When working with `ggplot2`

in R, you might encounter this error:

Don’t know how to automatically pick scale for object of type standardGeneric. Defaulting to continuous.

This error occurs when you attempt to create a plot using `ggplot2`

but mistakenly provide the name of a built-in R function (such as `mean`

, `median`

, `max`

, `sample`

, or `range`

) in the `aes()`

argument. Since these are functions, `ggplot2`

doesn’t know how to treat them as data.

## Example

Here’s an example to reproduce the error:

# Load ggplot2 library(ggplot2) # Attempt to plot using a function name in aes() ggplot(mtcars, aes(x = mean, y = mpg)) + geom_point()

When you run this, you’ll see the following error:

Don't know how to automatically pick scale for object of type <standardGeneric>. Defaulting to continuous.

### Explanation

In this example, `mean`

is a built-in R function, not a variable or column in your dataset. The `aes()`

function expects variables or data columns, but because `mean`

is a function, `ggplot2`

doesn’t know how to map it to the axes and defaults to assuming it might be continuous. This leads to the error.

### Solution 1: Use the Correct Variable

The easiest solution is to replace the function name with the actual column name from your dataset that you want to plot.

For example, if you meant to plot the `mpg`

column against `hp`

(horsepower), you can fix the code as follows:

# Correct usage of variables in aes() ggplot(mtcars, aes(x = hp, y = mpg)) + geom_point()

This will generate the scatter plot as intended without the error.

### Solution 2: Calculate the Statistic Outside `aes()`

If your goal is to use a function like `mean()`

to summarize your data, calculate the value outside of `aes()`

and then add it to the plot. For example, if you want to visualize how the cars in the dataset compare to the mean `mpg`

:

# Calculate the mean of mpg mean_mpg <- mean(mtcars$mpg) # Add the mean as a horizontal line to the plot ggplot(mtcars, aes(x = hp, y = mpg)) + geom_point() + geom_hline(yintercept = mean_mpg, linetype = "dashed", color = "red")

This method allows you to plot data and include statistics like the mean without causing errors.

### Solution 3: Using `stat_summary`

for Summarization in `ggplot2`

Alternatively, if you want `ggplot2`

to calculate the statistic for you, use `stat_summary()`

to summarize the data directly within the plot:

# Using stat_summary to plot mean values ggplot(mtcars, aes(x = factor(cyl), y = mpg)) + stat_summary(fun = mean, geom = "point", color = "blue", size = 3)

In this example, the plot shows the mean `mpg`

for each cylinder group, with `ggplot2`

handling the computation for you.

## Conclusion

The error `'Don’t know how to automatically pick scale for object of type standardGeneric'`

occurs when you pass a function instead of a variable into `aes()`

. The solution is to pass the correct variables or precompute any statistics before plotting. Additionally, you can use `stat_summary()`

to have `ggplot2`

calculate statistics directly.

Congratulations on reading to the end of this tutorial!

For further reading on `ggplot2`

errors, go to the articles:

- How to Solve R Error: ggplot2 doesn’t know how to deal with data of class character
- How to Solve R Error: ggplot2 doesn’t know how to deal with data of class matrix
- How to Solve R Error: StatBin requires a continuous x variable: the x variable is discrete. Perhaps you want stat=”count”?

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.