组合两个具有相同列名但 MultiIndex 不同的 Dataframe

Question

我有两个不同的 DataFrames 我想组合，但我无法得到我正在寻找的答案。下面给出了 MWE。

import numpy as np
import pandas as pd

index_tuple1 = [('car', 'green'), ('car', 'red'), ('boat', 'green')]
index1 = pd.MultiIndex.from_tuples(index_tuple1, names=['Vehicle', 'Color'])
data1 = np.array([[1,2], [3,4], [7,8]])
df1 = pd.DataFrame(data1, index=index1, columns=['2022-05-09', '2022-10-17'])

index_tuple2 = [('car', 'blue'), ('boat', 'blue')]
index2 = pd.MultiIndex.from_tuples(index_tuple2, names=['Vehicle', 'Color'])
data2 = np.array([[5,6], [9,0]])
df2 = pd.DataFrame(data2, index=index2, columns=['2022-05-09', '2022-10-17'])

print(df1)
print(df2)


Output:
               2022-05-09  2022-10-17
Vehicle Color
car     green           1           2
        red             3           4
boat    green           7           8

               2022-05-09  2022-10-17
Vehicle Color
car     blue            5           6
boat    blue            9           0

我希望看到的输出如下所示。我已经尝试过 concat、merge 和 join，但是我得到一个用 NaN 填充的 DataFrame 或“ValueError：列重叠但没有指定后缀：Index(['2022-05-09', '2022-10-17']

               2022-05-09  2022-10-17
Vehicle Color
car     green           1           2
        red             3           4
        blue            5           6
boat    green           7           8
        blue            9           0 

Answer 1

IIUC 用途：

df = pd.concat([df1, df2]).sort_index()
print (df)
               2022-05-09  2022-10-17
Vehicle Color                        
boat    blue            9           0
        green           7           8
car     blue            5           6
        green           1           2
        red             3           4