def summary(self,
                func=methodcaller('sum'),
                title='Total',
                axis=0,
                subset=None,
                *args,
                **kwargs):
        """Add multiple summary rows or columns to the dataframe.

        Parameters
        ----------
        :param func: function to be used for a summary.
        :param titles: Title for this summary column.
        :param axis:
            Same as numpy and pandas axis argument. A value of None will cause
            the summary to be applied to both rows and columns.
        :param args: Positional arguments passed to all the functions.
        :param kwargs: Keyword arguments passed to all the functions.

        The results of summary can be chained together.
        """

        if axis is None:
            return (
                self
                .summary(
                    func=func,
                    title=title,
                    axis=0,
                    subset=subset,
                    *args,
                    **kwargs
                )
                .summary(
                    func=func,
                    title=title,
                    axis=1,
                    subset=subset,
                    *args,
                    **kwargs
                )
            )
        else:
            agg = Aggregate(title, func, subset=subset,
                            axis=axis, *args, **kwargs)
            return self._add_summary(agg)
Add multiple summary rows or columns to the dataframe.

        Parameters
        ----------
        :param func: function to be used for a summary.
        :param titles: Title for this summary column.
        :param axis:
            Same as numpy and pandas axis argument. A value of None will cause
            the summary to be applied to both rows and columns.
        :param args: Positional arguments passed to all the functions.
        :param kwargs: Keyword arguments passed to all the functions.

        The results of summary can be chained together.