Don’t know how to automatically pick scale for object of type

Don’t know how to automatically pick scale for object of type, The ggplot2 error “Don’t know how to automatically pick scale for object type” in R is addressed in this article with examples.

Let’s start the discussion,

Take into account the example data below.

data <- data.frame(Mean = 1:6,Group = letters[1:6])
data
Mean Group
1 1 a
2 2 b
3 3 c
4 4 d
5 5 e
6 6 f

Our example data’s structure is shown in Table 1: Six rows with the columns “Mean” and “Group” make up this table.

We also need to load and install ggplot2 in order to use it to plot our data using the ggplot2 package:

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#install.packages("ggplot2")
library("ggplot2")

Example 1: Reproduce the ggplot2 error

We’ll show you how to make R produce the ggplot2 error in this example. Assume we want to create a ggplot2 barplot with our data. Then, we may attempt to use the R code below:

ggplot(data, aes(Group, mean)) +
geom_bar(stat = "identity")
Don't know how to automatically pick scale for object of type . Defaulting to
continuous.
Error in geom_bar():
! Problem while computing aesthetics.
i Error occurred in the 1st layer.
Caused by error in compute_aesthetics():
! Aesthetics are not valid data columns.
x The following aesthetics are invalid:
x y = mean
i Did you mistype the name of a data column or forget to add after_stat()?
Run rlang::last_trace() to see where the error occurred.

Unfortunately, the ggplot2 above error is returned by the R programming language.

This is because we specified the y variable to equal “mean” rather than “Mean” (notice the capitalization of the “M”).

Because of this, R makes the incorrect assumption that we want to utilize the mean function in place of our Mean variable.

How therefore can we resolve this issue? will go on to clarify that.

Example 2: Automatically select scale for objects of type standard generic to fix the ggplot2 error

This example demonstrates how to overcome the “Don’t know how to automatically pick scale for object type” error in ggplot2.

To achieve this, we merely need to appropriately describe the variable name of our data (i.e., capitalize “Mean”):

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