Attributes

codes :

categories :

ordered :

CategoricalIndex, like Categorical, can only take on a limited, and usually fixed, number of possible values (:None:None:`categories`). Also, like Categorical, it might have an order, but numerical operations (additions, divisions, ...) are not possible.

Methods

Notes

See the :None:None:`user guide <https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#categoricalindex>` for more.

Parameters

data : array-like (1-dimensional)

The values of the categorical. If :None:None:`categories` are given, values not in :None:None:`categories` will be replaced with NaN.

categories : index-like, optional

The categories for the categorical. Items need to be unique. If the categories are not given here (and also not in dtype ), they will be inferred from the :None:None:`data`.

ordered : bool, optional

Whether or not this categorical is treated as an ordered categorical. If not given here or in dtype , the resulting categorical will be unordered.

dtype : CategoricalDtype or "category", optional

If CategoricalDtype , cannot be used together with :None:None:`categories` or :None:None:`ordered`.

copy : bool, default False

Make a copy of input ndarray.

name : object, optional

Name to be stored in the index.

Raises

ValueError

If the categories do not validate.

TypeError

If an explicit ordered=True is given but no :None:None:`categories` and the :None:None:`values` are not sortable.

Index based on an underlying Categorical .

See Also

Categorical

A categorical array.

CategoricalDtype

Type for categorical data.

Index

The base pandas Index type.

Examples

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

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

CategoricalIndex can also be instantiated from a Categorical :

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

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

Ordered CategoricalIndex can have a min and max value.

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

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

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

>>> ci.min()
'c'

See :

Back References

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

pandas.core.arrays.categorical.Categorical pandas.core.dtypes.concat.union_categoricals pandas.core.indexes.base.Index.is_categorical pandas.core.indexes.base.Index

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