我就廢話不多說了，大家還是直接看程式碼吧！

# -*- encoding=utf-8 -*-
import pandas as pd
data=['abc','abc','asc','ase','ase']
num=[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',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)

執行：

 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

補充知識：python專案篇-對符合條件的某個欄位進行求和,聚合函式annotate(),aggregate()函式

對符合條件的某個欄位求和

需求是，計算每日的收入和

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'])

輸出結果：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'])

輸出結果:total_income 572

第二種輸出的是正確的數字

以上這篇python 實現分組求和與分組累加求和程式碼就是小編分享給大家的全部內容了，希望能給大家一個參考，也希望大家多多支援我們。