related recent issue: https://github.com/numpy/numpy/issues/4638 and pandas is now explicitly specifying the accumulator to avoid this problem: https://github.com/pydata/pandas/pull/6954/files
pandas also implemented the Welfords method for rolling_var in 0.14.0, see here: https://github.com/pydata/pandas/pull/6817 On Thu, Jul 24, 2014 at 3:05 PM, RayS <r...@blue-cove.com> wrote: > Probably a number of scipy places as well > > > > import numpy > import scipy.stats > print numpy.__version__ > print scipy.__version__ > for s in range(16777214, 16777944): > if scipy.stats.nanmean(numpy.ones((s, 1), numpy.float32))[0]!=1: > print '\nbroke', s, scipy.stats.nanmean(numpy.ones((s, 1), > numpy.float32)) > break > else: > print '\r',s, > > c:\temp>python np_sum.py > 1.8.0b2 > 0.11.0 > 16777216 > broke 16777217 [ 0.99999994] > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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