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(This article was first published on <strong><a href="http://www.win-vector.com/blog/2018/09/practical-data-science-with-r2/"> R – Win-Vector Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>The secret is out: Nina Zumel and I are busy working on <a rel="nofollow" href="https://www.manning.com/books/practical-data-science-with-r-second-edition" target="_blank"><em>Practical Data Science with R<sup>2</sup></em></a>, the second edition of our best selling book on learning data science using <a rel="nofollow" href="https://www.r-project.org/" target="_blank">the R language</a>.</p>
<p>Our publisher, Manning, has a great slide deck describing the book (and a discount code!!!) <a rel="nofollow" href="https://www.slideshare.net/ManningBooks/practical-data-science-with-r-second-edition" target="_blank">here</a>:</p>
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<p><a rel="nofollow" href="https://www.slideshare.net/ManningBooks/practical-data-science-with-r-second-edition" target="_blank"><img border="0" src="https://i2.wp.com/www.win-vector.com/blog/wp-content/uploads/2018/09/pdsr2s.png?resize=660%2C354" alt="Pdsr2s" width="450" title="pdsr2s.png" data-recalc-dims="1"></a></p>
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<p>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:</p>
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The dot notation for base <code>R</code> and the <code>dplyr</code> package did make me stand up and think. Certain things suddenly made sense.
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<p>The reviewer is reacting to an improved section on how to organize calculations that condenses and combines the best ideas from the following articles:</p>
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<li><a rel="nofollow" href="http://www.win-vector.com/blog/2018/03/r-tip-break-up-function-nesting-for-legibility/" target="_blank">R Tip: Break up Function Nesting for Legibility</a></li>
<li><a rel="nofollow" href="http://www.win-vector.com/blog/2017/01/using-the-bizarro-pipe-to-debug-magrittr-pipelines-in-r/" target="_blank">Using the Bizarro Pipe to Debug magrittr Pipelines in R</a></li>
<li><a rel="nofollow" href="http://www.win-vector.com/blog/2018/03/r-tip-make-arguments-explicit-in-magrittr-dplyr-pipelines/" target="_blank">R Tip: Make Arguments Explicit in magrittr/dplyr Pipelines</a></li>
</ul>
<p><a rel="nofollow" href="https://www.manning.com/books/practical-data-science-with-r" target="_blank"><em>Practical Data Science with R</em></a> and <a rel="nofollow" href="https://www.manning.com/books/practical-data-science-with-r-second-edition" target="_blank"><em>Practical Data Science with R<sup>2</sup></em></a> are what <em>you</em> get when <em>we</em> have an editor! Also <em>Practical Data Science with R<sup>2</sup></em> is going to be able to move faster through coding problems by using features from our <a rel="nofollow" href="https://winvector.github.io/wrapr/" target="_blank"><code>wrapr</code> package</a> (which was not available when we wrote the first edition). And we will show how to move <em>much faster</em> through data using the <a rel="nofollow" href="https://cran.r-project.org/package=data.table" target="_blank"><code>data.table</code></a> package!</p>
<p>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 <a rel="nofollow" href="https://www.manning.com/books/practical-data-science-with-r-second-edition" target="_blank"><em>Practical Data Science with R<sup>2</sup></em></a> right now through <a rel="nofollow" href="https://www.manning.com/meap-program" target="_blank">Manning’s Early Access Program (MEAP)</a>! Heck, we even throw in a complete e-copy of the first edition at no extra cost!</p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://www.win-vector.com/blog/2018/09/practical-data-science-with-r2/"> R – Win-Vector Blog</a></strong>.</div>
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