*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 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!