MultiIndex.set_labels(labels, level=None, inplace=False, verify_integrity=True) [source] Set new labels on MultiIndex. Defaults to returning new index. Parameters: labels : sequence or list of sequence new labels to apply level : int, level name, or sequence of int/level names (default None) level(s) to set (None for all levels) inplace : bool if True, mutates in place verify_integrity : bool (default True) if True, checks that levels and labels are compatible Returns: new index

MultiIndex.searchsorted(key, side='left', sorter=None) [source] Find indices where elements should be inserted to maintain order. Find the indices into a sorted IndexOpsMixin self such that, if the corresponding elements in v were inserted before the indices, the order of self would be preserved. Parameters: key : array_like Values to insert into self. side : {?left?, ?right?}, optional If ?left?, the index of the first suitable location found is given. If ?right?, return the last such

MultiIndex.reshape(*args, **kwargs) [source] NOT IMPLEMENTED: do not call this method, as reshaping is not supported for Index objects and will raise an error. Reshape an Index.

MultiIndex.rename(names, level=None, inplace=False) [source] Set new names on index. Defaults to returning new index. Parameters: names : str or sequence name(s) to set level : int, level name, or sequence of int/level names (default None) If the index is a MultiIndex (hierarchical), level(s) to set (None for all levels). Otherwise level must be None inplace : bool if True, mutates in place Returns: new index (of same type and class...etc) [if inplace, returns None] Examples >&

MultiIndex.reorder_levels(order) [source] Rearrange levels using input order. May not drop or duplicate levels

MultiIndex.repeat(n, *args, **kwargs) [source]

MultiIndex.ravel(order='C') [source] return an ndarray of the flattened values of the underlying data See also numpy.ndarray.ravel

MultiIndex.reindex(target, method=None, level=None, limit=None, tolerance=None) [source] Create index with target?s values (move/add/delete values as necessary) Returns: new_index : pd.MultiIndex Resulting index indexer : np.ndarray or None Indices of output values in original index

MultiIndex.nunique(dropna=True) [source] Return number of unique elements in the object. Excludes NA values by default. Parameters: dropna : boolean, default True Don?t include NaN in the count. Returns: nunique : int

MultiIndex.order(return_indexer=False, ascending=True) [source] Return sorted copy of Index DEPRECATED: use Index.sort_values()