Hi David,

You "just" need to learn how to subset your data.frame, see functions like ?subset and ?"[", as well as a good guide to understand the subtleties!

Some graphic functions also have a built-in argument to subset within the function (e.g. argument 'subset' in 'plot.formula'), although the ggplot() function doesn't seem to have it.

In any case, I would recommend you spend some time learning that aspect, as you will always need it in one situation or another.

HTH,
Ivan

--
Dr. Ivan Calandra
TraCEr, laboratory for Traceology and Controlled Experiments
MONREPOS Archaeological Research Centre and
Museum for Human Behavioural Evolution
Schloss Monrepos
56567 Neuwied, Germany
+49 (0) 2631 9772-243
https://www.researchgate.net/profile/Ivan_Calandra

On 29/11/2017 22:07, David Doyle wrote:
Say I have a dataset that looks like

Location    Year      GW_Elv
MW01        1999       546.63
MW02        1999       474.21
MW03        1999       471.94
MW04        1999        466.80
MW01        2000        545.90
MW02        2000        546.10

The whole dataset is at http://doylesdartden.com/ExampleData.csv
and I use the code below to do the graph but I want to do it without MW01.
How can I remove MW01??

I'm sure I can do it by SubSeting but I can not figure out how to do it.

Thank you
David

--------------------------------------------------------------

library(ggplot2)

MyData <- read.csv("http://doylesdartden.com/ExampleData.csv";, header=TRUE,
sep=",")



#Sets whic are detections and nondetects
MyData$Detections <- ifelse(MyData$D_GW_Elv ==1, "Detected", "NonDetect")

#Removes the NAs
MyDataWONA <- MyData[!is.na(MyData$Detections), ]

#does the plot
p <- ggplot(data = MyDataWONA, aes(x=Year, y=GW_Elv , col=Detections)) +
   geom_point(aes(shape=Detections)) +

   ##sets the colors
   scale_colour_manual(values=c("black","red")) + #scale_y_log10() +

   #location of the legend
   theme(legend.position=c("right")) +

   #sets the line color, type and size
   geom_line(colour="black", linetype="dotted", size=0.5) +
   ylab("Elevation Feet Mean Sea Level")

## does the graph using the Location IDs as the different Locations.
p + facet_grid(Location ~ .)

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