(col_name, static_nums, sparse_bin_points, label_counts)
return col_name, static_nums
Parameters
        ----------
        static_nums :  list.
            It is like:
                [[event_count, total_num], [event_count, total_num] ... ]


        sparse_bin_points : dict
            Dict of sparse bin num
                {"x1": 2, "x2": 3, "x3": 5 ... }

        label_counts: np.array
            eg. [100, 200, ...]

        Returns
        -------
        The format is same as result_counts.
Parameters
        ----------
        static_nums :  list.
            It is like:
                [[event_count, total_num], [event_count, total_num] ... ]
Parameters ---------- static_nums : list . It is like : [[ event_count total_num ] [ event_count total_num ] ... ]
def fill_sparse_result(col_name, static_nums, sparse_bin_points, label_counts):
        """
        Parameters
        ----------
        static_nums :  list.
            It is like:
                [[event_count, total_num], [event_count, total_num] ... ]


        sparse_bin_points : dict
            Dict of sparse bin num
                {"x1": 2, "x2": 3, "x3": 5 ... }

        label_counts: np.array
            eg. [100, 200, ...]

        Returns
        -------
        The format is same as result_counts.
        """

        curt_all = functools.reduce(lambda x, y: x + y, static_nums)
        sparse_bin = sparse_bin_points.get(col_name)
        static_nums[sparse_bin] = label_counts - curt_all
        return col_name, static_nums
def fill_sparse_result ( col_name , static_nums , sparse_bin_points , label_counts ) : curt_all = functools . reduce ( lambda x , y : x + y , static_nums ) sparse_bin = sparse_bin_points . get ( col_name ) static_nums [ sparse_bin ] = label_counts - curt_all return col_name , static_nums