pandas.Categorical.remove_unused_categories#

Categorical.remove_unused_categories()[source]#

Remove categories which are not used.

This method is useful when working with datasets that undergo dynamic changes where categories may no longer be relevant, allowing to maintain a clean, efficient data structure.

Returns:

Categorical: Categorical with unused categories dropped.

See also

rename_categories: Rename categories.
reorder_categories: Reorder categories.
add_categories: Add new categories.
remove_categories: Remove the specified categories.
set_categories: Set the categories to the specified ones.

Examples

>>> c = pd.Categorical(["a", "c", "b", "c", "d"])
>>> c
['a', 'c', 'b', 'c', 'd']
Categories (4, object): ['a', 'b', 'c', 'd']

>>> c[2] = "a"
>>> c[4] = "c"
>>> c
['a', 'c', 'a', 'c', 'c']
Categories (4, object): ['a', 'b', 'c', 'd']

>>> c.remove_unused_categories()
['a', 'c', 'a', 'c', 'c']
Categories (2, object): ['a', 'c']