I'm using a package (ggmap) that doesn't work on R 3.6.1 (Windows), so I would like to install a previous version of R. Once the version is installed, I found how to force Rstudio to use it (through the options panel).
The issue is I am not able to install a previous version. I've downloaded the directory (didn't do anything with it besides drag-and-drop into my R directory), but when I try to force Rstudio to use it, I get the following message:
"This directory does not seem to contain a valid R installation".
The parent directoy is the same that has the R 3.6.1, which works fine.
Thanks for any help!
I am using R version 3.6.0 (2019-04-26) and I was able to install the mentioned package:
install.packages('ggmap')
In my experience, sometimes I also think it's due to a version incompatibility when it isn't. For example, I might get a message similar to this:
Warning in install.packages :
package 'biomaRt' is not available (for R version 3.6.0)
To which most of the time the solution includes using setRepositories():
setRepositories()
Enter one or more numbers separated by spaces, or an empty line to cancel
1: 1 2 3 4 5 6 7 8
In this case, I added all of them just in case, which reassures that if the package exists and is available for my version, it will be installed (You may want to reset it again to a single repository, as it may slow the installation of other packages).
Edit: If you actually get the Error message I mentioned, you might be interested in looking at this answer if setRepositories() does not fix your issue.
Related
I tried to install the packages in the following way:
pacman::p_load(tidyverse, lubridate, zoo,
timetk, modeltime,
trelliscopejs, seasonal,
tsibble, feasts, fable)
However, I got the below errors:
I'm not sure what's wrong, I'm using the latest R version 4.2.1, the warning seems to suggest that need to change to 4.1.3, is there anyway to install those packages without changing the version?
The problem is not related to the package in itself. The warning about the version only tells you that the last time this package was built was on R 4.1.3, but it should work on R 4.2.
The problem is that the place where R searches this package doesn't exist. If you go here: https://www.stats.ox.ac.uk/pub/RWin/bin/windows/contrib/, you will see that the last version of R is 3.4, whereas you're looking for a package built in R 4.1 (see the version in the URL address in the error message).
Here's some advice to solve this (I can't reproduce your problem so I can't be sure this works): if you're using RStudio, go to "Tools -> Global Options -> Packages". I think that under "Primary CRAN repository", there should be the name of the current place where R searches for the files to install each package. You can change this: either pick "Global (CDN) - RStudio" or any other that is not too far from your location. Then restart R and try reinstalling the packages.
Downloaded package from below URL.
Attempted to install using below command; response shown.
library(dalton.rqi,lib.loc='/home/X/Desktop/')
Error: package ‘dalton.rqi’ was built before R 3.0.0: please re-install it
https://my.clevelandclinic.org/departments/anesthesiology/depts/outcomes-research/risk-quantification
It appears this is a compiled package that maybe I don't have the source for? Is there a way to force install of the package? I'm unable to install using Rstudio GUI in its current form as a zip. Tried repackaging to tar.gz has Rstudio was looking for and also had a non-zero exit status error.
Any ideas?
I'm afraid this can't be achieved directly. The error message says it well: to use a package in R it needs to be built on an R version matching yours.
I can suggest two ways to move forward:
Contact the authors, ask for the R sources (it is somewhat surprising they did not make them available in the first place), and build the package yourself.
Downgrade your R version as far back as needed to match the one this pre-built package used.
After changing all the needed environment varaibles ( Control Panel/ System/Advanced system settings/Environment Variables) in windows 8, when I am installing rJava Package I get errors as below
I tried in MsDOS immediately after changing environment variables,
first step >R "it was successful"
second >install.packages("rJava") "got error in this step"
then I tried >install.packages("rJava", repos="https://cran.rstudio.com/") "but again I did not succeeded"
I am tired of trying all this, I referred many links already but all in vain. Yes, I am using Proxy also. Please help any one.
1) It seems a download problem first. So do this:
Download rJava_0.9-8.zip from CRAN (cran.r-project.org/web/packages/rJava/index.html). Then, in Revolution R Enterprise; Packages - "Install Packages From local Zip Files..." - Choose rJava_0.9-8.zip - OK. If the problem is solved then OK.
If the problem persists, try the following Step.
2) Look at DESCRIPTION file in rJava (in library location):
Package: rJava
Version: 0.9-8
....
Depends: R (>= 2.5.0), methods
....
NeedsCompilation: yes
Your R version may be incompatible. Look at the warning: "rJava is not available for R3.3.0" in your screenshot. So do this:
Unzip file rJava_0.9-8.zip to R's working directory; the folder rJava is created there. Change R version accordingly (you may introduce lower version number in Depends section). Save the changed DESCRIPTION file. Apply classical procedure:
library(roxygen2) # install this package first if not done yet
library(devtools) # install this package first if not done yet
library(digest) # install this package first if not done yet
Note: Since rJava folder is created manually, no package.skeleton is needed at this stage.
roxygenize("rJava")
build("rJava")
install("rJava")
The above technique must solve the problem (It solved previously many R version problems!).
Analyze this one also:
Install a specific release of bioconductor package (where the solution I wrote solved the problem of the questioner).
If you still have problems, trigger the following:
sessionInfo(); getwd(); .libPaths()
and print the output in your question so that we can analyze if you have any machine-spesific or installation-spesific problems.
I am working on a Windows 7 machine without internet access. As yet, I got around the missing internet connection by creating a local copy of the binary CRAN repository in //server/x/bin/windows/contrib/3.1, then running write_PACKAGES("//server/x/bin/windows/contrib/3.1") and finally setting r["CRAN"]="file:////server/x";r["CRANextra"]=r["CRAN"]; in C:/Program Files/R/R-3.1.2/etc/Rprofile.site.
But this does not work any longer since R 3.2.1. The path in the error message of install.packages indicates that R is looking for the source package:
Cannot open compressed file '//server/x/src/contrib/PACKAGES'
I have thought that R on Windows only looks for binary packages!
Looking at a diff between install.packages for 3.1.2 and 3.2.1, I can see quite a few changes. However, the source code for the function has 500+ lines which makes it hard for me to see where specifically the problem lies.
I have tried to set
options(install.packages.check.source="no")
and to explicitly add type="win.binary" to install.packages - both without success.
It is also interesting that
contrib.url(options("repos")$repos["CRAN"],type="win.binary")
gives the correct path file:////server/x/bin/windows/contrib/3.2 but somehow this is not used by install.packages(...,type="win.binary")...
So my question is whether you guys have experienced similar problems?
If no, I would be grateful for any pointers to mistakes I could have made.
I have found the problem.
The R 3.2.1 NEWS section (https://cran.r-project.org/src/base/NEWS) says
The default for option pkgType on platforms using binary packages is now "both", so source packages will be tried if binary versions
are not available or not up to date.
The problem is that RStudio does not directly call install.packages but via a few other functions such as .rs.callAs. In one of these functions, available.packages() gets called without any arguments. So it determines the argument type via getOption("pkgType"). But since R 3.2.1 this is now "both" and not "win.binary" as in R 3.1.2.
A quick workaround for the problem is thus to add
options(pkgType="win.binary")
to the yourRinstallpath/etc/Rprofile.site
I'm building R packages in R 3.0.1 on a Windows machine, using Rtools30 and the 'Build' tools associated with RStudio, which I assume is tied in with devtools (which is up-to-date). My typical process to build a package is:
Load All
Reoxygenize
Build & Reload
Check
Build Source Package
If everything goes without errors or warnings, I then:
install.packages("foo.tar.gz", repos=NULL, type="source")
Since upgrading to R 3.0.1, I now get this warning:
Warning in install.packages :
foo.tar.gz is not available (for R version 3.0.1)
I also tried before installing, and it did not get rid of the warning:
options(install.packages.check.source = FALSE)
Also, I notice this warning when I open the devtools library:
WARNING: Rtools 3.0 found on the path at c:/Rtools is not compatible with R 3.0.1.
Which is weird, Rtools 3.0 is suppose to be good from R >2.15.1 to R 3.0.x
Any ideas what is going on?
This is RStudio specific, as they wrap and/or changed a lot of functions from the utils for better integration. The problem lies with a call to getDependencies() to check for dependencies. But that function will also check whether the original package exists on CRAN and throws the given warning when it doesn't. A package you just built on your own computer is obviously not on CRAN, hence the warning.
In the source of the native install.packages(), getDependencies() isn't called in case you build from source or install from a different repository respectively. RStudio on the other hand calls getDependencies() before it passes everything on to the native install.packages() function.
This has to my knowledge no further effects, apart from confusing people. I didn't find a way to conveniently get rid of this in RStudio, as suppressWarnings() doesn't work in this context due to the complex way RStudio deals with this.
In a basic R console, you shouldn't have any problem.
So for the time being, I'd just ignore this and hope the RStudio team finds time to take care of this minor glitch.