python pandas 按不同軸上的總和和平均值分組

Question

我需要對我的數據進行分組並在一個軸上計算平均值並在另一個軸上求和。 我一直在尋找類似的問題，但找不到合適的解決方案。

我有一個類似的df：

df = pd.DataFrame ({'A': ['XX','XX','XX','XX','XX','XX','XX','XX','XX',
                          'YY','YY','YY','YY','YY','YY','YY','YY','YY',
                          'ZZ','ZZ','ZZ','ZZ','ZZ','ZZ','ZZ','ZZ','ZZ'],
                    
                    'B': ['ind1','ind2','ind3','ind1','ind2','ind3','ind1','ind2','ind3',
                          'ind1','ind2','ind3','ind1','ind2','ind3','ind1','ind2','ind3',
                          'ind1','ind2','ind3','ind1','ind2','ind3','ind1','ind2','ind3'],   
                                        
                    'C': ['2017','2017','2017','2018','2018','2018','2019','2019','2019',
                          '2017','2017','2017','2018','2018','2018','2019','2019','2019',
                          '2017','2017','2017','2018','2018','2018','2019','2019','2019'],
                    
                    'D': np.random.randint(0,100,size=27)})

我需要以下df：

A   ind1    ind2    ind3    TOTAL
XX  52.33   73.00   37.00   162.33
YY  40.67   51.33   54.33   146.33
ZZ  84.00   28.67   62.00   174.67

其中 ind1、ind2、ind3 列是軸 = 0 的平均值，而 TOTAL 是軸 = 1 的 ind1、ind2、ind3 的總和

我嘗試了以下但不工作：

print(df.groupby('A')['D'].agg(['sum','mean']))

任何幫助都會很棒。

Answer 1

我相信您需要通過crosstab或DataFrame.pivot_table進行旋轉，然后添加帶有總和的新列DataFrame.assign ：

np.random.seed(20)
    
df = pd.DataFrame ({'A': ['XX','XX','XX','XX','XX','XX','XX','XX','XX',
                          'YY','YY','YY','YY','YY','YY','YY','YY','YY',
                          'ZZ','ZZ','ZZ','ZZ','ZZ','ZZ','ZZ','ZZ','ZZ'],
                    
                    'B': ['ind1','ind2','ind3','ind1','ind2','ind3','ind1','ind2','ind3',
                          'ind1','ind2','ind3','ind1','ind2','ind3','ind1','ind2','ind3',
                          'ind1','ind2','ind3','ind1','ind2','ind3','ind1','ind2','ind3'],   
                                        
                    'C': ['2017','2017','2017','2018','2018','2018','2019','2019','2019',
                          '2017','2017','2017','2018','2018','2018','2019','2019','2019',
                          '2017','2017','2017','2018','2018','2018','2019','2019','2019'],
                    
                    'D': np.random.randint(0,100,size=27)})

df = (pd.crosstab(df['A'], df['B'], df['D'], aggfunc='mean')
        .assign(Total = lambda x: x.sum(axis=1)))

print (df)
B        ind1       ind2       ind3       Total
A                                              
XX  67.666667  46.000000  60.000000  173.666667
YY  69.333333  45.666667  67.333333  182.333333
ZZ  16.333333  57.666667  32.333333  106.333333

或者：

df = (df.pivot_table(index='A',columns='B',values='D')
        .assign(Total = lambda x: x.sum(axis=1)))

Answer 2

如果您不熟悉 cross_tab 或 pivot 表，這是另一種方法。

df_n = df.groupby(['A','B'])['D'].mean().unstack()
df_n['Total'] = df_n.sum(axis=1)

Output 將是：

B        ind1       ind2       ind3       Total
A                                              
XX  67.666667  46.000000  60.000000  173.666667
YY  69.333333  45.666667  67.333333  182.333333
ZZ  16.333333  57.666667  32.333333  106.333333