You could do pd.DataFrame(df[col].values.tolist()) - is much faster ~500x
In [820]: pd.DataFrame(df[0].values.tolist())
Out[820]:
0 1 2
0 8 10 12
1 7 9 11
In [821]: pd.concat([pd.DataFrame(df[0].values.tolist()), df[1]], axis=1)
Out[821]:
0 1 2 1
0 8 10 12 A
1 7 9 11 B
Timings
Medium
In [828]: df.shape
Out[828]: (20000, 2)
In [829]: %timeit pd.DataFrame(df[0].values.tolist())
100 loops, best of 3: 15 ms per loop
In [830]: %timeit df[0].apply(pd.Series)
1 loop, best of 3: 4.06 s per loop
Large
In [832]: df.shape
Out[832]: (200000, 2)
In [833]: %timeit pd.DataFrame(df[0].values.tolist())
10 loops, best of 3: 161 ms per loop
In [834]: %timeit df[0].apply(pd.Series)
1 loop, best of 3: 40.9 s per loop
