将列转换为 r 中的行 [英] Converting columns into rows in r

问题描述

我使用代码形成了以下数据

I have the below data formed using code

test <- data.frame(dis = c(10,20,30,40),dur=c(30,40,60,90),method=c("car","car","Bicycle","Bicycle"),to_lon=c(-1.980,-1.5678,-1.324,-1.456),to_lat=c(55.3009,55.3416,55.1123,55.2234),from_lon=c(-1.4565,-1.3424,-1.4566,-1.1111),from_lat=c(76.8888,65.8999,76.9088,25.3344))

 dis dur  method  to_lon  to_lat from_lon from_lat
1  10  30     car -1.9800 55.3009  -1.4565  76.8888
2  20  40     car -1.5678 55.3416  -1.3424  65.8999
3  30  60 Bicycle -1.3240 55.1123  -1.4566  76.9088
4  40  90 Bicycle -1.4560 55.2234  -1.1111  25.3344

我想转换此数据框，使其在一行中包含 to_lat 和 to_lon，在下一行中包含 from_lat 和 from_lon.其余的细节不需要改变，可以复制.想要的结果应该如下

I want to convert this data frame such that it has one row for to_lat and to_lon and in the next row it has from_lat and from_lon. The rest of the details do not need to change and can be replicated. The desired result should be as below

    dis dur method  longitude   latitude
from    10  30  car -1.98   55.3009
to  10  30  car -1.4565 76.8888
from    20  40  car -1.5678 55.3416
to  20  40  car -1.3424 65.8999
from    30  60  Bicycle -1.324  55.1123
to  30  60  Bicycle -1.4566 76.9088
from    40  90  Bicycle -1.456  55.2234
to  40  90  Bicycle -1.1111 25.3344

任何帮助将不胜感激.

谢谢.

推荐答案

我们可以使用data.table中的melt，它可以采取多个measure> 列.

We can use melt from data.table which can take multiple measure columns.

library(data.table)
dM <- melt(setDT(test), measure=patterns('lon', 'lat'), 
          value.name=c('longitude', 'latitude'))
#change the 'variable' column from numeric index to 'from/to'
dM[, variable:= c('from', 'to')[variable]]
#create a sequence column grouped by 'variable'
dM[,i1:= 1:.N ,variable]
#order based on the 'i1'
res <- dM[order(i1)][,i1:=NULL]
res
#    dis dur  method variable longitude latitude
#1:  10  30     car     from   -1.9800  55.3009
#2:  10  30     car       to   -1.4565  76.8888
#3:  20  40     car     from   -1.5678  55.3416
#4:  20  40     car       to   -1.3424  65.8999
#5:  30  60 Bicycle     from   -1.3240  55.1123
#6:  30  60 Bicycle       to   -1.4566  76.9088
#7:  40  90 Bicycle     from   -1.4560  55.2234
#8:  40  90 Bicycle       to   -1.1111  25.3344

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