Displaying 20 results from an estimated 300 matches similar to: "Plotting w/multiple y-axes?"
2004 Feb 24
5
r: plots
hi all
i have another probably simple question.
I have three variables say x, y and z. x and y are quite large and z is
relative small.
how can one plot the three variables on the same graph with two separate
axis?
(one for x and y and the other for z)
e.g.
x<-c(101,110,150,167,120)
y<-c(120,135,175,95,200)
z<-c(0.001, 0.15, 0.6, 0.8, 1)
regards
Allan
2017 Nov 23
2
adding percentage secondary y-axis
Dear useRs,
I have this dataset (D) with three columns.
> dput(D)
structure(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 2.990484802, 3.005018792, 3.019552781, 3.03408677,
3.048620759, 3.063154749, 3.077688738, 3.092222727, 3.106756717,
3.121290706, 3.135824695, 3.150358684, 3.164892674, 3.179426663,
3.193960652, 3.208494642, 3.223028631, 3.23756262,
2017 Nov 23
2
adding percentage secondary y-axis
Thank you very much peter.
It worked out nicely.
I have additional question. How can I get Y-axis on log-scale?
Thank you very much in Advance,
Eliza
UoS
PP
________________________________
From: PIKAL Petr <petr.pikal at precheza.cz>
Sent: 23 November 2017 16:22:39
To: Eliza Botto; r-help at r-project.org
Subject: RE: adding percentage secondary y-axis
Hi
It is usually not
2017 Nov 23
0
adding percentage secondary y-axis
Hi
It is usually not recommended but if you insist
maybe
library(plotrix)
?twoord.plot
twoord.plot(lx=D[,1],ly=D[,2], rx=D[,1], ry=D[,3])
or
plot.yy(x=D[,1],yright=D[,3], yleft=D[,2])
which allows only one x axis (see below).
Cheers
Petr
plot.yy <- function (x, yright, yleft, yleftlim = NULL, yrightlim = NULL,
xlab = NULL, yylab = list(NA, NA), pch = c(1, 2),
col = c(1,2), linky
2002 Jun 17
3
Second axis in a plot
Hi to all,
First of all, I prefer to tell that I am a R-newbie,
so I apologize if this is a silly question (I have
tried looking in the manuals, but without luck).
I have two variables, y and z, that I want to plot
against x in the same plot. I have done this before,
using points() after plot(). But now the problem is
that y and z are in different units of measurement,
and their ranges are very
2002 Jun 11
5
Different y-axes
Hi All,
I have checked everything I could find abot graphics, but still cannot
solve the problem.
Are there any ways to make a graph that plots two lines and two
different y-axes, each of them has a scale that is related to the
respective line. For example, y1 has a range 1:50 and y1 ranges 0:1. The
x-axe is the same for both.
Thank you in advance.
---
Gregor Gawron
2004 Mar 17
0
Plot 2 time series with different y axes (left and right)
Petr Pikal said:
> I am not really a R specialist but for this task I use function:
and he pasted his code into the email. I reindented the code, and
wrote a fragment to experiment with it. Here it is:
---------------------------------------------------------------------------
plot.yy <- function(x, yright, yleft,
yleftlim=NULL, yrightlim = NULL,
2009 Jul 21
1
bug in approx crashes R
Dear R-devel,
The following line crashes R
> approx(1, 1, 0, method='const', rule=2, f=0, yleft=NULL, ties='ordered')$y
Process R:2 exited abnormally with code 5 at Tue Jul 21 14:18:09 2009
> version
_
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 2
minor 9.1
year
2010 Aug 25
3
approxfun-problems (yleft and yright ignored)
Dear all,
I have run into a problem when running some code implemented in the
Bioconductor panp-package (applied to my own expression data), whereby gene
expression values of known true negative probesets (x) are interpolated onto
present/absent p-values (y) between 0 and 1 using the *approxfun -
function*{stats}; when I have used R version 2.8, everything had
worked fine,
however, after updating
2008 Jul 20
3
asp and ylim
#See David Williams' book "Weighing the odds", p286
y <- c(1.21, 0.51, 0.14, 1.62, -0.8,
0.72, -1.71, 0.84, 0.02, -0.12)
ybar <- mean(y)
ylength <- length(y)
ybarv <- rep(ybar, ylength)
x <- 1:ylength
plot(x,y,asp=1,xlab="position",ylab="ybar",type="n",ylim=c(-1,1))
segments(x[1], ybar, x[ylength], ybar)
segments(x,ybarv,x,y)
2004 Oct 17
3
ecdf with lots of ties is inefficient (PR#7292)
Full_Name: Martin Frith
Version: R-2.0.0
OS: linux-gnu
Submission from: (NULL) (134.160.83.73)
I have large vectors containing 100,000 to 20,000,000 numbers. However, they
only contain a few hundred *distinct* numbers (e.g. positive integers < 200).
When I do ecdf(v), it either runs out of memory, or it succeeds, but when I plot
the ecdf with postscript, the output is unnecessarily bloated
2007 Mar 15
1
How to use result of approxfun in a package?
I am working on a project where we start with start with 2 long,
equal-length vectors, massage them in various ways, and end up with a
function mapping one interval to another. I'll call that function
"f1." The last step in R is to generate f1 as the value of the
approxfun function. I would like to put f1 into a package, but
without having the package redo the creation of
2005 Nov 02
2
help with the coordinates of the ECDF object
Hi all R users
I would like to know how acess the coordinates
of the ECDF object.
I look for the example,
in this part:
######################
print(ls.Fn12 <- ls(env= environment(Fn12)))
######################
but I do not know to extract
the Y coordinate and put it in other variable.
My objective is to make a plot
and identify the points with labels.
############# Example by
2006 Jul 17
3
information about a function
Hi people,
I am new in this list and could not find a FAQ for it in particular,
furthermore I could not find my question answered in the official R
FAQ or docs.
I have simply something like this:
> f<-approxfun(data[,1],data[,2])
and f is:
> f
function (v)
.C("R_approx", as.double(x), as.double(y), as.integer(n), xout = as.double(v),
as.integer(length(v)),
2011 Feb 08
1
help on stepfunction
Dear members,
I would like a help for extracting the values from a step function
(stepfun).
>From help(stepfun) we have the following example:
Y0<-c(1.,2.,4.,3.)
y0<-c(1.,2.,3.,4.)
sfun<-stepfun(1:3,y0,f=0)
plot(sfun)
Now, suppose instead I was given the object (*sfun*, say) from which I
wanted to extract the values generated by the function *stepfun*. More
precisely, I want to
2007 May 30
1
Sort in ecdf
Hi!
I've noticed the ecdf() R code (R ver. 2.5.0) contains two call to sort:
--- [R-code] ---
ecdf <- function(x)
x <- sort(x)
n <- length(x)
if (n < 1)
stop("'x' must have 1 or more non-missing values")
vals <- sort(unique(x))
rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n,
method
2011 Jul 06
3
finding the intersection of two vectors
Hi,
Suppose I have two vectors, not necessarily the same length (in fact,
they usually are different lengths): y.1 that has increasing values
between 0 and 1; y.2 that has decreasing values between 1.0 and 0. You
can picture these as being supply (= y.1) and demand (= y.2) curves from
economics. I typically plot these vectors on the same graph against a
common x variable, which happens to
2013 Feb 14
1
approxfun values
Readers,
According to the help '?approxfun', the function can be used to obtain
the interpolated values. The following test was tried:
> testinterpolation<-read.csv('test.csv',header=FALSE)
> testinterpolation
V1 V2
1 10 2
2 20 NA
3 30 5
4 40 7
5 50 NA
6 60 NA
7 70 2
8 80 6
9 90 9
10 100 NA
>
How to count from larger value to smaller value in ecdf (Empirical Cumulative Distribution Function)
2008 Feb 19
1
How to count from larger value to smaller value in ecdf (Empirical Cumulative Distribution Function)
Hi, all
ecdf function (Empirical Cumulative Distribution Function) in "stats"
package counts from smaller values to larger values.
However, I want to draw it by counting from larger value to smaller values
and I couldn't find options for this purpose.
How can I draw ecdf or ecdf like graph by counting from larger values to
smaller values.
Thank you in advance.
Hyunchul Kim
2006 Jun 23
1
integrate
Dear All,
My doubt about how to integrate a simple kernel density estimation goes on.
I have seen the recent posts on integrate density estimation, which seem
similar to my question. However, I haven't found a solution.
I have made two simple kernel density estimation by:
kde.1 <-density(x, bw=sd(x), kernel="gaussian")$y # x<- c(2,3,5,12)
kde.2 <-density(y,