python - pandas:如何重新索引多索引级别？

Question

按其中一个级别排序后，如何对 MultiIndex 级别重新编号？这是排序后的 DataFrame:

+--------+---+------+
|        |   | text |
+--------+---+------+
| letter |   |      |
+--------+---+------+
| a      | 0 | blah |
+--------+---+------+
|        | 3 | blah |
+--------+---+------+
|        | 6 | blah |
+--------+---+------+
| b      | 1 | blah |
+--------+---+------+
|        | 4 | blah |
+--------+---+------+
|        | 7 | blah |
+--------+---+------+
| c      | 2 | blah |
+--------+---+------+
|        | 5 | blah |
+--------+---+------+
|        | 8 | blah |
+--------+---+------+

这就是我想要的(但可能将原始索引留在自己的列中):

+--------+---+------+
|        |   | text |
+--------+---+------+
| letter |   |      |
+--------+---+------+
| a      | 0 | blah |
+--------+---+------+
|        | 1 | blah |
+--------+---+------+
|        | 2 | blah |
+--------+---+------+
| b      | 0 | blah |
+--------+---+------+
|        | 1 | blah |
+--------+---+------+
|        | 2 | blah |
+--------+---+------+
| c      | 0 | blah |
+--------+---+------+
|        | 1 | blah |
+--------+---+------+
|        | 2 | blah |
+--------+---+------+

我尝试过寻找答案，尝试编写不同的代码，但我被难住了。

重现上面第一个表的代码:

import pandas as pd
df = pd.DataFrame({'letter': ['a', 'b', 'c'] * 3, 'text': ['blah'] * 9})
df.set_index(keys='letter', append=True, inplace=True)
df = df.reorder_levels(order=[1, 0])
df.sort_index(level=0, inplace=True)
print(df)

Answer 1

您可以检查cumcount

df=df.assign(yourindex=df.groupby('letter').cumcount()).set_index(['letter','yourindex']).sort_index(level=[0,1])
df
Out[861]: 
                  text
letter yourindex      
a      0          blah
       1          blah
       2          blah
b      0          blah
       1          blah
       2          blah
c      0          blah
       1          blah
       2          blah