使用python字典统计CSV数据的步骤和示例代码

Name,Age,Gender  
Alice,25,Female  
Bob,30,Male  
Charlie,25,Male  
Alice,26,Female

import csv  
  
# 初始化一个空字典来存储统计信息  
age_counts = {}  
  
# 打开CSV文件并读取数据  
with open('data.csv', mode='r', encoding='utf-8') as csv_file:  
    csv_reader = csv.DictReader(csv_file)  
      
    # 跳过表头（如果有）  
    next(csv_reader, None)  # 消耗迭代器中的第一行（即表头）  
      
    # 遍历CSV文件的每一行数据  
    for row in csv_reader:  
        age = int(row['Age'])  # 假设年龄是整数，如果不是则需要相应处理  
          
        # 统计每个年龄的人数  
        if age in age_counts:  
            age_counts[age] += 1  
        else:  
            age_counts[age] = 1  
  
# 输出统计结果  
for age, count in age_counts.items():  
    print(f"Age {age}: {count} people")

Age 25: 2 people  
Age 26: 1 people  
Age 30: 1 people

Name  
Alice  
Bob  
Charlie  
Alice  
Bob  
David

import csv  
  
name_counts = {}  
  
with open('names.csv', mode='r', encoding='utf-8') as csv_file:  
    csv_reader = csv.reader(csv_file)  
    next(csv_reader, None)  # 跳过表头  
  
    for row in csv_reader:  
        name = row[0]  
        if name in name_counts:  
            name_counts[name] += 1  
        else:  
            name_counts[name] = 1  
  
# 输出统计结果  
for name, count in name_counts.items():  
    print(f"Name {name}: {count} occurrences")

Name,Age  
Alice,25  
Bob,32  
Charlie,18  
David,28  
Eve,19

import csv  
  
age_groups = {  
    '18-24': 0,  
    '25-30': 0,  
    '31+': 0  
}  
  
with open('users.csv', mode='r', encoding='utf-8') as csv_file:  
    csv_reader = csv.DictReader(csv_file)  
    next(csv_reader, None)  # 跳过表头  
  
    for row in csv_reader:  
        age = int(row['Age'])  
        if 18 <= age <= 24:  
            age_groups['18-24'] += 1  
        elif 25 <= age <= 30:  
            age_groups['25-30'] += 1  
        else:  
            age_groups['31+'] += 1  
  
# 输出统计结果  
for age_group, count in age_groups.items():  
    print(f"Age group {age_group}: {count} users")

Name,Age,Gender  
Alice,25,Female  
Bob,32,Male  
Charlie,18,Male  
David,28,Male  
Eve,19,Female

import csv  
  
age_gender_counts = {  
    '18-24': {'Male': 0, 'Female': 0},  
    '25-30': {'Male': 0, 'Female': 0},  
    '31+': {'Male': 0, 'Female': 0}  
}  
  
with open('users_advanced.csv', mode='r', encoding='utf-8') as csv_file:  
    csv_reader = csv.DictReader(csv_file)  
    next(csv_reader, None)  # 跳过表头  
  
    for row in csv_reader:  
        age = int(row['Age'])  
        gender = row['Gender']  
        if 18 <= age <= 24:  
            age_group = '18-24'  
        elif 25 <= age <= 30:  
            age_group = '25-30'  
        else:  
            age_group = '31+'  
        age_gender_counts[age_group][gender] += 1  
  
# 输出统计结果  
for age_group, gender_counts in age_gender_counts.items():  
    print(f"Age group {age_group}:")  
    for gender, count in gender_counts.items():  
        print(f"  {gender}: {count} users")  
    print()