pandas.CategoricalIndex#
- class pandas.CategoricalIndex(data=None, categories=None, ordered=None, dtype=None, copy=False, name=None)[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
- dataarray-like (1-dimensional)
The values of the categorical. If categories are given, values not in categories will be replaced with NaN.
- categoriesindex-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.
- orderedbool, 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.
- dtypeCategoricalDtype or “category”, optional
If
CategoricalDtype
, cannot be used together with categories or ordered.- copybool, default False
Make a copy of input ndarray.
- nameobject, 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')
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')
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') >>> ci.min() 'c'
Attributes
The category codes of this categorical.
The categories of this categorical.
Whether the categories have an ordered relationship.
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 an input mapping or function.