... and just for fun, here is a non-string version (more appropriate for
complex state labels??):
gvec <- function(ntimes, states, init, final, repeats = TRUE)
## ntimes: integer, number of unique times
## states: vector of unique states
## init: initial state
## final: final state
{
On Mon, 4 Sep 2023, Ivan Calandra wrote:
Thanks Rui for your help; that would be one possibility indeed.
But am I the only one who finds that behavior of aggregate() completely
unexpected and confusing? Especially considering that dplyr::summarise() and
doBy::summaryBy() deal with NAs
Well, if strings with repeats (as you defined them) are to be excluded, I
think it's simple just to use regular expressions to remove them.
e.g.
g <- function(ntimes, states, init, final, repeats = TRUE)
## ntimes: integer, number of unique times
## states: vector of unique states
##
Muchas gracias por la solución. Me ha funcionado. Tenía instalada una
versión un poco "vieja" de Rtools y eso puede haber influido.
Saludos,
José María
---
Dr. José María Santiago Sáez (PhD)
Madrid - España/Spain
+34 646 165 291
jms...@picos.com
Muchas gracias por la solución. Me ha funcionado. Tenía instalada una
versión un poco "vieja" de Rtools y eso puede haber influido.
Saludos,
José María
---
Dr. José María Santiago Sáez (PhD)
Madrid - España/Spain
+34 646 165 291
jms...@picos.com
My initial response was buggy and also used a deprecated function.
Also, it seems possible that one may want to rule out any strings where the
same state appears consecutively.
I say that such a string has a repeat.
myExpand <- function(v, n) {
do.call(tidyr::expand_grid, replicate(n, v,
Hola,Supongo que te estará preguntando si quieres instalar desde las fuentes porque hay una versión más nueva que la que hay en binario (supongo que usas Windows).Entonces, o respondes que NO a esa pregunta, o te instalas las Rtools .Espero que te sirva, un saludo,EmilioEl 4 sept 2023, a las
Sorry, my last line should have read:
If neither this nor any of the other suggestions is what is desired, I
think the OP will have to clarify his query.
Bert
On Mon, Sep 4, 2023 at 12:31 PM Bert Gunter wrote:
> I think there may be some uncertainty here about what the OP requested. My
>
I think there may be some uncertainty here about what the OP requested. My
interpretation is:
n different times
k different states
Any state can appear at any time in the vector of times and can be repeated
Initial and final states are given
So modifying Tim's expand.grid() solution a bit
Hola a todos:
He instalado las últimas versiones de R y R-studio y no consigo instalar
el paquete "dplyr". Al intentarlo me da el siguiente mensaje.
Por favor. si alguien tiene idea de cómo resolver este problema, por
favor, necesito ayuda.
Muchas gracias,
José M.
Hi,
I have
Does this work for you?
t0<-t1<-t2<-LETTERS[1:5]
al2<-expand.grid(t0, t1, t2)
al3<-paste(al2$Var1, al2$Var2, al2$Var3)
al4 <- gsub(" ", "", al3)
head(al3)
Tim
-Original Message-
From: R-help On Behalf Of Eric Berger
Sent: Monday, September 4, 2023 10:17 AM
To: Christofer Bogaso
Cc:
В Mon, 04 Sep 2023 12:05:38 +
Christophe Bousquet пишет:
> I will try compiling R from source when I am back from holidays, and
> ask you if I need assistance.
Make sure to compile with DEBUG=1 so that the compiler flags needed to
emit debugging information will be enabled. Good luck!
--
This is a great find for those of us lurking on this thread. Thanks for
sharing Greg (and of course Paul).
On 8/30/2023 3:52 PM, Greg Snow wrote:
Stephen, I see lots of answers with packages and resources, but not
book recommendations. I have used Introduction to Data Technologies
by Paul
Ivan:
Just one perhaps extraneous comment.
You said that you were surprised that aggregate() and group_by() did not
have the same behavior. That is a misconception on your part. As you know,
the tidyverse recapitulates the functionality of many base R functions; but
it makes no claims to do so in
The function purrr::cross() can help you with this. For example:
f <- function(states, nsteps, first, last) {
paste(first, unlist(lapply(purrr::cross(rep(list(v),nsteps-2)),
\(x) paste(unlist(x), collapse=""))), last, sep="")
}
f(LETTERS[1:5], 3, "B", "E")
[1] "BAE" "BBE" "BCE" "BDE" "BEE"
Thank you very much for all the responses; especially Duncan's guidance.
I will add some further ideas on workflows below.
There were quite a few views on GitHub; but there is not much to see, as
there is absolutely no documentation. I have added in the meantime a
basic example:
> siddharth sahasrabudhe via R-help
> on Sun, 3 Sep 2023 09:54:28 +0530 writes:
> I want to access the .csv file from my github
> repository. While connecting to the Github repository I am
> getting the following error:
> Error in curl::curl_fetch_memory(file) :
Let say I have 3 time points.as T0, T1, and T2.(number of such time
points can be arbitrary) In each time point, an object can be any of 5
states, A, B, C, D, E (number of such states can be arbitrary)
I need to find all possible ways, how that object starting with state
B (say) at time T0, can
Haha, got it now, there is an na.action argument (which defaults to
na.omit) to aggregate() which is applied before calling mean(na.rm =
TRUE). Thank you Rui for pointing this out.
So running it with na.pass instead of na.omit gives the same results as
dplyr::group_by()+summarise():
> If you're up to compiling R from source [] and using a symbolic
> debugger [**] to step through Rcmd.exe, we could try to do that.
> Murphy's law says that the copy of Rcmd.exe you'll build from source
> will work well and refuse to reproduce the problem for you to
> investigate. (Beyond that,
Às 12:51 de 04/09/2023, Ivan Calandra escreveu:
Thanks Rui for your help; that would be one possibility indeed.
But am I the only one who finds that behavior of aggregate() completely
unexpected and confusing? Especially considering that dplyr::summarise()
and doBy::summaryBy() deal with NAs
Thanks Rui for your help; that would be one possibility indeed.
But am I the only one who finds that behavior of aggregate() completely
unexpected and confusing? Especially considering that dplyr::summarise()
and doBy::summaryBy() deal with NAs differently, even though they all
use mean(na.rm
Às 10:44 de 04/09/2023, Ivan Calandra escreveu:
Dear useRs,
I have just stumbled across a behavior in aggregate() that I cannot
explain. Any help would be appreciated!
Sample data:
my_data <- structure(list(ID = c("FLINT-1", "FLINT-10", "FLINT-100",
"FLINT-101", "FLINT-102", "HORN-10",
> Duncan Murdoch
> on Mon, 4 Sep 2023 04:51:32 -0400 writes:
> On 03/09/2023 10:47 p.m., Jeff Newmiller wrote:
>> Leonard... the reason roxygen exists is to allow markup
>> in source files to be used to automatically generate the
>> numerous files required by standard
> Jeff Newmiller
> on Sun, 03 Sep 2023 19:47:32 -0700 writes:
> Leonard... the reason roxygen exists is to allow markup in
> source files to be used to automatically generate the
> numerous files required by standard R packages as
> documented in Writing R Extensions.
I want to access the .csv file from my github repository. While connecting
to the Github repository I am getting the following error:
Error in curl::curl_fetch_memory(file) :
Timeout was reached: [raw.githubusercontent.com] Failed to connect to
raw.githubusercontent.com port 443 after 5250 ms:
Thanks Iago for the pointer.
It then means that na.rm = TRUE is not applied in the same way within
aggregate() as opposed to dplyr::group_by() + summarise(), right? Within
aggregate, it behaves like na.omit(), that is, it excludes the
incomplete cases (whole rows), whereas with group_by() +
It seems that the issue are the missings. If in #1 you use the dataset
na.omit(my_data) instead of my_data, you get the same output that in #2 and in
#4, where all observations with missing data are removed since you are
including all the variables.
The second dataset has no issue since it
Dear useRs,
I have just stumbled across a behavior in aggregate() that I cannot
explain. Any help would be appreciated!
Sample data:
my_data <- structure(list(ID = c("FLINT-1", "FLINT-10", "FLINT-100",
"FLINT-101", "FLINT-102", "HORN-10", "HORN-100", "HORN-102", "HORN-103",
"HORN-104"),
On 03/09/2023 10:47 p.m., Jeff Newmiller wrote:
Leonard... the reason roxygen exists is to allow markup in source files to be
used to automatically generate the numerous files required by standard R
packages as documented in Writing R Extensions.
If your goal is to not use source files this
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