pyspark.pandas.Series.cat.rename_categories¶
- 
cat.rename_categories(new_categories: Union[list, dict, Callable], inplace: bool = False) → Optional[ps.Series]¶
- Rename categories. - Parameters
- new_categorieslist-like, dict-like or callable
- New categories which will replace old categories. - list-like: all items must be unique and the number of items in the new categories must match the existing number of categories. 
- dict-like: specifies a mapping from old categories to new. Categories not contained in the mapping are passed through and extra categories in the mapping are ignored. 
- callable : a callable that is called on all items in the old categories and whose return values comprise the new categories. 
 
- inplacebool, default False
- Whether or not to rename the categories inplace or return a copy of this categorical with renamed categories. - Deprecated since version 3.2.0. 
 
- Returns
- catSeries or None
- Categorical with removed categories or None if - inplace=True.
 
- Raises
- ValueError
- If new categories are list-like and do not have the same number of items than the current categories or do not validate as categories 
 
 - See also - reorder_categories
- Reorder 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 - >>> s = ps.Series(["a", "a", "b"], dtype="category") >>> s.cat.rename_categories([0, 1]) 0 0 1 0 2 1 dtype: category Categories (2, int64): [0, 1] - For dict-like - new_categories, extra keys are ignored and categories not in the dictionary are passed through- >>> s.cat.rename_categories({'a': 'A', 'c': 'C'}) 0 A 1 A 2 b dtype: category Categories (2, object): ['A', 'b'] - You may also provide a callable to create the new categories - >>> s.cat.rename_categories(lambda x: x.upper()) 0 A 1 A 2 B dtype: category Categories (2, object): ['A', 'B']