pandas.Index.reindex

Index.reindex(target, method=None, level=None, limit=None, tolerance=None)[source]

Create index with target’s values.

Parameters:

target:an iterable

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

• nearest: use the NEAREST index value if no exact match. Tied distances are broken by preferring the larger index value.

level:int, optional

Level of multiindex.

limit:int, optional

Maximum number of consecutive labels in target to match for inexact matches.

tolerance:int or float, optional

Maximum distance between original and new labels for inexact matches. The values of the index at the matching locations must satisfy the equation abs(index[indexer] - target) <= tolerance.

Tolerance may be a scalar value, which applies the same tolerance to all values, or list-like, which applies variable tolerance per element. List-like includes list, tuple, array, Series, and must be the same size as the index and its dtype must exactly match the index’s type.

Returns:

new_index:pd.Index

Resulting index.

indexer:np.ndarray[np.intp] or None

Indices of output values in original index.

Raises:

TypeError

If method passed along with level.

ValueError

If non-unique multi-index

ValueError

If non-unique index and method or limit passed.

See also

Series.reindex

Conform Series to new index with optional filling logic.

DataFrame.reindex

Conform DataFrame to new index with optional filling logic.

Examples

>>> idx = pd.Index(['car', 'bike', 'train', 'tractor'])
>>> idx
Index(['car', 'bike', 'train', 'tractor'], dtype='object')
>>> idx.reindex(['car', 'bike'])
(Index(['car', 'bike'], dtype='object'), array([0, 1]))