The traditional presentation workflow provided by PowerPoint and Keynote separate your analysis and visualisation scripts from your slides, immediately making your presentation out of date. By using RMarkdown presentations you can directly connect your analytical and communication workflows, improving the reproducability and replicability of your data presentations. Learn about the benefits of using RMarkdown for presentations over PowerPoint in this online video.
- [Voiceover] Reporting on your analyses should be a core part to your data processing workflow, particularly important if your analysis is of real-time data or it's performed according to a schedule. Let's compare the traditional workflow for creating presentations, using a tool like PowerPoint or Keynote to RMarkdown. In the traditional workflow, you have your data set or your data base, you import your data into RStudio, generate a chart, and then many people copy and paste this chart, perhaps directly into PowerPoint, but often into Photoshop or some other image editor, to slightly change how things look.
This is very problematic, because your presentation of your data is not reproducible. Immediately, your visualizations are out of date and, if you've gone through the Photoshop route, they are potentially misleading. With RMarkdown, you can create your presentations as you're writing your code, as your presentation is generated from the same environment in which you write your analytical code. Using RMarkdown, you have two choices. You can generate your presentations as either PDF or HTML files.
Let's compare the two options here. If you generate PDF presentations, then every time your data changes and you generate a new presentation, you've created a new, static file. So, what you've really replicated is the same issue we had before, with the traditional presentation workflow. Each time your data changes, your previous presentation is out of date. By using HTML presentations, you can ensure that your presentation is always pulling the most up-to-date data.
So, by using HTML, RMarkdown presentations with embedded Shiny apps, you can ensure that your presentation always includes up-to-date data. This reproducible of presentations is becoming ever more important, with a number of examples of poor reproducibility in a copy paste workflow. For instance, the Reinhart and Rogoff disaster a few years ago. So, what is Markdown? Markdown is a very simple markup language with only three types of instructions.
In fact, in Markdown, there are only seven things that you can do. You can Layout Text with Headings and Subheadings. You can Format Text with italics, bold, and bullet points. And you can also Link to Content. In summary, RMarkdown creates a seamless workflow between data, analysis, and presentation. HTML RMarkdown documents can easily be published to the web and kept up-to-date. And using Shiny apps inside of the RMarkdown presentations, you can ensure that the data you're displaying is always up-to-date and correct.
And finally, RMarkdown is incredibly simple to learn. There is one cheat sheet available at RStudio.com, which will teach you all you need to know.
This is an exciting course for analysts who want to increase the relevance and visibility of their work. Make sure to watch the knowledge checks at the end of each chapter to test your new skills.
- Installing and configuring RStudio
- Using R Markdown
- Adding slides to templates
- Working with code and charts
- Publishing presentations with RPubs
- Developing interactive charts and visualizations with Shiny
- Deploying presentations with shinyapps.io
- Making Shiny dashboards