Replace value that does not equal specific values

I've tried looking at other similar questions but haven't found an adequate answer for my needs.

I have a data frame with a column answer where respondents can answer yes, no, maybe, or some other response. The some other response is free text and for my purposes, I just need to categorize it as other but I can't quite figure out how to replace a value in a pandas dataframe that does not equal a few different values (I've seen answers for replacing values that do not equal one value, but I don't want it to effect the rows with yes, no, and maybe).

Sample data frame is below, any help is appreciated.

id | answer |
1  | Yes    |
2  | Maybe  |
3  | No     |
4  | idk    |
5  | wtf    |
6  | wth    |

Use pandas.Series.where with your condition

df['new_answer'] = df['answer'].where(df['answer'].isin(['Yes', 'No', 'Maybe']), 'other')
   id answer new_answer
0   1    Yes        Yes
1   2  Maybe      Maybe
2   3     No         No
3   4    idk      other
4   5    wtf      other
5   6    wth      other

Another option is to use categorical data :

cats = pd.Categorical(df["answer"], categories=["Yes", "No", "Maybe", "other"])
df["answer"] = pd.Series(cats).fillna("other")

Output :

print(df)
   id answer
0   1    Yes
1   2  Maybe
2   3     No
3   4  other
4   5  other
5   6  other