[R] barplot2 x-axis
marc_schwartz at comcast.net
Sun Mar 22 22:23:55 CET 2009
On Mar 22, 2009, at 2:31 PM, Mafalda Viana wrote:
> Dear R users,
> I am trying to build a barplot2 graph however I can't find a way of
> the scale for the x-axis.
> I would like to show in my x-axis only the numbers 0, 25, 50, 75
> etc. (so
> far R is giving me a random scale hard to interpret and it doens't
> nice...). Could anyone advise me on how to do this please, it would
> be a
> great help! Thank you.
> Below I show the code I have been using for my plots.
> my.plot<- barplot2(mydata.y, names.arg=mydata.x, width=1,
> xlab="km", ylab="kg", main="plot.name",
> plot.ci=TRUE, ci.l=data.lci,ci.u=data.uci, ci.col = "red", font=40,
> font.lab=60, xlim=c(0,250), xpd=FALSE)
It is not entirely clear what you are doing here an we cannot
reproduce it lacking your data.
Your x (horizontal) axis will have one tick mark below each bar, using
the labels that you have indicated with mydata.x. Based upon your
code, the x axis values would appear to be measures of distance.
Your y (vertical) axis would appear to be a measure of weight, perhaps
being some descriptive statistic (eg. mean) for weight at each distance.
It is unclear what you want to do with the x axis in lieu of the
default values. Modifying the tick marks on the y axis would seem to
make more sense here.
In general, with any R graphic, you would use the arguments 'xaxt =
"n"' and/or 'yaxt = "n"' to disable the default drawing of the x and y
axes, respectively. You would then call the axis() function passing
the specific locations and values of the tick marks that you wish to
draw. See ?par and ?axis for more information on these.
BTW if you are not plotting counts or proportions/percentages, then a
barplot is not the best approach for the display of summarized
continuous data. I would use a point plot with error bars/confidence
intervals. See the errbar() function in the Hmisc package or the
plotCI() or plotmeans() functions in gplots. You could also create
something manually by using plot() and then either segments() or
arrows() for the CIs.
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