如何将文本文件数据整理为嵌套字典以统计每日商品销量？

原始数据格式 #

DAY:Monday
Banana,Banana,Dragon Fruit
Dragon Fruit,Ice Pops,Ice Pops
Eggs,Dragon Fruit,Hamburger Buns,Dragon Fruit,Carrot,Apple,Banana
Ice Pops,Carrot,Dragon Fruit,Banana,Eggs,Eggs,Eggs,Eggs
DAY:Tuesday
Banana,Hamburger Buns,Dragon Fruit,Ice Pops
Hamburger Buns,Dragon Fruit,Dragon Fruit,Carrot,Apple,Carrot,Carrot,Eggs,Apple,Ice Pops
Carrot,Ice Pops,Apple,Dragon Fruit,Ice Pops,Apple,Banana,Eggs
Banana,Carrot,Eggs,Carrot,Eggs,Apple,Eggs
Carrot,Eggs,Hamburger Buns,Dragon Fruit,Apple,Hamburger Buns,Carrot,Dragon Fruit
Dragon Fruit,Ice Pops,Hamburger Buns,Hamburger Buns,Banana,Hamburger Buns,Carrot
DAY:Wednesday
Banana,Banana,Ice Pops
Apple,Carrot,Hamburger Buns
Apple,Carrot,Carrot,Carrot,Dragon Fruit,Carrot,Apple,Carrot,Dragon Fruit,Hamburger Buns
Apple,Hamburger Buns,Dragon Fruit,Ice Pops

现有代码问题 #

你已分别实现了日期字典的创建和单行商品统计，但未将两者关联，导致统计结果无法对应到正确日期下。

创建日期主字典的代码 #

weekly_sales = {}
source:str
purchases = []
for line in data_purchases:
    
    if line.split(":")[0] == "DAY": #Had to separate between the header and the rest. Once this statement is done, it would remove the first row
        source = line.strip().rpartition(":")[-1]
        if source not in weekly_sales:
            weekly_sales[source] = {}

单行商品统计代码 #

for line in data_purchases:
    if line.split(":")[0] == "DAY":
        line = next(data_purchases) 
        
        wordsCount = {}
        for item in line.split(",")[1:]: #.split so i can get each element in the lime
            item = item.strip() #strip \n from the elements. otherwise, the output would look like Dragon Fruit\n for instance
            if item not in wordsCount:
                wordsCount[item] = 1
            else:
                wordsCount[item] += 1
                    
    else: #for every other line of the data
        wordsCount = {}
        for item in line.split(','):
            item = item.strip()
            if item not in wordsCount:
                wordsCount[item] = 1
            else:
                wordsCount[item] += 1  

解决方案 #

将两个逻辑合并为一个循环，通过current_day变量跟踪当前处理的日期，同时完成单行统计和结果关联，还能同时计算每行统计和每日总销量：

weekly_sales = {}
current_day = None

for line in data_purchases:
    line = line.strip()
    if not line:  # 跳过空行
        continue
    
    if line.startswith("DAY:"):
        # 提取当前日期名称
        current_day = line.split(":")[-1].strip()
        # 初始化日期对应的嵌套结构：同时存储每行统计和每日总销量
        weekly_sales[current_day] = {
            "daily_total": {},  # 每日各商品总销量
            "line_stats": []    # 每行的商品统计结果列表
        }
    else:
        if current_day is None:
            continue  # 无对应日期的行直接跳过
        
        # 统计当前行的商品出现次数
        line_count = {}
        items = [item.strip() for item in line.split(",")]
        for item in items:
            # 用get方法简化计数逻辑，无需if-else判断
            line_count[item] = line_count.get(item, 0) + 1
        
        # 将单行统计结果存入当前日期的line_stats
        weekly_sales[current_day]["line_stats"].append(line_count)
        
        # 累计到每日总销量
        for item, count in line_count.items():
            weekly_sales[current_day]["daily_total"][item] = weekly_sales[current_day]["daily_total"].get(item, 0) + count

代码说明 #

1. 跟踪当前日期：用current_day变量记录正在处理的日期，避免分开循环导致的关联断层。
2. 嵌套结构初始化：每个日期下同时维护daily_total（累计总销量）和line_stats（每行明细统计），满足你两个核心需求。
3. 简化计数逻辑：使用dict.get(key, default)方法替代if-else判断，代码更简洁高效。
4. 结果关联：处理非日期行时，直接将统计结果关联到当前日期对应的字典中，无需额外操作。

示例输出（部分） #

打印weekly_sales["Monday"]["daily_total"]会得到：

{
    'Banana': 4,
    'Dragon Fruit': 5,
    'Ice Pops': 3,
    'Eggs': 5,
    'Hamburger Buns': 1,
    'Carrot': 2,
    'Apple': 1
}

内容的提问来源于stack exchange，提问作者Charl Margaux Elcano