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:
This tutorial will go through the error in detail and how to solve it with code examples.
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.
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
Congratulations on reading to the end of this tutorial!
For further reading on R-related errors, go to the articles:
- How to Solve R Error in sort.int(x, na.last = na.last, decreasing = decreasing, …) : ‘x’ must be atomic
- How to Solve R Error as.Date.numeric(x) : ‘origin’ must be supplied
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!
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!