Pandas dataframe: how to apply describe() to each group and add to new columns?

Question

df:

name score
A      1
A      2
A      3
A      4
A      5
B      2
B      4
B      6 
B      8

Want to get the following new dataframe in

Answer 1

Well I managed to get what you wanted but it doesn't scale very well.

import pandas as pd

name = ['a','a','a','a','a','b','b','b','b','b']
score = [1,2,3,4,5,2,4,6,8]

d = pd.DataFrame(zip(name,score), columns=['Name','Score'])
d = d.groupby('Name').describe()
d = d.reset_index()
df2 = pd.DataFrame(zip(d.level_1[8:], list(d.Score)[:8], list(d.Score)[8:]), columns = ['Name','A','B']).T

print df2

          0     1         2    3    4    5    6    7
Name  count  mean       std  min  25%  50%  75%  max
A         5     3  1.581139    1    2    3    4    5
B         4     5  2.581989    2  3.5    5  6.5    8