def append_to_multiple(self, d, value, selector, data_columns=None,<EOL>axes=None, dropna=False, **kwargs):
if axes is not None:<EOL><INDENT>raise TypeError("<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>")<EOL><DEDENT>if not isinstance(d, dict):<EOL><INDENT>raise ValueError(<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>)<EOL><DEDENT>if selector not in d:<EOL><INDENT>raise ValueError(<EOL>"<STR_LIT>"<EOL>)<EOL><DEDENT>axis = list(set(range(value.ndim)) - set(_AXES_MAP[type(value)]))[<NUM_LIT:0>]<EOL>remain_key = None<EOL>remain_values = []<EOL>for k, v in d.items():<EOL><INDENT>if v is None:<EOL><INDENT>if remain_key is not None:<EOL><INDENT>raise ValueError(<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>)<EOL><DEDENT>remain_key = k<EOL><DEDENT>else:<EOL><INDENT>remain_values.extend(v)<EOL><DEDENT><DEDENT>if remain_key is not None:<EOL><INDENT>ordered = value.axes[axis]<EOL>ordd = ordered.difference(Index(remain_values))<EOL>ordd = sorted(ordered.get_indexer(ordd))<EOL>d[remain_key] = ordered.take(ordd)<EOL><DEDENT>if data_columns is None:<EOL><INDENT>data_columns = d[selector]<EOL><DEDENT>if dropna:<EOL><INDENT>idxs = (value[cols].dropna(how='<STR_LIT:all>').index for cols in d.values())<EOL>valid_index = next(idxs)<EOL>for index in idxs:<EOL><INDENT>valid_index = valid_index.intersection(index)<EOL><DEDENT>value = value.loc[valid_index]<EOL><DEDENT>for k, v in d.items():<EOL><INDENT>dc = data_columns if k == selector else None<EOL>val = value.reindex(v, axis=axis)<EOL>self.append(k, val, data_columns=dc, **kwargs)<EOL><DEDENT>
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