Different std in pandas vs numpy

Question

The standard deviation differs between pandas and numpy. Why and which one is the correct one? (the relative difference is 3.5% which should not come from rounding, this is

Answer 1

In a nutshell, neither is "incorrect". Pandas uses the unbiased estimator (N-1 in the denominator), whereas Numpy by default does not.

To make them behave the same, pass ddof=1 to numpy.std().

For further discussion, see

• Can someone explain biased/unbiased population/sample standard deviation?
• Population variance and sample variance.
• Why divide by n-1?