由于日期时间列，使用 groupy 的 Pandas 数据透视总和无法工作

Question

我正在尝试根据“类别”列中的值对 pandas 数据帧枢轴的多列中的值进行求和。但是，由于数据透视表中的日期列，我收到错误。 如何按类别汇总所有转置的每月列？

可执行代码：

# test groupbysum
import pandas as pd
import numpy as np

df = pd.DataFrame({
        'JDate':["2022-01-31","2022-12-05","2023-11-10","2023-12-03","2024-01-16","2024-01-06","2011-01-04"],
        # 'Month':[1,12,11,12,1,1],
        'Code':[None,'John Johnson',np.nan,'John Smith','Mary Williams','ted bundy','George Lucas'],
        'Unit Price':[np.nan,200,None,56,75,65,60],
        'Quantity':[1500, 140000, 1400000, 455, 648, 759,1000],
        'Amount':[100, 10000, 100000, 5, 48, 59,449],
        'Invoice':['soccer','basketball','baseball','football','baseball','ice hockey','football'],
        'energy':[100.,100,100,54,98,3,45],
        'Category':['alpha','bravo','kappa','alpha','bravo','bravo','kappa']
})

df["JDate"] = pd.to_datetime(df["JDate"])

df["JYearMonth"] =  df['JDate'].dt.to_period('M')


index_to_use = ['Category','Code','Invoice','Unit Price','JDate']
values_to_use = ['Amount']
columns_to_use = ['JYearMonth']




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


df2 = df2['Amount'].reset_index()

df2_sum = df2.groupby('Category').sum()



writer= pd.ExcelWriter(
        "t2test18.xlsx",
        engine='xlsxwriter'
    )


df.to_excel(writer,sheet_name="t2",index=True)
df2.to_excel(writer,sheet_name="t2test",index=True)
df2_sum.to_excel(writer,sheet_name="t2testsum",index=True)

workbook = writer.book
worksheet = writer.sheets["t2"]

fmt_header = workbook.add_format({
    'bold':True,
    'text_wrap':True,
    'valign':'top',
    'fg_color': '#5DADE2',
    'font_color':'#2659D9',
    'border':1
})


writer.close()

Answer 1

IIUC你可以尝试：

df2_sum = df2.groupby("Category").agg(
    {
        "Code": list,  # or use `",".join` instead of `list`
        "Invoice": list,
        "Unit Price": list,
        "JDate": list,
        **{c: "sum" for c in df2.columns if not isinstance(c, str)},
    }
)

print(df2_sum)

打印：

JYearMonth                                      Code                             Invoice           Unit Price                                                            JDate  2011-01  2022-12  2023-12  2024-01
Category                                                                                                                                                                                                          
alpha                                   [John Smith]                          [football]               [56.0]                                            [2023-12-03 00:00:00]      0.0      0.0      5.0      0.0
bravo       [John Johnson, Mary Williams, ted bundy]  [basketball, baseball, ice hockey]  [200.0, 75.0, 65.0]  [2022-12-05 00:00:00, 2024-01-16 00:00:00, 2024-01-06 00:00:00]      0.0  10000.0      0.0    107.0
kappa                                 [George Lucas]                          [football]               [60.0]                                            [2011-01-04 00:00:00]    449.0      0.0      0.0      0.0