pandas.Index.is_categorical#

final Index.is_categorical()[source]#

Check if the Index holds categorical data.

Returns

bool: True if the Index is categorical.

See also

CategoricalIndex: Index for categorical data.
is_boolean: Check if the Index only consists of booleans.
is_integer: Check if the Index only consists of integers.
is_floating: Check if the Index is a floating type.
is_numeric: Check if the Index only consists of numeric data.
is_object: Check if the Index is of the object dtype.
is_interval: Check if the Index holds Interval objects.
is_mixed: Check if the Index holds data with mixed data types.

Examples

>>> idx = pd.Index(["Watermelon", "Orange", "Apple",
...                 "Watermelon"]).astype("category")
>>> idx.is_categorical()
True

>>> idx = pd.Index([1, 3, 5, 7])
>>> idx.is_categorical()
False

>>> s = pd.Series(["Peter", "Victor", "Elisabeth", "Mar"])
>>> s
0        Peter
1       Victor
2    Elisabeth
3          Mar
dtype: object
>>> s.index.is_categorical()
False

pandas.Index.is_boolean

pandas.Index.is_floating