Rug Plot

Plot marginal distributions by drawing ticks along the x and y axes. Commonly combined with kdeplot.

plot: 'rugplot'

Plot-Specific Parameters

hue (str, list, numpy.ndarray, pandas.core.indexes.base.Index, or None, default: None)

Semantic variable that is mapped to determine the color of plot elements.

height (float, default: 0.025)

Proportion of axes extent covered by each rug element.

expand_margins (bool, default: True)

If True, increase the axes margins by the height of the rug to avoid overlap with other elements.

palette (str, list, matplotlib.colors.Colormap, or None, default: None)

Method for choosing the colors to use when mapping the hue semantic. String values are passed to color_palette(). List values imply categorical mapping, while a colormap object implies numeric mapping.

hue_order (list or None, default: None)

Specify the order of processing and plotting for categorical levels of the hue semantic.

hue_norm (tuple, matplotlib.colors.Normalize, or None, default: None)

Either a pair of values that set the normalization range in data units or an object that will map from data units into a 0 until 1 interval. Usage implies numeric mapping.

legend (bool, default: True)

If False, do not add a legend for semantic variables.

alpha (float or None, default: None)

Proportional opacity of the points.

zorder (int or None, default: None)

Axes order. The default drawing order for axes is patches, lines, text for each plot order.

Example 1

from grplot import plot2d
import grplot_seaborn as gs
gs.set_theme(context='notebook', style='darkgrid', palette='deep')

tips = gs.load_dataset('tips')
ax = plot2d(plot='kdeplot+rugplot',
            df=tips,
            x='total_bill',
            xsep='.c',
            ysep='.',
            statdesc={'total_bill': 'general'},
            xtick_add='Rp(_)',
            title='KDE-Rug Density vs total_bill')

Example 2

from grplot import plot2d
import grplot_seaborn as gs
gs.set_theme(context='notebook', style='darkgrid', palette='deep')


tips = gs.load_dataset('tips')
ax = plot2d(plot='scatterplot+rugplot',
            df=tips,
            x='total_bill',
            y='tip',
            sep='.c',
            tick_add='Rp(_)',
            title='Scatter-Rug tip vs total_bill')