shap.plots.violin

shap.plots.violin(shap_values, features=None, feature_names=None, max_display=None, plot_type='violin', color=None, axis_color='#333333', title=None, alpha=1, show=True, sort=True, color_bar=True, plot_size='auto', layered_violin_max_num_bins=20, class_names=None, class_inds=None, color_bar_label='Feature value', cmap=<matplotlib.colors.LinearSegmentedColormap object>, color_bar_label_size=12, color_bar_tick_size=11, axhline_lw=0.5, use_log_scale=False)

Create a SHAP violin plot, colored by feature values when they are provided.

Parameters:

shap_valuesExplanation or numpy.ndarray

For single output explanations, this is a matrix of SHAP values (# samples x # features).

featuresnumpy.ndarray or pandas.DataFrame or list, optional

Matrix of feature values (# samples x # features), or a feature_names list as shorthand.

feature_nameslist, optional

Names of the features (length: # features).

max_displayint, optional

How many top features to include in the plot (default is 20).

plot_type{“violin”, “layered_violin”}, optional

What type of summary plot to produce. A “layered_violin” plot shows the distribution of the SHAP values of each variable. A “violin” plot is the same, except with outliers drawn as scatter points.

colorstr or None, optional

Color or colormap to use for the plot. If None, a default is chosen.

axis_colorstr, optional

Color for the plot axes.

titlestr or None, optional

Plot title (currently unused).

alphafloat, optional

Opacity of the plot elements.

showbool, optional

Whether matplotlib.pyplot.show() is called before returning. Setting this to False allows the plot to be customized further after it has been created.

sortbool, optional

Whether to sort features by the sum of their effect magnitudes.

color_barbool, optional

Whether to draw the color bar (legend).

plot_size{“auto”, float, (float, float), None}, optional

What size to make the plot. By default, the size is auto-scaled based on the number of features that are being displayed. Passing a single float will cause each row to be that many inches high. Passing a pair of floats will scale the plot by that number of inches. If None is passed, then the size of the current figure will be left unchanged.

layered_violin_max_num_binsint, optional

Maximum number of bins for layered violin plots.

color_bar_labelstr, optional

Label for the color bar.

cmapstr or Colormap, optional

Colormap to use for coloring points by feature value.

color_bar_label_sizeint, optional

Font size for the color bar label. Default is 11.

color_bar_tick_sizeint, optional

Font size for the color bar ticks. Default is 11.

axhline_lwfloat, optional

Line width for horizontal lines in the plot.

use_log_scalebool, optional

Whether to use a symmetric log scale for the x-axis.

Examples

See violin plot examples.