pandas.CategoricalIndex¶
-
class
pandas.
CategoricalIndex
[source]¶ Index based on an underlying
Categorical
.CategoricalIndex, like Categorical, can only take on a limited, and usually fixed, number of possible values (categories). Also, like Categorical, it might have an order, but numerical operations (additions, divisions, …) are not possible.
Parameters: data : array-like (1-dimensional)
The values of the categorical. If categories are given, values not in 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 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 the string “category”, optional
If
CategoricalDtype
, cannot be used together with categories or ordered.New in version 0.21.0.
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 categories and the values are not sortable.See also
Index
- The base pandas Index type.
Categorical
- A categorical array.
CategoricalDtype
- Type for categorical data.
Notes
See the user guide for more.
Examples
>>> pd.CategoricalIndex(['a', 'b', 'c', 'a', 'b', 'c']) CategoricalIndex(['a', 'b', 'c', 'a', 'b', 'c'], categories=['a', 'b', 'c'], ordered=False, dtype='category') # noqa
CategoricalIndex
can also be instantiated from aCategorical
:>>> 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') # noqa
Ordered
CategoricalIndex
can have a min and max value.>>> 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') # noqa >>> ci.min() 'c'
Attributes
codes categories ordered Methods
rename_categories
(*args, **kwargs)Rename categories. reorder_categories
(*args, **kwargs)Reorder categories as specified in new_categories. add_categories
(*args, **kwargs)Add new categories. remove_categories
(*args, **kwargs)Remove the specified categories. remove_unused_categories
(*args, **kwargs)Remove categories which are not used. set_categories
(*args, **kwargs)Set the categories to the specified new_categories. as_ordered
(*args, **kwargs)Set the Categorical to be ordered. as_unordered
(*args, **kwargs)Set the Categorical to be unordered. map
(mapper)Map values using input correspondence (a dict, Series, or function).