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