How to efficiently swap elements in a dataframe? - r

Question

Suppose that we have the following dataframe:
set.seed(1)
(tmp <- data.frame(x = 1:10, R1 = sample(LETTERS[1:5], 10, replace =
TRUE), R2 = sample(LETTERS[1:5], 10, replace = TRUE)))
x R1 R2
1 1 B B
2 2 B A
3 3 C D
4 4 E B
5 5 B D
6 6 E C
7 7 E D
8 8 D E
9 9 D B
10 10 A D
I want to do the following: if the difference between the level index
of factor R1 and that of factor R2 is an odd number, the levels of the
two factors need to be switched between them, which can be performed
through the following code:
for(ii in 1:dim(tmp)[1]) {
kk <- which(levels(tmp$R2) %in% tmp[ii,'R2'], arr.ind = TRUE) -
which(levels(tmp$R1) %in% tmp[ii,'R1'], arr.ind = TRUE)
if(kk%%2!=0) { # swap the their levels between the two factors
qq <- tmp[ii,]$R1
tmp[ii,]$R1 <- tmp[ii,]$R2
tmp[ii,]$R2 <- qq
}
}
More concise and efficient ways to achieve this?
P.S. A slightly different situation is the following.
set.seed(1)
(tmp <- data.frame(x = 1:10, R1 = sample(LETTERS[1:5], 10, replace =
TRUE), R2 = sample(LETTERS[2:6], 10, replace = TRUE)))
x R1 R2
1 C B
2 B B
3 C E
4 E C
5 E B
6 D E
7 E E
8 D F
9 C D
10 A E
Notice that the factor levels between the two factors, R1 and R2, slide by one level; that is, factor R1 does not have level F while factor R2 does not have level A. I want to swap the factor levels based on the combined levels of the two factors as shown below:
tl <- unique(c(levels(tmp$R1), levels(tmp$R2)))
for(ii in 1:dim(tmp)[1]) {
kk <- which(tl %in% tmp[ii,'R2'], arr.ind = TRUE) - which(tl %in%
tmp[ii,'R1'], arr.ind = TRUE)
if(kk%%2!=0) { # swap the their levels between the two factors
qq <- tmp[ii,]$R1
tmp[ii,]$R1 <- tmp[ii,]$R2
tmp[ii,]$R2 <- qq
}
}
How to go about this case? Thanks!

Answer 1

#Find out the indices where difference is odd
inds = abs(as.numeric(tmp$R1) - as.numeric(tmp$R2)) %% 2 != 0
#create new columns where values for the appropriate inds are from relevant columns
tmp$R1_new = replace(tmp$R1, inds, tmp$R2[inds])
tmp$R2_new = replace(tmp$R2, inds, tmp$R1[inds])
tmp
# x R1 R2 R1_new R2_new
#1 1 B B B B
#2 2 B A A B
#3 3 C D D C
#4 4 E B B E
#5 5 B D B D
#6 6 E C E C
#7 7 E D D E
#8 8 D E E D
#9 9 D B D B
#10 10 A D D A
Delete the old R1 and R2 if necessary

Answer 2

A solution using dplyr. dt is the final output. Notice that we need to use if_else from dplyr here, not the common ifelse from base R.
library(dplyr)
dt <- tmp %>%
mutate(R1_new = if_else((as.numeric(R2) - as.numeric(R1)) %% 2 != 0, R2, R1),
R2_new = if_else((as.numeric(R2) - as.numeric(R1)) %% 2 != 0, R1, R2)) %>%
select(x, R1 = R1_new, R2 = R2_new)
Update
For the updated case, add one mutate call to redefine the factor level of R1 and R2. The rest is the same.
tl <- unique(c(levels(tmp$R1), levels(tmp$R2)))
dt <- tmp %>%
mutate(R1 = factor(R1, levels = tl), R2 = factor(R2, levels = tl)) %>%
mutate(R1_new = if_else((as.numeric(R2) - as.numeric(R1)) %% 2 != 0, R2, R1),
R2_new = if_else((as.numeric(R2) - as.numeric(R1)) %% 2 != 0, R1, R2)) %>%
select(x, R1 = R1_new, R2 = R2_new)

Answer 3

Here is an option using data.table
library(data.table)
setDT(tmp)[(as.integer(R1) - as.integer(R2))%%2 != 0, c('R2', 'R1') := .(R1, R2)]
tmp
# x R1 R2
#1: 1 B B
#2: 2 A B
#3: 3 D C
#4: 4 B E
#5: 5 B D
#6: 6 E C
#7: 7 D E
#8: 8 E D
#9: 9 D B
#10:10 D A