How to replace all columns in matrix with NA based on variable in another dataframe?

Question

I have a large adjacency matrix and a dataframe with a variable 'missing'. I need to replace all rows in the matrix with NA, for which 'missing' = TRUE (rows match between matrix and dataframe).

Example: I have: matrix

     [,1] [,2] [,3]
[1,]    0    0    1
[2,]    1    0    1
[3,]    0    1    0

and dataframe

  ID missing
1  1   FALSE
2  2   FALSE
3  3    TRUE

I need: matrix

     [,1] [,2] [,3]
[1,]    0    0    1
[2,]    1    0    1
[3,]   NA    NA    NA

Reproducible data:

m1.data <- c(0, 1, 0, 0, 0, 1, 1, 1, 0 )
m1 <- matrix(m1.data, nrow = 3)

df <- data.frame(ID = c(1, 2, 3),
                missing = c(FALSE, FALSE, TRUE))

Hope that someone can help! Thank you so much in advance!

akrun · Accepted Answer · 2022-01-09 18:14:14Z

4

We can extract the missing column and use that as the row index in m1 and assign it to NA

m1[df$missing,] <- NA

-output

> m1
     [,1] [,2] [,3]
[1,]    0    0    1
[2,]    1    0    1
[3,]   NA   NA   NA

Or we may do

> NA^(df$missing) * m1
     [,1] [,2] [,3]
[1,]    0    0    1
[2,]    1    0    1
[3,]   NA   NA   NA

answered Jan 9, 2022 at 18:14

akrun

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3 Comments

TarJae Over a year ago

What are you doing with ^

akrun Over a year ago

The NA^ changes the TRUE values to NA and FALSE to 1

akrun Over a year ago

@TarJae It is a hacky way i.e for ^ if you use any other value other than 0, it returns NA i.e. NA^1 NA^2, NA^0. Since, TRUE -> 1, it returns the NA

TarJae · Accepted Answer · 2022-01-09 18:20:59Z

3

With which we could get the Id for the missing and assing a NA to m1 it is similar to akrun's approach m1[df$missing,] <- NA

m1[which(df$missing==TRUE),] <- NA

     [,1] [,2] [,3]
[1,]    0    0    1
[2,]    1    0    1
[3,]   NA   NA   NA

answered Jan 9, 2022 at 18:20

TarJae

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