On 6/13/12 5:11 PM, Wes McKinney wrote: > And retrieving group indicies/summing: > > In [8]: %timeit arr=='a' > 1000 loops, best of 3: 1.52 ms per loop > In [10]: vals = np.random.randn(1000000) > In [20]: inds = [arr==x for x in lets] > In [23]: %timeit for ind in inds: vals[ind].sum() > 10 loops, best of 3: 48.3 ms per loop > (FYI you're comparing an O(NK) algorithm with an O(N) algorithm for small K)
I am not familiar with the details of your groupby implementation (evidently!), consider me appropriately chastised. Bryan _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
