I can't get tidyverse to install. modules xml2 and rvest are failing to load properly. Root of the problem seems to be that package: libicui18n.so.58 is not being found and is needed for them. That file is not in R packages as far as I can see. Why is it not there?
I found libicui18n.so.58 in another app (anaconda python). Where do I put it so R finds it?
Using R version 4.3. RStudio 2023.06.2.
Another question is are the modules of tidyverse that perhaps were loaded, while xml2 and rvet were not, are they operational?
I was unaware of any connection between R and conda. After seeing your comment and looking it up, though, it looks like they can be used together in an R environment in anaconda. I do not have such a setup. So I am not using R from conda.
Where do I put the libicui18n.so.58 from anaconda into R so it can be found?
@gabor, you were right. I deactivated conda. tidyverse installed completely in R terminal window. It was also available as library in Rstudio. There were some conflicts that I do not yet know anything about yet.
See below for code from RStudio::
> library(tidyverse)
── Attaching core tidyverse packages ─────────────────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.3 ✔ readr 2.1.4
✔ forcats 1.0.0 ✔ stringr 1.5.0
✔ ggplot2 3.4.3 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.0
✔ purrr 1.0.2
── Conflicts ───────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package to force all conflicts to become errors
>
If anyone has insights as to what these mean let me know.
I had no idea tidyverse was a conda library as you indicated. Nothing I saw said there was a conda/R relationship.
I used my previously installed R and did not look into rig. I will look at rig to see if I should remove R and reinstall.
The conflicts listed when loading tidyverse are perfectly normal. It just means, for instance, that the dpylr package has a filter() function and so does the stats package. When you load dplyr, the filter function in stats is "masked" so that you have to call it with a reference to the stats package included, stats::filter(). Calling simply filter() gives you the function from dplyr.