Function violin_stats

lib/matplotlib/cbook.py:1485–1619

Return a list of dictionaries of data which can be used to draw a series of violin plots. See the ``Returns`` section below to view the required keys of the dictionary. Users can skip this function and pass a user-defined set of dictionaries with the same keys to `~.axes.A

(X, method=("GaussianKDE", "scott"), points=100, quantiles=None)

def violin_stats(X, method=("GaussianKDE", "scott"), points=100, quantiles=None):
    """
    Return a list of dictionaries of data which can be used to draw a series
    of violin plots.

    See the ``Returns`` section below to view the required keys of the
    dictionary.

    Users can skip this function and pass a user-defined set of dictionaries
    with the same keys to `~.axes.Axes.violin` instead of using Matplotlib
    to do the calculations. See the *Returns* section below for the keys
    that must be present in the dictionaries.

    Parameters
    ----------
    X : 1D array or sequence of 1D arrays or 2D array
        Sample data that will be used to produce the gaussian kernel density
        estimates. Non-finite and masked values are ignored.
        Possible values:

        - 1D array: Statistics are computed for that array.
        - sequence of 1D arrays: Statistics are computed for each array in the sequence.
        - 2D array: Statistics are computed for each column in the array.

    method : (name, bw_method) or callable,
        The method used to calculate the kernel density estimate for each
        column of data. Valid values:

        - a tuple of the form ``(name, bw_method)`` where *name* currently must
          always be ``"GaussianKDE"`` and *bw_method* is the method used to
          calculate the estimator bandwidth. Supported values are 'scott',
          'silverman' or a float or a callable. 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 float.

        - a callable with the signature ::

             def method(data: ndarray, coords: ndarray) -> ndarray

          It should return the KDE of *data* evaluated at *coords*.

          .. versionadded:: 3.11
             Support for ``(name, bw_method)`` tuple.

    points : int, default: 100
        Defines the number of points to evaluate each of the gaussian kernel
        density estimates at.

    quantiles : array-like, default: None
        Defines (if not None) a list of floats in interval [0, 1] for each
        column of data, which represents the quantiles that will be rendered
        for that column of data. Must have 2 or fewer dimensions. 1D array will
        be treated as a singleton list containing them.

    Returns
    -------
    list of dict