Fly me to the stars: Interactive graphs with Docker, Jupyter and R

What: Documented data analysis on the fly
Why: Keep documentation, implementation and operation in one document; create publication ready reports; explore data interactively
How: Use Docker (containerization), Jupyter (documenting and code execution), R (analysis) and Plotly (interactive plots, very interesting also for web-frontend Javascript graphs)

You have to install Docker to run this tutorial. All dependencies are automatically installed in the container. Otherwise, you have to install the dependencies manually. Additionally, you need a browser to get access to Jupyter. The interactive plots work best in Chrome. I had some issues running it with firefox.

Copy the following content in a file called Dockerfile:

In the same directory, you need the file installJupyter.R with the following content:

Now, run the following two docker commands in the same directory where the docker file is located:

You should now have the running docker instance available on the docker VM, port 8888:
screenshot_jupyter

Via the „Upload“ button, upload the Notebook from here: Interactive graphs with Jupyter and R and open it. Execute all steps via „Cell“ -> „Run all“. Now, it should look like:

screenshot_jupyter_plotly

Did you noticed the interactive plot? You can zoom, export as png, have tooltips, … All without anything to programm. Cool, isn’t it?

Ok. Your customer is impressed but does not like the modern html stuff? He wants to print it out and send it away via mail? No problem. Just change the interactive plots to none-interactive ones and export to pdf via „File“ -> „Download as“ -> „PDF via Latex“ (that ’s why the docker file above contains all the stuff like pandoc, latex, …). You will get nearly publication ready report out.