MultiIndex.tolist()

MultiIndex.tolist() [source] return a list of the Index values

MultiIndex.T

MultiIndex.T return the transpose, which is by definition self

MultiIndex.sym_diff()

MultiIndex.sym_diff(*args, **kwargs) [source]

MultiIndex.take()

MultiIndex.take(indices, axis=0, allow_fill=True, fill_value=None, **kwargs) [source] return a new %(klass)s of the values selected by the indices For internal compatibility with numpy arrays. Parameters: indices : list Indices to be taken axis : int, optional The axis over which to select values, always 0. allow_fill : bool, default True fill_value : bool, default None If allow_fill=True and fill_value is not None, indices specified by -1 is regarded as NA. If Index doesn?t hold NA,

MultiIndex.symmetric_difference()

MultiIndex.symmetric_difference(other, result_name=None) [source] Compute the symmetric difference of two Index objects. It?s sorted if sorting is possible. Parameters: other : Index or array-like result_name : str Returns: symmetric_difference : Index Notes symmetric_difference contains elements that appear in either idx1 or idx2 but not both. Equivalent to the Index created by idx1.difference(idx2) | idx2.difference(idx1) with duplicates dropped. Examples >>> idx1 = Index([1,

MultiIndex.swaplevel()

MultiIndex.swaplevel(i=-2, j=-1) [source] Swap level i with level j. Do not change the ordering of anything Parameters: i, j : int, string (can be mixed) Level of index to be swapped. Can pass level name as string. Returns: swapped : MultiIndex Changed in version 0.18.1: The indexes i and j are now optional, and default to the two innermost levels of the index.

MultiIndex.summary()

MultiIndex.summary(name=None) [source]

MultiIndex.str()

MultiIndex.str() [source] Vectorized string functions for Series and Index. NAs stay NA unless handled otherwise by a particular method. Patterned after Python?s string methods, with some inspiration from R?s stringr package. Examples >>> s.str.split('_') >>> s.str.replace('_', '')

MultiIndex.strides

MultiIndex.strides return the strides of the underlying data

MultiIndex.sort_values()

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