Append to multiple tables

        Parameters
        ----------
        d : a dict of table_name to table_columns, None is acceptable as the
            values of one node (this will get all the remaining columns)
        value : a pandas object
        selector : a string that designates the indexable table; all of its
            columns will be designed as data_columns, unless data_columns is
            passed, in which case these are used
        data_columns : list of columns to create as data columns, or True to
            use all columns
        dropna : if evaluates to True, drop rows from all tables if any single
                 row in each table has all NaN. Default False.

        Notes
        -----
        axes parameter is currently not accepted

def append_to_multiple(self, d, value, selector, data_columns=None,
                           axes=None, dropna=False, **kwargs):
        """
        Append to multiple tables

        Parameters
        ----------
        d : a dict of table_name to table_columns, None is acceptable as the
            values of one node (this will get all the remaining columns)
        value : a pandas object
        selector : a string that designates the indexable table; all of its
            columns will be designed as data_columns, unless data_columns is
            passed, in which case these are used
        data_columns : list of columns to create as data columns, or True to
            use all columns
        dropna : if evaluates to True, drop rows from all tables if any single
                 row in each table has all NaN. Default False.

        Notes
        -----
        axes parameter is currently not accepted

        """
        if axes is not None:
            raise TypeError("axes is currently not accepted as a parameter to"
                            " append_to_multiple; you can create the "
                            "tables independently instead")

        if not isinstance(d, dict):
            raise ValueError(
                "append_to_multiple must have a dictionary specified as the "
                "way to split the value"
            )

        if selector not in d:
            raise ValueError(
                "append_to_multiple requires a selector that is in passed dict"
            )

        # figure out the splitting axis (the non_index_axis)
        axis = list(set(range(value.ndim)) - set(_AXES_MAP[type(value)]))[0]

        # figure out how to split the value
        remain_key = None
        remain_values = []
        for k, v in d.items():
            if v is None:
                if remain_key is not None:
                    raise ValueError(
                        "append_to_multiple can only have one value in d that "
                        "is None"
                    )
                remain_key = k
            else:
                remain_values.extend(v)
        if remain_key is not None:
            ordered = value.axes[axis]
            ordd = ordered.difference(Index(remain_values))
            ordd = sorted(ordered.get_indexer(ordd))
            d[remain_key] = ordered.take(ordd)

        # data_columns
        if data_columns is None:
            data_columns = d[selector]

        # ensure rows are synchronized across the tables
        if dropna:
            idxs = (value[cols].dropna(how='all').index for cols in d.values())
            valid_index = next(idxs)
            for index in idxs:
                valid_index = valid_index.intersection(index)
            value = value.loc[valid_index]

        # append
        for k, v in d.items():
            dc = data_columns if k == selector else None

            # compute the val
            val = value.reindex(v, axis=axis)

            self.append(k, val, data_columns=dc, **kwargs)