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(This article was first published on <strong><a href="http://www.win-vector.com/blog/2018/07/john-mount-speaking-on-rquery-and-rqdatatable/"> R – Win-Vector Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p><a rel="nofollow" href="https://github.com/WinVector/rquery" target="_blank"><code>rquery</code></a> and <a rel="nofollow" href="https://github.com/WinVector/rqdatatable" target="_blank"><code>rqdatatable</code></a> are new <a rel="nofollow" href="https://www.r-project.org/" target="_blank"><code>R</code></a> packages for data wrangling; either at scale (in databases, or big data systems such as Apache Spark), or in-memory. The speed up both execution (through optimizations) and development (though a good mental model and up-front error checking) for data wrangling tasks.</p>
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<a rel="nofollow" href="https://github.com/WinVector/rquery" target="_blank"><img border="0" alt="Rquery" title="rquery.jpg" src="https://i1.wp.com/www.win-vector.com/blog/wp-content/uploads/2018/07/rquery.jpg?w=250" data-recalc-dims="1"></a><br>
<a rel="nofollow" href="https://github.com/WinVector/rqdatatable" target="_blank"><img border="0" alt="Rqdatatable" title="rqdatatable.png" src="https://i0.wp.com/www.win-vector.com/blog/wp-content/uploads/2018/07/rqdatatable.png?w=250" data-recalc-dims="1"></a><br>
</center></p>
<p><a rel="nofollow" href="http://www.win-vector.com/site/" target="_blank">Win-Vector LLC</a>‘s <a rel="nofollow" href="http://www.win-vector.com/site/staff/john-mount/" target="_blank">John Mount</a> will be speaking on the <a rel="nofollow" href="https://github.com/WinVector/rquery" target="_blank"><code>rquery</code></a> and <a rel="nofollow" href="https://github.com/WinVector/rqdatatable" target="_blank"><code>rqdatatable</code></a> packages at the <a rel="nofollow" href="https://www.meetup.com/r-enthusiasts/events/251390661/" target="_blank">The East Bay R Language Beginners Group Tuesday, August 7, 2018 (Oakland, CA)</a>.</p>
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<p>One may ask: “why share new packages with an “R Language Beginners Group?” (Though, I prefer to use the term <a rel="nofollow" href="http://www.win-vector.com/blog/tag/part-time-r-user/" target="_blank">“part time R user”</a>.) Because: such packages can give such users easy, safe, consistent, and performant access to powerful data systems. <code>rquery</code> establishes a notation and links to external data providers such as PostgreSQL, Amazon Redshift, and Apache Spark. <code>rqdatatable</code> supplies an additional in-memory implementation of the <code>rquery</code> notation using the powerful <a rel="nofollow" href="https://cran.r-project.org/package=data.table" target="_blank"><code>data.table</code></a> package.</p>
<p><code>rquery</code> and <code>rqdatatable</code> can, <em>if</em> given a fair chance, be significant <code>R</code> tools. Users <strong>are</strong> that chance.</p>
<p>If you are around please come see the talk.</p>
<p>Some earlier articles on <code>rquery</code> and <code>rqdatatable</code> can be found <a rel="nofollow" href="http://www.win-vector.com/blog/2018/01/rquery-fast-data-manipulation-in-r/" target="_blank">here</a> and <a rel="nofollow" href="http://www.win-vector.com/blog/2018/07/speed-up-your-r-work/" target="_blank">here</a>.</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/2018/07/john-mount-speaking-on-rquery-and-rqdatatable/"> R – Win-Vector Blog</a></strong>.</div>
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