pandas.Series.cat.reorder_categories#

Series.cat.reorder_categories(*args,**kwargs)[source]#

Reorder categories as specified in new_categories.

new_categories need to include all old categories and no new categoryitems.

Parameters:

new_categoriesIndex-like

The categories in new order.

orderedbool, 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 anynew 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

Forpandas.Series:

>>>ser=pd.Series(['a','b','c','a'],dtype='category')>>>ser=ser.cat.reorder_categories(['c','b','a'],ordered=True)>>>ser0   a1   b2   c3   adtype: categoryCategories (3, object): ['c' < 'b' < 'a']

>>>ser.sort_values()2   c1   b0   a3   adtype: categoryCategories (3, object): ['c' < 'b' < 'a']

Forpandas.CategoricalIndex:

>>>ci=pd.CategoricalIndex(['a','b','c','a'])>>>ciCategoricalIndex(['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')