将 R 数据框转换为自定义 json答案

【问题标题】：Convert R data frame to custom json将 R 数据框转换为自定义 json
【发布时间】：2021-09-27 23:04:27
【问题描述】：

我想在最后将数据框更改为自定义 json 格式。标签是从日期和压力列创建的，名称是值，列名是组名和需要。

以下是生成用于复制此问题的数据框的方法

    df<-setNames(
  data.frame(
    t(data.frame(c("",1,2,0,20,"2b9c5fb7-72a4-4482-baa1-34cc37522d24","Yes","210521"),c("",2,3,20,40,"7f615aea-330f-4c67-8101-0ae501c793cd","No","210522")))
    ,row.names = NULL,stringsAsFactors = FALSE
  ), 
  c("notes","instanceNum","modifyCount","startTime","endTime","uniqueId","Pressure","Date")
)

这是所需的自定义 json 格式。任何指导表示赞赏

                    {
                        "labels": [
                            {
                                "name": "Yes",
                                "group": "Pressure"
                            },
                            {
                                "name": "210521",
                                "group": "Date"
                            }
                        ],
                        "notes": "",
                        "instanceNum": 1,
                        "modifyCount": 2,
                        "startTime": 0,
                        "endTime": 20,
                        "uniqueId": "2b9c5fb7-72a4-4482-baa1-34cc37522d24"
                    },
                    {
                        "labels": [
                            {
                                "name": "No",
                                "group": "Pressure"
                            },
                            {
                                "name": "210522",
                                "group": "Date"
                            }
                        ],
                        "notes": "",
                        "instanceNum": 2,
                        "modifyCount": 3,
                        "startTime": 20,
                        "endTime": 40,
                        "uniqueId": "7f615aea-330f-4c67-8101-0ae501c793cd"
                    }

【问题讨论】：

标签： r arrays json dataframe jsonlite

【解决方案1】：

试试这些选项：

基础R

melted <- reshape2::melt(df[,c("instanceNum","Pressure","Date")], 
                         id.vars="instanceNum", variable.name="group", value.name="name")
melted$group <- as.character(melted$group)
# "nest" the other columns against a single row of "instanceNum"`
melted <- by(melted, melted[,"instanceNum"], function(z) {
  out <- out <- z[1,1,drop=FALSE]
  out$labels <- list(z[,-1])
  out
})
df2 <- merge(df[,setdiff(names(df), c("Pressure", "Date"))],
             do.call(rbind, melted), by = "instanceNum")
df2
#   instanceNum notes modifyCount startTime endTime                             uniqueId                      labels
# 1           1                 2         0      20 2b9c5fb7-72a4-4482-baa1-34cc37522d24 Pressure, Date, Yes, 210521
# 2           2                 3        20      40 7f615aea-330f-4c67-8101-0ae501c793cd  Pressure, Date, No, 210522

jsonlite::toJSON(df2, pretty = TRUE) 的输出是：

[
  {
    "instanceNum": "1",
    "notes": "",
    "modifyCount": "2",
    "startTime": "0",
    "endTime": "20",
    "uniqueId": "2b9c5fb7-72a4-4482-baa1-34cc37522d24",
    "labels": [
      {
        "group": "Pressure",
        "name": "Yes"
      },
      {
        "group": "Date",
        "name": "210521"
      }
    ]
  },
  {
    "instanceNum": "2",
    "notes": "",
    "modifyCount": "3",
    "startTime": "20",
    "endTime": "40",
    "uniqueId": "7f615aea-330f-4c67-8101-0ae501c793cd",
    "labels": [
      {
        "group": "Pressure",
        "name": "No"
      },
      {
        "group": "Date",
        "name": "210522"
      }
    ]
  }
]

dplyr/tidyr

library(dplyr)
# library(tidyr) # pivot_longer, nest
df %>%
  select(instanceNum, Pressure, Date) %>%
  tidyr::pivot_longer(-instanceNum, names_to = "group", values_to = "name") %>%
  tidyr::nest(labels = c("group", "name")) %>%
  full_join(df, ., by = "instanceNum") %>%
  select(-Pressure, -Date) %>%
  jsonlite::toJSON(., pretty = TRUE)

【讨论】：