pandas.Index.is_categorical
- 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
© 2008–2021, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/api/pandas.Index.is_categorical.html