advanced patterns when using `ggplot2` to map categorical variables to colors with `scale_color_manual()`
I'm stuck on something that should probably be simple. I'm working with `ggplot2` version 3.3.5 and trying to manually map colors to categorical variables using `scale_color_manual()`. I have a dataset with a categorical variable representing different species, and I want to assign specific colors to each species. However, when I try to create the plot, the colors are not applied as expected; instead, they appear to default to the ggplot color scale. Here’s the code I am using: ```R library(ggplot2) df <- data.frame( species = factor(c('setosa', 'versicolor', 'virginica', 'setosa', 'versicolor')), sepal_length = c(5.1, 7.0, 6.3, 5.5, 6.4) ) my_colors <- c('setosa' = '#FF9999', 'versicolor' = '#66B3FF', 'virginica' = '#99FF99') p <- ggplot(df, aes(x = sepal_length, y = species, color = species)) + geom_point(size = 4) + scale_color_manual(values = my_colors) print(p) ``` When I run this code, the points for the species appear in default colors instead of the specified colors in `my_colors`. Additionally, I receive a warning message: "Discrete value supplied to continuous scale". I’ve verified that the species variable is indeed a factor. What could be causing this scenario, and how can I ensure that my specified colors are applied correctly to the points in the plot? For context: I'm using R on Linux. I'd really appreciate any guidance on this. My development environment is Linux. How would you solve this? The stack includes R and several other technologies.