Using a function within mapply to create and save scatterplots - r

Question

I am trying to use mapply to automate saving scatterplots from ggplot to a folder.
To do this I have created lists of my x variable and y variable, as well as a list of the grouping variable I would like to colour my points by.
I then tried creating a function, and calling the function with mapply but the only output saved is a single blank image of the last variable in the list. Below is an example dataset.
df <- data.frame("ID" = 1:16)
df$VarA <- c(1,1,1,1,1,1,1,1,1,1,1,14,NA_real_,NA_real_,NA_real_,16)
df$VarB <- c(10,0,0,0,12,12,12,12,0,14,NA_real_,14,16,16,16,16)
df$VarC <- c(10,12,14,16,10,12,14,16,10,12,14,16,10,12,14,16)
df$VarD <- c(10,12,14,16,10,12,14,16,10,12,14,16,10,12,14,16)
df$ControlVarA <- factor(c("Group_1","Group_1","Group_1","Group_1","Group_1", "Group_1",
"Group_2","Group_2","Group_2","Group_2","Group_2","Group_2",
"Group_2","Group_2","Group_2","Group_2"))
df$ControlVarB <- factor(c("Group_1","Group_1","Group_1","Group_1","Group_1", "Group_1",
"Group_1","Group_1","Group_1","Group_1","Group_2","Group_2",
"Group_2","Group_2","Group_2","Group_2"))
df$ControlVarC <- factor(c("Group_2","Group_2","Group_2","Group_2","Group_1", "Group_1",
"Group_2","Group_2","Group_2","Group_2","Group_2","Group_2",
"Group_2","Group_2","Group_2","Group_2"))
Below is the code I used to call the lists for the x, y and colouring variable.
x_lists <- df %>% select(VarA:VarB) %>% colnames(.)
y_lists <- df %>% select(VarC:VarD) %>% colnames(.)
ControlVar_list <- df %>% select(contains("ControlVar")) %>% colnames(.)
Below is the function I have created and the mapply
save_plots <- function(dataset, x, y, z) {
first_plot <- ggplot(dataset) +
geom_point(data = subset(dataset, .data[[z]] == 'Group_1'),
aes(x = .data[[x]], y = .data[[y]], color = .data[[z]], size = 3)) +
geom_point(data = subset(dataset, .data[[z]] == 'Group_2'),
aes(x = .data[[x]], y = .data[[y]], color = .data[[z]], size = 3)) +
geom_smooth(aes(x = .data[[x]], y = .data[[y]], size = 0), method = "lm", colour="black", size=0.5) +
stat_cor(aes(x = .data[[x]], y = .data[[y]], color = .data[[z]],
label = ..rr.label..),
label.y.npc="top", label.x.npc = "left", method = "pearson",
size = 5) +
scale_color_manual(values = c("#C5BEC9", "#F2642b", "#F2642b")) +
labs(title = "test",
x = "VarA",
y = "VarB",
colour = "") +
guides(size = FALSE, color = FALSE) +
theme_bw(base_size = 14)
ggsave(sprintf("C:\\Documents\\%s.tiff", y), first_plot)
grDevices::dev.off()
}
mapply(save_plots, x_lists, y_lists, ControlVar_list, MoreArgs = list(dataset = df))

Answer 1

.data will not work with base R subset function. Try using dplyr::filter
library(tidyverse)
library(ggpubr)
save_plots <- function(dataset, x, y, z) {
first_plot <- ggplot(dataset) +
geom_point(data = filter(dataset, .data[[z]] == 'Group_1'),
aes(x = .data[[x]], y = .data[[y]], color = .data[[z]], size = 3)) +
geom_point(data = filter(dataset, .data[[z]] == 'Group_2'),
aes(x = .data[[x]], y = .data[[y]], color = .data[[z]], size = 3)) +
geom_smooth(aes(x = .data[[x]], y = .data[[y]], size = 0), method = "lm", colour="black", size=0.5) +
stat_cor(aes(x = .data[[x]], y = .data[[y]], color = .data[[z]],
label = ..rr.label..),
label.y.npc="top", label.x.npc = "left", method = "pearson",
size = 5) +
scale_color_manual(values = c("#C5BEC9", "#F2642b", "#F2642b")) +
labs(title = "test",
x = "VarA",
y = "VarB",
colour = "") +
guides(size = FALSE, color = FALSE) +
theme_bw(base_size = 14)
ggsave(sprintf("%s.tiff", y), first_plot)
grDevices::dev.off()
}