Installing a Jupyter Notebook application

Another famous editor these days is the Jupyter Notebook app. This app produces notebook documents that integrate documentation, code, and analysis together. It supports many computational kernels including R. It is a server, client-side, web-based application that can be accessed using a browser.

How to do it...

Jupyter Notebook can be installed using the following steps:

1. Jupyter Notebook can be installed using pip:

pip3 install --upgrade pip
pip3 install jupyter

2. If you have installed Anaconda, then the default computational kernel installed is Python. To install an R computation kernel in Jupyter within the same environment, type the following command in a terminal:

conda install -c r r-essentials

3. To install the R computational kernel in a new environment named new-env within conda, type as follows:

conda create -n new-env -c r r-essentials

4. Another way to include the R computational kernel in Jupyter Notebook uses the IRkernel package. To install through this process, start the R IDE. The first step is to install dependencies required for the IRkernal installation:

chooseCRANmirror(ind=55) # choose mirror for installation
install.packages(c('repr', 'IRdisplay', 'crayon', 'pbdZMQ',
'devtools'), dependencies=TRUE)

5. Once all the dependencies are installed from CRAN, install the IRkernal package from GitHub:

library(devtools)
library(methods)
options(repos=c(CRAN='https://cran.rstudio.com'))
devtools::install_github('IRkernel/IRkernel')

6. Once all the requirements are satisfied, the R computation kernel can be set up in Jupyter Notebook using the following script:

library(IRkernel)
IRkernel::installspec(name = 'ir32', displayname = 'R 3.2')

7. Jupyter Notebook can be started by opening a shell/terminal. Run the following command to start the Jupyter Notebook interface in the browser, as shown in the screenshot following this code:

jupyter notebook

Jupyter Notebook with the R computation engine

There's more...

R, as with most of the packages utilized in this book, is supported by most operating systems. However, you can make use of Docker or VirtualBox to set up a working environment similar to the one used in this book.

For Docker installation and setup information, refer to https://docs.docker.com/ and select the Docker image appropriate to your operating system. Similarly, VirtualBox binaries can be downloaded and installed at https://www.virtualbox.org/wiki/Downloads.