在R中将具有多个级别的列表合并到数据帧中
我从API中提取数据，输出的是一个具有多个级别的列表在R中将具有多个级别的列表合并到数据帧中,r,list,dataframe,rstudio,R,List,Dataframe,Rstudio,我从API中提取数据，输出的是一个具有多个级别的列表 #data is the list received from the call. str(data, 3) List of 2 $ :List of 1 ..$ data:List of 1 .. ..$ :List of 153 $ :List of 1 ..$ data:List of 1 .. ..$ :List of 153 我想做的是把这个列表变成一个数据框。下面的代码是我试图实现的，但是它是各种各样的枯燥
#data is the list received from the call.
str(data, 3)
List of 2
$ :List of 1
..$ data:List of 1
.. ..$ :List of 153
$ :List of 1
..$ data:List of 1
.. ..$ :List of 153
i = data[[1]][[1]][[1]]
j = data[[2]][[1]][[1]]
frame = as.data.frame(rbind(i,j))
head(frame)
ticker tradeDate assetType priorCls
i AAPL 2019-02-28 3 174.87
j MSFT 2019-02-28 3 112.17
dput(data)
list(list(data = list(list(ticker = "AAPL", tradeDate = "2019-02-28",
assetType = 3L, priorCls = 174.87, pxAtmIv = 174.02, mktCap = 855332L,
cVolu = 140594L, cOi = 1838296L, pVolu = 91852L, pOi = 1350168L,
orFcst20d = 17.827, orIvFcst20d = 18.884, orFcstInf = 20.91,
orIvXern20d = 19.02, orIvXernInf = 20.2, iv200Ma = 23.06,
atmIvM1 = 18.04, atmFitIvM1 = 18.804, atmFcstIvM1 = 17.827,
dtExM1 = 16L, atmIvM2 = 23.155, atmFitIvM2 = 22.798, atmFcstIvM2 = 19.479,
dtExM2 = 79L, atmIvM3 = 21.539, atmFitIvM3 = 21.962, atmFcstIvM3 = 19.668,
dtExM3 = 114L, atmIvM4 = 22.147, atmFitIvM4 = 21.582, atmFcstIvM4 = 19.772,
dtExM4 = 142L, iRate5wk = 2.44, iRateLt = 2.52, px1kGam = 2304.59,
volOfVol = 0.0668, volOfIvol = 0.0456, slope = 2.427827,
slopeInf = 3.29858, slopeFcst = 2.44455, slopeFcstInf = 3.24424,
deriv = 0.0443, derivInf = 0.053, derivFcst = 0.0677, derivFcstInf = 0.0681,
mktWidthVol = 0.35, mktWidthVolInf = 0.372, cAddPrem = 0L,
pAddPrem = 0L, rip = 1.85202, ivEarnReturn = 0L, fcstR2 = 0.35,
fcstR2Imp = 0.32, hiHedge = 0L, loHedge = 0L, stkVolu = 27942952L,
avgOptVolu20d = 451784L, sector = "XLK Electronic Computer Manufacturing42941",
orHv1d = 12.79, orHv5d = 12.74, orHv10d = 12.68, orHv20d = 23.4,
orHv60d = 34.69, orHv90d = 36.12, orHv120d = 34.3, orHv252d = 28.34,
orHv500d = 24.48, orHv1000d = 24.54, clsHv5d = 9.12, clsHv10d = 7.96,
clsHv20d = 26.91, clsHv60d = 39.34, clsHv90d = 40.12, clsHv120d = 37.43,
clsHv252d = 30.35, clsHv500d = 25.56, clsHv1000d = 24.88,
iv20d = 18.82, iv30d = 18.51, iv60d = 20.68, iv90d = 22.61,
iv6m = 22.33, clsPx1w = 171.06, stkPxChng1wk = 1.73, clsPx1m = 154.0194,
stkPxChng1m = 12.99, clsPx6m = 223.2899, stkPxChng6m = -22.07,
clsPx1y = 175.4484, stkPxChng1y = -0.81, divFreq = 91L, divYield = 1.8,
divGrwth = 0L, divDate = "2019-05-08", divAmt = 0.79, nextErn = "0000-00-00",
nextErnTod = 1630L, lastErn = "2019-01-29", lastErnTod = 3L,
absAvgErnMv = 4.7381, impliedIee = 4L, daysToNextErn = 0L,
tkOver = 0L, etfIncl = "", bestEtf = "XLK", sectorName = "Technology Hardware & Equipment",
correlSpy1m = 0.97, correlSpy1y = 0.92, correlEtf1m = 0.97,
correlEtf1y = 0.95, beta1m = 0.95, beta1y = 1.71, ivPctile1m = 9L,
ivPctile1y = 33L, ivPctileSpy = 37L, ivPctileEtf = 59L, ivStdvMean = -0.39,
ivStdv1y = 5.48, ivSpyRatio = 1.63, ivSpyRatioAvg1m = 1.49,
ivSpyRatioAvg1y = 1.51, ivSpyRatioStdv1y = 5.05, ivEtfRatio = 1.25,
ivEtfRatioAvg1m = 1.14, ivEtfRatioAvg1y = 1.13, ivEtFratioStdv1y = 4.16,
ivHvXernRatio = 1.12, ivHvXernRatio1m = 0.82, ivHvXernRatio1y = 0.8,
ivHvXernRatioStdv1y = 2.1, etfIvHvXernRatio = 1.03, etfIvHvXernRatio1m = 0.94,
etfIvHvXernRatio1y = 1.01, etfIvHvXernRatioStdv1y = 0.06,
slopepctile = 29.37, slopeavg1m = 2.17, slopeavg1y = 2.81,
slopeStdv1y = 0.7, etfSlopeRatio = 0.32, etfSlopeRatioAvg1m = 0.3,
etfSlopeRatioAvg1y = 0.38, etfSlopeRatioAvgStdv1y = 0.1,
impliedR2 = 0.4696, contango = 0.00818152984720655, nextDiv = 0.79,
impliedNextDiv = 0.47798, annActDiv = 3.17374, annIdiv = 0.952153,
borrow30 = 2.28035189211369, borrow2yr = 1.64744015783072,
error = 0.00449377548648044, confidence = 92.8030908107758,
updatedAt = "2019-02-28 15:00:06"))), list(data = list(list(
ticker = "MSFT", tradeDate = "2019-02-28", assetType = 3L,
priorCls = 112.17, pxAtmIv = 112.13, mktCap = 863378L, cVolu = 63737L,
cOi = 729653L, pVolu = 36709L, pOi = 657741L, orFcst20d = 17.765,
orIvFcst20d = 18.768, orFcstInf = 20.45, orIvXern20d = 18.87,
orIvXernInf = 20.05, iv200Ma = 21.85, atmIvM1 = 18.761, atmFitIvM1 = 18.543,
atmFcstIvM1 = 17.765, dtExM1 = 16L, atmIvM2 = 21.694, atmFitIvM2 = 21.287,
atmFcstIvM2 = 19.535, dtExM2 = 79L, atmIvM3 = 19.96, atmFitIvM3 = 20.837,
atmFcstIvM3 = 19.602, dtExM3 = 114L, atmIvM4 = 20.017, atmFitIvM4 = 20.639,
atmFcstIvM4 = 19.649, dtExM4 = 142L, iRate5wk = 2.44, iRateLt = 2.52,
px1kGam = 872.54, volOfVol = 0.0699, volOfIvol = 0.0501,
slope = 3.241947, slopeInf = 4.00082, slopeFcst = 3.83885,
slopeFcstInf = 4.27056, deriv = 0.0736, derivInf = 0.0719,
derivFcst = 0.0709, derivFcstInf = 0.0833, mktWidthVol = 0.609,
mktWidthVolInf = 0.338, cAddPrem = 0L, pAddPrem = 0L, rip = 1.23683,
ivEarnReturn = 0L, fcstR2 = 0.3431, fcstR2Imp = 0.2827, hiHedge = 0L,
loHedge = 0L, stkVolu = 27837946L, avgOptVolu20d = 149633.8,
sector = "XLK Prepackaged Software42936", orHv1d = 12.74,
orHv5d = 19.25, orHv10d = 16.32, orHv20d = 20.37, orHv60d = 32.59,
orHv90d = 34.45, orHv120d = 32.68, orHv252d = 28.56, orHv500d = 24.3,
orHv1000d = 23.86, clsHv5d = 12.38, clsHv10d = 12.61, clsHv20d = 21.48,
clsHv60d = 31.95, clsHv90d = 34.01, clsHv120d = 32.35, clsHv252d = 27.74,
clsHv500d = 23.44, clsHv1000d = 23.81, iv20d = 18.35, iv30d = 18.97,
iv60d = 20.1, iv90d = 21.11, iv6m = 20.62, clsPx1w = 109.41,
stkPxChng1wk = 2.49, clsPx1m = 102.5022, stkPxChng1m = 9.39,
clsPx6m = 110.9944, stkPxChng6m = 1.02, clsPx1y = 92.2135,
stkPxChng1y = 21.6, divFreq = 91L, divYield = 1.6, divGrwth = 0L,
divDate = "2019-05-16", divAmt = 0.46, nextErn = "0000-00-00",
nextErnTod = 1630L, lastErn = "2019-01-30", lastErnTod = 3L,
absAvgErnMv = 3.1854, impliedIee = 3.0533, daysToNextErn = 0L,
tkOver = 0L, etfIncl = "", bestEtf = "XLK", sectorName = "Software & Services",
correlSpy1m = 0.93, correlSpy1y = 0.96, correlEtf1m = 0.95,
correlEtf1y = 0.97, beta1m = 0.5, beta1y = 0.42, ivPctile1m = 18L,
ivPctile1y = 30L, ivPctileSpy = 31L, ivPctileEtf = 50L, ivStdvMean = -0.4,
ivStdv1y = 4.89, ivSpyRatio = 1.56, ivSpyRatioAvg1m = 1.42,
ivSpyRatioAvg1y = 1.44, ivSpyRatioStdv1y = 4.82, ivEtfRatio = 1.19,
ivEtfRatioAvg1m = 1.08, ivEtfRatioAvg1y = 1.08, ivEtFratioStdv1y = 3.98,
ivHvXernRatio = 1L, ivHvXernRatio1m = 0.82, ivHvXernRatio1y = 0.78,
ivHvXernRatioStdv1y = 1.9, etfIvHvXernRatio = 0.92, etfIvHvXernRatio1m = 0.93,
etfIvHvXernRatio1y = 0.92, etfIvHvXernRatioStdv1y = 0.06,
slopepctile = 78.57, slopeavg1m = 3.36, slopeavg1y = 2.65,
slopeStdv1y = 0.64, etfSlopeRatio = 0.47, etfSlopeRatioAvg1m = 0.46,
etfSlopeRatioAvg1y = 0.36, etfSlopeRatioAvgStdv1y = 0.09,
impliedR2 = 0.4359, contango = 0.28540981002152, nextDiv = 0.46,
impliedNextDiv = 0.231564, annActDiv = 1.84, annIdiv = 0.928459,
borrow30 = 2.23711058497429, borrow2yr = 1.93625316023827,
error = 0.00123339532365208, confidence = 95.1030135154724,
updatedAt = "2019-02-28 15:06:27"))))
我会做下面的事情
library(tidyverse)
map_dfr(data, ~bind_cols(flatten(.x)))
## A tibble: 2 x 153
# ticker tradeDate assetType priorCls pxAtmIv mktCap cVolu cOi pVolu pOi
# <chr> <chr> <int> <dbl> <dbl> <int> <int> <int> <int> <int>
#1 AAPL 2019-02-… 3 175. 174. 855332 140594 1.84e6 91852 1.35e6
#2 MSFT 2019-02-… 3 112. 112. 863378 63737 7.30e5 36709 6.58e5
## ... with 143 more variables: orFcst20d <dbl>, orIvFcst20d <dbl>,
## orFcstInf <dbl>, orIvXern20d <dbl>, orIvXernInf <dbl>, iv200Ma <dbl>,
## atmIvM1 <dbl>, atmFitIvM1 <dbl>, atmFcstIvM1 <dbl>, dtExM1 <int>,
## atmIvM2 <dbl>, atmFitIvM2 <dbl>, atmFcstIvM2 <dbl>, dtExM2 <int>,
## atmIvM3 <dbl>, atmFitIvM3 <dbl>, atmFcstIvM3 <dbl>, dtExM3 <int>,
## atmIvM4 <dbl>, atmFitIvM4 <dbl>, atmFcstIvM4 <dbl>, dtExM4 <int>,
## iRate5wk <dbl>, iRateLt <dbl>, px1kGam <dbl>, volOfVol <dbl>,
## volOfIvol <dbl>, slope <dbl>, slopeInf <dbl>, slopeFcst <dbl>,
## slopeFcstInf <dbl>, deriv <dbl>, derivInf <dbl>, derivFcst <dbl>,
## derivFcstInf <dbl>, mktWidthVol <dbl>, mktWidthVolInf <dbl>,
## cAddPrem <int>, pAddPrem <int>, rip <dbl>, ivEarnReturn <int>,
## fcstR2 <dbl>, fcstR2Imp <dbl>, hiHedge <int>, loHedge <int>, stkVolu <int>,
## avgOptVolu20d <dbl>, sector <chr>, orHv1d <dbl>, orHv5d <dbl>,
## orHv10d <dbl>, orHv20d <dbl>, orHv60d <dbl>, orHv90d <dbl>, orHv120d <dbl>,
## orHv252d <dbl>, orHv500d <dbl>, orHv1000d <dbl>, clsHv5d <dbl>,
## clsHv10d <dbl>, clsHv20d <dbl>, clsHv60d <dbl>, clsHv90d <dbl>,
## clsHv120d <dbl>, clsHv252d <dbl>, clsHv500d <dbl>, clsHv1000d <dbl>,
## iv20d <dbl>, iv30d <dbl>, iv60d <dbl>, iv90d <dbl>, iv6m <dbl>,
## clsPx1w <dbl>, stkPxChng1wk <dbl>, clsPx1m <dbl>, stkPxChng1m <dbl>,
## clsPx6m <dbl>, stkPxChng6m <dbl>, clsPx1y <dbl>, stkPxChng1y <dbl>,
## divFreq <int>, divYield <dbl>, divGrwth <int>, divDate <chr>, divAmt <dbl>,
## nextErn <chr>, nextErnTod <int>, lastErn <chr>, lastErnTod <int>,
## absAvgErnMv <dbl>, impliedIee <dbl>, daysToNextErn <int>, tkOver <int>,
## etfIncl <chr>, bestEtf <chr>, sectorName <chr>, correlSpy1m <dbl>,
## correlSpy1y <dbl>, correlEtf1m <dbl>, correlEtf1y <dbl>, …
库（tidyverse）
映射\u dfr（数据，~bind\u cols（展平（.x）））
##A tibble:2x153
#股票交易日资产类型priorCls pxAtmIv mktCap cVolu cOi pVolu pOi
#
#1 AAPL 2019-02-…3 175。174855332 140594 1.84e6 91852 1.35e6
#2 MSFT 2019-02-…3112。112863378 63737 7.30e5 36709 6.58e5
## ... 还有143个变量：orFcst20d、orIvFcst20d、，
##orFcstInf，ORIVXRN20D，ORIVXRINF，iv200Ma，
##atmIvM1、atmFitIvM1、atmFcstIvM1、dtExM1、，
##atmIvM2、atmFitIvM2、atmFcstIvM2、dtExM2、，
##atmIvM3、atmFitIvM3、atmFcstIvM3、dtExM3、，
##atmIvM4、atmFitIvM4、atmFcstIvM4、dtExM4、，
##iRate5wk、iRateLt、px1kGam、volOfVol、，
##沃洛菲沃，坡度，坡度，坡度，
##slopeFcstInf、deriv、derivInf、derivFcst、，
##derivFcstInf、mktWidthVol、mktWidthVolInf、，
##cAddPrem、pAddPrem、rip、ivEarnReturn、，
##fcstR2、fcstR2Imp、hiHedge、loHedge、stkVolu、，
##avgOptVolu20d，扇区，或HV1D，或HV5D，
##orHv10d、orHv20d、orHv60d、orHv90d、orHv120d、，
##orHv252d、orHv500d、orHv1000d、clsHv5d、，
##clsHv10d、clsHv20d、clsHv60d、clsHv90d、，
##clsHv120d、clsHv252d、clsHv500d、clsHv1000d、，
##iv20d、iv30d、iv60d、iv90d、iv6m、，
##clsPx1w、stkPxChng1wk、clsPx1m、stkPxChng1m、，
##clsPx6m、stkPxChng6m、clsPx1y、stkPxChng1y、，
##divFreq，divYield，divGrwth，divDate，divAmt，
##nextErn，nextErnTod，lastErn，lastErnTod，
##absAvgErnMv，impliedIee，daysToNextErn，tkOver，
##etfIncl、bestEtf、sectorName、correlSpy1m、，
##correlSpy1y，correlEtf1m，correlEtf1y…
列表