My understanding is that this question is better answered over in this post.

But briefly, the answer to the OP with this method is simply:

s1 = pd.merge(df1, df2, how='inner', on=['user_id'])

Which gives s1 with 5 columns: user_id and the other two columns from each of df1 and df2.