Groupby Pandas DataFrame and calculate mean and stdev of one column and add the std as a new column with reset_index

Question

I have a Pandas DataFrame as below:

   a      b      c      d
0  Apple  3      5      7
1  Banana 4      4      8
2  Cherry 7      1      3
3  Apple  3               


        

Answer 1

You could use a groupby-agg operation:

In [38]: result = df.groupby(['a'], as_index=False).agg(
                      {'c':['mean','std'],'b':'first', 'd':'first'})

and then rename and reorder the columns:

In [39]: result.columns = ['a','c','e','b','d']

In [40]: result.reindex(columns=sorted(result.columns))
Out[40]: 
        a  b    c  d         e
0   Apple  3  4.5  7  0.707107
1  Banana  4  4.0  8       NaN
2  Cherry  7  1.0  3       NaN

---

Pandas computes the sample std by default. To compute the population std:

def pop_std(x):
    return x.std(ddof=0)

result = df.groupby(['a'], as_index=False).agg({'c':['mean',pop_std],'b':'first', 'd':'first'})

result.columns = ['a','c','e','b','d']
result.reindex(columns=sorted(result.columns))

yields

        a  b    c  d    e
0   Apple  3  4.5  7  0.5
1  Banana  4  4.0  8  0.0
2  Cherry  7  1.0  3  0.0