map(self, mapper)

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 a ~pandas.CategoricalIndex which has the same order property as the original, otherwise an ~pandas.Index is returned.

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.

Parameters

mapper : function, dict, or Series

Mapping correspondence.

Returns

pandas.CategoricalIndex or pandas.Index

Mapped index.

Map values using input an input mapping or function.

See Also

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`.

Examples

This example is valid syntax, but we were not able to check execution

>>> idx = pd.CategoricalIndex(['a', 'b', 'c'])
... idx
CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'],
                  ordered=False, dtype='category')

This example is valid syntax, but we were not able to check execution

>>> idx.map(lambda x: x.upper())
CategoricalIndex(['A', 'B', 'C'], categories=['A', 'B', 'C'],
                 ordered=False, dtype='category')

This example is valid syntax, but we were not able to check execution

>>> 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:

This example is valid syntax, but we were not able to check execution

>>> idx = pd.CategoricalIndex(['a', 'b', 'c'], ordered=True)
... idx
CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'],
                 ordered=True, dtype='category')

This example is valid syntax, but we were not able to check execution

>>> 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 ~pandas.Index is returned:

This example is valid syntax, but we were not able to check execution

>>> idx.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 :

This example is valid syntax, but we were not able to check execution

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

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

pandas.core.arrays.categorical.Categorical.map

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File: /pandas/core/indexes/category.py#507
type: <class 'function'>
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