pandas.CategoricalIndex.reorder_categories

CategoricalIndex.reorder_categories(*args, **kwargs)[source]

Reorder categories as specified in new_categories.

new_categories need to include all old categories and no new category items.

Parameters:

new_categories:Index-like

The categories in new order.

ordered:bool, optional

Whether or not the categorical is treated as a ordered categorical. If not given, do not change the ordered information.

Returns:

Categorical

Categorical with reordered categories.

Raises:

ValueError

If the new categories do not contain all old category items or any new ones

See also

rename_categories

Rename categories.

add_categories

Add new categories.

remove_categories

Remove the specified categories.

remove_unused_categories

Remove categories which are not used.

set_categories

Set the categories to the specified ones.

Examples

For pandas.Series:

>>> ser = pd.Series(['a', 'b', 'c', 'a'], dtype='category')
>>> ser = ser.cat.reorder_categories(['c', 'b', 'a'], ordered=True)
>>> ser
0   a
1   b
2   c
3   a
dtype: category
Categories (3, object): ['c' < 'b' < 'a']

>>> ser.sort_values()
2   c
1   b
0   a
3   a
dtype: category
Categories (3, object): ['c' < 'b' < 'a']

For pandas.CategoricalIndex:

>>> ci = pd.CategoricalIndex(['a', 'b', 'c', 'a'])
>>> ci
CategoricalIndex(['a', 'b', 'c', 'a'], categories=['a', 'b', 'c'],
                 ordered=False, dtype='category')
>>> ci.reorder_categories(['c', 'b', 'a'], ordered=True)
CategoricalIndex(['a', 'b', 'c', 'a'], categories=['c', 'b', 'a'],
                 ordered=True, dtype='category')