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.