How to Solve R Error: non-conformable arguments

by | Programming, R, Tips

In order to perform matrix multiplication in R, the number of columns in the left matrix must be the same as the number of rows in the right matrix. This error occurs when you try to multiply two matrices where the number of columns in the left matrix does not match the number of rows in the right matrix.

You can get the dimensions of matrices using the dim() function to ensure the matrices have appropriate dimensions for multiplication.

This tutorial will go through the error in detail with code examples.

Table of contents


Let’s look at an example of trying to multiply two matrices in R. First, we will define the first matrix.

mat1 <- matrix(1:15, nrow=5)
     [,1] [,2] [,3]
[1,]    1    6   11
[2,]    2    7   12
[3,]    3    8   13
[4,]    4    9   14
[5,]    5   10   15

Next, we will define the second matrix.

mat2 <- matrix(1:10, nrow=2)
     [,1] [,2] [,3] [,4] [,5]
[1,]    1    3    5    7    9
[2,]    2    4    6    8   10

Next, we will attempt to multiply the first matrix by the second matrix.

mat1 %*% mat2

Let’s run the code to see what happens:

Error in mat1 %*% mat2 : non-conformable arguments

The error occurs because the number of columns in the left matrix does not match the number of rows in the right matrix.


We can solve the error by first checking the dimensions of the matrices that we want to multiply using the dim() function.

[1] 5 3
[1] 2 5

From the output from the dim() function, we can see:

  • The first matrix has 5 rows and 3 columns
  • The second matrix has 2 rows and 5 columns

Therefore, we need to have the second matrix on the left and the first matrix on the right during the multiplication operation. Let’s look at the revised code:

mat2 %*% mat1

Let’s run the code to see the result:

     [,1] [,2] [,3]
[1,]   95  220  345
[2,]  110  260  410

We successfully multiplied the two matrices.


Congratulations on reading to the end of this tutorial!

For further reading on R-related errors, go to the articles:

Go to the online courses page on R to learn more about coding in R for data science and machine learning.

Have fun and happy researching!

Research Scientist at Moogsoft | + posts

Suf is a research scientist at Moogsoft, specializing in Natural Language Processing and Complex Networks. Previously he was a Postdoctoral Research Fellow in Data Science working on adaptations of cutting-edge physics analysis techniques to data-intensive problems in industry. In another life, he was an experimental particle physicist working on the ATLAS Experiment of the Large Hadron Collider. His passion is to share his experience as an academic moving into industry while continuing to pursue research. Find out more about the creator of the Research Scientist Pod here and sign up to the mailing list here!