how to zscore normalize pandas column with nans?

Question

I have a pandas dataframe with a column of real values that I want to zscore normalize:

>> a
array([    nan,  0.0767,  0.4383,  0.7866,  0.8091,  0.195         


        

Answer 1

Well the pandas' versions of mean and std will hand the Nan so you could just compute that way (to get the same as scipy zscore I think you need to use ddof=0 on std):

df['zscore'] = (df.a - df.a.mean())/df.a.std(ddof=0)
print df

        a    zscore
0     NaN       NaN
1  0.0767 -1.148329
2  0.4383  0.071478
3  0.7866  1.246419
4  0.8091  1.322320
5  0.1954 -0.747912
6  0.6307  0.720512
7  0.6599  0.819014
8  0.1065 -1.047803
9  0.0508 -1.235699