How to Solve R Error: invalid (do_set) left-hand side to assignment

by | Programming, R, Tips

This error occurs if you try to create a variable with a name beginning with a number.

You can solve this error by ensuring the variable starts with a letter or a dot.

You can see the documentation for syntactically valid names by typing the following command:

?make.names

This tutorial will go through the error in detail and how to solve it with code examples.


Example

Let’s look at an example to reproduce the error.

# Attempt to create data frame

2 <- data.frame(x=c(rnorm(10)),
                  y=c(rnorm(10)))

2

Let’s run the code to see what happens:

Error in 2 <- data.frame(x = c(rnorm(10)), y = c(rnorm(10))) : 
  invalid (do_set) left-hand side to assignment

The error occurs because the variable name is a number.

Solution

We can solve this error by ensuring the variable names starts with a letter or a dot. Let’s look at the revised code:

# Attempt to create data frame with name starting with a letter

df2 <- data.frame(x=c(rnorm(10)),
                  y=c(rnorm(10)))

df2

Let’s run the code to see the result.

             x            y
1   1.487757090  1.052458495
2  -0.001891901 -1.305063566
3   1.381020790 -0.692607634
4  -0.380213631  0.602648854
5   0.184136230 -0.197753074
6  -0.246895883 -1.185874517
7  -1.215560910 -2.005512989
8   1.561405098  0.007509885
9   0.427310197  0.519490356
10 -1.201023506 -0.746295471

We can also use a data frame that starts with a dot. Let’s look at the revised code:

.df2 <- data.frame(x=c(rnorm(10)),
                  y=c(rnorm(10)))

.df2

Let’s run the code to see the result:

           x          y
1   0.7264546 -0.8174286
2   0.7136567  0.6758935
3  -0.6500629 -0.2154811
4   1.4986962 -0.1146497
5  -1.4358281 -0.2022654
6  -2.1613182  0.4064927
7   0.3952199  0.6567724
8  -0.3948340  0.1061908
9  -0.3097584 -0.1843974
10  1.3308266  0.9460342

Summary

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!