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DOC: Update violinplot() docs #27813

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Feb 23, 2024
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DOC: Update violinplot() docs #27813

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50 changes: 24 additions & 26 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -8206,43 +8206,41 @@ def violinplot(self, dataset, positions=None, vert=True, widths=0.5,
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.
The positions of the violins; i.e. coordinates on the x-axis for
vertical violins (or y-axis for horizontal violins).

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.
widths : float or array-like, default: 0.5
The maximum width of each violin in units of the *positions* axis.
The default is 0.5, which is half the available space when using default
*positions*.

showmeans : bool, default: False
If `True`, will toggle rendering of the means.
Whether to show the mean with a line.

showextrema : bool, default: True
If `True`, will toggle rendering of the extrema.
Whether to show extrema with a line.

showmedians : bool, default: False
If `True`, will toggle rendering of the medians.
Whether to show the median with a line.

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

data : indexable object, optional
DATA_PARAMETER_PLACEHOLDER
Expand Down Expand Up @@ -8329,26 +8327,26 @@ def violin(self, vpstats, positions=None, vert=True, widths=0.5,
for this violin's dataset.

positions : array-like, default: [1, 2, ..., n]
The positions of the violins. The ticks and limits are
automatically set to match the positions.
The positions of the violins; i.e. coordinates on the x-axis for
vertical violins (or y-axis for horizontal violins).

vert : bool, default: True.
If true, plots the violins vertically.
Otherwise, plots the violins horizontally.

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.
widths : float or array-like, default: 0.5
The maximum width of each violin in units of the *positions* axis.
The default is 0.5, which is half available space when using default
*positions*.

showmeans : bool, default: False
If true, will toggle rendering of the means.
Whether to show the mean with a line.

showextrema : bool, default: True
If true, will toggle rendering of the extrema.
Whether to show extrema with a line.

showmedians : bool, default: False
If true, will toggle rendering of the medians.
Whether to show the median with a line.

Returns
-------
Expand Down
9 changes: 4 additions & 5 deletions lib/matplotlib/mlab.py
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Expand Up @@ -776,12 +776,11 @@ class GaussianKDE:
dataset : array-like
Datapoints to estimate from. In case of univariate data this is a 1-D
array, otherwise a 2D array with shape (# of dims, # of data).
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 `kde.factor`. If a
bw_method : {'scott', 'silverman'} or float or callable, optional
The method used to calculate the estimator bandwidth. If a
float, this will be used directly as `kde.factor`. If a
callable, it should take a `GaussianKDE` instance as only
parameter and return a scalar. If None (default), 'scott' is used.
parameter and return a float. If None (default), 'scott' is used.

Attributes
----------
Expand Down