使用数据透视表重塑 pandas 中的数据，以便多个值以其自己的行出现在下面

Question

我有一个数据框，我正在尝试将其转换为长格式。可执行代码如下。但输出并没有按照我想要的方式输出。我希望金额和数量一个低于另一个

import pandas as pd
import numpy as np

df = pd.DataFrame({
        'Year':[2022,2022,2023,2023,2024,2024],
        'Month':[1,12,11,12,1,1],
        'Code':[None,'John Johnson',np.nan,'John Smith','Mary Williams','ted bundy'],
        'Unit Price':[np.nan,200,None,56,75,65],
        'Quantity':[1500, 140000, 1400000, 455, 648, 759],
        'Amount':[100, 10000, 100000, 5, 48, 59],
        'Invoice':['soccer','basketball','baseball','football','baseball','ice hockey'],
        'energy':[100.,100,100,54,98,3],
        'Category':['alpha','bravo','kappa','alpha','bravo','bravo']
})

index_to_use = ['Category','Code','Invoice','Unit Price']
values_to_use = ['Amount','Quantity']
columns_to_use = ['Year','Month']

df2 = df.pivot_table(index=index_to_use,
                            values=values_to_use,
                            columns=columns_to_use)

我想要这个输出，以便数量不在金额的右侧，而是在下方，然后我可以对其进行排序，以便相同的数量和金额（类别、COde、发票、单价）出现在金额的下方其他

                                                2022  
                                                 12
category   code   invoice   Unit Price  
                               200        Amount  10000  
                               200        Quantity   140000

其想法是，同类商品（具有相同单价）的销售金额和数量出现在后续行中。

Answer 1

您可以

stack

您的结果：

out = df2.stack(level=0)

输出：

Year                                                       2022   2023   2024
Month                                                        12     12     1
Category Code          Invoice    Unit Price
alpha    John Smith    football   56.0       Amount         NaN    5.0    NaN
                                             Quantity       NaN  455.0    NaN
bravo    John Johnson  basketball 200.0      Amount     10000.0    NaN    NaN
                                             Quantity  140000.0    NaN    NaN
         Mary Williams baseball   75.0       Amount         NaN    NaN   48.0
                                             Quantity       NaN    NaN  648.0
         ted bundy     ice hockey 65.0       Amount         NaN    NaN   59.0
                                             Quantity       NaN    NaN  759.0