Iterating through data frame and changing values on condition [R]

Question

Had to make an account because this sequence of for loops has been annoying me for quite some time.

I have a data frame in R with 1000 rows and 10 columns, with each value ranging from 1:3. I would like to re-code EVERY entry so that: 1==3, 2==2, 3==1. I understand that there are easier ways to do this, such as sub-setting each column and hard coding the condition, but this isn't always ideal as many of the data sets that I work with have up to 100 columns.

I would like to use a nested loop in order to accomplish this task -- this is what I have thus far:

for(i in 1:nrow(dat_trans)){
  for(j in length(dat_trans)){
    if(dat_trans[i,j] == 1){
      dat_trans[i,j] <- 3
    } else if(dat_trans[i,j] == 2){
      dat_trans[i,j] <- 2
    } else{
      dat_trans[i,j] <- 1
    }
  }
}

So I iterate through the first column, grab every value and change it based on the if/else's condition, I am still learning R so if you have any pointers in my code, feel free to point it out.

edit: code

Answer 1

R is a vectorized language, so you really don't need the inner loop.
Also if you notice that 4-"old value" = "new value", you can eliminate the if statements.

for(i in 1:ncol(dat_trans)){
        dat_trans[,i] <- 4-dat_trans[,i]
}

The outer loop is now iterating across the columns for only 10 iterations as opposed to 1000 for all of rows. This will greatly improve performance.

Answer 2

This type of operation is a swap operation. The ways to swap values without for loops are numerous.

To set up a simple dataframe:

df <- data.frame(
  col1 = c(1,2,3),
  col2 = c(2,3,1),
  col3 = c(3,1,2)
)

Using a dummy value:

df[df==1] <- 4
df[df==3] <- 1
df[df==4] <- 3

Using a temporary variable:

dftemp <- df
df[dftemp==1] <- 3
df[dftemp==3] <- 1

Using multiplication/division and addition/subtraction:

df <- 4 - df

Using Boolean operations:

df <- (df==1) * 3 + (df==2) * 2 + (df==3) * 1

Using a bitwise xor (in case you really have a need for speed):

df[df!=2] <- sapply(df, function(x){bitwXor(2,x)})[df!=2]

If a nested for loop is required the switch function is a good option.

for(i in seq(ncol(df))){
  for(j in seq(nrow(df))){
    df[j,i] <- switch(df[j,i],3,2,1)
  }
}

Text can be used if the values are not as nicely indexed as 1, 2, and 3.

for(i in seq(ncol(df))){
  for(j in seq(nrow(df))){
    df[j,i] <- switch(as.character(df[j,i]),
                      "1" = 3,
                      "2" = 2,
                      "3" = 1)
  }
}