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(This article was first published on <strong><a href="http://www.win-vector.com/blog/2018/08/meta-packages-nails-in-crans-coffin/"> R – Win-Vector Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Derek Jones recently discussed a possible future for the <a rel="nofollow" href="https://www.r-project.org/" target="_blank"><code>R</code></a> ecosystem in <a rel="nofollow" href="http://shape-of-code.coding-guidelines.com/2018/08/06/statsmodels-the-first-nail-in-rs-coffin/" target="_blank">“StatsModels: the first nail in R’s coffin”</a>.</p>
<p>This got me thinking on the future of <a rel="nofollow" href="https://cran.r-project.org/" target="_blank"><code>CRAN</code></a> (which I consider vital to <code>R</code>, and vital in distributing our work) in the era of super-popular meta-packages. Meta-packages are convenient, but they have a <em>profoundly negative impact</em> on the packages they exclude.</p>
<p>For example: <a rel="nofollow" href="https://www.tidyverse.org/packages/#installation-and-use" target="_blank"><code>tidyverse</code></a> advertises a popular <code>R</code> universe where the vital package <a rel="nofollow" href="https://cran.r-project.org/package=data.table" target="_blank"><code>data.table</code></a> never existed.</p>
<p><img border="0" src="https://i2.wp.com/www.win-vector.com/blog/wp-content/uploads/2018/08/NewImage.png?resize=279%2C300" alt="NewImage" width="279" title="NewImage.png" data-recalc-dims="1" height="300"></p>
<p>And now <a rel="nofollow" href="https://www.tidyverse.org/articles/2018/08/tidymodels-0-0-1/" target="_blank"><code>tidymodels</code></a> is shaping up to be a popular universe where our own package <a rel="nofollow" href="https://cran.r-project.org/package=vtreat" target="_blank"><code>vtreat</code></a> never existed, except possibly as a footnote to <a rel="nofollow" href="https://topepo.github.io/embed/" target="_blank"><code>embed</code></a>.</p>
<p><img border="0" src="https://i2.wp.com/www.win-vector.com/blog/wp-content/uploads/2018/08/NewImage-1.png?resize=243%2C300" alt="NewImage" width="243" title="NewImage.png" data-recalc-dims="1" height="300"></p>
<p><img border="0" src="https://i0.wp.com/www.win-vector.com/blog/wp-content/uploads/2018/08/NewImage-2.png?resize=299%2C185" alt="NewImage" width="299" title="NewImage.png" data-recalc-dims="1" height="185"></p>
<p>Users currently (with some luck) discover packages like ours and then (because they trust <code>CRAN</code>) feel able to try them. With popular walled gardens that becomes much less likely. It is one thing for a standard package to duplicate another package (it is actually hard to avoid, and how work legitimately competes), it is quite another for a big-brand meta-package to pre-pick winners (and losers).</p>
<p>All I can say is: please give <a rel="nofollow" href="https://github.com/WinVector/vtreat" target="_blank"><code>vtreat</code></a> a chance and a try. It is a package for preparing messy real-world data for predictive modeling. In addition to re-coding high cardinality categorical variables (into what we call effect-codes after Cohen, or impact-codes), it deals with missing values, can be parallelized, can be run on databases, and has years of production experience baked in.</p>
<p>Some places to start with <code>vtreat</code>:</p>
<ul>
<li><a rel="nofollow" href="https://winvector.github.io/vtreat/" target="_blank">Introduction to <code>vtreat</code></a></li>
<li><a rel="nofollow" href="https://github.com/WinVector/vtreat/blob/master/extras/vtreat.pdf" target="_blank">Working paper</a></li>
<li><a rel="nofollow" href="http://www.win-vector.com/blog/2017/09/custom-level-coding-in-vtreat/" target="_blank">Pooled estimators in <code>vtreat</code></a></li>
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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/2018/08/meta-packages-nails-in-crans-coffin/"> R – Win-Vector Blog</a></strong>.</div>
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