matching entries of a dataframe column with a list and creating a new column based on match

Question

I am looking for a pythonic way to handle this dataframe column and list matching problem:

Here is my dataframe:

Now, I have a list of roll_no.:

     roll_no_matching = [3,5]

I want to have a matching done between this list and column B aka roll_no. and insert a new column which will have a 0 for no match and 1 for match. eg the resulting dataframe will look like:

I know how to match two dataframes based on any index column and possibly merge some columns from the two dataframes but, I am not sure how to create a new column. Any guidance here is highly appreciated.

Answer 1

Use Series.isin for test membership with convert mask to integers by Series.astype :

df['Merit_list'] = df['roll No.'].isin(roll_no_matching).astype(int)

Or Series.view :

df['Merit_list'] = df['roll No.'].isin(roll_no_matching).view('i1')

Or by numpy.where :

df['Merit_list'] = np.where(df['roll No.'].isin(roll_no_matching), 1, 0)