R 读取和格式化多级、不均匀的JSON

我有一个JSON，如下所示

{
  "timestamps": [
    "2020-12-17T20:05:00Z",
    "2020-12-17T20:10:00Z",
    "2020-12-17T20:15:00Z",
    "2020-12-17T20:20:00Z",
    "2020-12-17T20:25:00Z",
    "2020-12-17T20:30:00Z"
  ],
  "properties": [
    {
      "values": [
        -20.58975828559592,
        -19.356728999226693,
        -19.808982964173023,
        -19.673928070777993,
        -19.712275037138411,
        -19.48422739982918
      ],
      "name": "Neg Flow",
      "type": "Double"
    },
    {
      "values": [
        2,
        20,
        19,
        20,
        19,
        16
      ],
      "name": "Event Count",
      "type": "Long"
    }
  ],
  "progress": 100.0
}

如何将其转换为如下所示的数据帧。虽然我能够循环遍历各个数据项，但我感兴趣的是，是否有一种圆滑的方法可以做到这一点

+----------------------+---------------------+-------------+
|Time Stamps           | Neg Flow            | Event Count |
+----------------------+---------------------+-------------+
|2020-12-17T20:05:00Z  |-20.58975828559592   | 2           |
+----------------------+---------------------+-------------+
|2020-12-17T20:10:00Z  |-19.356728999226693  | 20          |
+----------------------+---------------------+-------------+

---

这里有一个方法

library(jsonlite) # read json
library(dplyr) # maniputate data frame
library(magrittr) # for the use of %<>%

# temp.json is my file using the content you provided
json_data <- read_json("temp.json")

# initial data with timestamp
data <- tibble(`Time Stamps` = unlist(json_data[["timestamps"]]))

# properties process
for (property in json_data[["properties"]]) {
  property_name <- property[["name"]]
  # using dynamic namming for more reference please refer to link at end of post
  data %<>% mutate({{property_name}} := unlist(property[["values"]]))
}

library（jsonlite）#读取json
库（dplyr）#计算机数据帧
图书馆（magrittr）#供%%使用
#temp.json是使用您提供的内容的我的文件
json_数据您能否以可复制的形式提供数据，我们可以复制粘贴？@Ronaksah，上面的json文件就是数据。它可以复制！当我将它复制到R中时，它会返回许多错误消息，如“}”中的
error:unexpected'}'和“type”中的
error:“Long”：NA/NaN参数
以及其他许多错误消息。不知道如何复制它。
# A tibble: 6 x 3
  `Time Stamps`        `Neg Flow` `Event Count`
  <chr>                     <dbl>         <int>
1 2020-12-17T20:05:00Z      -20.6             2
2 2020-12-17T20:10:00Z      -19.4            20
3 2020-12-17T20:15:00Z      -19.8            19
4 2020-12-17T20:20:00Z      -19.7            20
5 2020-12-17T20:25:00Z      -19.7            19
6 2020-12-17T20:30:00Z      -19.5            16