我就废话不多说了，大家还是直接看代码吧！

# -*- encoding=utf-8 -*-import pandas as pddata=['abc','abc','abc','asc','ase','ase','ase']num=[1,2,2,1,2,1,2]df1=pd.DataFrame({'name':data,'num':num})print(df1)df1['mmm']=df1['num']df2=df1.groupby(['name', 'num'], as_index=False).count()print(df2)df2.sort_values(['name', 'num'], ascending=[1, 1], inplace=True)print(df2)df2['sum']=df2.groupby(['name'])['mmm'].cumsum()print(df2)kk=df2.groupby(['name'],as_index=False)['num'].sum()print(kk)df3 = pd.merge(df2, kk, on='name', how='left',)print(df3)df3['ratio']=df3['sum']/df3['num_y']df3.columns = ['name', 'num', 'mmm', 'sum','numsum','ratio']print(df3)df4=df3.groupby(['mmm'],as_index=False)['ratio'].mean()print(df4)

运行：

name num0 abc 11 abc 22 abc 23 asc 14 ase 25 ase 16 ase 2 name num mmm0 abc 1 11 abc 2 22 asc 1 13 ase 1 14 ase 2 2 name num mmm0 abc 1 11 abc 2 22 asc 1 13 ase 1 14 ase 2 2 name num mmm sum0 abc 1 1 11 abc 2 2 32 asc 1 1 13 ase 1 1 14 ase 2 2 3 name num0 abc 31 asc 12 ase 3 name num_x mmm sum num_y0 abc 1 1 1 31 abc 2 2 3 32 asc 1 1 1 13 ase 1 1 1 34 ase 2 2 3 3 name num mmm sum numsum ratio0 abc 1 1 1 3 0.3333331 abc 2 2 3 3 1.0000002 asc 1 1 1 1 1.0000003 ase 1 1 1 3 0.3333334 ase 2 2 3 3 1.000000 mmm ratio0 1 0.5555561 2 1.000000Process finished with exit code 0

补充知识：python项目篇-对符合条件的某个字段进行求和,聚合函数annotate(),aggregate()函数

对符合条件的某个字段求和

需求是，计算每日的收入和

1、

new_dayincome = request.POST.get("dayincome_time", None) # total_income = models.bathAccount.objects.filter(dayBath=new_dayincome).aggregate(nums=Sum('priceBath')) total_income = models.bathAccount.objects.values('priceBath').annotate(nums=Sum('priceBath')).filter(dayBath=new_dayincome) print("total_income",total_income[0]['nums'])

输出结果：total_income 132

2、

from django.db.models import Sum,Countnew_dayincome = request.POST.get("dayincome_time", None) total_income = models.bathAccount.objects.filter(dayBath=new_dayincome).aggregate(nums=Sum('priceBath')) print("total_income",total_income['nums'])

输出结果:total_income 572

第二种输出的是正确的数字

以上这篇python 实现分组求和与分组累加求和代码就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。