Question

This is my first post. Apologies in advance if my question is dumb. I’m new to programming.

Ok, So I have a a matrix(eBpvalues) in R that has 152720 rows and 2 columns.
I want to split into 10 separate matrices containing 15272 rows each.

I have tried this with:

> newmx <-split(as.data.frame(eBpvalues), rep(1:10, each = 15272)))

> summary(newmx)  

   Length Class      Mode  
1  2      data.frame list    
2  2      data.frame list  
3  2      data.frame list  
4  2      data.frame list  
5  2      data.frame list  
6  2      data.frame list  
7  2      data.frame list  
8  2      data.frame list  
9  2      data.frame list  
10 2      data.frame list  

How would I go about joining these matrices side-by-side so I have a new matrix with 20 columns and 15272 rows?

Cheers,

Neil

Answer 1

You are almost there. An often used function in these situations is do.call, which takes a function you want to apply and a list of data to apply it to. The function you want to apply is cbind to column bind the 10 data frames/matrices together.

Taking you literally, we start with a matrix mat (eBpvalues in your Q), of appropriate size. Convert to a data frame:

mat <- matrix(rnorm(152720 * 2), ncol = 2)
df <- data.frame(mat)

An easy way of producing an indicator factor is via the gl() function:

ind <- gl(10, 15272)

Then we have your split() call:

newMat <- split(df, ind)

The last step is this, where we us do.call() to apply cbind() to the set of data frames in newMat:

res <- do.call(cbind, newMat)

This gives us what you wanted (although you might need to tidy the column names up etc).

> str(res)
'data.frame':   15272 obs. of  20 variables:
 $ 1.X1 : num  -0.268 -0.8568 -0.0267 1.0894 1.5847 ...
 $ 1.X2 : num  0.71 -0.298 0.359 0.97 -2.158 ...
 $ 2.X1 : num  -0.987 -0.222 2.991 0.443 0.228 ...
 $ 2.X2 : num  -2.343 -1.023 -1.48 1.47 0.758 ...
 $ 3.X1 : num  -0.305 -0.761 0.817 1.347 0.694 ...
 $ 3.X2 : num  -0.0915 0.4816 1.4662 -1.2668 -1.3523 ...
 $ 4.X1 : num  -0.678 -1.056 1.029 -0.468 0.836 ...
 $ 4.X2 : num  -0.656 -0.459 -0.965 -1.666 0.877 ...
 $ 5.X1 : num  -0.295 -1.255 1.395 -1.985 -1.71 ...
 $ 5.X2 : num  1.141 1.177 -1.003 -0.29 -0.234 ...
 $ 6.X1 : num  -0.0548 1.8673 -1.5388 -1.1063 0.3923 ...
 $ 6.X2 : num  -1.399 0.57 0.367 -0.811 -2.434 ...
 $ 7.X1 : num  0.389 -1.058 0.61 1.102 -0.063 ...
 $ 7.X2 : num  0.854 1.251 1.095 -0.485 0.451 ...
 $ 8.X1 : num  -2.018 0.849 0.3 0.988 -1.993 ...
 $ 8.X2 : num  -1.23 -1.025 -0.546 1.674 0.588 ...
 $ 9.X1 : num  0.814 0.726 1.04 0.985 1.781 ...
 $ 9.X2 : num  -1.094 -1.051 0.749 1.426 0.402 ...
 $ 10.X1: num  0.3786 1.6131 -0.4149 0.0684 -0.815 ...
 $ 10.X2: num  0.383 -0.136 -0.751 -0.164 0.434 ...