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.
Related
I recently updated my MacBook air (2017) to the Mojave OS and proceeded to update my version of R and Rstudio. Unfortunately, ever since the 'plotTangentSpace' command no longer functions appropriately even when attempting to run the example 'plethodon' code from the Geomorph vingette, I always receive the following error in the output (bolded below):
data(plethodon)
Y.gpa<-gpagen(plethodon$land) #GPA-alignment
|====================================================================================| 100%
gp <- interaction(plethodon$species, plethodon$site)
plotTangentSpace(Y.gpa$coords, groups = gp)
Error in plotTangentSpace(Y.gpa$coords, groups = gp) :
unused arguments (Y.gpa$coords, groups = gp)
I have tried uninstalling and reinstalling R for a MacOS many times including versions 4.0.2, 3.6.3, 3.6.1, and 3.2.1. I have also uninstalled and reinstalled XQuartz several times.
If anyone has encountered a similar issue or has any other ideas I can try I would really appreciate the help. Thank you!
If you execute:
?plotTangentSpace
You should see that this is a deprecated function. That means you should not be using it. It says:
Notes for geomorph 3.3.0 and subsequent versions
I suspect you have not updated your copy of the vignette. There are instructions on the help page for an alternate approach. The example in the help page for the suggested function is:
data(plethspecies)
Y.gpa <- gpagen(plethspecies$land) #GPA-alignment
### Traditional PCA
PCA <- gm.prcomp(Y.gpa$coords)
summary(PCA)
plot(PCA, main = "PCA")
For the plethodon data they suggest:
PCA.w.phylo <- gm.prcomp(Y.gpa$coords, phy = plethspecies$phy)
summary(PCA.w.phylo)
plot(PCA.w.phylo, phylo = TRUE, main = "PCA.w.phylo")
So start a new session (to unload the currently loaded geomorph namespace, and execute this at the r session command line:
install.packages("geomorph")
You should be getting version 3.3.1 of the geomorph package.
I think I found the problem! In my case, the error was due to a old version of the package RRPP, which is required by Geomorph. After updating it, Geomorph is working perfectly! Hope this can be useful for you too.
I came across the same error but after updating the RRPP and rgl packages required for geomorph, the gm.prcomp() function worked for me. I hope this helps if you haven't figured it out already.
This worked in mid-February, but stopped as of yesterday. It looks like there might have been some updates to xml2 subsequently, not sure if this is a factor.
library(edgarWebR)
filing_list <-
edgarWebR::company_filings(
as.character("AAPL"),
ownership = FALSE,
type = "10-K",
before = "2020207",
count = 40,
page = 1)
Error in xml2::url_absolute(res[[ref]], xml2::xml_url(doc)): Base URL must be length 1
Using xml2 1.3.0 and edgarWebR 1.0.1, but also tried previous versions of both.
Raised an issue with edgarWebR, but any pointers would be greatly appreciated.
I had the same exact problem and your post actually helped me fix it.
1: Go into 'packages' on RStudio and delete all versions of the xml2 package.
2: Restart R
3: Run these lines of code:
require(devtools)
install_version("xml2", version = "1.2.2", repos = "http://cran.us.r-project.org")
More info here https://support.rstudio.com/hc/en-us/articles/219949047-Installing-older-versions-of-packages
Author of edgarWebR here - I did a bit of debugging, here is the issue in xml2 I opened that, once fixed, should allow using a current version - https://github.com/r-lib/xml2/issues/300
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$LibPath)
# create a vector with all the names of the packages you want to remove
pkgs.to.remove <- ip[,1]
head(pkgs.to.remove)
str(pkgs.to.remove)
sapply(pkgs.to.remove, remove.packages, lib = path.lib)
sapply(pkgs.to.remove, install.packages, lib = path.lib)
How we can get the list of installed packages by user in R along with its version?
I know about the command installed.packages() which will give information about all packages (base or non-base). But how we can get those installed by user to have something like this:
Package Version
X 3.01
Y 2.0.1
Z 1.0.2
For all user installed packages (i.e. those package you installed via install.packages("X"))
ref
ip = as.data.frame(installed.packages()[,c(1,3:4)])
ip = ip[is.na(ip$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
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.