R fromJSON - $ 运算符对原子向量无效

【问题标题】：R fromJSON - $ operator is invalid for atomic vectorsR fromJSON - $ 运算符对原子向量无效
【发布时间】：2017-07-08 21:47:01
【问题描述】：

为什么会出现以下错误：

Error: $ operator is invalid for atomic vectors

我的一个简单测试的虚拟代码：

l <- fromJSON('[{"winner":"68694999",  "votes":[
   {"ts":"Thu Mar 25 03:13:01 UTC 2010", "user":{"name":"Lamur","user_id":"68694999"}},
   {"ts":"Thu Mar 25 03:13:08 UTC 2010", "user":{"name":"Lamur","user_id":"68694999"}}],
  "lastVote":{"timestamp":1269486788526,"user":
   {"name":"Lamur","user_id":"68694999"}},"startPrice":0}]'
)

for(i in l) {
    print(i$votes)
}

我只想从votes获取数据

有什么想法吗？

这是我需要从中提取数据的更复杂的 json：

json <- '[{
    "data": {
        "dailysummary": [{
            "date": {
                "pretty": "12:20 AM BST on June 28, 2017",
                "year": "2017",
                "mon": "06",
                "mday": "28",
                "hour": "00",
                "min": "20",
                "tzname": "Europe/London"
            },
            "fog": "0",
            "rain": "1",
            "snow": "0",
            "snowfallm": "",
            "snowfalli": "",
            "monthtodatesnowfallm": "",
            "monthtodatesnowfalli": "",
            "since1julsnowfallm": "",
            "since1julsnowfalli": "",
            "snowdepthm": "",
            "snowdepthi": "",
            "hail": "0",
            "thunder": "0",
            "tornado": "0",
            "meantempm": "16",
            "meantempi": "60",
            "meandewptm": "13",
            "meandewpti": "56",
            "meanpressurem": "997.19",
            "meanpressurei": "29.45",
            "meanwindspdm": "9",
            "meanwindspdi": "6",
            "meanwdire": "NW",
            "meanwdird": "326",
            "meanvism": "8.9",
            "meanvisi": "5.5",
            "humidity": "86",
            "maxtempm": "17",
            "maxtempi": "62",
            "mintempm": "14",
            "mintempi": "57",
            "maxhumidity": "100",
            "minhumidity": "77",
            "maxdewptm": "15",
            "maxdewpti": "59",
            "mindewptm": "10",
            "mindewpti": "50",
            "maxpressurem": "1001",
            "maxpressurei": "29.56",
            "minpressurem": "996",
            "minpressurei": "29.42",
            "maxwspdm": "18",
            "maxwspdi": "12",
            "minwspdm": "6",
            "minwspdi": "4",
            "maxvism": "10.0",
            "maxvisi": "6.2",
            "minvism": "4.5",
            "minvisi": "2.8",
            "gdegreedays": "10",
            "heatingdegreedays": "6",
            "coolingdegreedays": "0",
            "precipm": "0.0",
            "precipi": "0.00",
            "precipsource": "3Or6HourObs",
            "heatingdegreedaysnormal": "",
            "monthtodateheatingdegreedays": "",
            "monthtodateheatingdegreedaysnormal": "",
            "since1sepheatingdegreedays": "",
            "since1sepheatingdegreedaysnormal": "",
            "since1julheatingdegreedays": "",
            "since1julheatingdegreedaysnormal": "",
            "coolingdegreedaysnormal": "",
            "monthtodatecoolingdegreedays": "",
            "monthtodatecoolingdegreedaysnormal": "",
            "since1sepcoolingdegreedays": "",
            "since1sepcoolingdegreedaysnormal": "",
            "since1jancoolingdegreedays": "",
            "since1jancoolingdegreedaysnormal": ""
        }],
        "airport": "LCY"
    },
    "date": "2017-06-28"
},{
    "data": {
        "dailysummary": [{
            "date": {
                "pretty": "12:20 AM BST on June 29, 2017",
                "year": "2017",
                "mon": "06",
                "mday": "29",
                "hour": "00",
                "min": "20",
                "tzname": "Europe/London"
            },
            "fog": "0",
            "rain": "0",
            "snow": "0",
            "snowfallm": "",
            "snowfalli": "",
            "monthtodatesnowfallm": "",
            "monthtodatesnowfalli": "",
            "since1julsnowfallm": "",
            "since1julsnowfalli": "",
            "snowdepthm": "",
            "snowdepthi": "",
            "hail": "0",
            "thunder": "0",
            "tornado": "0",
            "meantempm": "16",
            "meantempi": "60",
            "meandewptm": "11",
            "meandewpti": "51",
            "meanpressurem": "995.85",
            "meanpressurei": "29.41",
            "meanwindspdm": "14",
            "meanwindspdi": "9",
            "meanwdire": "WSW",
            "meanwdird": "256",
            "meanvism": "10.0",
            "meanvisi": "6.2",
            "humidity": "71",
            "maxtempm": "18",
            "maxtempi": "64",
            "mintempm": "13",
            "mintempi": "55",
            "maxhumidity": "82",
            "minhumidity": "63",
            "maxdewptm": "11",
            "maxdewpti": "52",
            "mindewptm": "10",
            "mindewpti": "50",
            "maxpressurem": "999",
            "maxpressurei": "29.50",
            "minpressurem": "994",
            "minpressurei": "29.36",
            "maxwspdm": "24",
            "maxwspdi": "15",
            "minwspdm": "9",
            "minwspdi": "6",
            "maxvism": "10.0",
            "maxvisi": "6.2",
            "minvism": "10.0",
            "minvisi": "6.2",
            "gdegreedays": "10",
            "heatingdegreedays": "6",
            "coolingdegreedays": "0",
            "precipm": "0.0",
            "precipi": "0.00",
            "precipsource": "3Or6HourObs",
            "heatingdegreedaysnormal": "",
            "monthtodateheatingdegreedays": "",
            "monthtodateheatingdegreedaysnormal": "",
            "since1sepheatingdegreedays": "",
            "since1sepheatingdegreedaysnormal": "",
            "since1julheatingdegreedays": "",
            "since1julheatingdegreedaysnormal": "",
            "coolingdegreedaysnormal": "",
            "monthtodatecoolingdegreedays": "",
            "monthtodatecoolingdegreedaysnormal": "",
            "since1sepcoolingdegreedays": "",
            "since1sepcoolingdegreedaysnormal": "",
            "since1jancoolingdegreedays": "",
            "since1jancoolingdegreedaysnormal": ""
        }],
        "airport": "LCY"
    },
    "date": "2017-06-29"
}]'

l <- fromJSON(json, ,flatten=TRUE)

我需要把它变成一个新的数据框：

airport key_date        ws      wd      tempi humidity
LCY     2017-06-28      x       x       x       x
LCY     2017-06-29      x       x       x       x

这是我的旧代码，但它不再适用于来自 json 的 l 数据帧：

# Initialize a data frame.
weatherDf <- data.frame()

# Set key conditions for checking later.
keyConditions <- c("meanwindspdi", "meanwdird", "meantempm", "humidity")

for(i in l) {
    # Get the airport code.
    airport <- i$airport

    # Get the date.
    date <- as.POSIXct(as.numeric(as.character(i$date))/1000, origin="1970-01-01", tz="UTC-1")

    # Get the data in dailysummary only.
    dailySummary <- i$dailysummary

    # print(all(keyConditions %in% names(dailySummary)))

    # Make sure key conditions exist in dailySummary,
    # then use rbind or will get 'numbers of columns of arguments do not match'
    if (all(keyConditions %in% names(dailySummary))) {
        weatherDf <- rbind(weatherDf, ldply(
            list(dailySummary),
            function(x) c(airport, format(as.Date(date), "%Y-%m-%d"), x[["meanwindspdi"]], x[["meanwdird"]], x[["meantempm"]], x[["humidity"]])
        ))
    }
}

# Rename column names.
colnames(weatherDf) <- c("airport", "key_date", "ws", "wd", "tempi", 'humidity')

# Convert certain columns weatherDf type to numberic.
columns <-c("ws", "wd", "tempi", "humidity")
weatherDf[, columns] <- lapply(columns, function(x) as.numeric(weatherDf[[x]]))

编辑：

weatherDf <- data.frame()
for(i in 1:nrow(l)) {
    row <- l[i,]
    # do stuff with row

    # Get the date.
    date <- row$date

    # Get the airport code.
    airport <- row$data.airport
    print(airport)

    # Get the data in dailysummary only.
    dailySummary <- row$data.dailysummary

    # print(all(keyConditions %in% names(dailySummary)))
    weatherDf <- rbind(weatherDf, ldply(
        list(dailySummary),
        function(x) c(airport, format(as.Date(date), "%Y-%m-%d"), x[["meanwindspdi"]], x[["meanwdird"]], x[["meantempm"]], x[["humidity"]])
    ))
}

编辑 2：

dailySummary <- row$data.dailysummary
print(names(dailySummary))

结果：

NULL

我想得到什么：

[1] "fog"                                "rain"                               "snow"                              
 [4] "snowfallm"                          "snowfalli"                          "monthtodatesnowfallm"              
 [7] "monthtodatesnowfalli"               "since1julsnowfallm"                 "since1julsnowfalli"                
[10] "snowdepthm"                         "snowdepthi"                         "hail"                              
[13] "thunder"                            "tornado"                            "meantempm"                         
[16] "meantempi"                          "meandewptm"                         "meandewpti"                        
[19] "meanpressurem"                      "meanpressurei"                      "meanwindspdm"                      
[22] "meanwindspdi"                       "meanwdire"                          "meanwdird"                         
[25] "meanvism"                           "meanvisi"                           "humidity"                          
[28] "maxtempm"                           "maxtempi"                           "mintempm"                          
[31] "mintempi"                           "maxhumidity"                        "minhumidity"                       
[34] "maxdewptm"                          "maxdewpti"                          "mindewptm"                         
[37] "mindewpti"                          "maxpressurem"                       "maxpressurei"                      
[40] "minpressurem"                       "minpressurei"                       "maxwspdm"                          
[43] "maxwspdi"                           "minwspdm"                           "minwspdi"                          
[46] "maxvism"                            "maxvisi"                            "minvism"                           
[49] "minvisi"                            "gdegreedays"                        "heatingdegreedays"                 
[52] "coolingdegreedays"                  "precipm"                            "precipi"                           
[55] "precipsource"                       "heatingdegreedaysnormal"            "monthtodateheatingdegreedays"      
[58] "monthtodateheatingdegreedaysnormal" "since1sepheatingdegreedays"         "since1sepheatingdegreedaysnormal"  
[61] "since1julheatingdegreedays"         "since1julheatingdegreedaysnormal"   "coolingdegreedaysnormal"           
[64] "monthtodatecoolingdegreedays"       "monthtodatecoolingdegreedaysnormal" "since1sepcoolingdegreedays"        
[67] "since1sepcoolingdegreedaysnormal"   "since1jancoolingdegreedays"         "since1jancoolingdegreedaysnormal"  
[70] "date.pretty"                        "date.year"                          "date.mon"                          
[73] "date.mday"                          "date.hour"                          "date.min"                          
[76] "date.tzname"                       
 [1] "fog"                                "rain"                               "snow"                              
 [4] "snowfallm"                          "snowfalli"                          "monthtodatesnowfallm"              
 [7] "monthtodatesnowfalli"               "since1julsnowfallm"                 "since1julsnowfalli"                
[10] "snowdepthm"                         "snowdepthi"                         "hail"                              
[13] "thunder"                            "tornado"                            "meantempm"                         
[16] "meantempi"                          "meandewptm"                         "meandewpti"                        
[19] "meanpressurem"                      "meanpressurei"                      "meanwindspdm"                      
[22] "meanwindspdi"                       "meanwdire"                          "meanwdird"                         
[25] "meanvism"                           "meanvisi"                           "humidity"                          
[28] "maxtempm"                           "maxtempi"                           "mintempm"                          
[31] "mintempi"                           "maxhumidity"                        "minhumidity"                       
[34] "maxdewptm"                          "maxdewpti"                          "mindewptm"                         
[37] "mindewpti"                          "maxpressurem"                       "maxpressurei"                      
[40] "minpressurem"                       "minpressurei"                       "maxwspdm"                          
[43] "maxwspdi"                           "minwspdm"                           "minwspdi"                          
[46] "maxvism"                            "maxvisi"                            "minvism"                           
[49] "minvisi"                            "gdegreedays"                        "heatingdegreedays"                 
[52] "coolingdegreedays"                  "precipm"                            "precipi"                           
[55] "precipsource"                       "heatingdegreedaysnormal"            "monthtodateheatingdegreedays"      
[58] "monthtodateheatingdegreedaysnormal" "since1sepheatingdegreedays"         "since1sepheatingdegreedaysnormal"  
[61] "since1julheatingdegreedays"         "since1julheatingdegreedaysnormal"   "coolingdegreedaysnormal"           
[64] "monthtodatecoolingdegreedays"       "monthtodatecoolingdegreedaysnormal" "since1sepcoolingdegreedays"        
[67] "since1sepcoolingdegreedaysnormal"   "since1jancoolingdegreedays"         "since1jancoolingdegreedaysnormal"  
[70] "date.pretty"                        "date.year"                          "date.mon"                          
[73] "date.mday"                          "date.hour"                          "date.min"                          
[76] "date.tzname"

【问题讨论】：

    标签： json r dataframe


    【解决方案1】：

    为什么不直接通过l$votes 访问数据？

    您使用的for 循环毫无意义。它没有将i 定义为l，而是将数据框l 的列输入到循环中，即“winner”、“votes”、“lastvote”和“startprice”。

    错误来自您尝试将$-indexing 与字符向量l$winner 一起使用，尝试打印l$winner$votes。

    编辑：这是您提供的新数据框的代码

    day_n <- length(l$data.dailysummary) # number of days
weather <- NULL; # daily summary data will be saved here

for (i in 1:day_n){
  weather <- rbind(weather, c(ws=as.numeric(l$data.dailysummary[[i]]$meanwindspdi),
                              wd=as.numeric(l$data.dailysummary[[i]]$meanwdird),
                              tempi=as.numeric(l$data.dailysummary[[i]]$meantempm),
                              humidity=as.numeric(l$data.dailysummary[[i]]$humidity))
        )
}

# make matrix of weather data for every day
# l$data.dailysummary is a list, containing the weather data in data frames for each day
# these data frames are accessed by l$data.dailysummary[[i]], to get the desired data

out <- data.frame(airport=l$data.airport, key_date=as.Date(l$date), 
                  weather, stringsAsFactors = F)

    我们得到了您在问题中要求的数据框：

    > str(out)
'data.frame':   2 obs. of  6 variables:
 $ airport : chr  "LCY" "LCY"
 $ key_date: Date, format: "2017-06-28" "2017-06-29"
 $ ws      : num  6 9
 $ wd      : num  326 256
 $ tempi   : num  16 16
 $ humidity: num  86 71
> out
  airport   key_date ws  wd tempi humidity
1     LCY 2017-06-28  6 326    16       86
2     LCY 2017-06-29  9 256    16       71

    【讨论】：

    • 谢谢。我有一排votes 我需要将它们转换成一个新的数据框。
    • @teelou 我添加了新数据的代码。它能解决你的问题吗？
    • 您必须更加小心，您正在使用哪些数据类型 - 您尝试在 dailySummary 上应用 ldply，它是一个仅包含一个元素（数据框）的列表。因此，rbind 只获取“机场”和“日期”数据。我看看能不能解决。
    • @teelou 如果将ldply 函数中的函数替换为function(x) c(airport, format(as.Date(date), "%Y-%m-%d"), x[[1]]$meanwindspdi, x[[1]]$meanwdird, x[[1]]$meantempm, x[[1]]$humidity)，它应该可以工作。
    • 正如“您必须更加小心...”评论中指出的那样，您必须使用 print(names(dailySummary[[1]])) 来访问数据框中的名称...再次：dailysummary 是一个包含 data.frame 的 list。如果要访问数据框，必须使用dailySummary[[1]]。
    【解决方案2】：

    l$votes 是一个列表。如果您需要在具有这种格式的列表中循环遍历其中的多个，则可以使用相对较新的 purrr 包：

    purrr::walk(l, ~ print(.x[[1]] ))

    如果你想做一个循环，打印出你展示的 json 结构中每个项目的整个数据框，这样可以工作：

    for(i in l){
  print(i[[1]])
}

    【讨论】：

    • 我有一排votes 我需要将它们转换成一个新的数据框。我不认为print(i[[1]]) 有帮助。
    • 如果所有选票都出现在获胜者：68694999 下，那么这应该有效。如果不是，并且您需要其他具有其他投票的获胜者，那么您的示例数据未包含完整结构。
    猜你喜欢
    • 1970-01-01
    • 2021-08-20
    • 2014-05-15
    • 2013-07-14
    • 1970-01-01
    • 1970-01-01
    • 2018-08-23
    • 1970-01-01
    • 1970-01-01
    相关资源
    最近更新 更多
    热门标签
    Java Python linux javascript Mysql C# Docker 算法 前端 SpringBoot Redis Vue spring 设计模式 .net core .net kubernetes c++ 数据库 数据结构 大数据 js 机器学习 微服务 Android Go 程序员 面试 JVM ASP.net core 云原生 人工智能 后端 PHP git CSS golang k8s Nginx Django mybatis 深度学习 多线程 React 架构 devops 爬虫 云计算 Spring Boot LeetCode