Converting columns into rows in r [duplicate]

Answer 1

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

Answer 2

This may not be the most elegant solution, but it should work and is hopefully understandable:

We split the data into two dataframes: one with the 'from' longitude and latitude data (call it testF) and the other with the 'to' data (call it test). We then use rbind to insert the rows of 'testF' in the appropriate places in 'test'.

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))

testF <- test[,c(1:3,6,7)]
names(testF)[4:5] <- c("lonitude", "latitude")
test <- test[,1:5]
names(test)[4:5] <- c("lonitude", "latitude")

for(i in dim(test)[1]:1) {
  test <- rbind(test[1:i,], testF[i,], test[-(1:i),])
}

Answer 3

Here is an alternative approach using package tidyr (a popular package for data munging), which avoids for loop.

library(tidyr)

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))
test$id <- 1:dim(test)[1]

# gather latitude columns
d1 <- gather(data = test, 
             key = direction, 
             value = latitude, 
             to_lat, from_lat)

# gather longitude columns
d2 <- gather(data = test, 
             key = direction, 
             value = longitude, 
             to_lon, from_lon)

d3 <- cbind(d1[,c("direction","dis","dur","method","latitude")],d2[,c("longitude","id"),drop=FALSE])

# Create names
dir <- unlist(strsplit(d3$direction,"_"))
dir <- dir[seq(from = 1, to = length(dir), by = 2)]

# Factor and sort
d3$direction <- factor(dir)
d3[order(d3$id),]