You have a million 32-bit floating point numbers that are in the thousands. Thus you are exceeding the 32-bitfloat precision and, if you can, you need to increase precision of the accumulator in np.mean() or change the input dtype:

a.mean(dtype=np.float32) # default and lacks precision 3067.0243839999998 a.mean(dtype=np.float64) 3045.747251076416 a.mean(dtype=np.float128) 3045.7472510764160156 b=a.astype(np.float128) b.mean() 3045.7472510764160156

Otherwise you are left to using some alternative approach to calculate the mean.

Bruce

Interesting -- I knew that float64 accumulators were used with integer arrays, and I had just assumed that 64-bit or higher accumulators would be used with floating-point arrays too, instead of the array's dtype. This is actually quite a bit of a gotcha for floating-point imaging-type tasks -- good to know! Zach