lynnyi - 8 months ago 42

R Question

I have a matrix of numerical data with pesky zero columns I want to remove to do some data processing. I keep track of what columns are zero columns with

`is_zero_column <- colSums(matrix) == 0`

`matrix <- matrix[,colSums(matrix)!=0]`

Now how would I do the reverse, where I use my

`is_zero_column`

If this were not R, I would go for a forloop where I construct a new matrix: (in python-ish pseudocode)

`new_matrix;`

for i in is_zero_column:

if i is TRUE:

new_matrix <- new_matrix.append_column(rep(0, columnlength))

else:

new_matrix <- new_matrix.append_column(matrix[,1])

matrix <- matrix[,-1]

return new_matrix;

But, this is R, so trying to find a non for loop way of doing this.

Answer

Say if `Q`

is the matrix without zero columns:

```
Q
# [,1] [,2]
#[1,] 1 0
#[2,] 0 0
#[3,] 0 1
```

And `is_zero_column`

is as follows:

```
is_zero_column = c(F,T,F)
```

You can create a zero matrix with number of rows equal to number of rows in Q, and number of columns equal to length of `is_zero_column`

vector and then update non zero columns values with values in `Q`

:

```
Q1 = matrix(0, nrow(Q), length(is_zero_column))
Q1[, !is_zero_column] = Q
Q1
# [,1] [,2] [,3]
#[1,] 1 0 0
#[2,] 0 0 0
#[3,] 0 0 1
```

Source (Stackoverflow)