And you will probably want to read the details of the ?round help, so
you understand how it handles 5 rounding. It is a little more
complicated than some of us learned in school.
On 11/22/2022 4:24 AM, Steven T. Yen wrote:
Thanks to all. And yes, Ivan, round() did it:
> dput(head(Mean))
c(
Dear Rui,
Thanks a lot..
Thanking you,
Yours sincerely,
AKSHAY M KULKARNI
From: Rui Barradas
Sent: Sunday, December 11, 2022 11:27 PM
To: akshay kulkarni ; R help Mailing list
Subject: Re: [R] remembering the state of an action in R
�s 17:4
On Sun, Dec 11, 2022 at 11:05 PM Laurent Rhelp wrote:
>
> Excellent, it works.
>
> But, may you please explain me how xyplot knows that it has to apply
> panel.bwplot on every groups according to the groups factor ? Because
> there is only one panel. I introduced the groups argument in order to
>
Thank you very much Deepayan, I will see the help of panel.bwplot.
Best regards
L.
Le 11/12/2022 à 18:53, Deepayan Sarkar a écrit :
On Sun, Dec 11, 2022 at 11:05 PM Laurent Rhelp wrote:
Excellent, it works.
But, may you please explain me how xyplot knows that it has to apply
panel.bwplot on
Às 17:46 de 11/12/2022, akshay kulkarni escreveu:
Dear Rui,
Thanks for your replyyour reply covers the first part of
my question. What about the second part? i.e remembering the state when the
price q breaches Q? Will some thing like this work:
f <- function(envir) {expr1
Dear Rui,
Thanks for your replyyour reply covers the first part of
my question. What about the second part? i.e remembering the state when the
price q breaches Q? Will some thing like this work:
f <- function(envir) {expr1; expr2; expr3; envir$j <- envir$j + 1L}
e <- new.en
Às 17:28 de 11/12/2022, Rui Barradas escreveu:
Às 17:11 de 11/12/2022, akshay kulkarni escreveu:
Dear members,
I am a stock trader and using R for my
research. I am monitoring stock prices in real time. I have the
following code:
if (sock price q, breaches a cer
Excellent, it works.
But, may you please explain me how xyplot knows that it has to apply
panel.bwplot on every groups according to the groups factor ? Because
there is only one panel. I introduced the groups argument in order to
apply the bwplot function only on the values of every group.
Às 17:11 de 11/12/2022, akshay kulkarni escreveu:
Dear members,
I am a stock trader and using R for my research. I
am monitoring stock prices in real time. I have the following code:
if (sock price q, breaches a certain value Q) { expr1; expr2; expr3}
THe point i
Dear members,
I am a stock trader and using R for my research. I
am monitoring stock prices in real time. I have the following code:
> if (sock price q, breaches a certain value Q) { expr1; expr2; expr3}
THe point is, expr1,expr2,expr3 should execute only once, i.e wh
On Sun, Dec 11, 2022 at 2:33 PM Laurent Rhelp wrote:
>
> I understand the idea but I did not succeed.
>
> Here is what I tried:
>
> ## 1.middles of classes calculation
>
> m <- tapply(DF$x, groups, mean)
>
> ## 2. create a new factor columns with the levels deduced from
> ## the va
Indeed, I have to clarify my problem.
I have to display my physical measurements in a log-log representation.
I can do that with xyplot from the lattice package. But I would like to
show the dispersion of my measurement. So I wanted to use the bwplot
function but it is not possible because the
There can be **no log scale** for the x axis, only labels, if x is a factor
(Groups).
If what you mean is that there are no tick marks o the x-axis, they can be
added in my code in the scales list (for my reprex with 5 levels of group):
scales = list(
alternating = 1 ## ticls only on b
Ok for the labels but the x-axis is not displayed in log scale ?
Le 10/12/2022 à 22:36, Bert Gunter a écrit :
> ... and here's a version where the x variable is different than y.
> It's basically the same.
>
>
> set.seed(123)
> y <- runif(40,min=0, max= 10)
> x <- seq(0,10, length = 40)
> ## 5
I understand the idea but I did not succeed.
Here is what I tried:
## 1. middles of classes calculation
m <- tapply(DF$x, groups, mean)
## 2. create a new factor columns with the levels deduced from
## the values of the middles of the classes
##
DF$m <- DF$groups
levels(DF$m) <
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