如何使用Python将CSV文件转为字典并按条件完成疫情与人口数据计算

依赖说明 #

全程使用Python标准库实现，无需安装第三方包，依赖模块如下：

• csv：用于CSV文件读取
• 可选使用collections.defaultdict，统计州累计数据时更便捷

一、新冠县域疫情数据处理 #

1. 生成(州名,县名)为键的结果字典 #

注：若数据为包含多日期的时间序列，可先过滤出各县最新日期的记录再执行以下逻辑，避免重复统计

import csv

covid_dict = {}
with open("替换为你的新冠数据文件路径.csv", "r", encoding="utf-8") as f:
    reader = csv.reader(f)
    # 读取表头匹配字段位置
    header = next(reader)
    county_idx = header.index("county")
    state_idx = header.index("state")
    cases_idx = header.index("confirmed_cases")
    deaths_idx = header.index("confirmed_deaths")
    
    for row in reader:
        state = row[state_idx].strip()
        county = row[county_idx].strip()
        # 数值转整数，空值默认填0可根据需求调整
        cases = int(row[cases_idx]) if row[cases_idx].strip().isdigit() else 0
        deaths = int(row[deaths_idx]) if row[deaths_idx].strip().isdigit() else 0
        covid_dict[(state, county)] = [cases, deaths]

2. 统计指定州累计确诊死亡总和 #

def count_state_deaths(target_state: str, covid_dict: dict) -> int:
    total = 0
    for (state, _), (_, deaths) in covid_dict.items():
        if state == target_state:
            total += deaths
    return total

# 示例：统计阿拉巴马州的死亡总和
alabama_deaths = count_state_deaths("Alabama", covid_dict)
print(alabama_deaths)

3. 统计确诊病例落在指定区间的县域数量 #

def count_counties_in_case_range(low: int, high: int, covid_dict: dict) -> int:
    count = 0
    for cases, _ in covid_dict.values():
        if low <= cases <= high:
            count += 1
    return count

# 示例：统计确诊在1000到10000之间的县数量
range_count = count_counties_in_case_range(1000, 10000, covid_dict)
print(range_count)

二、各州人口数据及死亡密度计算 #

1. 生成州名到最新人口的字典 #

pop_dict = {}
with open("替换为你的人口数据文件路径.csv", "r", encoding="utf-8") as f:
    reader = csv.reader(f)
    for row in reader:
        if not row:
            continue
        # 首个字段去除前导点得到州名
        state = row[0].lstrip(".").strip()
        # 末尾字段转整数为最新人口，空值处理可按需调整
        pop = int(row[-1]) if row[-1].strip().isdigit() else 0
        pop_dict[state] = pop

2. 计算各州确诊死亡密度 #

注：密度默认单位为每10万人死亡数，可按需调整倍数；未匹配到人口的州会自动跳过

# 先预统计所有州的累计死亡数
state_total_deaths = {}
for (state, _), (_, deaths) in covid_dict.items():
    state_total_deaths[state] = state_total_deaths.get(state, 0) + deaths

state_death_density = {}
for state, deaths in state_total_deaths.items():
    pop = pop_dict.get(state, 0)
    if pop > 0:
        state_death_density[state] = round(deaths / pop * 100000, 2)

3. 计算全美总确诊死亡密度 #

us_total_deaths = sum(state_total_deaths.values())
us_total_pop = sum(pop for pop in pop_dict.values() if pop > 0)
us_total_density = round(us_total_deaths / us_total_pop * 100000, 2) if us_total_pop > 0 else 0
print(f"全美每10万人确诊死亡密度为：{us_total_density}")

内容的提问来源于stack exchange，提问作者Answersplease