(This article was first published on

**Joris Muller's blog - Posts about R**, and kindly contributed to R-bloggers)Learning data science is a long path well described in this datacamp’s post. And as any skill, the best way to get it is to practise! Then, I would like to start some pet projects clearly distinct from my work projects. This way I could test as I want without being constraints by some technical limits or goal that don’t fit with what I want to learn.

Let’s put some rules on this game:

- These projects will be centred on some techniques (
*i.e.*: new package, data visualisation techniques…), not on particular practical question to answer with some data. - But I will write an objective for each analysis that fit with the technique I want to test.
- Keep the thing small enough to be achieved in a reasonable time. Due to my professional and family duties, I have few spare time.
- Keep things fun enough to keep the taste to do it.
- Publish everything on GitHub and, when done, a small post on this blog.

Enough rules for the moment! Let’s start! Because I’m a French medical doctor, I will pick up some data about health from the official government’s open data repository (data.gouv.fr).

To

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