Index.get_indexer_non_unique(target) [source] return an indexer suitable for taking from a non unique index return the labels in the same order as the target, and return a missing indexer into the target (missing are marked as -1 in the indexer); target must be an iterable

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

Index.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. Parameters: target : Index method : {None, ?pad?/?ffill?, ?backfill?/?bfill?, ?nearest?}, optional default: exact matches only. pad / ffill: find the PREVIOUS index value if no exact match. backfill / bfill: use NEXT index value if no exact match ne

Index.get_duplicates() [source]

Index.format(name=False, formatter=None, **kwargs) [source] Render a string representation of the Index

Index.flags

Index.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

Index.factorize(sort=False, na_sentinel=-1) [source] Encode the object as an enumerated type or categorical variable Parameters: sort : boolean, default False Sort by values na_sentinel: int, default -1 Value to mark ?not found? Returns: labels : the indexer to the original array uniques : the unique Index

Index.equals(other) [source] Determines if two Index objects contain the same elements.

Index.duplicated(*args, **kwargs) [source] Return boolean np.ndarray denoting duplicate values Parameters: keep : {?first?, ?last?, False}, default ?first? first : Mark duplicates as True except for the first occurrence. last : Mark duplicates as True except for the last occurrence. False : Mark all duplicates as True. take_last : deprecated Returns: duplicated : np.ndarray