Rank the values along a given axis.

    Parameters
    ----------
    values : array-like
        Array whose values will be ranked. The number of dimensions in this
        array must not exceed 2.
    axis : int, default 0
        Axis over which to perform rankings.
    method : {'average', 'min', 'max', 'first', 'dense'}, default 'average'
        The method by which tiebreaks are broken during the ranking.
    na_option : {'keep', 'top'}, default 'keep'
        The method by which NaNs are placed in the ranking.
        - ``keep``: rank each NaN value with a NaN ranking
        - ``top``: replace each NaN with either +/- inf so that they
                   there are ranked at the top
    ascending : boolean, default True
        Whether or not the elements should be ranked in ascending order.
    pct : boolean, default False
        Whether or not to the display the returned rankings in integer form
        (e.g. 1, 2, 3) or in percentile form (e.g. 0.333..., 0.666..., 1).

def rank(values, axis=0, method='average', na_option='keep',
         ascending=True, pct=False):
    """
    Rank the values along a given axis.

    Parameters
    ----------
    values : array-like
        Array whose values will be ranked. The number of dimensions in this
        array must not exceed 2.
    axis : int, default 0
        Axis over which to perform rankings.
    method : {'average', 'min', 'max', 'first', 'dense'}, default 'average'
        The method by which tiebreaks are broken during the ranking.
    na_option : {'keep', 'top'}, default 'keep'
        The method by which NaNs are placed in the ranking.
        - ``keep``: rank each NaN value with a NaN ranking
        - ``top``: replace each NaN with either +/- inf so that they
                   there are ranked at the top
    ascending : boolean, default True
        Whether or not the elements should be ranked in ascending order.
    pct : boolean, default False
        Whether or not to the display the returned rankings in integer form
        (e.g. 1, 2, 3) or in percentile form (e.g. 0.333..., 0.666..., 1).
    """
    if values.ndim == 1:
        f, values = _get_data_algo(values, _rank1d_functions)
        ranks = f(values, ties_method=method, ascending=ascending,
                  na_option=na_option, pct=pct)
    elif values.ndim == 2:
        f, values = _get_data_algo(values, _rank2d_functions)
        ranks = f(values, axis=axis, ties_method=method,
                  ascending=ascending, na_option=na_option, pct=pct)
    else:
        raise TypeError("Array with ndim > 2 are not supported.")

    return ranks