Python 计算 CSV 数据集中不同类别的人均价格平均值

以下是使用Python语言解决这个问题的示例代码：

import csv
from collections import defaultdict

# 读取data.csv文件
data = []
with open('data.csv', 'r', encoding='utf-8') as file:
    reader = csv.reader(file)
    header = next(reader)  # 跳过头部行
    for row in reader:
        data.append(row)

# 统计不同餐厅种类的人均价格的平均值
category_prices = defaultdict(list)
for row in data:
    category = row[1]
    price = float(row[5])
    category_prices[category].append(price)

average_category_prices = {}
for category, prices in category_prices.items():
    average_price = sum(prices) / len(prices)
    average_category_prices[category] = average_price

# 统计不同所在地区的人均价格的平均值
area_prices = defaultdict(list)
for row in data:
    area = row[2]
    price = float(row[5])
    area_prices[area].append(price)

average_area_prices = {}
for area, prices in area_prices.items():
    average_price = sum(prices) / len(prices)
    average_area_prices[area] = average_price

# 统计不同评分的人均价格的平均值
rating_prices = defaultdict(list)
for row in data:
    rating = float(row[6])
    price = float(row[5])
    rating_prices[rating].append(price)

average_rating_prices = {}
for rating, prices in rating_prices.items():
    average_price = sum(prices) / len(prices)
    average_rating_prices[rating] = average_price

# 输出结果
print('不同餐厅种类的人均价格的平均值：')
for category, average_price in average_category_prices.items():
    print(f'{category}: {average_price}')

print('
不同所在地区的人均价格的平均值：')
for area, average_price in average_area_prices.items():
    print(f'{area}: {average_price}')

print('
不同评分的人均价格的平均值：')
for rating, average_price in average_rating_prices.items():
    print(f'{rating}: {average_price}')

你可以将上述代码保存为一个Python脚本，并确保在同一目录下有名为'data.csv'的CSV文件。然后运行脚本，你将获得输出结果，分别是不同餐厅种类的人均价格的平均值、不同所在地区的人均价格的平均值和不同评分的人均价格的平均值。