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@moorepants
Created December 4, 2010 17:48
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Yumi's data analysis in R
# bring in the data
Redox = read.csv('Redox.csv', header=TRUE)
print(names(Redox))
# make an example plot for iron, PH average
ironsub = subset(Redox, trt == "High Fe(II)" | trt == "Low Fe(II)")
xlim = range(Redox$day, na.rm=TRUE)
ylim = range(Redox$pH, na.rm=TRUE)
ylim = c(floor(ylim[1]), ceiling(ylim[2]))
plot(0, 0, type="n", xlim=xlim, ylim=ylim, axes=FALSE, frame.plot=TRUE,
xlab="Time(d)", ylab="pH")
lowFe100 = subset(Redox, trt == "Low Fe(II)" & per.dose == 100,
select=c(day, pH))
# setup a dummy avgpH vector that gives a place for the avg values to go
#avgpH = 1:length(unique(lowFe100$day))
#stdpH = avgpH
#
#for (i in avgpH)
#{
#phforthatday = subset(lowFe100, day == unique(lowFe100$day)[i], select = pH)
#avgpH[i] = mean(phforthatday, na.rm=TRUE)
#stdpH[i] = sd(phforthatday, na.rm=TRUE)
#}
#points(unique(lowFe100$day), avgpH)
avgperday = aggregate(lowFe100, by=list(lowFe100$day), mean, na.rm=TRUE)
points(avgperday$day, avgperday$pH)
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