Athlete Monitoring: Data Analysis and Visualization

As the tradition demands, when learning a new programming language, one needs to create the Hello World program. In this version of the Hello World, I am explaining the atomic vectors classes in R, as well some of the specific of the language (such as vectorized variables, vectors recycling and so forth). I am also explaining how to load an external CVS file (which can also work for the CSV file on the web, using URL – i.e., we can use this to sync the data from the AthleteSR).

I will fool you not – learning R is tricky, especially if you never used to code. But it is important to learn it as a programming language, rather than a script to do statistical analysis or plotting. As a sports scientist, knowing at least one programming language (e.g., R, Python, Matlab, C) can be very powerful, since it allows you to expand and deploy your knowledge.

If you want to learn more about R, I highly recommend checking these resources:

• Learning Statistics with R by Danielle Navarro
• R for Dummies by Andrie de Vries and Joris Meys
• R for Data Science by Garrett Grolemund and Hadley Wickham
• R for Data Science online FREE
• The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff
• The Book of R: A First Course in Programming and Statistics by Tilman M. Davies
• R in Action: Data Analysis and Graphics with R by Dr. Rob Kabacoff
• Advanced R by Hadley Wickham
• Advanced R online FREE

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