透视pandas数据帧以获得正确顺序的结果数据帧



我有一个excel数据,格式如下:

Original Data Frame
Package FISCAL_YR   SCENARIO    PERIOD   USD_AMT     LY_USD_AMT      CY_NetSales     LY_NetSales 
Canada  2021            Plan    Per01    1.00            2.00            3.00            4.00 
Africa  2021            Actual  Per04    1.00            2.00            3.00            4.00 
Africa  2021            Actual  Per09    1.00            2.00            3.00            4.00 
Brazil  2021            Plan    Per11    1.00            2.00            3.00            4.00 
Brazil  2021            Actual  Per05    1.00            2.00            3.00            4.00 
Africa  2021            Actual  Per07    1.00            2.00            3.00            4.00 
Mexico  2021            Plan    Per10    1.00            2.00            3.00            4.00 
Canada  2021            Actual  Per02    1.00            2.00            3.00            4.00                   

为了简化我的计算,我试图将场景列中的值与最后4列中的数值进行适当分配:

Expected dataframe:
                      
Actual                                                              Plan            
Package   Sum of USD_AMT    Sum of LY_USD_AMT   Sum of CY_NetSales  Sum of LY_NetSales  Sum of USD_AMT  Sum of LY_USD_AMT   Sum of CY_NetSales  Sum of LY_NetSales
Africa          3           6                           9                   12              
Brazil          2           4                           6                   8               
Canada          1           2                           3                   4                   1                   2                   3                   4
Mexico          1           2                           3                   4               

我正在Panda中尝试数据透视表选项,但它呈现了以下输出:

失败的解决方案:

pd_piv=pd.pivot_table(df_dummy,index=['Package', 'FISCAL_YR', 'PERIOD'], 
columns=['SCENARIO'],
values=['USD_AMT', 'LY_USD_AMT', 'CY_NetSales', 'LY_NetSales'], aggfunc=np.sum, fill_value=0)
pd_piv.head()
CY_NetSales         LY_NetSales         LY_USD_AMT          USD_AMT     
SCENARIO    Actual  Plan    WRKG_FCST   Actual  Plan    WRKG_FCST   Actual  Plan    WRKG_FCST   Actual  Plan    WRKG_FCST
Package_SubCategory FISCAL_YR_NBR   FISCAL_PERIOD_NBR

*数字没有显示,因为实际数据与完全不同

是否有任何方法可以获得上面显示的预期数据帧?

也许这就是您想要的:1-制作您的数据透视表:

import pandas as pd
import numpy as np
data={"package":["Canada","Africa","Africa","Brazil","Brazil","Africa","Mexico","Canada"],
"scenario":["Plan","Actual","Actual","Plan","Actual","Actual","Plan","Actual"],
"USD_AMT":[1,1,1,1,1,1,1,1,],
"LY_USD_AMT":[1,1,1,1,1,1,1,1,]}
df=pd.DataFrame(data)

pd_piv=pd.pivot_table(df,index=['package'],
columns=['scenario'],
values=['USD_AMT', 'LY_USD_AMT',], aggfunc=np.sum,fill_value=0)

结果:

LY_USD_AMT      USD_AMT
scenario     Actual Plan  Actual Plan
package
Africa            3    0       3    0
Brazil            1    1       1    1
Canada            1    1       1    1
Mexico            0    1       0    1

2-交换索引级别:

pd_piv.columns=pd_piv.columns.swaplevel(0, 1)
pd_piv.sort_index(axis=1, level=0, inplace=True)

最终结果:

scenario     Actual               Plan
LY_USD_AMT USD_AMT LY_USD_AMT USD_AMT
package
Africa            3       3          0       0
Brazil            1       1          1       1
Canada            1       1          1       1
Mexico            0       0          1       1

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