Classe « CategoricalIndex »

Méthode pandas.CategoricalIndex.get_indexer

Signature de la méthode get_indexer

def get_indexer(self, target, method=None, limit=None, tolerance=None) 

Description

get_indexer.__doc__

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 : CategoricalIndex
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.
limit : int, optional
    Maximum number of consecutive labels in ``target`` to match for
    inexact matches.
tolerance : 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
-------
indexer : ndarray of int
    Integers from 0 to n - 1 indicating that the index at these
    positions matches the corresponding target values. Missing values
    in the target are marked by -1.

Examples
--------
>>> index = pd.Index(['c', 'a', 'b'])
>>> index.get_indexer(['a', 'b', 'x'])
array([ 1,  2, -1])

Notice that the return value is an array of locations in ``index``
and ``x`` is marked by -1, as it is not in ``index``.