pandas much slower than numpy?

Question

The code below suggests that pandas may be much slower than numpy, at least in the specifi case of the function clip(). What is surprising is that making a roundtrip from pa

Answer 1

In master/0.13 (release very shortly), this is much faster (still slightly slower that native numpy because of handling of alignment/dtype/nans).

In 0.12 it was applying per column, so this was a relatively expensive operation.

In [4]: arr = np.random.randn(1000, 1000)

In [5]: df=pd.DataFrame(arr)

In [6]: %timeit np.clip(arr, 0, None)
100 loops, best of 3: 6.62 ms per loop

In [7]: %timeit df.clip_lower(0)
100 loops, best of 3: 12.9 ms per loop