MultiIndex.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True) [source] Returns object containing counts of unique values. The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by default. Parameters: normalize : boolean, default False If True then the object returned will contain the relative frequencies of the unique values. sort : boolean, default True Sort by values ascen

MultiIndex.values

MultiIndex.unique() [source] Return Index of unique values in the object. Significantly faster than numpy.unique. Includes NA values. The order of the original is preserved. Returns: uniques : Index

MultiIndex.union(other) [source] Form the union of two MultiIndex objects, sorting if possible Parameters: other : MultiIndex or array / Index of tuples Returns: Index >>> index.union(index2)

MultiIndex.truncate(before=None, after=None) [source] Slice index between two labels / tuples, return new MultiIndex Parameters: before : label or tuple, can be partial. Default None None defaults to start after : label or tuple, can be partial. Default None None defaults to end Returns: truncated : MultiIndex

MultiIndex.transpose(*args, **kwargs) [source] return the transpose, which is by definition self

MultiIndex.to_series(**kwargs) [source] Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index Returns: Series : dtype will be based on the type of the Index values.

MultiIndex.to_native_types(slicer=None, **kwargs) [source] slice and dice then format

MultiIndex.to_hierarchical(n_repeat, n_shuffle=1) [source] Return a MultiIndex reshaped to conform to the shapes given by n_repeat and n_shuffle. Useful to replicate and rearrange a MultiIndex for combination with another Index with n_repeat items. Parameters: n_repeat : int Number of times to repeat the labels on self n_shuffle : int Controls the reordering of the labels. If the result is going to be an inner level in a MultiIndex, n_shuffle will need to be greater than one. The size o

MultiIndex.to_datetime(dayfirst=False) [source] DEPRECATED: use pandas.to_datetime() instead. For an Index containing strings or datetime.datetime objects, attempt conversion to DatetimeIndex