The secret is out: Nina Zumel and I are busy working on *Practical Data Science with R ^{2}*, the second edition of our best selling book on learning data science using the R language.

Our publisher, Manning, has a great slide deck describing the book (and a discount code!!!) here:

We also just got back our part-1 technical review for the new book. Here is a quote from the technical review we are particularly proud of:

The dot notation for base

`R`

and the`dplyr`

package did make me stand up and think. Certain things suddenly made sense.

The reviewer is reacting to an improved section on how to organize calculations that condenses and combines the best ideas from the following articles:

- R Tip: Break up Function Nesting for Legibility
- Using the Bizarro Pipe to Debug magrittr Pipelines in R
- R Tip: Make Arguments Explicit in magrittr/dplyr Pipelines

*Practical Data Science with R* and *Practical Data Science with R ^{2}* are what

*you*get when

*we*have an editor! Also

*Practical Data Science with R*is going to be able to move faster through coding problems by using features from our

^{2}`wrapr`

package (which was not available when we wrote the first edition). And we will show how to move *much faster*through data using the

`data.table`

package!We really think this is a book you are going to want to learn from, or even teach from. The great thing is you can start working with *Practical Data Science with R ^{2}* right now through Manning’s Early Access Program (MEAP)! Heck, we even throw in a complete e-copy of the first edition at no extra cost!

Categories: Opinion Practical Data Science Statistics

### jmount

Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.

Got mine! And there is no questioning ^2 vs ++ here.

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Oh it gets worse: check out this thread on

`**`

versus`^`

in`R`

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