如何使用对应的列值对多索引列名进行排序？

Question

I have a table like the image

I want to sort the second column names of multiindex but the columns must keep their corresponding column values.

So I tried this code:

df.columns=df.sort_index(axis=1,level=[1],ascending=[True]).columns

But is sorting only the names of the columns, and the columns are changing the data.

How can I sort the name of the columns without changing their corresponding data?

Thanks in advance

Answer 1

Sample DataFrame:

import numpy as np
import pandas as pd

df = pd.DataFrame(np.arange(1, 17).reshape(-1, 4),
                  columns=pd.MultiIndex.from_product([['a', 'b'], ['d', 'c']]))

    a       b    
    d   c   d   c
0   1   2   3   4
1   5   6   7   8
2   9  10  11  12
3  13  14  15  16

Modifying columns will overwrite the columns and not affect the values:

df.columns = ['w', 'x', 'y', 'z']

    w   x   y   z
0   1   2   3   4
1   5   6   7   8
2   9  10  11  12
3  13  14  15  16

*Notice no values have changed even though the columns have been.

---

To actually sort the DataFrame based on values, overwrite the DataFrame with the return from sort_index :

df = df.sort_index(axis=1, level=1, ascending=True)

Or inplace :

df.sort_index(axis=1, level=1, ascending=True, inplace=True)

df :

    a   b   a   b
    c   c   d   d
0   2   4   1   3
1   6   8   5   7
2  10  12   9  11
3  14  16  13  15

---

It's interesting that in my search for duplicates the first and closest result I could find is Sorting columns of multiindex dataframe which has an answer very similar to OP's attempt. But in that question the goal was to "sort only the column names and keep the values as it is within each column" which does not sort the DataFrame values but only modifies the DataFrame cosmetically.