This error occurs if you try to perform a mathematic operation on a character vector. You can solve this error by converting the characters to numeric values using the as.numeric()
function. For example,
x <- c("2", "3", "4", "5") x_num <- as.numeric(x) sum(x_num)
Alternatively, if the character values represent categories you can use the aggregate()
function to group by the categories.
This tutorial will go through the error in detail with code examples.
Example #1
Let’s look at an example to reproduce the error.
# Define a character vector x <- c("2", "3", "4", "5") # Attempt to calculate sum sum(x)
Let’s run the code to see what happens:
Error in sum(x) : invalid 'type' (character) of argument
The error occurs because mathematical operations like sum()
are only suitable for numeric vectors. The vector x
is of a character vector, which we can confirm using the class()
function.
class(x)
[1] "character"
Solution
We can solve the error by converting the character
vector to a numeric
vector using the as.numeric()
function. Let’s look at the revised code:
x <- c("2", "3", "4", "5") x_num <- as.numeric(x) sum(x_num)
Let’s run the code to get the sum:
[1] 14
We can confirm that x_num
is a numeric vector using the class()
function:
class(x_num)
[1] "numeric"
Example #2
Let’s look at a second example to reproduce the error:
# Define data frame df <- data.frame(fruit=c('pineapple', 'apple', 'pineapple', 'blueberry', 'apple', 'apple', 'pear', 'blueberry'), amount_sold=c(75, 50, 89, 76, 45, 98, 58, 64)) # Calculate some of values in fruit column sum(df$fruit)
Let’s run the code to see what happens:
Error in sum(df$fruit) : invalid 'type' (character) of argument
The error occurs because the column 'fruit'
is a character column, which we can confirm using the class()
function:
class(df$fruit)
[1] "character"
Solution
We can solve the error by only using mathematical operations with numeric vectors. We could use the sum()
function on the amount_sold
column as it is numeric.
df <- data.frame(fruit=c('pineapple', 'apple', 'pineapple', 'blueberry', 'apple', 'apple', 'pear', 'blueberry'), amount_sold=c(75, 50, 89, 76, 45, 98, 58, 64)) sum(df$amount_sold)
[1] 555
We can also use the aggregate function to group the rows in the data frame by fruit
and calculate the sum of the amount_sold
for each category.
aggregate(amount_sold ~ fruit, df, sum)
Let’s run the code to see the result:
fruit amount_sold 1 apple 193 2 blueberry 140 3 pear 58 4 pineapple 164
We successfully summed up the amount sold for each type of fruit in the data frame.
Summary
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: Arguments imply differing number of rows
- How to Solve R Error: more columns than column names
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 senior advisor in data science with deep expertise in Natural Language Processing, Complex Networks, and Anomaly Detection. Formerly a postdoctoral research fellow, he applied advanced physics techniques to tackle real-world, data-heavy industry challenges. Before that, he was a particle physicist at the ATLAS Experiment of the Large Hadron Collider. Now, he’s focused on bringing more fun and curiosity to the world of science and research online.