How we can get the list of installed packages by user in R along with its version?
I know about the command installed.packages() which will give information about all packages (base or non-base). But how we can get those installed by user to have something like this:
Package Version
X 3.01
Y 2.0.1
Z 1.0.2
For all user installed packages (i.e. those package you installed via install.packages("X"))
ref
ip = as.data.frame(installed.packages()[,c(1,3:4)])
ip = ip[is.na(ip$Priority),1:2,drop=FALSE]
ip
I just found another ways to see the list of the packages without writing any code:
Open RStudio
Navigate to Help --> R Help (from the menu above)
You will see the help panel opened.
Then follow, Reference --> Packages
There you are.
OR
Open R console
Navigate to Help --> Html help
Then follow, Reference --> Packages
str(allPackage <- installed.packages(.Library, priority = "high"))
allPackage [, c(1,3:5)]
You will get all the active package List
Here's my solution.
tibble::tibble(
Package = names(installed.packages()[,3]),
Version = unname(installed.packages()[,3])
)
You can even filter some packages that you want to show.
pkg = tibble::tibble(
Package = names(installed.packages()[,3]),
Version = unname(installed.packages()[,3])
)
dplyr::filter(pkg, Package %in% c("tibble", "dplyr"))
If I develop an app or model and want to record the package versions used, I call sessionInfo()
One trick would be to use library() and a window with all the packages will pop up
Related
I try to use the function "get_data_structure" but got an error as below.
Could anyone know how to fix it?
Thank you in advance
get_data_structure("DUR_D")
Error in data.frame(data_structure#concepts) :
trying to get slot "concepts" from an object (class "data.frame") that is not an S4 object
The problem appears to be a bug in the version of the OECD package on CRAN. If you install the development version, it works. First, close R and reopen a clean new session, then run this:
remotes::install_github("https://github.com/expersso/OECD")
library(OECD)
get_datasets()
get_data_structure("DUR_D")
remotes::install_github("https://github.com/expersso/OECD")
library(OECD)
dataset <- "DUR_D"
dstruc <- get_data_structure(dataset)
Try with get_dataset("DUR_D") i.e. without -s. as get_datasets() with -s will return a dataframe of available datasets.
It is a bug in the package OECD 0.2.5.
It works with the package version 0.2.4 which you can install from CRAN's archived package section (https://cran.r-project.org/src/contrib/Archive/OECD).
If you want to access the archived package version directly in R, use the following code:
devtools::install_version("OECD", version = "0.2.4", repos = "https://stat.ethz.ch/CRAN/")
Note that this requires the package 'devtools' to be installed.
I am brand new to this so please forgive my inexperience...I'm trying to learn.
I'm attempting to install an R package called "Doublet Finder" using the specified code given on the Github site.
When I do this, I get this error immediately:
Error in rbind(info, getNamespaceInfo(env, "S3methods")) :
number of columns of matrices must match (see arg 2)
Being new to R, I'm not sure what this error means and when I google this something similar comes up and the individual removed and re-installed ALL of their libraries...that seems crazy. Does anyone have advice on what this could be, how to fix it, or why the package won't install?
Your problem seems to be fairly similar to this one. It might be the case that the dependencies (packages that Doublet Finder relies on) are outdated. What you can try is to follow these steps to uninstall and reinstall all packages with the hope that by updating packages there isn't a version mismatch.
This code is copied from the website above:
ip <- as.data.frame(installed.packages(lib.loc = .libPaths()[1]),
stringsAsFactors = FALSE)
head(ip)
str(ip)
path.lib <- unique(ip$LibPath)
# create a vector with all the names of the packages you want to remove
pkgs.to.remove <- ip[,1]
head(pkgs.to.remove)
str(pkgs.to.remove)
sapply(pkgs.to.remove, remove.packages, lib = path.lib)
sapply(pkgs.to.remove, install.packages, lib = path.lib)
I'm trying to use copula on Rmd but am coming across a lot of issues with the formula:
Error: could not find function "pobs"
For example, I have already installed the packages before by typing this:
install.packages("VineCopula")
u <- pobs(as.matrix(cbind(cree,yahoo)))[,1]
v <- pobs(as.matrix(cbind(cree,yahoo)))[,2]
selectedCopula <- BiCopSelect(u,v,familyset=NA)
selectedCopula
Code based off this link: https://www.r-bloggers.com/modelling-dependence-with-copulas-in-r/
It seems you didn't load the VineCopula package before using it. install.packages is used to install packages, library is used to load them into your R session. This is what you should run:
library(VineCopula)
u <- pobs(as.matrix(cbind(cree,yahoo)))[,1]
v <- pobs(as.matrix(cbind(cree,yahoo)))[,2]
selectedCopula <- BiCopSelect(u,v,familyset=NA)
selectedCopula
You have installed the library in your code but haven't referenced it hence the functions are not available.
An example of this for reference would be installing an application on your phone; it gets installed but you need to open it in order to use it.
By using install.packages, the package was downloaded in your default home folder. You can change that using install.packages('package_name',lib.loc='path_on_your_system').
It is also a good practice to specify the library path before loading it.
.libPaths('path_on_your_system')
library(VineCopula)
u <- pobs(as.matrix(cbind(cree,yahoo)))[,1]
v <- pobs(as.matrix(cbind(cree,yahoo)))[,2]
selectedCopula <- BiCopSelect(u,v,familyset=NA)
selectedCopula
Let me know if this explanation helps.
Suppose that
the version of R I have installed is 3.3.1;
my environment variable $R_LIBS_USER is set to $HOME/my/R_lib/%V; and
I have a directory $HOME/my/R_lib/3.3.1 containing a large number of packages I've installed over time.
Now I want to upgrade my version of R, to 3.4.1, say.
I'm looking for a convenient way to install a new collection of packages under the new directory $HOME/my/R_lib/3.4.1 that is the "version-3.4.1-equivalent" of the library I currently have under $HOME/my/R_lib/3.3.1.
(IOW, I'm looking for a functionality similar to what one can do with Python's pip installer's "freeze" option, which, essentially, produces the input one would have to give the installer in the future to reproduce the current installation.)
You can use function installed.packages for that purpose. Namely:
installed.packages(lib.loc = "$HOME/my/R_lib/3.3.1")
The returned object contains a lot of informations (most fields from each package DESCRIPTION file) but the names of the packages are in the first column. So something like the following should do the trick:
inst <- installed.packages(lib.loc = "$HOME/my/R_lib/3.3.1")
install.packages(inst[,1], lib="$HOME/my/R_lib/3.4.1", dependencies=FALSE)
To answer the additional question in the comments:
If your old library contained packages from other sources than CRAN, you will have to do some gymnastic based on the content of the DESCRIPTION files, and thus will depend on how well the package author documented it.
Argument field in installed.packages allows you to select some additional fields from those files. Fields of interest to determine the source of a package are fields Repository, URL and Maintainer. Here are some ideas on how to split them apart:
CRAN vs non-CRAN:
inst <- installed.packages(lib.loc = "$HOME/my/R_lib/3.3.1",
fields=c("URL","Repository","Maintainer"))
inst <- as.data.frame(inst, row.names=NA, stringsAsFactors=FALSE)
cran <- inst[inst$Repository%in%"CRAN",]
non_cran <- inst[!inst$Repository%in%"CRAN" & !inst$Priority%in%"base",]
Bioconductor packages:
bioc <- inst[grepl("Bioconductor",inst$Maintainer),]
source("https://bioconductor.org/biocLite.R")
biocLite(pkgs=bioc$Packages)
Github packages:
git <- non_cran[grepl("github", non_cran$URL),]
install.packages("devtools")
library(devtools)
for(i in seq(nrow(git))){
install_github(repo=gsub("http://github.com/","",git$URL[i]))
}
The following R commands will install all CRAN packages:
availablePackages <- available.packages()[,1]
install.packages(availablePackages)
And the following command will list all installed packages:
installedPackages <- .packages(all.available = TRUE)
My question is: How do I instruct R to install all CRAN packages that are not already installed?
Frankly, I think it's painstaking job... it would last for days, even weeks (depending on resources), but here's the code (I just enjoy doing trivial things):
# get names of installed packages
packs <- installed.packages()
exc <- names(packs[,'Package'])
# get available package names
av <- names(available.packages()[,1])
# create loooong string
ins <- av[!av %in% exc]
install.packages(ins)
I still don't get why you're doing this, but, hey... some things are just not meant to be....
What wonders me the most is the fact that you've already answered your own question! You got what you needed, and it's just up to you to put things together...
Are we missing the point? Did you have something else in mind?!?
1) Why would you want to do that? There are over 3500 (as of Feb 2012) of them?
2) Did you look at CRAN Task Views and the ctv package that allows you to install packages from a given task?
3) You bold-face question is a simple indexing query you can do by hand (and besides that, also see help(sets))
R> available <- LETTERS # a simple set
R> installed <- LETTERS[c(1:10, 15:26)] # a simple subset
R> available[ ! available %in% installed ]
[1] "K" "L" "M" "N"
R>
Edit: in response to your follow-up:
a) If a package does not pass 'R CMD check' on Linux and Windows, it does not get uploaded to CRAN. So that job is done.
b) Getting all depends at your end is work too as you will see. We did it for cran2deb which is at http://debian.cran.r-project.org (which does full-blown Debian package building which is more than just installing). We get about 2050 out of 2150 packages built. There are a few we refuse to build because of license, a few we cannot because of missing headers or libs and a few we cannot build because they need e.g. BioConductor packages.
type this command and then all packages will be installed automatically:
install.packages(available.packages()[,1])
Better if you use:
check.and.install.Package<-function(package_name){
if(!package_name%in%installed.packages()){
install.packages(package_name)
}
}
call the function and check if required package is installed:
check.and.install.Package("pkgName")
I've tested this and it works
availablePackages=available.packages()
availablePackages<-as.vector(availablePackages[,1])
installedPackages=.packages(all.available = TRUE)
missedPackages<-setdiff(availablePackages, installedPackages)
for (i in 1:length(missedPackages))
{
pkgName <- missedPackages[i]
install.packages(pkgName)
}
print("END")
Regards
From my experience, it is not wise to install all the R packages at once! Even if you do not call upon (using library function) all those packages, by just sitting in the home directory, they can slow down your R studio. At least that's what happened in my case.