如何基于字典构建DataFrame并生成值组合与乘积列

直接用zip按索引匹配各键的取值，再计算乘积，最后组装成DataFrame：

import pandas as pd
import math  # Python3.8+支持math.prod，用于快速计算乘积

# 给定数据
names = [["name_0", "name_1"], ["name_2", "name_3"], ["name_2", "name_3", "name_4"]]
dict_1 = {"name_0": [1,2], "name_1": [1,2]}
dict_2 = {"name_2": [2,3], "name_3": [1,3]}
dict_3 = {"name_2": [2,3], "name_3": [1,3], "name_4": [2,3]}
data_3 = [dict_1, dict_2, dict_3]

# 收集每行数据
rows = []
for name_group, curr_dict in zip(names, data_3):
    # 按names列表的顺序提取对应值的列表，保证组合顺序正确
    value_lists = [curr_dict[name] for name in name_group]
    # 按索引打包所有值的组合（同位置元素配对）
    for combo in zip(*value_lists):
        # 计算组合的乘积
        product = math.prod(combo)
        # 添加到行列表
        rows.append({
            "names": name_group,
            "values": list(combo),
            "multi": product
        })

# 生成DataFrame
result_df = pd.DataFrame(rows)
print(result_df)

关键说明： #

• 按顺序匹配：通过[curr_dict[name] for name in name_group]确保提取的值列表顺序和names中的键顺序一致，避免字典键无序导致的错误。
• 同索引组合：zip(*value_lists)会把每个值列表的同索引元素打包成元组，正好对应你需要的values列内容。
• 兼容低版本Python：如果使用Python3.7及以下版本，替换math.prod(combo)为手动循环相乘即可：

  product = 1
  for num in combo:
      product *= num
  

运行后输出的DataFrame完全符合期望：

names      values  multi
0           [name_0, name_1]      [1, 1]      1
1           [name_0, name_1]      [2, 2]      4
2           [name_2, name_3]      [2, 1]      2
3           [name_2, name_3]      [3, 3]      9
4  [name_2, name_3, name_4]  [2, 1, 2]      4
5  [name_2, name_3, name_4]  [3, 3, 3]     27

内容的提问来源于stack exchange，提问作者shaftel