Installing the R kernel in Jupyter Lab

I was recently pretty impressed with Jupyter's newest creation, the Jupyter Lab IDE. You can test drive an online demostration of Jupyter Lab with a Python and R kernel here.

I downloaded a version, and found that the R Kernel was missing! To get the R kernel up and running in Jupyter Lab was a bit more complicated than expected. This guide is meant to break things down step by step.

I did this on Windows and OSX.

Windows Instructions

1. Install Anaconda

Download here. This gives you a few important things: Jupyter notebooks, and the Anaconda Prompt.

2. Install the Jupyter client

Search for the Anaconda Prompt in your computer, right click, and run As Adminstrator.

In the prompt type:

conda install -c anaconda jupyter_client

3. Install the IR Kernel

I assume you have R on your computer. If not, I recommend downloading it here.

Find the location of R.exe on your computer. In my computer this executable is at: C:\Program Files\R\R-3.4.3\bin.

Open another Anaconda Prompt as Adminstrator and change directories to wherever R.exe is on your computer with cd file path. On my computer it's: cd C:\Program Files\R\R-3.4.3\bin, but it might be different for you.

Then run R from within Anaconda Prompt in Admin mode with R.exe.

Once in an R session, run the following three commands:


In order, they (1) install the devtools package which gets you the install_github() function, (2) install the IR Kernel from github, and (3) tell Jupyter where to find the IR Kernel.

4. Open Jupyter Lab and enjoy your new R kernel!

Open Anaconda Prompt and type in jupyter lab. Jupyter Lab should launch and display both a python and R kernel.

OSX Instructions

I found installation on my Mac a lot easier. I just followed the steps here.

1. Install Anaconda

Download the Mac version here and run through the setup.

2. Open R and install the necessary packages

Open up the R prompt and enter:

install.packages(c('repr', 'IRdisplay', 'evaluate', 'crayon', 'pbdZMQ', 'devtools', 'uuid', 'digest'))

3. Configure IRkernel from within R

It's important that these next commands are done from within the version of R that you want to link to Jupyter Lab.

I found my version of R in richpauloo$ /Library/Frameworks/R.framework/Versions/3.4/Resources/bin/R. Navigate to the version of R you're using, lanuch R.exe, and enter:

IRkernel::installspec() # install for the current user
IRkernel::installspec(user = FALSE) # install system-wide

Fire up Anaconda, launch a Jupyter Lab session, and you should see an R kernel waiting for you!

Lastly, I found the Jupyter Lab User's Guide to be pretty helpful, and you might too.

Rich Pauloo, PhD
Data Scientist

My interests include data science, hydrology, geology, physical simulation, building simple solutions to complex problems, and expedition behavior.