在解析 JSON 文件时，如何处理按原样导入的“{key:value}”对的存在？

Question

我有一个标准的 Android 设备状态 JSON 文件，我试图将其读取为 Pandas DF，然后将其导出到 Excel 文件。

我将文件的前两行粘贴到下面：

{"ageCorrectionFactor":{"d":"Age Correction Factor","i":"1252"},"backCamera":{"d":"Working Fine. No issues","i":"79"},"battery":{"d":"Working Fine. No issues","i":"86"},"bill":{"d":"No"},"bluetooth":{"d":"Working Fine. No issues"},"box":{"d":"No"},"boxHidden":{"d":"Box hidden","i":"467"},"cameraHidden":{"d":"Camera hidden ","i":"494"},"charger":{"d":"No","i":"87"},"chargerHidden":{"d":"Charger hidden","i":"476"},"chargingDefect":{"d":"Working Fine. No issues"},"chargingPortHidden":{"d":"Charging Port Hidden","i":"764"},"earphone":{"d":"No","i":"88"},"frontCamera":{"d":"Front Camera"},"hiddenBattery":{"d":"Hidden battery","i":"777"},"mobileAge":{"d":"Above 11 months","i":"97"},"physicalCondition":{"d":"Physical Condition","i":"800"},"powerButton":{"d":"Working Fine. No issues"},"screen":{"d":"Working Fine. No issues"},"screenHidden":{"d":"NA","i":"220"},"screenIssue":{"d":"Screen Touch Issue"},"speakers":{"d":"Working Fine. No issues"},"tmsPrice":{"d":"TMS Price Improvement"},"volumeButton":{"d":"Working Fine. No issues"},"wifiGpsBluetooth":{"d":"Working Fine. No issues"},"workingNonworking":{"d":"Yes","i":"76"}},
{"ageCorrectionFactor":{"d":"Age Correction Factor","i":"1252"},"backCamera":{"d":"Working Fine. No issues","i":"79"},"battery":{"d":"Working Fine. No issues"},"bill":{"d":"No","i":"90"},"bluetooth":{"d":"Working Fine. No issues"},"box":{"d":"No","i":"89"},"boxHidden":{"d":"Box hidden","i":"467"},"cameraHidden":{"d":"Camera hidden ","i":"496"},"charger":{"d":"No","i":"87"},"chargerHidden":{"d":"Charger hidden","i":"477"},"chargingDefect":{"d":"Working Fine. No issues"},"chargingPortHidden":{"d":"Charging Port Hidden","i":"764"},"earphone":{"d":"No","i":"88"},"frontCamera":{"d":"Front Camera"},"hiddenBattery":{"d":"Hidden battery","i":"779"},"mobileAge":{"d":"Above 11 months","i":"96"},"physicalCondition":{"d":"Physical Condition","i":"91"},"powerButton":{"d":"Working Fine. No issues"},"screen":{"d":"Working Fine. No issues"},"screenHidden":{"d":"NA","i":"219"},"screenIssue":{"d":"Screen Touch Issue"},"speakers":{"d":"Working Fine. No issues"},"tmsPrice":{"d":"TMS Price Improvement"},"volumeButton":{"d":"Working Fine. No issues"},"wifiGpsBluetooth":{"d":"Working Fine. No issues","i":"81"},"workingNonworking":{"d":"Yes"}},

现在我使用 read_json() 函数将文件转换为 Pandas 数据框对象，我得到以下结果（我在此处粘贴的整个第一行的一部分）:

>>> df.head(1)


ageCorrectionFactor  \
0  {u'i': u'1252', u'd': u'Age Correction Factor'}   

                                        backCamera  \
0  {u'i': u'79', u'd': u'Working Fine. No issues'}   

                                           battery           bill  \
0  {u'i': u'86', u'd': u'Working Fine. No issues'}  {u'd': u'No'}   

                            bluetooth            box  \
0  {u'd': u'Working Fine. No issues'}  {u'd': u'No'}

显然，问题是我无法分解内部 'key':'value' 对，所以我得到了不正确的输出。

此外，我使用正则表达式删除不需要的对，但我的动机是尽量不更改任何原始数据。

有什么方法可以使用 pandas 或正则表达式与 python 的原生 JSON 解析函数的组合来获得正确的输出？

在 R 中同样的操作产生了一个稍微令人信服的结果，

json_file <- fromJSON("E:/pathto/file.json")
json_file <- lapply(json_file, function(x) {
  x[sapply(x, is.null)] <- NA
  unlist(x)
})    
JSON_DF <- as.data.frame(do.call("rbind", json_file))

Answer 1

试试这个：

df = pd.io.json.json_normalize(f) #f is the json filename

它返回一个包含 40 列的数据框

Answer 2

尝试使用 Vaishali Garg 的方法，但首先使用 json 模块加载文件。

import json
import pandas as pd

with open('E:/pathto/file.json') as f:
    data = json.load(f)

df = pd.io.json.json_normalize(data)

在解析 JSON 文件时，如何处理按原样导入的“{key:value}”对的存在？

How do I handle the presence of `{key:value}' pairs that get imported as is when parsing a JSON file?

python

json

pandas

rjsonio