Open Dr-Albert-MD opened 3 years ago
To install R Kernel in JupyterLab Desktop follow the instructions in https://github.com/jupyterlab/jupyterlab-desktop/blob/master/user-guide.md#customizing-the-bundled-python-environment (i.e. set appropriate permissions to the environment) but then at the point, when %pip install scikit-learn
example is suggested please instead run:
%conda install -c conda-forge r-irkernel
Please note that this will install a new copy of R from conda (which may use up a bit of space).
Please leave a comment sharing your experience: did it work for you? Is this what you would expect? Should we include it in the user guide, or do we need a different solution?
Tested on Ubuntu 21.10 with JupyterLab Desktop v3.2.1-2.
I've tried this (on Windows 10) and it seems to have worked. However, it seems like I can only pick one kernel per notebook. Is it possible to use the R and python kernels side-by-side?
Kind of. You can install rpy2
to access R from the Python kernel and then use magics see https://rpy2.github.io/doc/v3.4.x/html/generated_rst/notebooks.html
It would be great to have details of how to install alternative kernels in the README or at least a link from the README to some instructions.
I've just followed this through on macOS with success.
Hello there, can anyone please give directions on how to install the ijava kernel in JupyterLab desktop? I already have this kernel installed in web based jupyterlab, but I am wondering if the procedure is the same in JupyterLab for dektop.
Thank you!
Kind of. You can install
rpy2
to access R from the Python kernel and then use magics see rpy2.github.io/doc/v3.4.x/html/generated_rst/notebooks.html
let's try
~/Library/jupyterlab-desktop/jlab_server
, find under it share/jupyter/kernels/
https://github.com/evcxr/evcxr/tree/main/evcxr_jupyter
) $ butuzov ~/Library/jupyterlab-desktop/jlab_server/share/jupyter/kernels
> tree
.
├── python3
│ ├── kernel.json
│ ├── logo-32x32.png
│ ├── logo-64x64.png
│ └── logo-svg.svg
└── rust
├── kernel.js
├── kernel.json
├── lint-LICENSE
├── lint.css
├── lint.js
├── logo-32x32.png
├── logo-64x64.png
├── logo-LICENSE.md
└── version.txt
2 directories, 13 files
now you have new kernel and you can use it!
I have always used this procedure inside an R session for the standard jupyter lab R kernal installation: install.packages("devtools") devtools::install_github("IRkernel/IRkernel") IRkernel::installspec()
Anyway, the same procedure seems not to work for Jupyter Lab Desktop app. Any help is appreciated. Thanks