On Wed, Mar 3, 2010 at 16:23, Marco Tuckner <marcotuck...@public-files.de> wrote: > Thanks to all who answered. > This is really helpful! > >>> If you are still seeing actual calculation differences, we will >>> need to see a complete, self-contained example that demonstrates >>> the difference. >> >> To add a bit more detail -- unless you are explicitly specifying >> single precision floats (dtype=float32), then both numpy and excel >> are using doubles -- so that's not the source of the differences. >> Even if you are using single precision in numpy, It's pretty rare for >> that to make a significant difference. Something else is going on. >> >> I suspect a different algorithm, you can tell timeseries.convert how >> you want it to interpolate -- who knows what excel is doing. > I checked the values row by row comparing Excel against the Python results. > > The the values of both programs match perfectly at the data points where > no periodic sequence occurs: > so those values where the aggregated value results in a straight value > (e.g. 12.04) the results were the same. > At values points where the result was a periodic sequence (e.g. > 12.222222 ...) the described difference could be observed.
I think you are just seeing the effect of the different printing that I described. These are not differences in the actual values. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
