Scipy gmean with missing values
I was not sure how to deal with a two dimensional array [stock returns] that has some missing values.
I want to get geometric mean for each row [ average return for each month]. I got missing values for geometric mean for those months that I have missing values.
One way is to filling the missing values with something like 1 or mean but I don't want to mess with the mean.
Any advice how to calculate the gmean for each date just based on the not-missing values?
Solution
You should go with numpy.nanmean()
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.nanmean.html
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