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Fonction rankdata - module scipy.stats

Signature de la fonction rankdata

def rankdata(a, method='average', *, axis=None) 

Description

rankdata.__doc__

Assign ranks to data, dealing with ties appropriately.

    By default (``axis=None``), the data array is first flattened, and a flat
    array of ranks is returned. Separately reshape the rank array to the
    shape of the data array if desired (see Examples).

    Ranks begin at 1.  The `method` argument controls how ranks are assigned
    to equal values.  See [1]_ for further discussion of ranking methods.

    Parameters
    ----------
    a : array_like
        The array of values to be ranked.
    method : {'average', 'min', 'max', 'dense', 'ordinal'}, optional
        The method used to assign ranks to tied elements.
        The following methods are available (default is 'average'):

          * 'average': The average of the ranks that would have been assigned to
            all the tied values is assigned to each value.
          * 'min': The minimum of the ranks that would have been assigned to all
            the tied values is assigned to each value.  (This is also
            referred to as "competition" ranking.)
          * 'max': The maximum of the ranks that would have been assigned to all
            the tied values is assigned to each value.
          * 'dense': Like 'min', but the rank of the next highest element is
            assigned the rank immediately after those assigned to the tied
            elements.
          * 'ordinal': All values are given a distinct rank, corresponding to
            the order that the values occur in `a`.
    axis : {None, int}, optional
        Axis along which to perform the ranking. If ``None``, the data array
        is first flattened.

    Returns
    -------
    ranks : ndarray
         An array of size equal to the size of `a`, containing rank
         scores.

    References
    ----------
    .. [1] "Ranking", https://en.wikipedia.org/wiki/Ranking

    Examples
    --------
    >>> from scipy.stats import rankdata
    >>> rankdata([0, 2, 3, 2])
    array([ 1. ,  2.5,  4. ,  2.5])
    >>> rankdata([0, 2, 3, 2], method='min')
    array([ 1,  2,  4,  2])
    >>> rankdata([0, 2, 3, 2], method='max')
    array([ 1,  3,  4,  3])
    >>> rankdata([0, 2, 3, 2], method='dense')
    array([ 1,  2,  3,  2])
    >>> rankdata([0, 2, 3, 2], method='ordinal')
    array([ 1,  2,  4,  3])
    >>> rankdata([[0, 2], [3, 2]]).reshape(2,2)
    array([[1. , 2.5],
          [4. , 2.5]])
    >>> rankdata([[0, 2, 2], [3, 2, 5]], axis=1)
    array([[1. , 2.5, 2.5],
           [2. , 1. , 3. ]])