R-markdown is a great tool for keeping your workflow organized and keeping track of each one of your research projects: you can add very easily, images, regression tables, graphs, etc. R-markdown documents are great for creating reproducible research. You can create:

  • Notebooks which include narrative text, and code to produce reproducible data analysis.
  • Slides such as io_slides or beamer_slides, whose figures and tables are also built for primitive data sets.

R-markdown allows you to use multiple programming languages including R, Python, SQL, and the shell. Bookdown is built on top of R-markdown and allows you to write more extensive documents such as book, including multiple chapters.

Cheatsheets

Again, cheatsheets are a good way to learn. There are 4 main references:

Python, Julia, C++, SQL engines

Another advantage of R-Markdown is that many other languages are also supported, such as Python, Julia, C++, and SQL. You may read more about it here. I will also introduce you quickly to Python, Julia, and SQL, which are all useful for data work.

Bookdown

You need to create PDF versions of the figures for creating the PDF version of the thesis, as well as PNGs for Word/HTML output. If you specify the path to a PNG file, include_graphics() knows to look in the same folder for a PDF version of the figure when creating the PDF output.

Slides