Are the values ​of column xy of df1 also present in column zy of df2? [duplicate]

Question

I have two dataframes and I want to check which value of df1 in col1 also occurs in df2 in col1. If it occurs: a 1 in col2_new, otherwise a 0. Is it best to do this using a list? So column of df1 converted into list and then a loop over the column of the other data frame or is there a more elegant way?

df1 (before):

index	col1
1	a
2	b
3	c

df2:

index	col1
1	a
2	e
3	b

df1 (after):

index	col1	col2_new
1	a	1
2	b	1
3	c	0

Answer 1

Use Series.isin with converting mask to integers:

df1['col2_new'] = df1['col1'].isin(df2['col1']).astype(int)

Or:

df1['col2_new'] = np.where(df1['col1'].isin(df2['col1']), 1, 0)