How to Set Unique Row and Column Names of a Matrix When Its Dimension Is Unknown

R adding extra rows in a matrix where row names are unique

Use setdiff to figure out which rows need to be added, create an empty matrix, and rbind them together:

toAdd <- setdiff(colnames(mat), rownames(mat))
m <- matrix(0, ncol = ncol(mat), nrow = length(toAdd), 
            dimnames = list(toAdd, colnames(mat)))
rbind(mat, m)
#   a b c d e
# a 1 0 0 1 0
# e 1 0 0 1 0
# b 0 0 0 0 0
# c 0 0 0 0 0
# d 0 0 0 0 0

This assumes "mat" is defined as:

mat <- structure(c(1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L), 
                .Dim = c(2L, 5L), 
                .Dimnames = list(c("a", "e"), c("a", "b", "c", "d", "e")))

How to save values from matrix to another with keeping columns and rows names unchanged in R?

Something like this should simplify your code and work for you:

# Toy data
data.corr <- cor(matrix(rnorm(200), 20, 10))
rownames(data.corr) <- colnames(data.corr) <- paste0("company", 1:10)
print(data.corr)

# Get highest correlations for each company
COR <- apply(data.corr, 2, sort, decreasing = TRUE)[1:5 + 1, ]

# Get corresponding rows / companies
COR_comp <- apply(data.corr, 2, order, decreasing = TRUE)[1:5 + 1, ]

If you insist that it is the names that appear (and not numbers) that appear in COR_comp, you can modify it further. For example, the following will fill in the company names:

COR_comp[]  <- colnames(COR_comp )[c(COR_comp )]

Create a matrix to be filled in without specifying its dimension

When vector length is known

Here's a solution where you create an empty matrix M of known dimensions (number of rows is vector length (lVector) and number of columns (nCols) you pick yourself). After nCols (when matrix is full) you write it to a disc with a unique identifier.

# These parameters are known
lVector <- 10
nCols <- 1e4
# Create matrix
M <- matrix(nrow = lVector, ncol = nCols)
iter <- 0

# This is unknown before
nIterations <- 1e5 + 10

# Perform iterations
for(i in seq_len(nIterations)) {
    iter <- iter + 1

    # Perform simulation and write result to a matrix column
    M[, iter] <- sample(100, 10)

    if (iter == nCols) {
        # Write result to disc
        saveRDS(M, paste0("result_", i, ".RDS"))
        # Reset counter
        iter <- 0
        # Create new empty matrix
        M <- matrix(nrow = lVector, ncol = nCols)
    }
}
# Write last 10 iterations to a disc (they didn't reach 1e4)
saveRDS(M[, 1:iter], paste0("result_", i, ".RDS"))

This will write matrices (result_10000.RDS, result_20000.RDS, ...)

When vector length is unknown

Here you can create an empty list of length lList and after lList iterations write it to a disc and re-create a new list.

# These parameters are known
lList <- 1e4
iter <- 0
# Create empty list
L <- rep(list(NA), lList)

# This is unknown before
nIterations <- 1e5 + 10

# Perform iterations
for(i in seq_len(nIterations)) {
    iter <- iter + 1
    L[[iter]] <- sample(100, 10)
    if (iter == lList) {
        saveRDS(L, paste0("result_", i, ".RDS"))
        iter <- 0
        L <- rep(list(NA), lList)
    }
}
saveRDS(L[1:iter], paste0("result_", i, ".RDS"))

add row and column to matrix based on sequence and fill it with NaN

There was an answer a minute ago, which I believe was a very good one, and I actually came by again to comment on it with some modifications, and up-vote it, but it seems it was deleted

In any case here is the updated version of the mentioned answer

#create matrix with missing column and row
mat_1 = matrix(rnorm(16), nrow=4, ncol=4, byrow = TRUE) 

#rename columns and rows
dimnames(mat_1) = list(c("a", "c", "d", "e"), c("a", "c", "d", "e")) 

mat_2 <- matrix(
  NA,
  nrow = length(letters[1:5]),
  ncol = length(letters[1:5]),
  dimnames = list(letters[1:5], letters[1:5]))

mat_2[rownames(mat_1), colnames(mat_1)] <- mat_1

mat_2

#            a  b          c           d           e
# a -0.5021924 NA  0.1315312 -0.07891709  0.88678481
# b         NA NA         NA          NA          NA
# c  0.1169713 NA  0.3186301 -0.58179068  0.71453271
# d -0.8252594 NA -0.3598621  0.08988614  0.09627446
# e -0.2016340 NA  0.7398405  0.12337950 -0.02931671

Selecting a single row of a named matrix and keeping the row name

Thanks to ZheyuanLi, we can search ?Extract which gives the options to [] (note that this is different than ?subset). We realize that there is a drop argument which does the job of keeping a row matrix: M[1, , drop = FALSE].

Here is the relevant part from R-FAQ, again courtesy of ZheyuanLi.

Select a column by column-name, but a different name for each row of a matrix in R?

As the help page ?`[` says, you can subset with a matrix to get individual elements. Each row of the subsetting matrix is an element, and the columns specify the indices for each dimension.

match(columns,colnames(aMatrix)) #gets the column indices
# [1] 1 5 4
b <- cbind(seq_along(columns),match(columns,colnames(aMatrix))) #subset matrix
#      [,1] [,2]
# [1,]    1    1 #first element: first row first column
# [2,]    2    5 #second element: second row fifth column
# [3,]    3    4 #third element: third row fourth column
aMatrix[b]
# [1]  1 14 12