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how-to-make-mistakes-in-R

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How To Make Mistakes in R

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## What are your “favorite” R mistakes?

### R is great, but it’s also weird.

R was built by and for statisticians, so it’s not like other programming languages. Its idiosyncrasies can be a source of deep frustration for beginners. But I’d argue there is no better tool for data analysis.

That’s why I’m writing a free ebook *How To Make Mistakes In R* for O’Reilly. It’s modeled after the excellent [*How To Make Mistakes In Python*](http://www.oreilly.com/programming/free/how-to-make-mistakes-in-python.csp), by [Mike Pirnat](http://mike.pirnat.com/).

The target audience is all R coders, from those just starting out all the way to the advanced developers. It’ll cover mistakes in set-up, style, and statistics -- and other surprises, too. I’m especially qualified to write this book because I’ve made so many R mistakes in my own work.

It's an exciting project, but I need your help. **What are your “favorite” R mistakes?**

I’m looking for all types, ranging from the dead-simple, beginner-level screwups to the subtle, advanced bugs you’ve encountered. Here are a few examples of mistakes I plan to address:

- Function masking due to conflicting packages (e.g., dplyr and plyr)
- Repeatedly typing `stringsAsFactors = FALSE`
- The default `table()` function masking NA values
- Not using piping (`%>%`) to improve code readability
- Not using the `broom` package to standardize the output of statistical models
- Not using GitHub and/or RStudio Projects for collaboration

Send them to me, via [email](mailto:andrew.w.flowers@gmail.com), a [GitHub pull request](https://github.com/andrewflowers/how-to-make-mistakes-in-R) or on [Twitter](https://twitter.com/andrewflowers). The more the merrier. Feel free to contact me multiple times, as you recall your “favorite” R mistakes.

how-to-make-mistakes-in-R

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