class_day <- c(1:10)
control_group <- c(67,72,69,81,73,66,71,72,77,71)
A_treatment_group <- c(NA,72,77,81,73,85,69,73,74,77)
B_treatment_group <- c(NA,66,68,69,67,72,73,75,79,77)
class.df<-data.frame(class_day, control_group, A_treatment_group, B_treatment_group)
I tried to convert vecotrs to a table but I am not sure how to include three categories in one plot.
How can I get a scatter plot with three different colors? I would like to set x-axis as class_day above and y axis as scores.
First, A cleaner way to make a dataframe without the intermediate variables.
You can make this type of chart by pivoting the data into "long" form:
class.df<-data.frame(class_day = c(1:10),
control_group = c(67,72,69,81,73,66,71,72,77,71),
A_treatment_group = c(NA,72,77,81,73,85,69,73,74,77),
B_treatment_group = c(NA,66,68,69,67,72,73,75,79,77) )
library(tidyverse)
class.df %>%
pivot_longer(!class_day) %>%
ggplot(aes(x=class_day, y=value, color=name))+
geom_point()
Here is a version with ggscatter from ggpubr:
library(ggpubr)
library(tidyverse)
class.df %>%
pivot_longer(-class_day,
names_to= "group",
values_to = "score") %>%
ggscatter(x = "class_day", y = "score", color = "group",
palette = c("#00AFBB", "#E7B800", "#FC4E07"))
