def std(self):
        """Standard deviation

        Note that is by default normalizd by n - 1
        # TODO, what does pandas do for multiple grouping columns?
        # Currently we are just going to use one grouping column
        """
        std_expr = grizzly_impl.groupby_std(
            [self.column],
            [self.column_type],
            self.grouping_columns,
            self.grouping_column_types
        )
        unzipped_columns = grizzly_impl.unzip_columns(
            std_expr,
            self.grouping_column_types + [WeldDouble()],
        )
        index_expr = LazyOpResult(
            grizzly_impl.get_field(unzipped_columns, 0),
            self.grouping_column_types[0],
            1
        )
        column_expr = LazyOpResult(
            grizzly_impl.get_field(unzipped_columns, 1),
            self.grouping_column_types[0],
            1
        )
        group_expr = utils.group([index_expr, column_expr])
        return SeriesWeld(
            group_expr.expr,
            WeldDouble(),
            index_type=self.grouping_column_types[0],
            index_name=self.grouping_column_names[0]
        )
Standard deviation

        Note that is by default normalizd by n - 1
        # TODO, what does pandas do for multiple grouping columns?
        # Currently we are just going to use one grouping column