将按行排序的数据框映射到原始列标签( pandas ) [英] Mapping row-wise sorted dataframe to original column labels (Pandas)

问题描述

我正面临涉及数据框架的问题，因此在Google花费了大量时间后，我在这里提出了一个问题. 我有一个数据框-

I am facing this problem involving dataframes, so after spending a lot of time on Google, I am opening a question here. I am having a Dataframe -

df 
   A  B  C   D
0  8  3  6   2
1  1 -3  5   2
2  4  9  5  10
3  2 -4 -8  -2

我想按降序对每一行进行排序，但我不想保存值，而是要保存对应的列名.

I want to sort every row in descending order, but instead of saving the values, I want to save the corresponding column name.

排序的数据框看起来像这样-

Sorted dataframe would look like this -

df 
       A  B  C   D
    0  8  6  3   2
    1  5  2  1  -3
    2 10  9  5   4
    3  2 -2 -4  -8

我最终想要的是下面的结构，它对应于排序后的数据框df-

What I ultimately want is this structure below, which corresponds to the column indices of the sorted dataframe df -

df_col 
       1  2  3   4
    0  A  C  B   D
    1  C  D  A   B
    2  D  B  C   A
    3  A  D  B   C

我敢肯定，如果没有明确的for loop

I am sure there will be a simpler one liner solution to this problem, without coding an explicit for loop

推荐答案

应用np.argsort，对索引进行排序，然后索引到df.columns.

Apply np.argsort, sort the indices, and then index into df.columns.

In [129]: pd.DataFrame(df.columns[df.apply(np.argsort, axis=1).T[::-1].T])
Out[129]: 
   0  1  2  3
0  A  C  B  D
1  C  D  A  B
2  D  B  C  A
3  A  D  B  C

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