Backup options to Launch R notebooks#

If you are an user who cannot access Datahub due to the following reasons,

  • You don’t have a Calnet log-in currently or

  • You are not able to access the Datahub service as it is down

then you can explore the below mentioned options to launch R notebooks.

Option #1: Launch Jupyter R Kernel locally#

Step 1: Install Anaconda distribution (JupyterLab application gets installed through this process) locally in your device. Check this link for the installation process.

Step 2: Search for “Anaconda Powershell Prompt” and Open it. Run the following code to install R Kernel in Jupyter Lab,

conda install -c r r-essentials

Note

Press “y” when command line prompts

The following is a screenshot of running this command in Anaconda Powershell Prompt

../../_images/rkernel_package.PNG

Step 3: Run the following command in “Anaconda Powershell Prompt” to install tidyverse packages

conda install -c r r-tidyverse

Note

Press “y” when command line prompts to install all the packages

The following is a screenshot of running the command to install tidyverse packages in Anaconda Powershell Prompt

../../_images/tidyverse_package.PNG

Step 4: Run the following command to launch Jupyter Lab

jupyter lab

Step 5: Now, from the launcher tab, choose R kernel to start a new notebook

../../_images/launcher_tab_r_kernel.jpg

The following is a screenshot of Jupyter notebook having R kernel.

../../_images/jupyter_notebook_r_kernel.jpg

Option #2: Use Google Colab to launch R Kernel#

Step 1: Launch R Kernel in Google Colab by accessing this link

Step 2: Check whether the tidyverse packages (or any other package you need) is already installed in Colab by using the following code,

print(installed.packages())

Step 3: If not installed, Install tidyverse package using the following command

devtools::install_github("tidyverse/tidyverse")

Option #3: Launch R notebooks using Binder#

If you want a hosted Jupyterhub experience to launch your R notebooks then Binder is an option. Binder allows creating R notebooks in an executable environment. Launch Jupyter R notebook or R Studio using the shared binder links.

Option #4: Launch R notebooks using R Studio#

If you are a RStudio fan, you can access RStudio Cloud where you can purchase a hosted environment for your coursework.

Note

Students need to create R Studio accounts.

If you don’t want to purchase an R Studio cloud account, you can ask students to download and install a free RStudio Desktop application on their desktop or use the free tier account.

Note

Workflow while using free RStudio cloud account would look like below,

  • Students need to download their homework from the github repository/canvas/google drive.

  • They should upload the homework to their RStudio server account.

  • Post completion, They should download the completed homework from RStudio server account.