Pandas fillna throws ValueError: fill value must be in categories

Use Series.cat.add_categories for add categories first:

AM_train['product_category_2'] = AM_train['product_category_2'].cat.add_categories('Unknown')AM_train['product_category_2'].fillna('Unknown', inplace =True) AM_train['city_development_index'] = AM_train['city_development_index'].cat.add_categories('Missing')AM_train['city_development_index'].fillna('Missing', inplace =True)

Sample:

AM_train = pd.DataFrame({'product_category_2': pd.Categorical(['a','b',np.nan])})AM_train['product_category_2'] = AM_train['product_category_2'].cat.add_categories('Unknown')AM_train['product_category_2'].fillna('Unknown', inplace =True) print (AM_train)  product_category_20                  a1                  b2            Unknown

I was getting the same error in a data frame while trying to get rid of all the NaNs.
I did not look too much into it, but substituting .fillna() for .replace(np.nan, value) did the trick.
Use with caution, since I am not sure np.nan catches all the values that are interpreted as NaN

Load the original dataset without inplace=True, always before running the fillna secondtime.

This problem arises because, you run the code twice, so fillna cannot be performed.