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pythonpandasscipykurtosis

Python Pandas: rolling_kurt vs. scipy.stats.kurtosis

I am trying to figure out why the following code returns different values for the sample's kurtosis:

import pandas
import scipy
e = pandas.DataFrame([1, 2, 3, 4, 5, 4, 3, 2, 1])
print "pandas.rolling_kurt:\n", pandas.rolling_kurt(e, window=9)
print "\nscipy.stats.kurtosis:", scipy.stats.kurtosis(e)

The output I am getting:

pandas.rolling_kurt:
          0
0       NaN
1       NaN
2       NaN
3       NaN
4       NaN
5       NaN
6       NaN
7       NaN
8 -1.060058

scipy.stats.kurtosis: [-1.15653061]

I have tried to play with the pearson vs fisher setting but to no avail.

Solution

  • Setting bias=False seems to do it:

    In [3]: scipy.stats.kurtosis(e,bias=False)
Out[3]: array([-1.06005831])