I have a collection of bacteria data from approximately 140 monitoring locations in California. I would like to produce a scatterplot for each monitoring location with the Sampling Date on the Y-axis and the Bacteria Data on the X-axis. The Sampling Date, Bacteria Data, and Monitoring Location all reside within their own column.
I've come up with the below code:
## Create List of Files ## filenames <- list.files(path = "C:\\Users\\...") ## Combine into one CSV ## All_Data <- ldply(filenames, read.csv) All_Data$SampleDate <- as.Date(All_Data$SampleDate, origin="1899-12-30") ## Save CSV for possible future use ## write.csv(All_Data, file= "C://Users//...", row.names = FALSE) ## Construct Plots ## ggplot(All_Data) + geom_point(mapping =aes(SampleDate, Total.Result)) + facet_wrap( ~ Identifier) +ylim(0,20000)
I tried to incorporate the subset function like so
ggplot(All_Data) + geom_point(mapping =aes(SampleDate, Total.Result)) + facet_wrap( ~ subset(All_Data, Identifier)) +ylim(0,20000)
but received the error
Error in subset.data.frame(All_Data, Identifier) : 'subset' must be logical
Alternatively, is it better to do this through some sort of loop through the original 15 csvs that I've combined together? I would still have the challenge of creating one plot per monitoring location. Thanks in advance for any suggestions!