Sparse Matrix to a Data Frame in R

Sparse matrix to a data frame in R

Using summary, here is an example:

mat <- Matrix(data = c(1, 0, 2, 0, 0, 3, 4, 0, 0), nrow = 3, ncol = 3,
              dimnames = list(Origin      = c("A", "B", "C"),
                              Destination = c("X", "Y", "Z")),
              sparse = TRUE)
mat
# 3 x 3 sparse Matrix of class "dgCMatrix"
#    Destination
#     X Y Z
#   A 1 . 4
#   B . . .
#   C 2 3 .

summ <- summary(mat)
summ
# 3 x 3 sparse Matrix of class "dgCMatrix", with 4 entries 
#   i j x
# 1 1 1 1
# 2 3 1 2
# 3 3 2 3
# 4 1 3 4

data.frame(Origin      = rownames(mat)[summ$i],
           Destination = colnames(mat)[summ$j],
           Weight      = summ$x)
#   Origin Destination Weight
# 1      A           X      1
# 2      C           X      2
# 3      C           Y      3
# 4      A           Z      4

converting a dgCMatrix to data frame

You can use

b = as.data.frame(summary(a))
#   i j x
# 1 2 1 2
# 2 2 2 1
# 3 3 3 3
# 4 1 4 1
# 5 3 5 1

If you need the same order as in your example, you can use

b = b[order(b$i),]
#   i j x
# 4 1 4 1
# 1 2 1 2
# 2 2 2 1
# 3 3 3 3
# 5 3 5 1

Another alternative, though not quite as neat, is to use

b = as(a, "dgTMatrix")
cbind.data.frame(r = b@i + 1, c = b@j + 1, x = b@x)

how to coerce a data.frame into a sparse matrix in R

Following user20650's comment, first coerce the CUI* columns to factor with the same levels, then use xtabs to create a sparse matrix, then add its transpose.

txt <- '
        CUI1     CUI2 Count
1   C0000699 C3894683     2
2   C0000699 C0101725     1
3   C0000699 C1882413     3
4   C0000699 C0245531     3
5   C0000699 C0068475     2
6   C0000699 C0538927     3
7   C0000699 C0724693     1
8   C0000699 C0216784     2
9   C0000699 C2248020     1
10  C0000699 C0069449     3
'
test <- read.table(textConnection(txt), header = TRUE)

library(Matrix)

levls <- Reduce(union, test[1:2])
test[1:2] <- lapply(test[1:2], factor, levels = levls)
res <- xtabs(Count ~ CUI1 + CUI2, data = test, sparse = TRUE)
res <- forceSymmetric(res)
class(res)
#> [1] "dsCMatrix"
#> attr(,"package")
#> [1] "Matrix"

^{Created on 2022-02-13 by the reprex package (v2.0.1)}

Build identity matrix from dataframe (sparsematrix) in R

A possible solution:

tidyr::pivot_wider(dis_matrix, id_cols = i, names_from = j,
         values_from = distance, values_fill = 0)

#> # A tibble: 2 × 4
#>   i           Rwanda France `South Korea`
#>   <chr>        <dbl>  <dbl>         <dbl>
#> 1 South Korea 10845.   9384             0
#> 2 France       6003       0          9384

R convert matrix or data frame to sparseMatrix

Here are two options:

library(Matrix)

A <- as(regMat, "sparseMatrix")       # see also `vignette("Intro2Matrix")`
B <- Matrix(regMat, sparse = TRUE)    # Thanks to Aaron for pointing this out

identical(A, B)
# [1] TRUE
A
# 10 x 10 sparse Matrix of class "dgCMatrix"
#                              
#  [1,] . . .  .  . 45 .  . . .
#  [2,] . . .  .  .  . . 59 . .
#  [3,] . . .  . 95  . .  . . .
#  [4,] . . .  .  .  . .  . . .
#  [5,] . . .  .  .  . .  . . .
#  [6,] . . .  .  .  . .  . . .
#  [7,] . . . 23  .  . .  . . .
#  [8,] . . . 63  .  . .  . . .
#  [9,] . . .  .  .  . .  . . .
# [10,] . . .  .  .  . .  . . .

Convert a dgCMatrix to data frame

I think you have your matrix inside a list.

library(Matrix)
m <- matrix(c(1,4,rep(0,100),10), ncol = 1)
group_x <- as(m, "Matrix")

as.data.frame(as.matrix(..)) works fine:

str(as.data.frame(as.matrix(group_x)))
## 'data.frame':    103 obs. of  1 variable:
##  $ V1: num  1 4 0 0 0 0 0 0 0 0 ...

but:

gx <- list(group_x)
as.data.frame(as.matrix(gx))
##                                                       V1
## 1 <S4 class ‘dgCMatrix’ [package “Matrix”] with 6 slots>

So if what you have is gx, then

data.frame(Group = rownames(gx[[1]]), Value = gx[[1]][,1])

should work.

Create Sparse Matrix from a data frame

The Matrix package has a constructor made especially for your type of data:

library(Matrix)
UIMatrix <- sparseMatrix(i = trainingData$UserID,
                         j = trainingData$MovieID,
                         x = trainingData$Rating)

---

Otherwise, you might like knowing about that cool feature of the [ function known as matrix indexing. Your could have tried:

buildUserMovieMatrix <- function(trainingData) {
  UIMatrix <- Matrix(0, nrow = max(trainingData$UserID),
                        ncol = max(trainingData$MovieID), sparse = TRUE);
  UIMatrix[cbind(trainingData$UserID,
                 trainingData$MovieID)] <- trainingData$Rating;
  return(UIMatrix);
}

(but I would definitely recommend the sparseMatrix approach over this.)

---

Related Topics