Plotting NDs

One very useful procedure is to plot nondetects a different color and/or symbols.

Here is the simple code to load and generate the plot. The example spreadsheet is below.

#Add line between the points

lines(Year,MW1)

#NDs plotted different colors For spreadsheet with Year and data in MW01 and Detect on and off in D_MW01

attach(data)

reg1 <- lm(MW1~Year)

par(cex=1)

plot(Year, MW1, col=ifelse(D_MW1, "black", "red"),ylab = "Parameter X mg/L", pch=ifelse(D_MW1, 19, 17), cex = 1.5)

#Load your data. The data is in a spreadsheet named nd-spreadsheet and we are going to call it data in R

data <- read.table("nd-spreadsheet.csv", header=TRUE, sep=",",)

#set the dir to where you data is

setwd("c:/R")

#Load your data. The data is in a spreadsheet named nd-spreadsheet and we are going to call it data in R

data <- read.table("nd-spreadsheet.csv", header=TRUE, sep=",",)

#NDs plotted different colors For spreadsheet with Year and data in MW01 and Detect on and off in D_MW01

attach(data)

reg1 <- lm(MW1~Year)

par(cex=1)

plot(Year, MW1, col=ifelse(D_MW1, "black", "red"), pch=ifelse(D_MW1, 19, 17), cex = 1.5)

# Done

__________________________________________________________________________________________

#BELLS AND WHISTLES CODE (Has a regression line with confidence intervals at 95% around it)

Notes Read 1st:

lines with # in front is for your information and will be ignored by R.
You will need make a dir on your C drive named R.
You will need to save the attached spreadsheet to that dir.
Nondetects are defined by the 0 in the D_MW1 column and detects have a 1

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#SIMPLE CODE

#set the dir to where you data is

setwd("c:/R")

#Adds confindance bands at 0.95 level

ciband= with(data,predict(reg1,as.data.frame(Year),interval='confidence',level=.95))

ciband= data.frame(Year,ciband)

with(ciband,lines(Year,fit,lty=1,lwd=3))

with(ciband,lines(Year,lwr,lty=3,lwd=3,col="blue"))

with(ciband,lines(Year,upr,lty=3,lwd=3,col="blue"))

#Add Legend to graph

legend("topleft", c("Confidence interval 95%","Regression", "Detected", "NonDetect"), col = c("blue",1, "black","red"), cex = 1,

text.col = "black", lty = c(2, 1 ,-1, -1), pch = c(-1, -1, 19, 17),

merge = TRUE, bg = 'gray90')

#Add title

title(main="MW1")

# Done

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Here is a little different ver using a different data set format.

#Makes the scale log

scale_y_log10()+

##sets the colors

scale_colour_manual(values=c("black","red")) +

#location of the legend

theme(legend.position=c(0.05,0.1)) +

#sets the line color, type and size

geom_line(colour="black", linetype="dotted", size=0.5) +

##Graph title

ggtitle("Antimony mg/L")

## does the graph using the Well IDs as the different wells.

p + facet_grid(Well.ID ~ .)

#saves the graph to the working dir. Note if you want pdf just change jpg to pdf

ggsave("Antimony.jpg")

##Note you can adjust the print size by adjusting the output window in R or you can do some searches for ggplot size.

#######

#does the plot

p <- ggplot(data = mydata, aes(x=Year, y=Antimony, col=Detections)) +

geom_point(aes(shape=Detections)) +

#Sets whic are detections and nondetects

mydata$Detections <- ifelse(mydata$D_Antimony==1, "Detected", "NonDetect")

#Loads data

mydata <-read.csv("http://doylesdartden.com/R/2014_02_data.csv", sep=",")

#Loads ggplot2 package NOTE you must install it 1st.

library(ggplot2)

#sets the working dir

setwd("c:/R")

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