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我就废话不多说了,大家还是直接看代码吧!

# -*- encoding=utf-8 -*-
import pandas as pd
data=['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 num
0 abc  1
1 abc  2
2 abc  2
3 asc  1
4 ase  2
5 ase  1
6 ase  2
 name num mmm
0 abc  1  1
1 abc  2  2
2 asc  1  1
3 ase  1  1
4 ase  2  2
 name num mmm
0 abc  1  1
1 abc  2  2
2 asc  1  1
3 ase  1  1
4 ase  2  2
 name num mmm sum
0 abc  1  1  1
1 abc  2  2  3
2 asc  1  1  1
3 ase  1  1  1
4 ase  2  2  3
 name num
0 abc  3
1 asc  1
2 ase  3
 name num_x mmm sum num_y
0 abc   1  1  1   3
1 abc   2  2  3   3
2 asc   1  1  1   1
3 ase   1  1  1   3
4 ase   2  2  3   3
 name num mmm sum numsum   ratio
0 abc  1  1  1    3 0.333333
1 abc  2  2  3    3 1.000000
2 asc  1  1  1    1 1.000000
3 ase  1  1  1    3 0.333333
4 ase  2  2  3    3 1.000000
  mmm   ratio
0  1 0.555556
1  2 1.000000

Process 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,Count
new_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。

标签:
python,分组求和,分组累加求和

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