python pandas数据帧多索引concat

Question

在下面的示例中，如何连接具有相同多索引的两个数据帧？

数据帧1:

EOAN
Close
DateTime   Stock       
2021-02-27 EOAN   8.450
2021-03-06 EOAN   8.436
2021-03-13 EOAN   8.812
2021-03-20 EOAN   8.820
2021-03-24 EOAN   9.084

数据帧2:

SAP
Close
DateTime   Stock        
2021-02-27 SAP    102.06
2021-03-06 SAP    101.78
2021-03-13 SAP    103.04
2021-03-20 SAP    103.60
2021-03-24 SAP    103.06
0      1

当代码被执行时，我得到以下结果：

DateTime   Stock               
2021-02-27 EOAN      NaN  8.450
SAP    102.06    NaN
2021-03-06 EOAN      NaN  8.436
SAP    101.78    NaN
2021-03-13 EOAN      NaN  8.812
SAP    103.04    NaN
2021-03-20 EOAN      NaN  8.820
SAP    103.60    NaN
2021-03-24 EOAN      NaN  9.084
SAP    103.06    NaN

我得到的数据帧是这样的：

for stock in stocks:
df = pandas.DataFrame(app.data, columns=['DateTime', 'Close'])
df['DateTime'] = pandas.to_datetime(df['DateTime'], yearfirst=False)
df['Stock'] = my_stock
df = df.set_index(['DateTime', 'Stock'])
app.data.clear()

if df_all is None:
df_all = df
else:
df_all = pandas.concat([df,df_all], axis = 1)
df_all.stack()
print(df_all)

我试图得到的是以下结果，这也适用于两种以上的股票：

DateTime   Stock   Close            
2021-02-27 EOAN    8.450  
SAP    102.06
2021-03-06 EOAN    8.436  
SAP    101.78
2021-03-13 EOAN    8.812  
SAP    103.04
2021-03-20 EOAN    8.820 
SAP    103.60    
2021-03-24 EOAN    9.084  
SAP    103.06    

Answer 1

样本数据：

df1 = pd.DataFrame.from_dict({'Close': {('2021-02-27', 'EOAN'): 8.45,
('2021-03-06', 'EOAN'): 8.436,
('2021-03-13', 'EOAN'): 8.812,
('2021-03-20', 'EOAN'): 8.82,
('2021-03-24', 'EOAN'): 9.084}})
df2 = pd.DataFrame({'Close': {('2021-02-27', 'SAP'): 102.06,
('2021-03-06', 'SAP'): 101.78,
('2021-03-13', 'SAP'): 103.04,
('2021-03-20', 'SAP'): 103.6,
('2021-03-24', 'SAP'): 103.06}})

沿着索引进行级联将创建MultiIndex作为df1和df2的索引的并集。为了获得所需的输出，您可能需要在级联后使用sort_index()：

pd.concat([df1, df2], axis=0).sort_index()