marsilea.plotter.Box

class Box(data, hue_order=None, palette=None, orient=None, legend_kws=None, group_kws=None, label=None, label_loc=None, label_props=None, **kwargs)

Bases: _SeabornBase

Wrapper for seaborn’s boxplot

Note

About data format

You can only use wide-format for this plot, the number of columns of your input data should match your main data, this allow the data to be split and reorder if split and cluster is applied.

Parameters:

datanp.ndarray, pd.DataFrame

The wide-format data. To input ‘hue’ like data, you need to input a dict. eg: {'hue1': data1, 'hue2': data2}.

hue_orderarray of str

The order of hue

palettedict of label, color

labelstr

The label of your data

legend_kwsdict

Configurations for legend

group_kwsdict

Configurations that apply to each group, should be something like {'colors': ['C0', 'C1', 'C2']} if you have three groups.

kwargs

See seaborn.boxplot()

Examples

To render seaborn plots as side plots

>>> import marsilea as ma
>>> from marsilea.plotter import Box
>>> data = np.random.randn(10, 10)
>>> sdata = np.random.rand(10, 10)
>>> plot = Box(sdata, color='#DB4D6D')
>>> h = ma.Heatmap(data)
>>> h.cut_rows(cut=[3, 7])
>>> h.add_right(plot)
>>> h.render()

It’s possible to add hue data

>>> plot = Box({'a': sdata, 'b': sdata}, color='#DB4D6D')
>>> h = ma.Heatmap(data)
>>> h.cut_rows(cut=[3, 7])
>>> h.add_right(plot)
>>> h.render()

You can also draw it on the main canvas

>>> plot = Box(sdata, color='#DB4D6D')
>>> colors = ['#66327C', '#FFB11B', '#A8D8B9']
>>> anno = ma.plotter.Chunk(['C1', 'C2', 'C3'], colors, padding=10)
>>> cb = ma.ClusterBoard(data, height=2, margin=.5)
>>> cb.add_layer(plot)
>>> cb.cut_cols([3, 7])
>>> cb.add_bottom(anno)
>>> cb.render()

To layout in a different orient and style each group

>>> plot = Box(sdata, orient='h',
...                   group_kws={'color': colors})
>>> anno = ma.plotter.Chunk(['C1', 'C2', 'C3'], colors, padding=10)
>>> cb = ma.ClusterBoard(data.T, width=2)
>>> cb.add_layer(plot)
>>> cb.cut_rows([3, 7])
>>> cb.add_left(anno)
>>> cb.render()