I have a matrix mat_1 with specular rows and columns but one of both is missing. So let's say I want rows and columns following the alphabetical order: a, b, c, d, e, but my matrix is missing one of the letter, i.e. b.
How can I generate a code snippet that finds the gap(s) in the alphabetical sequence in mat_1, adds the missing row and column, and fills the observations with NaN in a second matrix mat_2?
Here is my reproducible example:
set.seed(100)
#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"))
#expected output
> mat_2
a b c d e
a -0.5021924 NaN 0.1315312 -0.07891709 0.88678481
b NaN NaN NaN NaN NaN
c 0.1169713 NaN 0.3186301 -0.58179068 0.71453271
d -0.8252594 NaN -0.3598621 0.08988614 0.09627446
e -0.2016340 NaN 0.7398405 0.12337950 -0.02931671
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