如何重新排序Pandas中的多索引列？

Question

df=pd.DataFrame({'Country':["AU","GB","KR","US","GB","US","KR","AU","US"],'Region Manager':['TL','JS','HN','AL','JS','AL','HN','TL','AL'],'Curr_Sales': [453,562,236,636,893,542,125,561,371],'Curr_Revenue':[4530,7668,5975,3568,2349,6776,3046,1111,4852],'Prior_Sales': [235,789,132,220,569,521,131,777,898],'Prior_Revenue':[1530,2668,3975,5668,6349,7776,8046,2111,9852]})

pd.pivot_table(df, values=['Curr_Sales', 'Curr_Revenue','Prior_Sales','Prior_Revenue'],index=['Country', 'Region Manager'],aggfunc=np.sum,margins=True)

嗨伙计，

我有以下数据框，我想重新排序muti-index列

['Prior_Sales','Prior_Revenue','Curr_Sales', 'Curr_Revenue']

我怎么能在熊猫中做到这一点？

代码如上所示

在此先感谢您的帮助！

Answer 1

切片结果数据帧

pd.pivot_table(
    df,
    values=['Curr_Sales', 'Curr_Revenue', 'Prior_Sales', 'Prior_Revenue'],
    index=['Country', 'Region Manager'],
    aggfunc='sum',
    margins=True
)[['Prior_Sales', 'Prior_Revenue', 'Curr_Sales', 'Curr_Revenue']]


                        Prior_Sales  Prior_Revenue  Curr_Sales  Curr_Revenue
Country Region Manager                                                      
AU      TL                     1012           3641        1014          5641
GB      JS                     1358           9017        1455         10017
KR      HN                      263          12021         361          9021
US      AL                     1639          23296        1549         15196
All                            4272          47975        4379         39875

Answer 2

cols = ['Prior_Sales','Prior_Revenue','Curr_Sales', 'Curr_Revenue']

df = df[cols]