Error Loading Packages...I think?

Hi!

I'm working on a school assignment and I loaded my data set and now I'm trying to run the following:

uncomment install.packages("caret") if already installed

install.packages("caret")

library(caret)

but I keep getting the following error message:
Error: package or namespace load failed for ‘caret’ in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]):
namespace ‘cli’ 3.3.0 is already loaded, but >= 3.4.0 is required

I have tried updating packages, uninstalling/reinstalling packages, I'm not sure what to do here. Can anyone please help?

Thanks!

This tells you to re-install an outdated dependency with

install.packages("cli")

Thanks for your response. I tried that previously and it didn't work. I just tried to install again, and got the same error message when I re-ran the code.

This is actually what comes up when I try to do install.packages(). But I have RTools installed already.

WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/
Installing package into ‘C:/Users/XXXXXXXXXX/AppData/Local/R/win-library/4.2’
(as ‘lib’ is unspecified)
trying URL 'https://cran.rstudio.com/bin/windows/contrib/4.2/cli_3.6.0.zip'
Content type 'application/zip' length 1299125 bytes (1.2 MB)
downloaded 1.2 MB

Did you restart R after successfully updating cli?

Hi @teitva,
You're using Windows, so you don't need to build (compile) the package from the source code - just install the latest pre-compiled binary from CRAN. Using this approach rtools is not needed.
Run install.packages("caret", dependencies=TRUE, type="win.binary"),
or use the RStudio pull-down menu in the "Packages" pane and answer "No" if you're asked about installing from source.

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Whether on Win, Mac or Lin, if presented with the option to install from source, take it once. If it works fine. If it doesn’t, it will never compile for the vast majority of RStudio users who do not devote an appreciable portion of their time to development and are well versed in modifying source code to address situations peculiar to their choice of OS.

The “later source version” temptation can be avoided with a little patience. Binary versions usually do not lag past 10-14 days.

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  • Installations are fast, automated and reversible thanks to package management layer.
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  • Optional (but recommeded) bspm use automagically connects R functions like install.packages() to apt for access to binaries and dependencies.

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Thank you thank you! I don't know what I kept doing wrong, but I ran the install.packages() you suggested, restarted RStudio, and IT WORKED! Phew! Thank you so much!

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