Installing an R Kernel in Jupyter¶
Jupyter is commonly thought of as a resource for python. But it works just as well with R. In this brief post I will show you how to create a Jupyter kernel for R, so you can run R line by line.
If you don't already have R follow these two instructions to download R and R studio. R studio isn't necessarily needed if you will be working in jupyter, but it's always a good piece of software to have.
INSTALLING R:¶
- Go to http://www.r-project.org/, and in the “Getting Started” box, click on “download R.”
INSTALLING R STUDIO:¶
- Go to http://www.rstudio.com, click on “Download RStudio” and follow the directions for your operating system.
Installing an R Kernel is actually extremely easy¶
The first thing you will want to do is open up an R console. You can do this in Rstudio if you already use that.
Then you will run the following two commands. Either by running a script or by entering them into the console:
- install.packages('IRkernel')
- IRkernel::installspec()
Open Jupyter Notebook¶
After running this in your our console you will then go to your terminal/anaconda prompt and type the following to launch Jupyter Notebook:
Which will launch your web browser with Jupyter. And like I mentioned earlier on the far right you can view your current kernels. As mentioned earlier, I have a few, one of which is R.
Now I can start programming in R
X_vals <- c(1,2,3,4,5)
y_vals <- c(1,2,4,8,16)
plot(X_vals,y_vals,
col='blue', pch=12,
main='R plot in Jupyter')