| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263 |
- # -*- coding: utf-8 -*-
- """生成示例销售数据集 sample_sales.csv（100 条记录，<1MB）"""
- import csv
- import random
- from datetime import date, timedelta
- random.seed(42)
- REGIONS = ["华东", "华北", "华南", "西南", "东北"]
- PRODUCTS = {
- "智能手机": ("数码电子", 3999),
- "笔记本电脑": ("数码电子", 5999),
- "无线耳机": ("数码电子", 499),
- "电饭煲": ("家用电器", 399),
- "空气净化器": ("家用电器", 1899),
- "电动牙刷": ("个护健康", 299),
- "按摩仪": ("个护健康", 899),
- }
- CHANNELS = ["线上商城", "线下门店", "直播带货"]
- rows = []
- start = date(2025, 1, 1)
- for i in range(97):
- product, (category, price) = random.choice(list(PRODUCTS.items()))
- quantity = random.randint(1, 20)
- # 区域系数：华东/华南销售额偏高
- region = random.choices(REGIONS, weights=[30, 22, 25, 13, 10])[0]
- region_factor = {"华东": 1.2, "华北": 1.0, "华南": 1.15, "西南": 0.8, "东北": 0.7}[region]
- sales = round(price * quantity * region_factor * random.uniform(0.85, 1.15), 2)
- d = start + timedelta(days=random.randint(0, 180))
- rows.append({
- "order_id": f"ORD2025{i:04d}",
- "order_date": d.isoformat(),
- "region": region,
- "channel": random.choice(CHANNELS),
- "product": product,
- "category": category,
- "unit_price": float(price),
- "quantity": quantity,
- "sales_amount": sales,
- "customer_satisfaction": round(random.uniform(3.0, 5.0), 1) if random.random() > 0.08 else "",
- })
- # 人为制造数据质量问题：缺失值 + 重复行
- rows[5]["sales_amount"] = "" # 缺失销售额
- rows[20]["region"] = "" # 缺失区域
- rows[40]["customer_satisfaction"] = ""
- rows[66]["sales_amount"] = ""
- rows.append(dict(rows[10])) # 3 条重复行
- rows.append(dict(rows[33]))
- rows.append(dict(rows[71]))
- random.shuffle(rows)
- fieldnames = ["order_id", "order_date", "region", "channel", "product", "category",
- "unit_price", "quantity", "sales_amount", "customer_satisfaction"]
- out = "data/sample_sales.csv"
- with open(out, "w", newline="", encoding="utf-8-sig") as f:
- writer = csv.DictWriter(f, fieldnames=fieldnames)
- writer.writeheader()
- writer.writerows(rows)
- print(f"已生成 {out}，共 {len(rows)} 条记录")
|
