嵌套字典到MultiIndex pandas DataFrame(3级)

Question

我想为3级嵌套字典做相同的操作

嵌套字典到多索引数据框,其中字典键是列标签

Answer 1

使用三级dict的例子

In [1]: import pandas as pd

In [2]: dictionary = {'A': {'a': {1: [2,3,4,5,6],
   ...:                           2: [2,3,4,5,6]},
   ...:                     'b': {1: [2,3,4,5,6],
   ...:                           2: [2,3,4,5,6]}},
   ...:               'B': {'a': {1: [2,3,4,5,6],
   ...:                           2: [2,3,4,5,6]},
   ...:                     'b': {1: [2,3,4,5,6],
   ...:                           2: [2,3,4,5,6]}}}

以下字典理解基于你所链接的问题之一

In [3]: reform = {(level1_key, level2_key, level3_key): values
   ...:           for level1_key, level2_dict in dictionary.items()
   ...:           for level2_key, level3_dict in level2_dict.items()
   ...:           for level3_key, values      in level3_dict.items()}

这使

In [4]: reform
Out[4]:
{('A', 'a', 1): [2, 3, 4, 5, 6],
 ('A', 'a', 2): [2, 3, 4, 5, 6],
 ('A', 'b', 1): [2, 3, 4, 5, 6],
 ('A', 'b', 2): [2, 3, 4, 5, 6],
 ('B', 'a', 1): [2, 3, 4, 5, 6],
 ('B', 'a', 2): [2, 3, 4, 5, 6],
 ('B', 'b', 1): [2, 3, 4, 5, 6],
 ('B', 'b', 2): [2, 3, 4, 5, 6]}

对于pandas DataFrame

In [5]: pd.DataFrame(reform)
Out[5]:
   A           B
   a     b     a     b
   1  2  1  2  1  2  1  2
0  2  2  2  2  2  2  2  2
1  3  3  3  3  3  3  3  3
2  4  4  4  4  4  4  4  4
3  5  5  5  5  5  5  5  5
4  6  6  6  6  6  6  6  6

In [6]: df = pd.DataFrame(reform).T
Out[6]:
       0  1  2  3  4
A a 1  2  3  4  5  6
    2  2  3  4  5  6
  b 1  2  3  4  5  6
    2  2  3  4  5  6
B a 1  2  3  4  5  6
    2  2  3  4  5  6
  b 1  2  3  4  5  6
    2  2  3  4  5  6

正如您所看到的,您可以通过在理解中添加另一行以及向元组添加新键来轻松增加级别数.

额外奖励:为索引添加名称

In [7]: names=['level1', 'level2', 'level3']

In [8]: df.index.set_names(names, inplace=True)

In [9]: df
Out[9]:
                      0  1  2  3  4
level1 level2 level3
A      a      1       2  3  4  5  6
              2       2  3  4  5  6
       b      1       2  3  4  5  6
              2       2  3  4  5  6
B      a      1       2  3  4  5  6
              2       2  3  4  5  6
       b      1       2  3  4  5  6
              2       2  3  4  5  6