Related
The title with the following example should be self-explanatory:
m = unique(replicate(5, sample(1:5, 5, rep=F)), MARGIN = 2)
m
[,1] [,2] [,3] [,4] [,5]
[1,] 1 5 1 4 3
[2,] 5 1 5 1 2
[3,] 4 3 3 3 1
[4,] 3 4 4 5 5
[5,] 2 2 2 2 4
But what I want is instead:
[,1] [,2] [,3] [,4] [,5]
[1,] 1 1 3 4 5
[2,] 5 5 2 1 1
[3,] 3 4 1 3 3
[4,] 4 3 5 5 4
[5,] 2 2 4 2 2
Ideally, I would like to find a method that allows the same process to be carried out when the column vectors are words (alphabetic order).
I tried things like m[ , sort(m)] but nothing did the trick...
m[, order(m[1, ]) will order the columns by the first row. m[, order(m[1, ], m[2, ])] will order by the first row, using second row as tie-breaker. Getting fancy, m[, do.call(order, split(m, row(m)))] will order the columns by the first row, using all subsequent rows for tie-breakers. This will work character data just as well as numeric.
set.seed(47)
m = replicate(5, sample(1:5, 5, rep=F))
m
# [,1] [,2] [,3] [,4] [,5]
# [1,] 5 4 1 5 1
# [2,] 2 2 3 2 3
# [3,] 3 5 5 1 2
# [4,] 4 3 2 3 5
# [5,] 1 1 4 4 4
m[, do.call(order, split(m, row(m)))]
# [,1] [,2] [,3] [,4] [,5]
# [1,] 1 1 4 5 5
# [2,] 3 3 2 2 2
# [3,] 2 5 5 1 3
# [4,] 5 2 3 3 4
# [5,] 4 4 1 4 1
I have this matrix:
mat=matrix(c(1,1,1,2,2,2,3,4,NA,
4,4,4,4,4,3,5,6,4,
3,3,5,5,6,8,0,9,NA,
1,1,1,1,1,4,5,6,1),nrow=4,byrow=TRUE)
print(mat)
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
# [1,] 1 1 1 2 2 2 3 4 NA
# [2,] 4 4 4 4 4 3 5 6 4
# [3,] 3 3 5 5 6 8 0 9 NA
# [4,] 1 1 1 1 1 4 5 6 1
I should replace the NA values with other values, in this way:
I have another matrix:
mat2=matrix(c(24,1,3,2, 4,4,4,4, 3,2,2,5, 1,3,5,1),nrow=4,byrow=TRUE)
[,1] [,2] [,3] [,4]
[1,] 24 1 3 2
[2,] 4 4 4 4
[3,] 3 2 2 5
[4,] 1 3 5 1
and the subset with the index of the rows with NA of the first matrix "mat":
subset=c(1,3)
I want to replcace the NA of the matrix with the colnames of the value of the row with the max value.
in this case, I will have "1" for the first row and "4" for the third one, I don't care about row 2 and 4.
Use this
mat[subset,9] <- apply(mat2[subset,],1,which.max)
mat[which(is.na(mat))] <- apply(mat2,1,max)[which(is.na(mat), arr.ind = T)[1,]]
This should replace every NA value with the maximum value from the same row in mat2. I don't have an open core to debug on so I hope this works. If you have any questions or it crashes just comment.
Apologies, if the question is too basic. What would be an effective approach/idea (in R) to convert
list(c(1), c(1,2), c(1,2,3), c(1,2,3,4))
to square matrix form
[,1] [,2] [,3] [,4]
[1,] 1 NA NA NA
[2,] 1 2 NA NA
[3,] 1 2 3 NA
[4,] 1 2 3 4
I suppose there is some quick dynamic way to append just the right number of NA values and then convert to a matrix.
Naturally, the size of the (square) matrix can change).
Thanks in advance for your time.
You can use
## create the list
x <- Map(":", 1, 1:4)
ml <- max(lengths(x))
do.call(rbind, lapply(x, "length<-", ml))
# [,1] [,2] [,3] [,4]
# [1,] 1 NA NA NA
# [2,] 1 2 NA NA
# [3,] 1 2 3 NA
# [4,] 1 2 3 4
Or you could do
library(data.table)
as.matrix(unname(rbindlist(lapply(x, as.data.frame.list), fill = TRUE)))
# [,1] [,2] [,3] [,4]
# [1,] 1 NA NA NA
# [2,] 1 2 NA NA
# [3,] 1 2 3 NA
# [4,] 1 2 3 4
And one more for good measure ... Fore!
m <- stringi::stri_list2matrix(x, byrow = TRUE)
mode(m) <- "numeric"
m
# [,1] [,2] [,3] [,4]
# [1,] 1 NA NA NA
# [2,] 1 2 NA NA
# [3,] 1 2 3 NA
# [4,] 1 2 3 4
For, example I if a had matrix like this:
realmatrix=matrix(1:16,ncol=4,nrow=4)
Which would give this:
[,1] [,2] [,3] [,4]
[1,] 1 5 9 13
[2,] 2 6 10 14
[3,] 3 7 11 15
[4,] 4 8 12 16
And I would like to make a function that would replace the two columns with a certain value ( for example 1:4) if it has a even number of colums, then the result should be something like this:
[,1] [,2] [,3] [,4]
[1,] 1 1 1 13
[2,] 2 2 2 14
[3,] 3 3 3 15
[4,] 4 4 4 16
And if the matrix has odd numbers of colums, the function should replace only the odd column, that is to say the central one:
This is the matrix with odd numbers of columns:
realmatrix2=matrix(1:12,ncol=3,nrow=4)
The final result:
[,1] [,2] [,3]
[1,] 1 1 9
[2,] 2 2 10
[3,] 3 3 11
[4,] 4 4 12
Thanks a lot!
Try:
fun2 <- function(mat, val){
stopifnot(length(val)==nrow(mat))
n <- ncol(mat)
if( (n/2) %%2 ==0){
mat[, c(n/2, n/2+1)] <- val
}
else {
mat[, ceiling(n/2)] <- val
}
mat
}
fun2(realmatrix, 1:4)
# [,1] [,2] [,3] [,4]
#[1,] 1 1 1 13
#[2,] 2 2 2 14
#[3,] 3 3 3 15
#[4,] 4 4 4 16
fun2(realmatrix2,1:4)
# [,1] [,2] [,3]
#[1,] 1 1 9
#[2,] 2 2 10
#[3,] 3 3 11
#[4,] 4 4 12
realmatrix5=matrix(1:32, ncol=8,nrow=4)
fun2(realmatrix5, 1:4)
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
#[1,] 1 5 9 1 1 21 25 29
#[2,] 2 6 10 2 2 22 26 30
#[3,] 3 7 11 3 3 23 27 31
#[4,] 4 8 12 4 4 24 28 32
Update
If you want to change the rows:
funR <- function(mat, val){
stopifnot(length(val)==ncol(mat))
n <- nrow(mat)
if((n/2) %%2==0){
mat[c(n/2, n/2+1),] <- rep(val, each=2)
}
else {
mat[ceiling(n/2),] <- val
}
mat
}
funR(realmatrix, 1:4)
# [,1] [,2] [,3] [,4]
#[1,] 1 5 9 13
#[2,] 1 2 3 4
#[3,] 1 2 3 4
#[4,] 4 8 12 16
realmatrix3 <- matrix(1:15, ncol=5)
funR(realmatrix3, 1:5)
# [,1] [,2] [,3] [,4] [,5]
#[1,] 1 4 7 10 13
#[2,] 1 2 3 4 5
#[3,] 3 6 9 12 15
I have a matrix with some NA values
for example:
[,1] [,2] [,3] [,4]
[1,] 1 4 7 10
[2,] 2 NA 8 11
[3,] 3 6 NA 12
I want to create new matrix with data from my matrix above with new dimension and no NA value. (it is ok to have NA only some last elements)
something like:
[,1] [,2] [,3]
[1,] 1 6 11
[2,] 2 7 12
[3,] 3 8 NA
[4,] 4 10 NA
I would appreciate if anyone can help me.
Thanks
Something like this as well:
m <- matrix(1:12, nc=4)
m[c(5, 9)] <- NA
matrix(c(na.omit(c(m)), rep(NA, sum(is.na(m)))), nrow=4)
m <- matrix(1:12, nc=4)
m[c(5, 9)] <- NA
# create an array of the appropriate class and dimension (filled with NA values)
dims <- c(4, 3)
md <- array(m[0], dim=dims)
# replace first "n" values with non-NA values from m
nonNAm <- na.omit(c(m))
md[seq_along(nonNAm)] <- nonNAm
md
# [,1] [,2] [,3]
# [1,] 1 6 11
# [2,] 2 7 12
# [3,] 3 8 NA
# [4,] 4 10 NA
Yet another attempt. This will keep the order of the values in column order as a matrix usually would. E.g.:
mat <- matrix(c(1,2,3,4,NA,6,7,8,NA,10,11,12),nrow=3)
array(mat[order(is.na(mat))],dim=dim(mat))
# [,1] [,2] [,3] [,4]
#[1,] 1 4 8 12
#[2,] 2 6 10 NA
#[3,] 3 7 11 NA
Now change a value to check it doesn't affect the ordering.
mat[7] <- 20
array(mat[order(is.na(mat))],dim=dim(mat))
# [,1] [,2] [,3] [,4]
#[1,] 1 4 8 12
#[2,] 2 6 10 NA
#[3,] 3 20 11 NA
You can then specify whatever dimensions you feel like to the dim= argument:
array(mat[order(is.na(mat))],dim=c(4,3))
# [,1] [,2] [,3]
#[1,] 1 6 11
#[2,] 2 20 12
#[3,] 3 8 NA
#[4,] 4 10 NA
This is fairly straightforward if you want to preserve order column-wise or row-wise.
originalMatrix <- matrix(c(1,2,3,4,NA,6,7,8,NA,10,11,12),nrow=3)
[,1] [,2] [,3] [,4]
[1,] 1 4 7 10
[2,] 2 NA 8 11
[3,] 3 6 NA 12
newMatrixNums <- originalMatrix[!is.na(originalMatrix)]
[1] 1 2 3 4 6 7 8 10 11 12
Pad with NA:
newMatrixNums2 <- c(newMatrixNums,rep(NA,2))
Column-wise:
matrix(newMatrixNums2,nrow=3)
[,1] [,2] [,3] [,4]
[1,] 1 4 8 12
[2,] 2 6 10 NA
[3,] 3 7 11 NA
Row-wise:
matrix(newMatrixNums2,nrow=3,byrow=T)
[,1] [,2] [,3] [,4]
[1,] 1 2 3 4
[2,] 6 7 8 10
[3,] 11 12 NA NA
Here's one way:
# Reproducing your data
m <- matrix(1:12, nc=4)
m[c(5, 9)] <- NA
# Your desired dimensions
dims <- c(4, 3)
array(c(na.omit(c(m)), rep(NA, prod(dims) - length(na.omit(c(m))))), dim=dims)
# [,1] [,2] [,3]
# [1,] 1 6 11
# [2,] 2 7 12
# [3,] 3 8 NA
# [4,] 4 10 NA
This can do the job but dunno whether it is a good way.
list1 <- m[m]
list2 <- m[!is.na(m)]
element1 <- list2
element2 <- rep(NA, (length(list1)-length(list2)))
newm <- matrix(c(element1,element2), nrow=4)
If you increase the length of a numeric vector with length(x)<- without assigning values to the new elements, the new values are given NA as their value. So length(M2) <- length(M) takes the shorter M2 vector and makes it the same length as M by adding NA values to the new elements.
## original
> (M <- matrix(c(1:4,NA,6:8,NA,10:12), nrow = 3))
# [,1] [,2] [,3] [,4]
# [1,] 1 4 7 10
# [2,] 2 NA 8 11
# [3,] 3 6 NA 12
## new
> M2 <- M[!is.na(M)]; length(M2) <- length(M)
> matrix(M2, ncol(M))
# [,1] [,2] [,3]
# [1,] 1 6 11
# [2,] 2 7 12
# [3,] 3 8 NA
# [4,] 4 10 NA