dataframe sorting by sum of values-CodePudding

I have the following df:

df = pd.DataFrame({'from':['A','A','A','B','B','C','C','C'],'to':['J','C','F','C','M','Q','C','J'],'amount':[1,1,2,12,13,5,5,1]})
df

and I wish to sort it is such way that the highest amount of 'from' is first. So in this example, 'from' B has 12 13 = 25 so B is the first in the list. Then comes C with 11 and then A with 4.

One way to do it is like this:

df['temp'] = df.groupby(['from'])['amount'].transform('sum')
df.sort_values(by=['temp'], ascending =False)

but I'm just adding another column. Wonder if there's a better way?

CodePudding user response：

I think your method is good and explicit.

A variant without the temporary column could be:

df.sort_values(by='from', ascending=False,
               key=lambda x: df['amount'].groupby(x).transform('sum'))

output:

  from to  amount
3    B  C      12
4    B  M      13
5    C  Q       5
6    C  C       5
7    C  J       1
0    A  J       1
1    A  C       1
2    A  F       2

CodePudding user response：

In your case do with argsort

out = df.iloc[(-df.groupby(['from'])['amount'].transform('sum')).argsort()]
Out[53]: 
  from to  amount
3    B  C      12
4    B  M      13
5    C  Q       5
6    C  C       5
7    C  J       1
0    A  J       1
1    A  C       1
2    A  F       2