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DS-1000 / 780 / I have the following data frame:

Problem

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Problem:
I have the following data frame:
import pandas as pd
import io
from scipy import stats
temp=u"""probegenes,sample1,sample2,sample3
1415777_at Pnliprp1,20,0.00,11
1415805_at Clps,17,0.00,55
1415884_at Cela3b,47,0.00,100"""
df = pd.read_csv(io.StringIO(temp),index_col='probegenes')
df
It looks like this
                     sample1  sample2  sample3
probegenes
1415777_at Pnliprp1       20        0       11
1415805_at Clps           17        0       55
1415884_at Cela3b         47        0      100
What I want to do is too perform column-zscore calculation using SCIPY. AND I want to show data and zscore together in a single dataframe. For each element, I want to only keep 3 decimals places. At the end of the day. the result will look like:
                               sample1  sample2  sample3
probegenes
1415777_at Pnliprp1   data     20.000    0.000    11.000
					zscore	   -0.593    NaN    -1.220
1415805_at Clps		  data     17.000	0.000	55.000
					zscore     -0.815    NaN    -0.009
1415884_at Cela3b	  data     47.000	0.000	100.000
					zscore     1.408     NaN     1.229

A:
<code>
import pandas as pd
import io
import numpy as np
from scipy import stats

temp=u"""probegenes,sample1,sample2,sample3
1415777_at Pnliprp1,20,0.00,11
1415805_at Clps,17,0.00,55
1415884_at Cela3b,47,0.00,100"""
df = pd.read_csv(io.StringIO(temp),index_col='probegenes')
</code>
result = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Scipy

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Source and history

upstream_id / Original problem ID
780
task_id
04158e0f-49e5-5ee4-912e-80abd1a52f36
task_key
default--test--780
task_revision_id
1
config / split
default / test

Official source

initial import