i realy appreciate your concern..
here is a small piece of my data. if you see the first and last part data, they
contain 366 entries but the middle one has 365 entries. i want to put first and
last entries is one matrix.
list(c(0.86, 0.86, 0.86, 0.86, 0.86, 1.08, 1.08, 1.08, 1.08,
1.08, 1.08, 1.4, 1.4, 23, 11.18, 38.83, 23, 3.45, 3.45, 3.45,
3.45, 3.45, 3.45, 3.45, 3.45, 3.02, 2.58, 2.58, 2.15, 2.15, 2.15,
2.15, 2.15, 2.15, 2.15, 2.15, 3.02, 1.72, 1.72, 1.72, 1.72, 1.72,
1.72, 1.72, 1.72, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6,
1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6,
1.6, 1.6, 1.6, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.8, 2.8, 2.8,
4.1, 4.1, 13.55, 9.34, 8.32, 7.31, 4.5, 4.1, 14.63, 24.88, 39.99,
23.69, 14.63, 7.31, 4.5, 7.31, 16.82, 21.35, 24.88, 20.2, 24.88,
26.07, 30.98, 49.58, 51.01, 26.07, 24.88, 30.98, 34.77, 58.26,
30.98, 23.69, 26.07, 19.06, 16.82, 20.2, 16.82, 23.69, 14.63,
16.82, 11.42, 11.42, 11.42, 11.42, 10.38, 10.38, 8.32, 7.31,
6.31, 16.82, 6.31, 6.31, 6.31, 4.9, 4.9, 4.5, 4.5, 4.5, 4.5,
4.5, 4.1, 4.1, 2.8, 2.4, 2.4, 26.07, 45.4, 16.82, 7.31, 4.5,
3.2, 3.2, 2.8, 2.8, 2.4, 2.4, 2.8, 3.2, 3.2, 4.9, 4.9, 36.05,
65.8, 76.86, 53.87, 26.07, 20.2, 21.36, 14.63, 10.38, 10.38,
7.31, 7.31, 51.01, 16.82, 14.63, 12.48, 14.63, 10.38, 11.42,
52.44, 64.27, 36.05, 26.07, 21.36, 21.36, 23.69, 47.79, 52.44,
167.9, 97.12, 76.86, 144.71, 90.18, 34.77, 30.98, 28.5, 26.07,
26.07, 14.63, 14.63, 6.31, 6.31, 6.31, 4.5, 4.1, 3.2, 6.31, 6.31,
16.82, 4.5, 3.2, 3.2, 3.2, 3.2, 4.5, 8.32, 10.38, 10.38, 8.32,
11.42, 10.38, 7.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31,
8.32, 6.31, 6.31, 20.2, 14.63, 7.31, 4.9, 34.77, 26.07, 14.63,
10.38, 6.31, 4.9, 7.31, 4.9, 4.5, 4.5, 4.5, 21.36, 12.48, 7.31,
4.5, 4.5, 6.31, 4.9, 4.9, 6.31, 8.32, 7.31, 6.31, 6.31, 14.63,
11.42, 6.31, 6.31, 4.9, 6.31, 14.63, 7.31, 12.48, 6.31, 6.31,
24.88, 15.72, 33.49, 111.57, 44.03, 39.99, 44.03, 24.88, 12.48,
39.99, 11.42, 7.31, 4.9, 4.5, 4.1, 4.5, 4.1, 4.1, 3.2, 3.2, 3.2,
3.2, 3.2, 2.8, 2.8, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8,
3.2, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8,
4.1, 4.1, 2.4, 3.2, 10.38, 8.32, 4.5, 3.2, 3.2, 2.8, 3.2, 3.2,
3.2, 2.4, 2.4, 2.4, 15.72, 23.69, 12.48, 14.63, 4.5, 4.1, 4.5,
4.1, 4.1, 4.1, 3.2, 2.8, 2.8, 3.2, 2.8, 2.4, 4.5, 4.5, 12.48,
68.9, 30.98, 39.99, 29.73, 95.37, 44.03, 26.07, 41.33, 49.58,
23.69, 28.5), c(16.82, 14.63, 6.31, 6.31, 4.5, 4.5, 4.1, 4.1,
4.1, 3.2, 3.2, 4.1, 3.2, 3.2, 4.1, 4.5, 4.1, 4.1, 167.9, 75.24,
44.03, 23.69, 19.06, 15.72, 11.42, 8.32, 6.31, 4.9, 6.31, 4.9,
4.9, 4.1, 4.1, 3.2, 4.1, 4.1, 4.1, 90.18, 102.45, 39.99, 29.73,
8.32, 21.36, 21.36, 21.36, 12.48, 11.42, 12.48, 11.42, 12.48,
14.63, 14.63, 15.72, 23.69, 28.5, 29.73, 33.49, 29.73, 23.69,
21.36, 6.31, 16.82, 15.72, 15.72, 15.72, 15.72, 16.82, 20.2,
20.2, 21.36, 21.36, 26.07, 28.5, 29.73, 33.49, 29.73, 33.49,
34.77, 26.07, 26.07, 23.69, 23.69, 26.07, 21.36, 23.69, 23.69,
23.69, 24.88, 21.36, 20.2, 16.82, 19.06, 20.2, 21.36, 20.2, 20.2,
24.88, 23.69, 26.07, 29.73, 23.69, 24.88, 29.73, 36.05, 33.49,
34.77, 28.5, 28.5, 26.07, 153, 70.47, 58.26, 81.77, 36.05, 39.99,
30.98, 33.49, 28.5, 28.5, 33.49, 29.73, 28.5, 24.88, 30.98, 38.67,
30.98, 50.01, 65.8, 51.01, 38.67, 34.77, 29.73, 29.73, 33.49,
30.98, 30.98, 30.98, 33.49, 34.77, 33.49, 30.98, 88.48, 14.63,
8.32, 19.06, 14.63, 104.25, 44.03, 33.49, 21.36, 20.2, 15.72,
15.72, 11.42, 7.31, 6.31, 4.9, 4.5, 4.5, 4.5, 3.2, 8.32, 8.32,
14.63, 97.12, 310.8, 88.48, 36.05, 24.88, 19.06, 14.63, 12.48,
8.32, 23.69, 11.42, 19.06, 90.18, 90.18, 33.49, 16.82, 70.47,
38.67, 29.73, 34.77, 33.49, 68.9, 102.45, 176.7, 78.48, 45.4,
106.06, 83.43, 45.4, 68.9, 39.99, 28.5, 23.69, 20.2, 36.05, 38.67,
30.98, 26.07, 20.2, 47.79, 52.44, 28.5, 23.69, 20.2, 14.63, 14.63,
14.63, 12.48, 21.36, 24.88, 47.79, 38.67, 34.77, 21.36, 16.82,
8.32, 153, 47.79, 53.87, 29.73, 23.69, 15.72, 19.06, 97.12, 33.49,
15.72, 10.38, 6.31, 4.5, 11.42, 6.31, 6.31, 6.31, 4.5, 19.06,
14.63, 4.9, 4.9, 28.5, 70.47, 15.72, 4.9, 4.1, 41.33, 241, 85.1,
38.67, 28.5, 20.2, 15.72, 12.48, 12.48, 20.2, 14.63, 12.48, 10.38,
7.31, 7.31, 15.72, 33.49, 20.2, 15.72, 12.48, 8.32, 7.31, 6.31,
4.9, 4.5, 4.1, 4.9, 4.5, 4.9, 20.2, 11.42, 6.31, 4.9, 4.9, 4.9,
4.5, 4.5, 4.5, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 6.31,
6.31, 4.5, 4.9, 4.9, 4.5, 4.5, 4.5, 4.9, 4.5, 15.72, 24.88, 4.1,
58.26, 23.69, 26.07, 28.5, 174.5, 58.26, 49.58, 23.69, 23.69,
23.69, 28.5, 26.07, 15.72, 20.2, 26.07, 23.69, 19.06, 21.36,
15.72, 4.1, 4.1, 6.31, 15.72, 24.88, 39.99, 45.4, 23.69, 33.49,
33.49, 33.49, 23.69, 23.69, 20.2, 24.88, 19.06, 23.69, 20.2,
8.32, 6.31, 6.31, 4.1, 4.1, 14.63, 106.06, 51.01, 26.07, 23.69,
20.2, 15.72, 15.72, 12.48, 19.06, 16.82, 14.63, 12.48, 12.48,
11.42, 11.42, 12.2), c(8.32, 8.32, 8.32, 8.32, 8.32, 8.32, 8.32, 8.32,
8.32, 8.32, 8.32, 8.32, 8.32, 7.31, 8.32, 8.32, 8.32, 8.32, 6.31,
6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31,
6.31, 6.31, 6.31, 4.5, 4.5, 4.5, 4.5, 4.5, 6.31, 6.31, 4.1, 4.1,
4.1, 4.5, 6.31, 6.31, 6.31, 6.31, 4.9, 10.38, 12.48, 15.72, 8.32,
11.42, 78.48, 65.8, 85.1, 29.73, 26.07, 29.73, 21.36, 26.07,
23.69, 28.5, 15.72, 12.48, 12.48, 14.63, 12.48, 12.48, 8.32,
8.32, 11.42, 6.31, 6.31, 6.31, 4.9, 4.9, 6.31, 10.38, 15.72,
16.82, 19.06, 34.77, 20.2, 20.2, 15.72, 14.63, 33.49, 28.5, 28.5,
28.5, 64.27, 29.73, 20.2, 15.72, 11.42, 11.42, 11.42, 7.31, 4.9,
6.31, 12.48, 10.38, 8.32, 7.31, 14.63, 15.72, 16.82, 20.2, 19.06,
19.06, 28.5, 19.06, 15.72, 28.5, 29.73, 38.67, 20.2, 30.98, 21.36,
14.63, 12.48, 10.38, 47.79, 23.69, 14.63, 10.38, 8.32, 11.42,
11.42, 15.72, 12.48, 11.42, 14.63, 26.07, 23.69, 36.05, 167.9,
44.03, 21.36, 15.72, 12.48, 8.32, 8.32, 8.32, 21.36, 20.2, 15.72,
30.98, 21.36, 15.72, 53.87, 29.73, 21.36, 12.48, 11.42, 10.38,
10.38, 6.31, 39.99, 19.06, 4.1, 2.8, 44.03, 24.88, 11.42, 8.32,
6.31, 78.48, 38.67, 34.77, 19.06, 12.48, 15.72, 15.72, 59.74,
34.77, 21.36, 14.63, 12.48, 11.42, 11.42, 11.42, 10.38, 8.32,
6.31, 6.31, 4.9, 4.9, 4.9, 4.9, 4.1, 4.5, 6.31, 4.1, 4.5, 4.5,
8.32, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 4.9, 4.5,
4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.1, 2.8, 2.8, 2.8,
2.8, 2.8, 2.8, 2.4, 2.8, 2.8, 2.8, 2.8, 2.4, 2.8, 2.4, 1.3, 1.3,
1.3, 1.3, 29.73, 21.36, 4.1, 3.2, 2.8, 6.31, 3.2, 3.2, 3.2, 3.2,
3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 7.31,
8.32, 8.32, 4.1, 3.2, 4.9, 4.1, 23.69, 23.69, 19.06, 11.42, 14.63,
7.31, 4.9, 14.63, 36.05, 28.5, 15.72, 10.38, 12.48, 14.63, 20.2,
14.63, 15.72, 23.69, 10.38, 4.9, 4.1, 3.2, 3.2, 3.2, 3.2, 3.2,
3.2, 3.2, 3.2, 3.2, 3.2, 4.9, 2.8, 2.8, 1.6, 14.63, 7.31, 11.42,
7.31, 3.2, 3.2, 3.2, 3.2, 3.2, 23.69, 4.5, 3.2, 3.2, 3.2, 4.5,
3.2, 3.2, 3.2, 3.2, 3.2, 1.3, 2.8, 4.5, 4.5, 3.2, 3.2, 4.5, 4.5,
11.42, 4.5, 4.5, 4.5, 1.3, 1.3, 1.3, 3.2, 1.6, 2.8, 2.8, 1.3,
2.8, 2.8, 2.8, 2.8, 4.1, 4.1, 4.1, 4.1, 4.1, 7.31, 4.1, 2.8,
2.8, 3.2, 4.1, 4.9, 26.07, 24.88, 15.72, 20.2, 21.36, 30.98,
21.36, 20.2, 19.06, 14.3)
thankyou very much..
bye
Date: Mon, 4 Jun 2012 22:27:55 +0100
From: ruipbarra...@sapo.pt
To: eliza_bo...@hotmail.com
CC: r-help@r-project.org
Subject: Re: Spliting Lists into matrices
Hello,
I'm glad it helped.
To answer to this new question, we need to see what your data looks like.
When you say 'list' are you refering to the type of R data structure
'list'? Or to data.frames?
For us to see the best way is to use function dput. Example:
df1<- data.frame(A=rnorm(10), B=runif(10))
df2<- data.frame(A=rnorm(11), B=runif(11))
lst1<- list(df1, df2) # a list of data.frames
dput(lst1) #<----- paste the output of this in a post
(If your data.frames are not in a list do NOT create a list just to
post, dput them _as_they_are_.)
Can be dput(df1); dput(df2)
If they are in a list, don't dput the entire list, 50x365 or 366 is
endless, just enough for us to see.
If you have several (50) data.frames, do they share something such as a
name prefix?
Any information you find relevant, post it.
Rui Barradas
Em 04-06-2012 21:41, eliza botto escreveu:
Dear Rui Barradas, Mackay and all R Users,
Thankyou
very much for your reply. You helped me a lot. I got what I wanted. I just want
one more favor from you, if you could.
Suppose
I have certain number of lists of data frame, say 50. Each list has yearly data
in it. Of-course, some lists have 365 readings and some have 366(due to leap
year). Now I want to split lists into two different matrices, one containing
leap years and other with normal years.
I
hope you will be kind enough to help me as you did before.
Eliza
Botto
Waters
Inn
Date: Mon, 4 Jun 2012 10:51:49 +0100
From: ruipbarra...@sapo.pt
To: eliza_bo...@hotmail.com
CC: r-help@r-project.org
Subject: Re: [R] Variate
Hello,
Sorry for not understanding your problem, but it really seemed like
homework.
Now, when I answered scale(x) I meant it, it transforms a matrix in (x -
mean)/sd, column by column.
If you're new to R, to use the on-line help the instruction is
help("scale")
?scale # shortcut
As for your graph, I agree with Duncan, 92 lines on the same graph
doesn't seem to be a good idea. Anyway, using base R, it could be done
along the lines of
set.seed(1)
nc<- 92 # number of columns
nr<- 366 # number of rows
x<- matrix(rexp(nr*nc), ncol=nc)
x1<- scale(x) # "z", standard normal (in fact, studentized)
y1<- apply(x, 2, plnorm) # log-normal
colrs<- rainbow(nc)
plot(1, type="n", xlim=c(min(x1), max(x1)), ylim=c(min(y1), max(y1)),
xlab="", ylab="")
# if you want lines
sapply(seq_len(nc), function(j){
i<- order(x1[, j])
lines(x1[i, j], y1[i, j], col=colrs[j])})
# if you want points
sapply(seq_len(nc), function(j) points(x1[, j], y1[, j], col=colrs[j],
pch="."))
Hope this helps,
Rui Barradas
Em 04-06-2012 07:38, eliza botto escreveu:
Dear Mc kay,
thankyou very much for your reply. we are extremly greatful to you. we actually
wanted all on one scale. we want to compare them all on one axis. kindle see if
you could help us on that. one more thing, does this practice give us normal
reduced variant on x-axis because we stricktly want normal reduced variant on
x-axis.
i hope you will cooperate.
eliza botto
waters inn
Date: Mon, 4 Jun 2012 11:54:11 +1000
To: r-help@r-project.org
From: mac...@northnet.com.au
Subject: Re: [R] Variate
Hi Eliza
You will not want 1 panel with 96 lines - too confusing after about 20
Instead 1 per panel or with groups using useOuterStrips and
combineLimits from latticeExtra package
Try this -- a minimal example with an 12 row 8 col grid done on the fly
setseed(12)
Sites<- 1:92
dat<-
data.frame(y = rep(rnorm(5),92), x = rep(1:5,92), site = rep(Sites,each = 5))
xyplot(y ~ x|site,dat,
as.table=T,
strip = F,
layout = c(8,12),
scales = list(x = list(alternating = 2),y=list(alternating=1)),
type = "b",
panel = function(x,y,...){
pnl=panel.number()
panel.xyplot(x,y,...)
panel.text(4,-1.5,Sites[pnl], cex = 0.6)
}
)
or with groupings for Site something like (untested)
xyplot(y ~ x|groupings,dat,
as.table=T,
strip = F,
strip.left = T,
groups = site,
scales = list(x = list(alternating = 2),y=list(alternating=1)),
type = "b",
panel = function(x,y,...){
pnl=panel.number()
panel.xyplot(x,y,...)
panel.text(4,-1.5,Sites[pnl], cex = 0.6)
}
)
You will need an extra column for groupings
This can also be done with the base plot function but lattice gives
more flexibility, see ?xyplot and particularly par.settings into
get things right size
Regards
Duncan
Duncan Mackay
Department of Agronomy and Soil Science
University of New England
Armidale NSW 2351
Email: home: mac...@northnet.com.au
At 11:01 4/06/2012, you wrote:
Content-Type: text/plain
Content-Disposition: inline
Content-length: 2431
Dear
R users,
We
are working on a project called,"Environmental Impact Assessment".
We are stationed
at alpine regions of Ireland to see the impact of rainfall on
localities. We have
divided our study area into 92 stations. We have also collected 1 year data
>from each station. Afterwards we placed data into a matrix in such a way that
we got 366*92 matrix. 366 stands for number of days.
What
we want is a lognormal probability plot, of each station(which is individual
column of matrix) with normal reduced variant on x-axis. In this
way, we should
be getting, at the end, 92 curves, one for each station, on same coordinate
axis.
Kindly
help us on that. We are all very new to R.
Eliza
botto
Waters
Inn
CC: r-help@r-project.org
From: dwinsem...@comcast.net
To: eliza_bo...@hotmail.com
Subject: Re: [R] Log-normal probability plot
Date: Sun, 3 Jun 2012 13:11:35 -0400
On Jun 2, 2012, at 9:38 PM, eliza botto wrote:
You might consider the strategy of reading the Posting Guide, followed
by posting an intelligible message.
Dear R users,
You can literally safe my
life my telling me the solution of my problem. I have created matrix
of a data
frame with 3 columns, with each column representing data of
different year.
2
...snipped useless srting of numbers mangled by mailer processing of
HTML.
4
I now want to plot "Lognormal
probability plot" of each column data against its respective "normal
reduced
variante(z)".
"Normal reduced variate"? What is that? Is it a set of numbers that
have been centered and scaled, also known as a z-transform? If so, I
do not think it should affect the results of a probability plot since
it is just a linear transformation and the theoretical quantiles will
be unaffected.
You might look at qqplot()
How to do that?
If you don't know the
answer, consider me dead.
What greater lifesaving project are you trying to accomplish, ....
other than getting homework done?
[[alternative HTML version deleted]]
--
David Winsemius, MD
West Hartford, CT
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
