Python 展平深度嵌套的JSON垂直转换为熊猫

您好，我正在尝试展平JSON文件，但无法。我的JSON有3个缩进重复示例，如下所示

floors": [
        {
            "uuid": "8474",
            "name": "some value",
            "areas": [
                {
                    "uuid": "xyz",
                    "**name**": "qwe",
                    "roomType": "Name1",
                    "templateUuid": "sdklfj",
                    "templateName": "asdf",
                    "templateVersion": "2.7.1",
                    "Required1": [
                        {
                            "**uuid**": "asdf",
                            "description": "asdf3",
                            "categoryName": "asdf",
                            "familyName": "asdf",
                            "productName": "asdf3",
                            "Required2": [
                                {
                                    "**deviceId**": "asdf",
                                    "**deviceUuid**": "asdf-asdf"
                                }
                            ]
                        }

我想要嵌套Required1中对应的区域值和Required1对应的required 2中对应的区域值。（在**中突出显示） 我尝试了JSON规范化，如下所示，但失败，其他免费LIB：

尝试： 没有显示区域值。仅需要1个需要2个仍然嵌套

---

希望获得以下值： 预期列数： 楼层.区域.需要1.需要2.设备UUID 楼层、区域、名称 （并排）

---

如果我在尝试中遗漏了什么，请帮助我。我对JSON加载相当陌生。

假设以下JSON（正如许多人指出的，它是不完整的）。所以我根据你的支架开口完成了它

dct = {"floors": [
        {
            "uuid": "8474",
            "name": "some value",
            "areas": [
                {
                    "uuid": "xyz",
                    "name": "qwe",
                    "roomType": "Name1",
                    "templateUuid": "sdklfj",
                    "templateName": "asdf",
                    "templateVersion": "2.7.1",
                    "Required1": [
                        {
                            "uuid": "asdf",
                            "description": "asdf3",
                            "categoryName": "asdf",
                            "familyName": "asdf",
                            "productName": "asdf3",
                            "Required2": [
                                {
                                    "deviceId": "asdf",
                                    "deviceUuid": "asdf-asdf"
                                }
                            ]
                        }
                    ]
                }
            ]
        }
]}

您可以执行以下操作（需要0.25.0）

这就给了,

>>>     floors.areas.name   uuid    deviceId    deviceUuid
>>> 0   qwe asdf    asdf    asdf-asdf

---

您的初始json有一些错误，您能纠正它吗？嗨，DataNearoor，{“floor:：{}”，val1:：{“areas:：{“val2:：{}}”，Devices:：{“val3:：：{}}val1嵌套在val2中，val3中嵌套在val2中。需要将所有内容都放在一行中，下一行则是添加新值并垂直向下移动，您可以使用预期的输出进行更新吗？表中包含以下列：name | uuid | deviceId | deviceUuid@user3280146Hi@thushv89，感谢您的回复，并对延迟确认您的解决方案表示抱歉。不幸的是，如果有两级嵌套，那么这个解决方案工作得很好。假设所需的2个标记有多个条目。你有没有一个解决方案？下面的评论有一个例子。假设一个必需的1“Required2”有许多必需的2:[{“deviceId”：“asdf”，“deviceUuid”：“asdf asdf”}，{“deviceId”：“bhgk”，“deviceUuid”：“bhgk bhgk”}]@superetbose，您能用示例和所需输出编辑您的问题吗？

from flatten_json import flatten_json
Flat_J1= pd.DataFrame([flatten_json(data_item)]) 

dct = {"floors": [
        {
            "uuid": "8474",
            "name": "some value",
            "areas": [
                {
                    "uuid": "xyz",
                    "name": "qwe",
                    "roomType": "Name1",
                    "templateUuid": "sdklfj",
                    "templateName": "asdf",
                    "templateVersion": "2.7.1",
                    "Required1": [
                        {
                            "uuid": "asdf",
                            "description": "asdf3",
                            "categoryName": "asdf",
                            "familyName": "asdf",
                            "productName": "asdf3",
                            "Required2": [
                                {
                                    "deviceId": "asdf",
                                    "deviceUuid": "asdf-asdf"
                                }
                            ]
                        }
                    ]
                }
            ]
        }
]}

df = pd.io.json.json_normalize(
    dct, record_path=['floors','areas', 'Required1'],meta=[['floors', 'areas', 'name']])
df = df.explode('Required2')
df = pd.concat([df, df["Required2"].apply(pd.Series)], axis=1)
df = df[['floors.areas.name', 'uuid', 'deviceId', 'deviceUuid']]

>>>     floors.areas.name   uuid    deviceId    deviceUuid
>>> 0   qwe asdf    asdf    asdf-asdf