Python Pandas数据分析：实现利润最大化的进货方案

import pandas as pd

# 读取数据
data = pd.read_csv('data5.csv')

# 计算每种单品的收益和进货量
data['单品收益'] = data['销量'] * data['成本加成定价'] * (1 - data['单品损耗'] * 0.01) - data['销量'] * data['批发价格']
data['进货量'] = data['销量'] * (1 + data['单品损耗'] * 0.01)

# 按照单品收益降序排序
sorted_data = data.sort_values(by='单品收益', ascending=False)

# 初始化进货方案
purchase_plan = {}

# 设定目标进货种类范围
min_items = 27
max_items = 33

# 遍历排序后的单品
for index, row in sorted_data.iterrows():
    # 如果进货种类数达到最大值，则跳出循环
    if len(purchase_plan) >= max_items:
        break

    # 获取单品名称和进货量
    item = row['单品名称']
    quantity = row['进货量']

    # 如果进货种类数已达到最小值，且该商品不在方案中，则跳过
    if len(purchase_plan) >= min_items and item not in purchase_plan:
        continue

    # 添加进货方案
    purchase_plan[item] = quantity

# 计算总收益
total_profit = sorted_data['单品收益'].sum()

print('进货方案：')
for item, quantity in purchase_plan.items():
    print(f'{item}: {quantity}')

print('总收益：', total_profit)