(self, quantile)
return quantile_points
Return the specific quantile point value

        Parameters
        ----------
        quantile : float, 0 <= quantile <= 1
            Specify which column(s) need to apply statistic.

        Returns
        -------
        return a dict of result quantile points.
        eg.
        quantile_point = {"x1": 3, "x2": 5... }
Return the specific quantile point value
Return the specific quantile point value
def get_quantile_point(self, quantile):
        """
        Return the specific quantile point value

        Parameters
        ----------
        quantile : float, 0 <= quantile <= 1
            Specify which column(s) need to apply statistic.

        Returns
        -------
        return a dict of result quantile points.
        eg.
        quantile_point = {"x1": 3, "x2": 5... }
        """
        if not self.has_fit:
            raise RuntimeError("Quantile Binning Tool's split points should be fit before calling"
                               " get quantile points")

        f = functools.partial(self._get_split_points,
                              allow_duplicate=self.allow_duplicate,
                              percentile_rate=[quantile])
        quantile_points = dict(self.summary_dict.mapValues(f).collect())
        quantile_points = {k: v[0] for k, v in quantile_points.items()}
        return quantile_points
def get_quantile_point ( self , quantile ) : if not self . has_fit : raise RuntimeError ( "Quantile Binning Tool's split points should be fit before calling" " get quantile points" ) f = functools . partial ( self . _get_split_points , allow_duplicate = self . allow_duplicate , percentile_rate = [ quantile ] ) quantile_points = dict ( self . summary_dict . mapValues ( f ) . collect ( ) ) quantile_points = { k : v [ 0 ] for k , v in quantile_points . items ( ) } return quantile_points