Transposing part of a pandas dataframe

Question

I have the following dataframe:

>>> df
Out[15]: 
      group   type  amount  number
0   group_A    buy     100     123
1   group_A   view       0     111
2   group_B   view       0     222
3   group_A   view       0     222 

I'd like to pivot the data so that I end up with:

              type  group_A   group_B
0    amount    buy      100         0
1    number    buy        0       123
2    number   view      333       222

How do I accomplish this?

Answer 1

Using:

df=pd.DataFrame([['group_A','buy',100,123],['group_A','view',0,111],['group_B','view',0,222],['group_A','view',0,222]],columns=['group','type','amount','number'])

First sum the indices and orientate:

>>> df = df.groupby(['type','group']).sum().transpose().stack(0).reset_index()
>>> df
group level_0  type  group_A  group_B
0      amount   buy      100      NaN
1      amount  view        0        0
2      number   buy      123      NaN
3      number  view      333      222

Drop rows that are all zero:

df = df[~((df['group_A']==0) | (df['group_B']==0))]

Fillna's:

>>> df.fillna(0)
group level_0  type  group_A  group_B
0      amount   buy      100        0
2      number   buy      123        0
3      number  view      333      222

Somewhat guessing in a few place here, but it should give you a start.