为什么我在下面收到此错误：
Error: $ operator is invalid for atomic vectors
我的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)
}
我只是希望关闭数据votes
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)
我需要将其转换为新的数据框：
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数据框：
# 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]]))
修改
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
我想要得到的东西：
[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"
答案 0 :(得分：1)
为什么不按l$votes访问数据？
您正在使用的for循环毫无意义。它没有将i定义为l，而是将数据框l的列提供给循环，即＆＃34;赢家＆＃34;，＆＃34;投票＆＃ 34;，＆＃34; lastvote＆＃34;和＆＃34; startprice＆＃34;。
错误来自于您尝试使用$ - 使用字符向量l$winner建立索引，尝试打印l$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)
我们会在问题中找到您要求的数据框：
> 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
答案 1 :(得分：0)
l $ votes是一个列表。如果你需要在具有这种格式的列表中循环遍历这些格式的多个，这可能使用相对较新的purrr包：
purrr::walk(l, ~ print(.x[[1]] ))
如果你想做一个循环，打印出你所展示的json结构中每个项目的整个数据框，这样的东西可以工作：
for(i in l){
print(i[[1]])
}