Wie selektiv Wörterbuch zusammenzufassen Werte

Question

ich bestimmte Abteilungen Gehalt und zusammenzufassen filtern will, ich habe erste Hälfte getan, aber das Gehalt hinzugefügt hat, kann durch Sehen des Code unten irgendein vorschlagen ....

chennai = {"name": "Kumar", "Department": "Sales",  "Age": 39,"Salary": 20} 
mumbai = {"name": "Suresh","Department": "Finance", "Age": 53,"Salary": 35} 
delhi = {"name": "Babu", "Department": "QC",  "Age": 28,"Salary": 10} 
kolkata = {"name": "Satish","Department": "Production","Age": 34,"Salary": 15} 
madurai = {"name": "Dev", "Department": "Management","Age": 45,"Salary": 23} 
hyderabad = {"name": "Rani", "Department": "Marketing", "Age": 46,"Salary": 25} 
bengalore = {"name": "Devi", "Department": "Production","Age": 24,"Salary": 5} 
cochin = {"name": "Sarath","Department": "Production","Age": 26,"Salary": 12} 
jaipur = {"name": "Senu", "Department": "Production","Age": 25,"Salary": 8} 
shimla = {"name": "Kumari","Department": "Management","Age": 37,"Salary": 20} 
lucknow = {"name": "Sanjay","Department": "Marketing", "Age": 52,"Salary": 30} 

employ = [chennai,mumbai,delhi,kolkata,madurai,hyderabad,bengalore,cochin,jaipur,shimla,lucknow] 

#Finding Production unit salary expenditure 
for x in employ: 
    sums = 0 
    if x ["Department"] == 'Production': 
     print x["Salary"] 

Answer 1

Wenn Sie einen Einzeiler

result = sum(d.get("Salary", 0) for d in employ if d.get("Department") == "Production") 

Kann auch Gesamtsumme für mehrere.

departments = {"Production", "Marketing"} 
result = sum(d.get("Salary", 0) for d in employ if d.get("Department") in departments) 

Answer 2

ich würde vorschlagen, Pandas (http://pandas.pydata.org/)

import pandas as pd 
# Creating the dataframe 
dataset = pd.DataFrame(employ) 
print (dataset) 
#Out[3]: 
# Age Department Salary name 
#0 39  Sales  20 Kumar 
#1 53  Finance  35 Suresh 
#2 28   QC  10 Babu 
#3 34 Production  15 Satish 
#4 45 Management  23  Dev 
#5 46 Marketing  25 Rani 
#6 24 Production  5 Devi 
#7 26 Production  12 Sarath 
#8 25 Production  8 Senu 
#9 37 Management  20 Kumari 
#10 52 Marketing  30 Sanjay 

# Production Salary 
dataset1 = dataset[dataset['Department'] == 'Production'].Salary 
print (dataset1) 
#Out[6]: 
#3 15 
#6  5 
#7 12 
#8  8 
#Name: Salary, dtype: int64 

# Sum Salaries 
dataset2 = dataset[dataset['Department'] == 'Production'].Salary.sum() 
print (dataset2) 
# 40 

Der obige Code nicht sieht so hübsch, aber Pandas ist sehr mächtig werden. Hier ist, wie Sie das Gesamtgehalt von Abteilung zu bekommen:

dataset3 = dataset.groupby('Department').sum()['Salary'] 
print (dataset3) 
#Out[8]: 
#Department 
#Finance  35 
#Management 43 
#Marketing  55 
#Production 40 
#QC   10 
#Sales   20 
#Name: Salary, dtype: int64 

Answer 3

Wenn Sie nicht wollen, Pandas dies nutzen versuchen,

from collections import defaultdict 
salary = defaultdict(int) 
# for specific departments 
required_departments = ["Production"] 
for i in employ: 
    if i["Department"] in required_departments: 
     salary[i["Department"]] += i["Salary"] 
print(salary) 
# for all departments 
salary = defaultdict(int) 
for i in employ: 
    salary[i["Department"]] += i["Salary"] 

print(salary)