How to install R packages that are not available in "R-essentials"?

Now I have found the documentation:

This is the documentation that explains how to generate R packages that are only available in the CRAN repository: https://www.continuum.io/content/conda-data-science

Go to the section "Building a conda R package".

(Hint: As long as the R package is available under anaconda.org use this resource. See here: https://www.continuum.io/blog/developer/jupyter-and-conda-r)

alistaire's answer is another possibility to add R packages:

If you install packages from inside of R via the regular install.packages (from CRAN mirrors), or devtools::install_github (from GitHub), they work fine. @alistaire

How to do this: Open your (independent) R installation, then run the following command:

install.packages("png", "/home/user/anaconda3/lib/R/library")

to add new package to the correct R library used by Jupyter, otherwise the package will be installed in /home/user/R/i686-pc-linux-gnu-library/3.2/png/libs mentioned in .libPaths() .

To install other R Packages on Jupyter beyond R-essentials

install.packages('readr', repos='http://cran.us.r-project.org')

One issue is that the specific repository is the US.R-Project (as below). I tried others and it did not work.

N.B. Replace readr with any desired package name to install.

Here's a conda-centric answer. It builds on Frank's answer and the continuum website: https://www.continuum.io/content/conda-data-science with a bit more detail.

Some packages not available in r-essentials are still available on conda channels, in that case, it's simple:

conda config --add channels r
conda install r-readxl

If you need to build a package and install using conda:

conda skeleton cran r-xgboost
conda build r-xgboost
conda install --use-local r-xgboost

that last line is absent in the continuum website because they assume it gets published to anaconda repository first. Without it, nothing will be put in the envs/ directory and the package won't be accessible to commandline R or Jupyter.

On a mac, I found it important to install the Clang compiler for package builds:

conda install clangxx_oxs-64

I found an easy workaround. I suppose that you have an RStudio IDE for you R. It is weird to use RStudio for that, but I tried straight from R in my terminal and it didn't work. So, in RStudio console, just do the usual adding the path to your anaconda directory (in OSX,'/Users/yourusernamehere/anaconda/lib/R/library')

So, for example,

install.packages('package','/Users/yourusernamehere/anaconda/lib/R/library')

I feel ashamed to post such a non-fancy answer, but that is the only one that worked for me.