Classe « Axes »

Méthode matplotlib.figure.Axes.violinplot

Signature de la méthode violinplot

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

Description

violinplot.__doc__

Make a violin plot.

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 `True`, will toggle rendering of the means.

showextrema : bool, default: True
  If `True`, will toggle rendering of the extrema.

showmedians : bool, default: False
  If `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 `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.

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.

Notes
-----


.. note::
    In addition to the above described arguments, this function can take
    a *data* keyword argument. If such a *data* argument is given,
    the following arguments can also be string ``s``, which is
    interpreted as ``data[s]`` (unless this raises an exception):
    *dataset*.

    Objects passed as **data** must support item access (``data[s]``) and
    membership test (``s in data``).