处理预期寿命CSV数据集遇ValueError，求代码纠错与功能实现

运行代码时出现如下错误：

ValueError: invalid literal for int() with base 10: 'Year'

需求是从指定CSV文件提取并输出整体最高预期寿命，同时实现年份查询统计功能，但当前代码无法正常运行，求错误原因及修正方案。

当前代码：

import math
import csv

print()

with open("life-expectancy.csv") as data_set:
    for row in data_set:
        row = row.split(",")

        entity = row[0].strip()
        code = row[1].strip()
        year = int(row[2])
        life_expectancy = (row[3])

        max_life = -1
        min_life = min(life_expectancy)
        avg_life = sum(life_expectancy) / len(life_expectancy)

        max_country = ""
        max_year = max(year)
        min_country = min(entity)
        min_year = min(year)

        chosen_year = ""

print()
year_lookup = input(float("Enter the year of interest: "))
print()
if life_expectancy > max_life:

        max_life = life_expectancy
        max_country = entity

        print()
        print(f"The overall max life expectancy is:{max_life:.2f} from {max_country} in {max_year:.2f}.\n")
        print(f"The overall min life expectancy is:{min_life:.2f} from {min_country} in {min_year:.2f}.\n")
    
        if chosen_year == year_lookup:
            chosen_year = year_lookup
        print(f"For the year: {year_lookup}.\n")
        print(f"The average life expectancy across all countries was str{avg_life:.2f}\n")
        print(f"The max life expectancy was in {max_country} with {max_life:.2f}\n")
        print(f"The min life expectancy was in {min_country} with {min_life:.2f}\n")

错误原因拆解 #

1. 未跳过CSV表头：CSV第一行是表头（含"Year"字符串），直接转int必然报错，这是触发ValueError的直接原因。
2. 变量初始化逻辑错误：max_life、max_country等统计变量在循环内重复初始化，每次循环都会重置，根本没法累积统计结果。
3. 数值类型未转换：life_expectancy保留成字符串类型，后续的比较、求和操作全是对字符串的无效操作。
4. 统计逻辑混乱：min(life_expectancy)、max(year)这类代码完全逻辑错误——前者是对单个字符串求最小，后者是对单个年份数值求最大，毫无意义。
5. 输入处理语法错误：input(float("Enter..."))写法错误，input的参数只能是提示字符串，不能直接套float转换。
6. 代码结构混乱：统计逻辑和输出逻辑位置完全错误，循环内没累积数据，循环外的判断和输出根本拿不到正确结果。

修正后的代码 #

import csv

# 初始化全局统计变量
overall_max_life = -1.0
overall_max_country = ""
overall_max_year = 0
overall_min_life = float('inf')
overall_min_country = ""
overall_min_year = 0
all_life_expectancies = []
year_data = {}  # 按年份存储数据：键=年份，值=(寿命列表, 对应国家列表)

# 读取并处理CSV数据
with open("life-expectancy.csv") as data_set:
    reader = csv.reader(data_set)
    next(reader)  # 跳过表头行
    
    for row in reader:
        entity = row[0].strip()
        code = row[1].strip()
        year = int(row[2])
        life_expectancy = float(row[3].strip())
        
        # 更新全局最高/最低寿命
        if life_expectancy > overall_max_life:
            overall_max_life = life_expectancy
            overall_max_country = entity
            overall_max_year = year
        if life_expectancy < overall_min_life:
            overall_min_life = life_expectancy
            overall_min_country = entity
            overall_min_year = year
        
        # 收集所有寿命数据用于计算全局平均
        all_life_expectancies.append(life_expectancy)
        
        # 按年份分组存储数据
        if year not in year_data:
            year_data[year] = ([], [])
        year_data[year][0].append(life_expectancy)
        year_data[year][1].append(entity)

# 输出全局统计结果
print("=== 全局预期寿命统计 ===")
print(f"最高预期寿命: {overall_max_life:.2f}，来自{overall_max_country}，年份{overall_max_year}")
print(f"最低预期寿命: {overall_min_life:.2f}，来自{overall_min_country}，年份{overall_min_year}")
print(f"所有国家平均预期寿命: {sum(all_life_expectancies)/len(all_life_expectancies):.2f}\n")

# 处理年份查询（带输入验证）
while True:
    try:
        year_lookup = int(input("请输入要查询的年份: "))
        break
    except ValueError:
        print("请输入有效的整数年份！")

if year_lookup in year_data:
    life_list, country_list = year_data[year_lookup]
    year_avg = sum(life_list)/len(life_list)
    year_max = max(life_list)
    year_max_country = country_list[life_list.index(year_max)]
    year_min = min(life_list)
    year_min_country = country_list[life_list.index(year_min)]
    
    print(f"\n=== {year_lookup}年预期寿命统计 ===")
    print(f"该年所有国家平均预期寿命: {year_avg:.2f}")
    print(f"该年最高预期寿命: {year_max:.2f}，来自{year_max_country}")
    print(f"该年最低预期寿命: {year_min:.2f}，来自{year_min_country}")
else:
    print(f"\n未找到{year_lookup}年的数据！")

修正说明 #

1. 跳过表头：用next(reader)跳过CSV第一行表头，避免字符串转整数错误。
2. 正确初始化变量：把统计变量放在循环外，确保循环中能累积更新数据。
3. 数值类型转换：将life_expectancy转为float，保证后续数值计算正确。
4. 分组统计：用字典按年份存储对应数据，方便后续年份查询。
5. 输入验证：添加异常处理，确保用户输入有效的整数年份。
6. 清晰结构：拆分数据读取、全局统计、年份查询三个模块，逻辑更清晰。

内容的提问来源于stack exchange，提问作者RP116