John, Thanks for the quick reply. Unfortunately, no, they're not indexed like that. The first columns are actually floating-point date numbers from matplotlib.dates.date2num. Looks like this is just going to be painful... Thanks for the tip though. That'll definitely be useful elsewhere. -paul From: numpy-discussion-bounces@scipy.org [mailto:numpy-discussion-bounces@scipy.org] On Behalf Of John Salvatier Sent: Wednesday, August 04, 2010 5:34 PM To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Quick array value assignment based on common values Are they numbered like that? If so you can index into the first array by the second one. x[y[:,0], 1] if you can't get them into an indexable format, I think it's going to be slow no matter how you do it. On Wed, Aug 4, 2010 at 4:59 PM, <PHobson@geosyntec.com<mailto:PHobson@geosyntec.com>> wrote: Hey folks, I've one array, x, that you could define as follows: [[1, 2.25], [2, 2.50], [3, 2.25], [4, 0.00], [8, 0.00], [9, 2.75]] Then my second array, y, is: [[1, 0.00], [2, 0.00], [3, 0.00], [4, 0.00], [5, 0.00], [6, 0.00], [7, 0.00], [8, 0.00], [9, 0.00], [10,0.00]] Is there a concise, Numpythonic way to copy the values of x[:,1] over to y[:,1] where x[:,0] = y[:,0]? Resulting in, z: [[1, 2.25], [2, 2.50], [3, 2.25], [4, 0.00], [5, 0.00], [6, 0.00], [7, 0.00], [8, 0.00], [9, 2.75], [10,0.00]] My current task has len(x) = 25000 and len(y) = 350000 and looping through is quite slow unfortunately. Many thanks, -paul _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org<mailto:NumPy-Discussion@scipy.org> http://mail.scipy.org/mailman/listinfo/numpy-discussion