python - Vectorized way of finding position of one column value in another in Pandas -


basically following code returns position of character in column 'a' in string (in case '}jklmnopqr'). in example, column 'b' has same value in rows, have different values.

is there vectorized way this?

frame = pd.dataframe({'a' : ['l', '}', 'p']}) frame['b']='}jklmnopqr' frame['c'] = frame.apply(lambda row: row.b.find(row.a), axis=1) frame            b         c 0  l    }jklmnopqr    3  1  }    }jklmnopqr    0  2  p    }jklmnopqr    7

not vectorized faster solution using zip:

lframe1 = pd.concat([frame]*1000) lframe2 = pd.concat([frame]*1000)  %timeit lframe1['c'] = lframe1.apply(lambda row: row.b.find(row.a), axis=1) # 10 loops, best of 3: 77.7 ms per loop  %timeit lframe2['c'] = [b.find(a) a, b in zip(lframe2.a, lframe2.b)] # 1000 loops, best of 3: 1.4 ms per loop  lframe1.c.eq(lframe2.c).all() # true

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