[R] Formatting Y axis.

sock.o mrsockman at gmail.com
Fri Feb 10 17:43:39 CET 2012

I've looked around and I just can't find anything that will work for my
needs. This is a bit of a 2 part question but pertaining to the same topic
so bare with me. 

The first is with my qq plot. On the Y axis of my qq plot it'll have my
sample quantities but because my data is log-normal it'll show numbers
between 0 - 5 (depending on the data). I'd like to know how to get it,
instead of displaying 0-5 to display actual values so that way when reading
it I know where my potential problems are. Would just save a lot of time and
be an easier more understandable read. Here's sample code to plug in and

x <- rlnorm(400, 2.3, .8)
y <- rlnorm(400, 3, 1.6)

	q1 <- qqnorm(log1p(y))
	q2 <- qqnorm(log1p(x))
		points( q1, col = "red")
		points( q2, col = "blue")
		abline( qqline(log1p(y), col = "red") )
		abline( qqline(log1p(x), col = "blue") )
		legend( "bottomright", inset = 0.02, title = "Loc_ID", c("Sayincom",
"Sayout"), fill = c( "red", "blue"), horiz = TRUE)

So what I want is for the y axis. or even secondary y axis if it's lined up
properly to read the actual values rather than the logged values. 

The second part of this is in regards to my boxplots. In order to fit all of
the data in a readable manner I've been making log = "y". Which is fine, but
when trying to estimate the difference via notches it's difficult to
estimate how far it really is based on the axis being logged. You can use
the same x as above, or y, whichever floats your boat. 

boxplot ( x,  notch = TRUE, log = "y", boxwex = .50)


boxplot ( x,  notch = TRUE, boxwex = .50)

What I need from this is for the ability to zoom in on a particular
location. Rather than be forced to look at things in a log format on my y
axis to just be able to say, ok I have my mean at 25 and my standard
deviation is 10 so I want to concentrate this boxplot between 5 and 45 to
view 2 standard deviations. (That whole mean thing and standard deviations
are arbitrary numbers but the concept remains)

Any help would be much appreciated. If there are particular packages
required for any suggestions please include their name in your response. 

If you need actual imaging of what the actual graphs I'm working with look
like as opposed to the randomly generated values that I'm supplying then
just say so and I'll post the actual graphs I'm trying to work with. 



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