pandas将嵌套字典转换为mutiIndex行和列

import pandas as pd

nested_dict = {
    'A': {'a': 1, 'b': 2},
    'B': {'a': 3, 'b': 4}
}

df = pd.DataFrame.from_dict(nested_dict, orient='index')
print(df)

   a  b
A  1  2
B  3  4

import pandas as pd

nested_dict = {
    'A': {'a': {'x': 1, 'y': 2}, 'b': {'x': 3, 'y': 4}},
    'B': {'a': {'x': 5, 'y': 6}, 'b': {'x': 7, 'y': 8}}
}

df = pd.DataFrame.from_dict(nested_dict, orient='index')

# 创建多级行索引和列索引
rows = pd.MultiIndex.from_product([df.index, df.columns])
cols = pd.MultiIndex.from_product([df.columns, df.index])

# 重新构造DataFrame
df = pd.DataFrame(df.values.flatten(), index=rows, columns=cols)
print(df)

     a     b   
     A  B  A  B
a x  1  5  3  7
  y  2  6  4  8
b x  1  5  3  7
  y  2  6  4  8