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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/01/cran-10000.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p><a target="_blank" rel="nofollow" href="https://cran.r-project.org/">CRAN</a>, the global repository of open-source packages that extend the capabiltiies of R, reached a milestone today. There are now more than 10,000 R packages available for download*.</p>
<p>(Incidentally, that count doesn't even include all the R packages out there. There are also <a target="_blank" rel="nofollow" href="https://www.bioconductor.org/packages/release/BiocViews.html#___Software">another 1294 packages for genomic analysis in the BioConductor repository</a>, hundreds of R packages published only on GitHub, commercial R packages from vendors such as Microsoft and Oracle, and an unknowable number of private, unpublished packages.)</p>
<p>Why so many packages? R has a <em>very</em> active developer community, who contribute new packages to CRAN on a daily basis. As a result, R is unparalleled in its capabilities for statistical computing, data science, and data visualization: almost anything you might care to do with data has likely already been implemented for you and released as an R package. There are several reasons behind this:</p>
<ul>
<li>R is the <a target="_blank" rel="nofollow" href="http://blog.revolutionanalytics.com/popularity/">most popular language for data scientists</a> — <em>and</em> it's been around for almost 20 years — and so by sheer force of numbers and time, R has more extensions than any other data science software.</li>
<li>R is the primary tool used for statistical <em>research: </em>when new methods are developed, they're not just published as a paper — they're also published as an R package. That means R is always at the cutting edge of new methodologies.</li>
<li>R was <a target="_blank" rel="nofollow" href="http://blog.revolutionanalytics.com/2014/07/reflections-on-john-chambers-userr-2014-keynote-address.html">designed as an interface language</a> — a means to present a consistent language interface for algorithms written in other languages. Many packages work by providing R language bindings to other open-source software, making R a convenient hub for all kinds of algorithms and methods.</li>
<li>Last but certainly now least, the CRAN system itself is a very effective platform for sharing R extensions, with a mature system for package authoring, building, testing, and distribution. The R core team and in particular the CRAN maintainers deserve significant credit for creating such a vibrant ecosystem for R packages. </li>
</ul>
<p>Having so many packages available can be a double-edged sword though: it can take some searching to find the package you need. Luckily, there are some resources available to help you:</p>
<ul>
<li>MRAN (the Microsoft R Application Network) provides a <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/packages/">search tool for R packages on CRAN</a>. </li>
<li>To find the most popular packages, Rdocumentation.org provides a <a target="_blank" rel="nofollow" href="https://www.rdocumentation.org/trends">leaderboard</a> of packages by number of downloads. It also provides lists of newly-released and recently-updated packages.</li>
<li>CRAN provides <a target="_blank" rel="nofollow" href="https://cran.r-project.org/web/views/">package Task Views</a>, providing a directory of packages by topic area (such as <a target="_blank" rel="nofollow" href="https://cran.r-project.org/web/views/Finance.html">Finance</a> or <a target="_blank" rel="nofollow" href="https://cran.r-project.org/web/views/ClinicalTrials.html">Clinical Trials</a>). <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/taskview/">MRAN</a> and <a target="_blank" rel="nofollow" href="https://www.rdocumentation.org/taskviews">RDocumentation.org</a> also provide searchable versions based on the CRAN task views.</li>
<li>To find popular and active R packages on GitHub, see the <a target="_blank" rel="nofollow" href="https://github.com/trending/r?since=monthly">Trending R repositories</a> list.</li>
<li>For curated news on updated and new R packages, check out the <a target="_blank" rel="nofollow" href="https://www.rstudio.com/rviews/category/packages/">Package Picks</a> by Joseph Rickert on RStudio's RViews blog, and also the <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/spotlight/">Package Spotlights</a> published with each Microsoft R Open release. <a target="_blank" rel="nofollow" href="http://dirk.eddelbuettel.com/cranberries/">Cranberries</a> also provides a comprehensive uncurated feed of new and updated packages.</li>
</ul>
<p>The rate of R package growth shows no signs of abating, either. As you can see from this chart (created using <a target="_blank" rel="nofollow" href="https://gist.github.com/daroczig/3cf06d6db4be2bbe3368">this script</a> by Gergely Daróczi), the growth in R packages shows no signs of plateauing soon. (This chart includes packages released and subsequently withdrawn from CRAN, which is why it goes over 10,000.)</p>
<p><a target="_blank" rel="nofollow" href="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d2594d25970c-pi"><img title="Rpackages" alt="Rpackages" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d2594d25970c-800wi" border="0"></a></p>
<p>Know of any other resources for exploring R packages? Let us know in the comments.</p>
<p><em>*Actually, as of this writing, there are 9,999 packages on CRAN. So close! But it won't be long…</em></p>
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