map(self, mapper)
Maps the categories to new categories. If the mapping correspondence is one-to-one the result is a ~pandas.Categorical
which has the same order property as the original, otherwise a ~pandas.Index
is returned. NaN values are unaffected.
If a :None:None:`dict` or ~pandas.Series
is used any unmapped category is mapped to NaN
. Note that if this happens an ~pandas.Index
will be returned.
Mapping correspondence.
Mapped categorical.
Map categories using an input mapping or function.
CategoricalIndex.map
Apply a mapping correspondence on a :None:class:`~pandas.CategoricalIndex`.
Index.map
Apply a mapping correspondence on an :None:class:`~pandas.Index`.
Series.apply
Apply more complex functions on a :None:class:`~pandas.Series`.
Series.map
Apply a mapping correspondence on a :None:class:`~pandas.Series`.
>>> cat = pd.Categorical(['a', 'b', 'c'])This example is valid syntax, but we were not able to check execution
... cat ['a', 'b', 'c'] Categories (3, object): ['a', 'b', 'c']
>>> cat.map(lambda x: x.upper()) ['A', 'B', 'C'] Categories (3, object): ['A', 'B', 'C']This example is valid syntax, but we were not able to check execution
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'third'}) ['first', 'second', 'third'] Categories (3, object): ['first', 'second', 'third']
If the mapping is one-to-one the ordering of the categories is preserved:
This example is valid syntax, but we were not able to check execution>>> cat = pd.Categorical(['a', 'b', 'c'], ordered=True)This example is valid syntax, but we were not able to check execution
... cat ['a', 'b', 'c'] Categories (3, object): ['a' < 'b' < 'c']
>>> cat.map({'a': 3, 'b': 2, 'c': 1}) [3, 2, 1] Categories (3, int64): [3 < 2 < 1]
If the mapping is not one-to-one an ~pandas.Index
is returned:
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'first'}) Index(['first', 'second', 'first'], dtype='object')
If a :None:None:`dict` is used, all unmapped categories are mapped to NaN
and the result is an ~pandas.Index
:
>>> cat.map({'a': 'first', 'b': 'second'}) Index(['first', 'second', nan], dtype='object')See :
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