Common R Errors (and What They Mean)

R error messages can be cryptic, especially when you’re just starting out. This page translates the most common ones into plain English and shows you how to fix them.

Reading error messages

Every R error has the same structure:

Error in <where it happened>: <what went wrong>

Read from right to left: the what is usually more helpful than the where. And remember — errors are normal. Every R programmer sees them daily.

Object and function errors

object 'x' not found

ggplot(dat, aes(x = age, y = score)) + geom_point()
#> Error in ggplot(dat, aes(x = age, y = score)) : object 'dat' not found

What it means: R doesn’t know what dat is. You either haven’t created it yet, misspelled it, or forgot to run the line that defines it.

Fix: Check for typos. Make sure you ran the code that creates the object. If you’re in a Quarto document, remember that chunks run top-to-bottom — you can’t use something defined in a later chunk.

could not find function "x"

ggplot(data, aes(x = age)) + geom_bar()
#> Error in ggplot(data, aes(x = age)) : could not find function "ggplot"

What it means: R doesn’t recognize the function name. You probably forgot to load the package.

Fix: Add library(tidyverse) (or whatever package the function comes from) to the top of your script and run it. If you get an error on library() too, you need to install the package first:

# Run once in the Console (not in your script):
install.packages("tidyverse")

unused argument

mean(c(1, 2, NA), na.rm = true)
#> Error in mean(c(1, 2, NA), na.rm = true) : unused argument (na.rm = true)

What it means: You passed an argument the function doesn’t recognize — usually because of a typo or capitalization error.

Fix: R is case-sensitive. It’s TRUE, not true. Check the spelling of argument names too (na.rm, not na_rm).

Syntax errors

unexpected ')' or unexpected '}'

filter(data, age > 18
       species == "dog")
#> Error: unexpected symbol in "species"

What it means: R hit something it wasn’t expecting, almost always because of a missing comma, parenthesis, or pipe.

Fix: Check for:

  • Missing commas between arguments
  • Unmatched parentheses — count your ( and ) to make sure they pair up
  • A missing pipe |> or + between ggplot layers
TipRStudio helps with this

If you put your cursor next to a parenthesis, RStudio highlights its match. If there’s no highlight, you’re missing one.

unexpected input or unexpected string constant

name <- "Sara
#> Error: unexpected end of input

What it means: You opened a quote or parenthesis but never closed it. R is waiting for the rest.

Fix: Make sure every " has a matching ". If your Console shows a + instead of >, R is waiting for you to finish the expression. Press Escape to cancel and fix the line.

unexpected '='

data |> filter(age = 18)
#> Error in filter(age = 18) : unused argument (age = 18)

What it means: You used = (assignment) when you needed == (comparison).

Fix: Inside filter(), comparisons need ==:

data |> filter(age == 18)

Data errors

x must be numeric or non-numeric argument

mean(data$age)
#> Warning: argument is not numeric or logical: returning NA

What it means: You’re trying to do math on something that isn’t a number. The column might have been read as character or factor instead of numeric.

Fix: Check the column type with class(data$age) or glimpse(data). If it’s character, convert it:

data <- data |> mutate(age = as.numeric(age))

Column name issues

data |> select(reaction time)
#> Error: unexpected symbol in "data |> select(reaction time)"

What it means: Column names with spaces or special characters need backticks.

Fix:

data |> select(`reaction time`)

Even better — rename it right away:

data <- data |> rename(reaction_time = `reaction time`)

ggplot errors

mapping must be created by aes()

ggplot(data, x = age, y = score)
#> Error: mapping must be created by `aes()`

What it means: You forgot to wrap the aesthetics in aes().

Fix:

ggplot(data, aes(x = age, y = score))

geom_bar requires a missing aesthetic: y (or x)

ggplot(data, aes(x = age)) + geom_col()
#> Error: geom_col requires the following missing aesthetics: y

What it means: geom_col() needs both x and y. You might want geom_bar() instead (which counts for you), or you need to supply a y variable.

Fix: Use geom_bar() for counts, geom_col() when you have pre-computed values:

# Count how many in each group:
ggplot(data, aes(x = condition)) + geom_bar()

# Plot pre-computed values:
ggplot(summary_data, aes(x = condition, y = mean_score)) + geom_col()

stat_count() can only have an x or y aesthetic

What it means: You gave geom_bar() both x and y, but it only needs one (it counts the other automatically).

Fix: Either drop the y aesthetic from geom_bar(), or switch to geom_col() if you want to supply your own y values.

Plot doesn’t show up

What it means: You assigned the plot to an object but didn’t print it.

Fix: Either type the object name on its own line, or don’t assign it:

# This won't display:
my_plot <- ggplot(data, aes(x = age)) + geom_histogram()

# Add this line to display it:
my_plot

File and path errors

cannot open file 'data.csv': No such file or directory

read_csv("data.csv")
#> Error: 'data.csv' does not exist in current working directory

What it means: R can’t find the file. It’s looking in your working directory, and the file isn’t there.

Fix:

  1. Check you opened the R Project (look at the upper-right corner of RStudio)
  2. Check the file is in your project folder (look in the Files pane)
  3. Check for typos in the filename (capitalization matters!)

See Setting Up an R Project for more on how working directories work.

Warnings vs. errors

Not everything red is an error. R has two kinds of messages:

Type What it means What to do
Error Something broke. Code didn’t run. Fix it.
Warning Code ran, but R wants you to know something. Read it. Usually fine, sometimes important.

Common warnings you can usually ignore:

  • Removed N rows containing missing values — ggplot dropped NAs from your plot
  • package was built under R version X.X.X — version mismatch, usually harmless

Common warnings you should pay attention to:

  • NAs introduced by coercion — as.numeric() couldn’t convert some values
  • Removed N rows containing non-finite values — you might have unexpected Inf or NaN values

When you’re really stuck

  1. Read the error message carefully — it’s often more helpful than you think
  2. Google the exact error message (in quotes) — someone has had this problem before
  3. Restart R (Session > Restart R) and run your code from the top — this fixes more problems than you’d expect
  4. Ask for help — bring the error message to office hours or post it on the Canvas discussion board