For each row in a dataframe, return a list of columns that are NaN. But not all columns, only those in a given list

Question

Looking at building out some logging of errors and trying to catch null values in specific columns.
Essentially, I want to go from a dataframe and list of columns, to then output a dataframe with a column containing which of those columns from the list are null for each row. Note, I will also be doing this for negative values etc.
Example:

columns_list = ['A','B','D']

Date	A	B	C	D
2022-01-01	1	22	1231	-121
2022-01-02	11	NaN	NaN	NaN
2022-01-03	NaN	52	12	0
2022-01-04	11	27	NaN	3434

The following code will give the following output but I want to be able to use columns_list to not have column C being returned in X:

df['X']= df.apply(lambda x: ','.join(x[x.isnull()].index), axis=1)

Date	A	B	C	D	X
2022-01-02	11	NaN	NaN	NaN	B,C,D
2022-01-03	NaN	52	12	0	A
2022-01-04	11	27	NaN	3434	C

Thanking you all in advance!

Answer 1

Just subset your columns:

df['X']= df[columns_list].apply(lambda x: ','.join(x[x.isnull()].index), axis=1)