pandas.dataframe groupby and transpose

Question

I am a beginner at Python and Pandas. I have trouble putting words to my problem, so instead, here is a sample of my dataframe (there are more values and more columns as well):

Reason          Grade     
'course'        15
'home'          10
'reputation'    12
'other'         16
'other'         9
'home'          14
'reputation'    10
'reputation'    8
'course'        20
'home'          19
'course'        12
'other'         10
'home'          17
'reputation'    18

And, I will like to get this:

     course      home     reputation   other
       15         10          12        16
       20         14          10        9
       12         19          8         10
                  17          18

Answer 1

Use GroupBy.cumcount for counter by Reason column with DataFrame.assign for new column and last use DataFrame.pivot - for not exist values are added missing values:

df = df.assign(count = df.groupby('Reason').cumcount()).pivot('count','Reason','Grade')
print (df)
Reason  'course'  'home'  'other'  'reputation'
count                                          
0           15.0    10.0     16.0          12.0
1           20.0    14.0      9.0          10.0
2           12.0    19.0     10.0           8.0
3            NaN    17.0      NaN          18.0