyter_text>Declaring data<jupyter_code>from bokeh.sampledata.iris import flowers
from holoviews.operation import gridmatrix

iris_ds = hv.Dataset(flowers).groupby('species').overlay()<jupyter_output><empty_output><jupyter_text>Plot<jupyter_code>%%opts Bivariate [bandwidth=0.5] (cmap=Cycle(values=['Blues', 'Reds', 'Oranges'])) Points (s=4) Histogram (alpha=0.5)
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<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12351543942992874, 'fraction_numerical': 0.0059382422802850355, 'mean_word_length': 10.708333333333334, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '197246', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 323, 'n_tokens_neox': 312, 'n_words': 47, 'path': 'examples/gallery/demos/matplotlib/iris_grouped_grid.ipynb', 'repo_name': 'jsignell/holoviews', 'size': '842'}