MultiIndex.get_level_values(level) [source] Return vector of label values for requested level, equal to the length of the index Parameters: level : int or level name Returns: values : ndarray

MultiIndex.get_indexer_for(target, **kwargs) [source] guaranteed return of an indexer even when non-unique

MultiIndex.get_indexer(target, method=None, limit=None, tolerance=None) [source] Compute indexer and mask for new index given the current index. The indexer should be then used as an input to ndarray.take to align the current data to the new index. The mask determines whether labels are found or not in the current index Parameters: target : MultiIndex or Index (of tuples) method : {?pad?, ?ffill?, ?backfill?, ?bfill?} pad / ffill: propagate LAST valid observation forward to next valid bac

MultiIndex.get_duplicates() [source]

classmethod MultiIndex.from_product(iterables, sortorder=None, names=None) [source] Make a MultiIndex from the cartesian product of multiple iterables Parameters: iterables : list / sequence of iterables Each iterable has unique labels for each level of the index. sortorder : int or None Level of sortedness (must be lexicographically sorted by that level). names : list / sequence of strings or None Names for the levels in the index. Returns: index : MultiIndex See also MultiInd

classmethod MultiIndex.from_tuples(tuples, sortorder=None, names=None) [source] Convert list of tuples to MultiIndex Parameters: tuples : list / sequence of tuple-likes Each tuple is the index of one row/column. sortorder : int or None Level of sortedness (must be lexicographically sorted by that level) Returns: index : MultiIndex See also MultiIndex.from_arrays Convert list of arrays to MultiIndex MultiIndex.from_product Make a MultiIndex from cartesian product of iterables

classmethod MultiIndex.from_arrays(arrays, sortorder=None, names=None) [source] Convert arrays to MultiIndex Parameters: arrays : list / sequence of array-likes Each array-like gives one level?s value for each data point. len(arrays) is the number of levels. sortorder : int or None Level of sortedness (must be lexicographically sorted by that level) Returns: index : MultiIndex See also MultiIndex.from_tuples Convert list of tuples to MultiIndex MultiIndex.from_product Make a

MultiIndex.format(space=2, sparsify=None, adjoin=True, names=False, na_rep=None, formatter=None) [source]

MultiIndex.flags

MultiIndex.fillna(value=None, downcast=None) [source] Fill NA/NaN values with the specified value Parameters: value : scalar Scalar value to use to fill holes (e.g. 0). This value cannot be a list-likes. downcast : dict, default is None a dict of item->dtype of what to downcast if possible, or the string ?infer? which will try to downcast to an appropriate equal type (e.g. float64 to int64 if possible) Returns: filled : %(klass)s