pandas.CategoricalIndex.map — pandas 0.24.0rc1 documentation (original) (raw)

CategoricalIndex. map(mapper)[source]¶

Map values using input correspondence (a dict, Series, or function).

Maps the values (their categories, not the codes) of the index to new categories. If the mapping correspondence is one-to-one the result is aCategoricalIndex which has the same order property as the original, otherwise an Index is returned.

If a dict or Series is used any unmapped category is mapped to NaN. Note that if this happens an Indexwill be returned.

Examples

idx = pd.CategoricalIndex(['a', 'b', 'c']) idx CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'], ordered=False, dtype='category') idx.map(lambda x: x.upper()) CategoricalIndex(['A', 'B', 'C'], categories=['A', 'B', 'C'], ordered=False, dtype='category') idx.map({'a': 'first', 'b': 'second', 'c': 'third'}) CategoricalIndex(['first', 'second', 'third'], categories=['first', 'second', 'third'], ordered=False, dtype='category')

If the mapping is one-to-one the ordering of the categories is preserved:

idx = pd.CategoricalIndex(['a', 'b', 'c'], ordered=True) idx CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'], ordered=True, dtype='category') idx.map({'a': 3, 'b': 2, 'c': 1}) CategoricalIndex([3, 2, 1], categories=[3, 2, 1], ordered=True, dtype='category')

If the mapping is not one-to-one an Index is returned:

idx.map({'a': 'first', 'b': 'second', 'c': 'first'}) Index(['first', 'second', 'first'], dtype='object')

If a dict is used, all unmapped categories are mapped to NaN and the result is an Index:

idx.map({'a': 'first', 'b': 'second'}) Index(['first', 'second', nan], dtype='object')