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


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


index col1
1 a
2 e
3 b

df1 (after):

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


Use Series.isin with converting mask to integers:

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


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

Answered By – jezrael

Answer Checked By – Timothy Miller (BugsFixing Admin)

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