I have a technical issue with my attempts to plot group differences whilst accounting for 3 variables. This all works fine until I attempt to plot the line of best fit for each group; which results in a plot that makes it difficult to distinguish between groups (as seen below)
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, color = Petal.Length, shape = Species)) + geom_point() +
scale_color_viridis_c() +
geom_smooth(method = "lm", se = FALSE, show.legend = TRUE)
I would like to provide a manual discrete colour for each best fit line, so that readers can distinguish between groups easier (for example; something like having a red line for setosa, a white line for versicolor and black line for virginica). Below are the examples of what I have tried so far with their associated error messages.
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, color = Petal.Length, shape = Species)) + geom_point() +
scale_color_viridis_c() +
geom_smooth(method = "lm", se = FALSE, show.legend = TRUE, aes(color = Species))
"Error: Discrete value supplied to continuous scale"
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, color = Petal.Length, shape = Species)) + geom_point() +
scale_color_viridis_c() +
geom_smooth(method = "lm", se = FALSE, show.legend = TRUE , aes(color = Species)) +
scale_color_discrete()
"Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing scale.
geom_smooth() using formula 'y ~ x'
Error: Continuous value supplied to discrete scale"
Any recommendations on how to manually assign a colour to each line (whilst leaving the scatter plot colours unchanged) would be very appreciated.
Many thanks in advance,
Rhys
