how do i vectorise (automate) plot creation in R - r

Question

edited to include sample data:
Sample data
I have been trying to write code to generate and save multiple plots from a large dataset and have to admit defeat. Would love some help if possible..
i have a df (dat) of 4 years of daily monitoring data (sampling year goes July - June, so Sampling.Year notation is YYYY-YYYY). I would like to export jpgs for each SITENAME, with facet wrap/facet grid so each Sampling.Year is stacked vertically. Individual Sampling.Year plots show timeseries data for the full year (x=DATE, y = Daily.Ave.PAF). End result should be individual jpg files (SITENAME saved in file name) with sampling years stacked but DATE (x axis) aligned. That way we can get a quick snapshot of differences over time. The string is below and my (probably crappy) code is below that. The code is exporting plots just fine, but the data seems to be mixed up - i.e. where a SITENAME only has 2 Sampling.Years worth of data there should only be 2 plots in the jpg but this code produces 4... it's obviously wrong but I don't know how to fix it. THanks in advance.
'data.frame': 521 obs. of 6 variables:
$ STATION : chr "1240062" "125013A" "122013A" "126001A" ...
$ SITENAME : chr "Oconnell River at Caravan Park" "Pioneer River at Dumbleton Weir Headwater" "Proserpine River at Glen Isla" "Sandy Creek at Homebush" ...
$ Sampling.Year: chr "2016-2017" "2018-2019" "2018-2019" "2018-2019" ...
$ DATE : Date, format: "2017-02-01" "2019-02-01" "2019-02-01" "2019-02-01" ...
$ Daily.Ave.PAF: num 24.344 15.226 45.529 44.936 0.208 ...
$ Site.Year : chr "Oconnell River at Caravan Park_2016-2017" "Pioneer River at Dumbleton Weir Headwater_2018-2019" "Proserpine River at Glen Isla_2018-2019" "Sandy Creek at Homebush_2018-2019" …
CODE:
for(i in 1:length(dat)){
png(filename = paste("N:/Projects and project proposals/", dat$SITENAME[i], ".png", sep=""), width = 1500, height = 1000)
print({pesticidePlot <- ggplot(dat, aes(DATE, Daily.Ave.PAF)) +
geom_point(aes(colour = Daily.Ave.PAF)) +
scale_colour_gradientn(colours=c("dark green","yellow","orange", "red"),
breaks=c(5,10,20), labels=format(c("5", "10", "20"))) +
facet_wrap(~Sampling.Year, ncol = 1,scales="free") +
labs(x = "Month", y = "Total PAF (% affected)") +
scale_x_date(breaks = "1 month", labels = date_format("%B")) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))})
dev.off()
}

Answer 1

This code can help you. I have used the data you included (Just define a directory to save the plots):
library(tidyverse)
#Data
dat <- read.csv('Sample.csv',stringsAsFactors = F)
dat$DATE <- as.Date(dat$DATE,'%d/%m/%Y')
#Create a list
List <- split(dat,dat$SITENAME)
#Function for plots
myplot <- function(x)
{
pesticidePlot <- ggplot(x, aes(DATE, Daily.Ave.PAF)) +
geom_point(aes(colour = Daily.Ave.PAF)) +
scale_colour_gradientn(colours=c("dark green","yellow","orange", "red"),
breaks=c(5,10,20), labels=format(c("5", "10", "20"))) +
facet_wrap(~Sampling.Year, ncol = 1,scales="free") +
labs(x = "Month", y = "Total PAF (% affected)") +
scale_x_date(breaks = "1 month", labels = scales::date_format("%B-%y")) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+
ggtitle(unique(x$SITENAME))
return(pesticidePlot)
}
#Create plots
List2 <- lapply(List,myplot)
#Export
namesvec <- paste0(names(List2),'.png')
mapply(ggsave, List2,filename=namesvec,width = 15,units = 'cm')
That code will create next plots:
You can modify myplot if you need a more customized plots.

Answer 2

Here is a solution that will save the plots created in a lapply loop. The files are then written in another loop, this time with mapply.
In the example below the files are saved in the working directory, change this at will.
library(ggplot2)
SITENAME_plot <- function(X){
ggplot(X, aes(DATE, Daily.Ave.PAF)) +
geom_point(aes(colour = Daily.Ave.PAF)) +
scale_colour_gradientn(colours=c("dark green","yellow","orange", "red"),
breaks=c(5,10,20), labels=format(c("5", "10", "20"))) +
labs(x = "Month", y = "Total PAF (% affected)") +
scale_x_date(breaks = "1 month", labels = scales::date_format("%B")) +
facet_wrap(~Sampling.Year, ncol = 1, scales = "free") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1))
}
SITENAME_plot_write <- function(name, g, dir = "N:/Projects and project proposals"){
flname <- file.path(dir, name)
flname <- paste0(flname, ".png")
png(filename = flname, width = 1500, height = 1000)
print(g)
dev.off()
flname
}
dat$DATE <- as.Date(dat$DATE, format = "%d/%m/%Y")
sp <- split(dat, dat$SITENAME)
gg_list <- sapply(sp, SITENAME_plot, simplify = FALSE)
mapply(SITENAME_plot_write, names(gg_list), gg_list, MoreArgs = list(dir = getwd()))
rm(sp) # final clean-up