Hi Eric,
Thanks, it works. If I want to convert the matrix to the 1-D vector for the
levelplot, should I use the command below? I thought the t() is a reverse
function, but may be not.
values <- layer$z
values.v <- as.vector(t(values))
On Tue, Jan 16, 2018 at 12:36 AM, Eric Berger
To expand on what Bert suggests. Use:
loadToEnv <- function(file, ..., envir = new.env()) {
base::load(file = file, envir = envir, ...)
}
envA <- loadToEnv("a.RData")
envB <- loadToEnv("b.RData")
and then access the objects in environments envA and envB using
environment access methods, e.g.
Thanks everyone.
Got it to work like this, if anyone is interested:
import the data with readr, taking in only the columns that have numeric
values ("n" and "y") and the column with the groups ("city").
aggregate the data by the group ("city") so that each variable has a sum:
|sum_data
Of course... R _is_ open source. However, it is unwise to assume that the
volunteers scratching itches for their preferred distros will take on
additional work... it is more likely that you will need to take on scratching
that new itch.
--
Sent from my phone. Please excuse my brevity.
On
Is there any chance for a distribution independent flatpak installation package
for R ?
See: http://flatpak.org
Background: I recently bought an Acer notebook with endless OS preinstalled
(see: http://endlessos.com). It is Debian based, but uses only flatpak as
installation
package format.
?load
Read this carefully. Pay attention to its instructions re: overwriting
existing objects.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On
This depends on the resources of your computer. If it's very small,
some dependencies can take a long time.
My record is the glmmTMB dependency with over 24 hours compilation (on
an old netbook).
One helpful way round can be to download the .tar.gz of the package,
close down all other programs,
On 16/01/2018 7:13 AM, Steven Yen wrote:
Understood. In my case, a.RData and b.RData contain identical
variables/data, plus simulation outputs from separate runs. The codes
deliver what I need. Good to know the three lines work. Thank you.
You might also want to investigate saveRDS/readRDS.
Hello everybody,
I use the sweetpotato database included in R package:
data(sweetpotato) This dataset contains two variables: yield(continous
variable) and virus(factor variable).
Due to Levene test is significant I cannot assume homogeneity of variances
and I apply Welch test in R instead of
You need to make sure that the rJava package is working.
Consider using the readxl package instead of xlsx.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Understood. In my case, a.RData and b.RData contain identical
variables/data, plus simulation outputs from separate runs. The codes
deliver what I need. Good to know the three lines work. Thank you.
On 1/16/2018 8:06 PM, Duncan Murdoch wrote:
> On 16/01/2018 6:33 AM, Steven Yen wrote:
>> Hi
Dear All,
I have been trying to install Xlsx package in R but i have been getting
this error after the installation. Please can anyone help?
> any(grepl("xlsx",installed.packages()))
[1] TRUE
> library("xlsx")
Loading required package: rJava
Error: package or namespace load failed for ‘rJava’:
On 16/01/2018 6:33 AM, Steven Yen wrote:
Hi all,
This is great. Again, here is what I need. I run two separate jobs (a.R
and b.R) with results (say regression outputs) going to a.RData and
b.RData. I like to put all results in one place (where I can retrieve
them in one place, ab.RData). The
Hi all,
This is great. Again, here is what I need. I run two separate jobs (a.R
and b.R) with results (say regression outputs) going to a.RData and
b.RData. I like to put all results in one place (where I can retrieve
them in one place, ab.RData). The following codes do it (I am not sure
if
Huh.
I may by completely wrong but you cannot do such "merging". .RData files are
AFAIK places where all objects from given session are stored.
However you could load each .RData file and save/export result (one object).
BTW, what do you mean exactly by "combine/consolidate"?
And finally,
On 16/01/2018 3:43 AM, Steven Yen wrote:
I ran two separate hours-long projects. Results of each were saved to
two separate .RData files.
Content of each includes, among others, the following:
me se t p sig
pc21.age 0.640 0.219 2.918 0.004 ***
pc21.agesq
Hi all,
Thanks for your help and sorry for the confusion. Also Thanks Jeff,
your solution worked well, I was trying to perform matrix
(element-wise) addition as you mentioned, but I didn't know how to
formulate my question. Thanks for the references, they also help me to
understand more.
Cheers,
I ran two separate hours-long projects. Results of each were saved to
two separate .RData files.
Content of each includes, among others, the following:
me se t p sig
pc21.age 0.640 0.219 2.918 0.004 ***
pc21.agesq 0.000 0.000 NaN NaN
pc21.inc
Dear R users,
I'm happy to announce the release of version 0.3 of the udpipe R package on
CRAN (https://CRAN.R-project.org/package=udpipe). The udpipe R package is a
Natural Language Processing toolkit that provides language-agnostic
'tokenization', 'parts of speech tagging', 'lemmatization',
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