reverse the order of CategoricalDtype in Pandas

Question

I have an ordered categorical variable in my dataframe like the following:

CategoricalDtype(categories=['UNDER $1 000', '$1 000 TO 2 999', '$3 000 TO 3 999', 
                              '$90000 - $109999', '$110000 OR OVER', 'REFUSED'], 
                               ordered=True)

For CategoricalIndex in a dataframe I know I can do the following:

df.sort_index(ascending=False, inplace=True)

I tried the method I find here for the CategoricalDtype object:

from pandas import Categorical
Categorical.sort(ascending=False)

but it doesn't work and returned:

AttributeError: type object 'Categorical' has no attribute 'sort'.

Thus, I wonder if there is an easy way to reverse the order for CategoricalDtype with Pandas.

Answer 1

You can use list slicing / NumPy array syntax, i.e. [::-1], to reverse the order. This is natural because dtype.categories returns a pd.Index object, which has an underlying NumPy array.

from pandas.api.types import CategoricalDtype

dtype = CategoricalDtype(categories=['UNDER $1 000', '$1 000 TO 2 999', '$3 000 TO 3 999',
                                     '$90000 - $109999', '$110000 OR OVER', 'REFUSED'],
                         ordered=True)

dtype_reversed = CategoricalDtype(categories=dtype.categories[::-1], ordered=True)

# CategoricalDtype(categories=['REFUSED', '$110000 OR OVER', '$90000 - $109999',
#                   '$3 000 TO 3 999', '$1 000 TO 2 999', 'UNDER $1 000'],
#                  ordered=True)