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

import pandas as pd
import io
import numpy as np

data = """
name score
A      1
A      2
A      3
A      4
A      5
B      2
B      4
B      6
B      8
    """

df = pd.read_csv(io.StringIO(data), delimiter='\s+')

df2 = df.groupby('name').describe().reset_index().T.drop('name')
arr = np.array(df2).reshape((4,8))

df2 = pd.DataFrame(arr[1:], index=['name','A','B'])

print(df2)

That will give you df2 as:

              0     1        2    3    4    5    6    7
    name  count  mean      std  min  25%  50%  75%  max
    A         5     3  1.58114    1    2    3    4    5
    B         4     5  2.58199    2  3.5    5  6.5    8