violinplot(dataset, positions=None, vert=True, widths=0.5, showmeans=False, showextrema=True, showmedians=False, quantiles=None, points=100, bw_method=None, *, data=None)

Make a violin plot for each column of dataset or each vector in sequence dataset. Each filled area extends to represent the entire data range, with optional lines at the mean, the median, the minimum, the maximum, and user-specified quantiles.

Parameters

dataset : Array or a sequence of vectors.

The input data.

positions : array-like, default: [1, 2, ..., n]

The positions of the violins. The ticks and limits are automatically set to match the positions.

vert : bool, default: True.

If true, creates a vertical violin plot. Otherwise, creates a horizontal violin plot.

widths : array-like, default: 0.5

Either a scalar or a vector that sets the maximal width of each violin. The default is 0.5, which uses about half of the available horizontal space.

showmeans : bool, default: False

If :None:None:`True`, will toggle rendering of the means.

showextrema : bool, default: True

If :None:None:`True`, will toggle rendering of the extrema.

showmedians : bool, default: False

If :None:None:`True`, will toggle rendering of the medians.

quantiles : array-like, default: None

If not None, set a list of floats in interval [0, 1] for each violin, which stands for the quantiles that will be rendered for that violin.

points : int, default: 100

Defines the number of points to evaluate each of the gaussian kernel density estimations at.

bw_method : str, scalar or callable, optional

The method used to calculate the estimator bandwidth. This can be 'scott', 'silverman', a scalar constant or a callable. If a scalar, this will be used directly as :None:None:`kde.factor`. If a callable, it should take a GaussianKDE instance as its only parameter and return a scalar. If None (default), 'scott' is used.

data : indexable object, optional

If given, the following parameters also accept a string s , which is interpreted as data[s] (unless this raises an exception):

dataset

Returns

dict

A dictionary mapping each component of the violinplot to a list of the corresponding collection instances created. The dictionary has the following keys:

• bodies : A list of the ~.collections.PolyCollection instances containing the filled area of each violin.

• cmeans : A ~.collections.LineCollection instance that marks the mean values of each of the violin's distribution.

• cmins : A ~.collections.LineCollection instance that marks the bottom of each violin's distribution.

• cmaxes : A ~.collections.LineCollection instance that marks the top of each violin's distribution.

• cbars : A ~.collections.LineCollection instance that marks the centers of each violin's distribution.

• cmedians : A ~.collections.LineCollection instance that marks the median values of each of the violin's distribution.

• cquantiles : A ~.collections.LineCollection instance created to identify the quantile values of each of the violin's distribution.

Make a violin plot.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

matplotlib.pyplot.boxplot matplotlib.pyplot.plotting

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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