binnings.py 文件源码

def quantile_binning(data=None, bins=10, qrange=(0.0, 1.0), **kwargs):
    """Binning schema based on quantile ranges.

    This binning finds equally spaced quantiles. This should lead to
    all bins having roughly the same frequencies.

    Note: weights are not (yet) take into account for calculating
    quantiles.

    Parameters
    ----------
    bins: sequence or Optional[int]
        Number of bins
    qrange: Optional[tuple]
        Two floats as minimum and maximum quantile (default: 0.0, 1.0)

    Returns
    -------
    StaticBinning
    """

    if np.isscalar(bins):
        bins = np.linspace(qrange[0] * 100, qrange[1] * 100, bins + 1)
    bins = np.percentile(data, bins)
    return static_binning(bins=make_bin_array(bins), includes_right_edge=True)