分别计算男女宿舍

我想要的结果是这样的

(males {1990: {Q1:value, Q2:value, Q3:Value, Q4: Value}, 
 females {Q1:value, Q2:value, Q3:Value, Q4:value})

如果任何值不存在则默认值 0

import csv
male_count = {}
female_count = {}


 with open('1000 Records.csv') as csv_file:
    
    csv_reader = csv.reader(csv_file)
    for row in csv_reader:
        
        year_of_joining = int(row[17])
        quarter_of_joining = row[15]
        gender = row[5]
        
        if year_of_joining not in female_count and gender == 'F':
            female_count[year_of_joining] = {'Q1': 0, 'Q2': 0, 'Q3': 0, 'Q4': 0}
            female_count[year_of_joining][quarter_of_joining] = 1
        elif year_of_joining in female_count and gender == 'F':
            female_count[year_of_joining][quarter_of_joining] += 1

        if year_of_joining not in male_count and gender == 'M':
            male_count[year_of_joining] = {'Q1': 0, 'Q2': 0, 'Q3': 0, 'Q4': 0}
            male_count[year_of_joining][quarter_of_joining] = 1
        elif year_of_joining in male_count and gender == 'M':
            male_count[year_of_joining][quarter_of_joining] += 1
print(male_count)
print(female_count)

假设您想要单独的字典，而不是“性别，按年份分组”（意味着年份是两个性别字典的顶级键），答案与您的上一个问题基本相同，除了您有两个单独的“result" 字典（你可以组合它们，因为 Python 对象是引用）

import csv

males = {}
females = {}

with open('records.csv') as csv_file:
  csv_reader = csv.DictReader(csv_file)
  for row in csv_reader: 
        
    year_of_joining = int(row['Year of Join'])
    quarter_of_joining = row['Quarter of Join']
    gender = row['Gender']
    result = males if gender == 'M' else females
    
    if year_of_joining not in result:
      result[year_of_joining] = {f'Q{i+1}': 0 for i in range(4)}
        
    result[year_of_joining][quarter_of_joining] += 1

final_result = {"males": males, "females": females} 

Input

Gender,Year of Join,Quarter of Join
F,2010,Q1
M,2010,Q2
F,2017,Q1

Output

from pprint import pprint
print('males', end=' ')
pprint(males)
print('females', end=' ')
pprint(females)

males {2010: {'Q1': 0, 'Q2': 1, 'Q3': 0, 'Q4': 0}}
females {2010: {'Q1': 1, 'Q2': 0, 'Q3': 0, 'Q4': 0},
 2017: {'Q1': 1, 'Q2': 0, 'Q3': 0, 'Q4': 0}}