我有GPS日志中的数据，如下所示:(这些数据在数据框列的行中）
{"mAccuracy":20.0,"mAltitude":0.0,"mBearing":0.0,"mElapsedRealtimeNanos":21677339000000,"mExtras":{"networkLocationSource":"cached","networkLocationType":"wifi","noGPSLocation":{"mAccuracy":20.0,"mAltitude":0.0,"mBearing":0.0,"mElapsedRealtimeNanos":21677339000000,"mHasAccuracy":true,"mHasAltitude":false,"mHasBearing":false,"mHasSpeed":false,"mIsFromMockProvider":false,"mLatitude":35.1811956,"mLongitude":126.9104909,"mProvider":"network","mSpeed":0.0,"mTime":1402801381486},"travelState":"stationary"},"mHasAccuracy":true,"mHasAltitude":false,"mHasBearing":false,"mHasSpeed":false,"mIsFromMockProvider":false,"mLatitude":35.1811956,"mLongitude":126.9104909,"mProvider":"network","mSpeed":0.0,"mTime":1402801381486,"timestamp":1402801665.512}
问题是我只需要纬度和经度值，所以我认为我可以使用substring和sappy来应用数据帧中的所有数据。
但我不确定这种方式是否很帅，因为当我使用子串ex：substr("abcdef", 2, 4)时，我需要计算从开始到＃34; mLatitude＆＃34;那么任何人都能给出建议快速处理它的方法吗？
感谢@mnel回答问题，它的工作，但我仍然有问题
从mnel回答我已经创建了这样的功能：
fgps <- function(x) {
out <- fromJSON(x)
c(out$mExtras$noGPSLocation$mLatitude,
out$mExtras$noGPSLocation$mLongitude)
}
然后这是我的数据：
gpsdata <- head(dfallgps[,4],2)
[1] "{\"mAccuracy\":23.128,\"mAltitude\":0.0,\"mBearing\":0.0,\"mElapsedRealtimeNanos\":76437488000000,\"mExtras\":{\"networkLocationSource\":\"cached\",\"networkLocationType\":\"wifi\",\"noGPSLocation\":{\"mAccuracy\":23.128,\"mAltitude\":0.0,\"mBearing\":0.0,\"mElapsedRealtimeNanos\":76437488000000,\"mHasAccuracy\":true,\"mHasAltitude\":false,\"mHasBearing\":false,\"mHasSpeed\":false,\"mIsFromMockProvider\":false,\"mLatitude\":35.1779956,\"mLongitude\":126.9089661,\"mProvider\":\"network\",\"mSpeed\":0.0,\"mTime\":1402894224187},\"travelState\":\"stationary\"},\"mHasAccuracy\":true,\"mHasAltitude\":false,\"mHasBearing\":false,\"mHasSpeed\":false,\"mIsFromMockProvider\":false,\"mLatitude\":35.1779956,\"mLongitude\":126.9089661,\"mProvider\":\"network\",\"mSpeed\":0.0,\"mTime\":1402894224187,\"timestamp\":1402894517.425}"
[2] "{\"mAccuracy\":1625.0,\"mAltitude\":0.0,\"mBearing\":0.0,\"mElapsedRealtimeNanos\":77069916000000,\"mExtras\":{\"networkLocationSource\":\"cached\",\"networkLocationType\":\"cell\",\"noGPSLocation\":{\"mAccuracy\":1625.0,\"mAltitude\":0.0,\"mBearing\":0.0,\"mElapsedRealtimeNanos\":77069916000000,\"mHasAccuracy\":true,\"mHasAltitude\":false,\"mHasBearing\":false,\"mHasSpeed\":false,\"mIsFromMockProvider\":false,\"mLatitude\":35.1811881,\"mLongitude\":126.9084072,\"mProvider\":\"network\",\"mSpeed\":0.0,\"mTime\":1402894857416},\"travelState\":\"stationary\"},\"mHasAccuracy\":true,\"mHasAltitude\":false,\"mHasBearing\":false,\"mHasSpeed\":false,\"mIsFromMockProvider\":false,\"mLatitude\":35.1811881,\"mLongitude\":126.9084072,\"mProvider\":\"network\",\"mSpeed\":0.0,\"mTime\":1402894857416,\"timestamp\":1402894857.519}"
当运行sapply为什么数据仍然显示在结果中而不仅仅是结果值。
sapply(gpsdata, function(gpsdata) fgps(gpsdata))
{"mAccuracy":23.128,"mAltitude":0.0,"mBearing":0.0,"mElapsedRealtimeNanos":76437488000000,"mExtras":{"networkLocationSource":"cached","networkLocationType":"wifi","noGPSLocation":{"mAccuracy":23.128,"mAltitude":0.0,"mBearing":0.0,"mElapsedRealtimeNanos":76437488000000,"mHasAccuracy":true,"mHasAltitude":false,"mHasBearing":false,"mHasSpeed":false,"mIsFromMockProvider":false,"mLatitude":35.1779956,"mLongitude":126.9089661,"mProvider":"network","mSpeed":0.0,"mTime":1402894224187},"travelState":"stationary"},"mHasAccuracy":true,"mHasAltitude":false,"mHasBearing":false,"mHasSpeed":false,"mIsFromMockProvider":false,"mLatitude":35.1779956,"mLongitude":126.9089661,"mProvider":"network","mSpeed":0.0,"mTime":1402894224187,"timestamp":1402894517.425}
[1,] 35.178
[2,] 126.909
{"mAccuracy":1625.0,"mAltitude":0.0,"mBearing":0.0,"mElapsedRealtimeNanos":77069916000000,"mExtras":{"networkLocationSource":"cached","networkLocationType":"cell","noGPSLocation":{"mAccuracy":1625.0,"mAltitude":0.0,"mBearing":0.0,"mElapsedRealtimeNanos":77069916000000,"mHasAccuracy":true,"mHasAltitude":false,"mHasBearing":false,"mHasSpeed":false,"mIsFromMockProvider":false,"mLatitude":35.1811881,"mLongitude":126.9084072,"mProvider":"network","mSpeed":0.0,"mTime":1402894857416},"travelState":"stationary"},"mHasAccuracy":true,"mHasAltitude":false,"mHasBearing":false,"mHasSpeed":false,"mIsFromMockProvider":false,"mLatitude":35.1811881,"mLongitude":126.9084072,"mProvider":"network","mSpeed":0.0,"mTime":1402894857416,"timestamp":1402894857.519}
[1,] 35.18119
[2,] 126.90841
我希望结果如下：
[1] 35.178 126.909
[2] 35.18119 126.90841
谢谢
答案 0 :(得分：2)
您的数据似乎是JSON格式。因此，请使用RJSONIO::fromJSON来读取文件。
E.g：
txt <- "{\"mAccuracy\":20.0,\"mAltitude\":0.0,\"mBearing\":0.0,\"mElapsedRealtimeNanos\":21677339000000,\"mExtras\":{\"networkLocationSource\":\"cached\",\"networkLocationType\":\"wifi\",\"noGPSLocation\":{\"mAccuracy\":20.0,\"mAltitude\":0.0,\"mBearing\":0.0,\"mElapsedRealtimeNanos\":21677339000000,\"mHasAccuracy\":true,\"mHasAltitude\":false,\"mHasBearing\":false,\"mHasSpeed\":false,\"mIsFromMockProvider\":false,\"mLatitude\":35.1811956,\"mLongitude\":126.9104909,\"mProvider\":\"network\",\"mSpeed\":0.0,\"mTime\":1402801381486},\"travelState\":\"stationary\"},\"mHasAccuracy\":true,\"mHasAltitude\":false,\"mHasBearing\":false,\"mHasSpeed\":false,\"mIsFromMockProvider\":false,\"mLatitude\":35.1811956,\"mLongitude\":126.9104909,\"mProvider\":\"network\",\"mSpeed\":0.0,\"mTime\":1402801381486,\"timestamp\":1402801665.512}"
然后处理：
library(RJSONIO)
out <- fromJSON(txt)
out$$mLongitude
#[1] 126.9105
out$mLatitude
#[1] 35.1812
# to process multiple values
tt <- rep(txt,2)
myData <- lapply(tt, fromJSON)
latlong <- do.call(rbind,lapply(myData, `[` ,c('mLatitude','mLongitude')))
# or using rbind list
library(data.table)
latlong <- rbindlist(lapply(myData, `[` ,c('mLatitude','mLongitude')))