如何将层级字典转换为Pandas DataFrame（电池层级数据场景）

需求背景 #

需要将对应以下层级关系的嵌套字典转换为Pandas DataFrame，每一行对应一个电芯，包含其所属的城市、车辆、Pack、模块及电芯ID：

delhi = 10 vehicle
1 vehicle = 1 battery
1 battery = 4 packs
a pack = 2 modules 
1 module = 104 cells

示例与完整字典结构 #

示例字典 #

tempdict = {
    'vehicle1':[
        {'pack1':[{'module1':pack104}, {'module2':pack104}]}, 
        {'pack2':[{'module1':pack104}, {'module2':pack104}]}, 
        {'pack3':[{'module1':pack104}, {'module2':pack104}]}, 
        {'pack4':[{'module1':pack104}, {'module2':pack104}]}
    ]
}

完整字典 #

import itertools

listone = ['pack' ]
listtwo = ["{0}".format(i) for i in range(1,105)]
pack104 = list(''.join(e) for e in itertools.product(listone, listtwo))
data_dict = {'delhi': [{'vehicle1':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle2':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle3':[{'pack1':[{'module1':pack104}, {'module2':pack104}]},{ 'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle4':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle5':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle6':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle7':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle8':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle9':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]},
 {'vehicle10':[{'pack1':[{'module1':pack104}, {'module2':pack104}]}, {'pack2':[{'module1':pack104}, {'module2':pack104}]}, {'pack3':[{'module1':pack104}, {'module2':pack104}]}, {'pack4':[{'module1':pack104}, {'module2':pack104}]}]}]}

转换方法 #

通过多层循环遍历嵌套字典的每一层，收集每个电芯的完整层级信息，再转换为DataFrame：

import pandas as pd

# 初始化空列表存储每条电芯记录
records = []

# 遍历层级结构
for city, vehicles in data_dict.items():
    for vehicle_item in vehicles:
        for vehicle_name, packs in vehicle_item.items():
            for pack_item in packs:
                for pack_name, modules in pack_item.items():
                    for module_item in modules:
                        for module_name, cells in module_item.items():
                            for cell_id in cells:
                                records.append({
                                    '城市': city,
                                    '车辆': vehicle_name,
                                    'Pack': pack_name,
                                    '模块': module_name,
                                    '电芯ID': cell_id
                                })

# 转换为DataFrame
df = pd.DataFrame(records)

# 验证结果（可选）
print(df.head())

说明 #

• 这段代码逐层遍历嵌套字典，将每个电芯的所属城市、车辆、Pack、模块及自身ID存入字典，再统一存入列表records
• 最终用pd.DataFrame()将列表转换为结构化的DataFrame，每一行对应一个电芯的完整归属信息

内容的提问来源于stack exchange，提问作者Sachin Shinde