<p><div><div><div><div data-width="100" data-show-faces="false" data-send="true" data-layout="button_count" data-height="21" data-href="https://www.r-bloggers.com/rstudio-conference-2017-recap/"></div></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="http://www.gettinggeneticsdone.com/2017/01/rstudio-conference-2017-recap.html"> Getting Genetics Done</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<div data-md-url="https://www.blogger.com/blogger.g?blogID=6232819486261696035#editor/&gt;
&lt;div style=">The first ever <a target="_blank" rel="nofollow" href="https://www.rstudio.com/conference/">RStudio conference</a> was held January 11-14, 2017 in Orlando, FL. For anyone else like me who spends hours each working day staring into an RStudio session, the conference was truly <em>excellent</em>. The <a target="_blank" rel="nofollow" href="https://www.rstudio.com/conference/#speakers">speaker lineup</a> was diverse and covered lots of areas related to development in R, including the tidyverse, the RStudio IDE, Shiny, htmlwidgets, and authoring with RMarkdown. </div>
<div>This is <em>not</em> a complete list by any means — with split sessions I could only go to half the talks at most. Here are some noncomprehensive notes and links to slides and resources for some of the awesome things are doing with R and RStudio that I learned about at the RStudio Conference.</div>
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<div><strong>Hadley Wickham</strong> kicked off the meeting with a keynote on <strong>doing data science in R</strong>. The talk focused on the <strong><a target="_blank" rel="nofollow" href="http://tidyverse.org/">tidyverse</a></strong>, and the notion of splitting functions into <em>commands</em> that <em>do something</em>, as compared to <em>queries</em> that <em>calculate something</em>, and how it’s generally a good idea to keep these different functionalties contained in their own separate functions. (Contrast this to things like <code>lm</code> that both computes values and does things, like printing those values to the screen, making it difficult to capture (see <a target="_blank" rel="nofollow" href="https://cran.r-project.org/web/packages/broom/index.html">broom</a>). </div>
<div>I asked Hadley after his talk about strategies to reduce issues getting Bioconductor data structures to play nicely with tidyverse tools. Within minutes <strong><a target="_blank" rel="nofollow" href="https://twitter.com/drob">David Robinson</a></strong> released a new feature in the <strong><a target="_blank" rel="nofollow" href="https://github.com/dgrtwo/fuzzyjoin">fuzzyjoin package</a></strong> that leverages IRanges within this tidyverse-friendly package for efficiently doing things like joining on genomic intervals.</div>
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<blockquote data-cards="hidden" data-conversation="none" class="twitter-tweet" data-partner="tweetdeck"><div dir="ltr" lang="en">Another <a target="_blank" rel="nofollow" href="https://twitter.com/hashtag/rstudioconf?src=hash">#rstudioconf</a>-inspired addition to fuzzyjoin:
<p>genome_join, for overlapping intervals on the same chromosome<a target="_blank" rel="nofollow" href="https://twitter.com/genetics_blog">@genetics_blog</a> <a target="_blank" rel="nofollow" href="https://twitter.com/hashtag/rstats?src=hash">#rstats</a> <a target="_blank" rel="nofollow" href="https://t.co/oUctyNYc09">pic.twitter.com/oUctyNYc09</a></div>
<p>— David Robinson (@drob) <a target="_blank" rel="nofollow" href="https://twitter.com/drob/status/820054313909284865">January 13, 2017</a></p></blockquote>
<div></div>
<div><strong><a target="_blank" rel="nofollow" href="https://twitter.com/CVWickham/">Charlotte Wickham’s</a></strong> 2-hour <strong>purrr tutorial</strong> was awesome. <a target="_blank" rel="nofollow" href="http://bit.ly/purrr-rstudioconf">Here’s a link</a> to a shared dropbox folder with code, challenges, slides, data, etc. The <a target="_blank" rel="nofollow" href="https://github.com/hadley/purrr#readme">purrr package</a> is a core package in the tidyverse, and I’ll be replacing many of the base <code>?apply</code> and plyr <code>??ply</code> functions that I still use here and there. The <code>map_*</code> functions are integral to working with nested list-columns in dplyr, and I think I’m finally starting to grok how to work with these.</div>
<div><strong><a target="_blank" rel="nofollow" href="https://twitter.com/JennyBryan">Jenny Bryan</a></strong> gave a great talk on <strong>list columns</strong>. You can see her <a target="_blank" rel="nofollow" href="https://speakerdeck.com/jennybc/putting-square-pegs-in-round-holes-using-list-cols-in-your-dataframe">slides here</a>. Jenny also put together <a target="_blank" rel="nofollow" href="https://jennybc.github.io/purrr-tutorial/">this excellent tutorial</a> with lots of worked examples and code snippets. And if you need some example list data structures for more practice or for teaching that aren’t foo/bar/iris/mtcars-level boring, see her <a target="_blank" rel="nofollow" href="https://github.com/jennybc/repurrrsive">repurrrsive package</a>. Related to this, for more on list columns and purrr map functions, start reading at the <a target="_blank" rel="nofollow" href="http://r4ds.had.co.nz/many-models.html">“Many Models” section of Hadley’s <em>R for Data Science</em> book</a>.</div>
<div><strong><a target="_blank" rel="nofollow" href="https://twitter.com/juliasilge">Julia Silge</a></strong>, data scientist at Stack Overflow, gave a great introduction to tidy text mining with R. You can read Julia and David’s <a target="_blank" rel="nofollow" href="http://tidytextmining.com/"><em>Tidy Text Mining with R</em> book here online</a> (the book was authored in Rmarkdown using bookdown!).</div>
<div><strong><a target="_blank" rel="nofollow" href="https://twitter.com/andrewflowers">Andrew Flowers</a></strong>, data journalist and former <a target="_blank" rel="nofollow" href="https://fivethirtyeight.com/contributors/andrew-flowers/">writer at FiveThirtyEight</a> gave the second day’s keynote address on finding and telling stories using R. He gave a series of examples illustrating six motivating features that make data stories worth telling, along with potential danger inherent to each one:</div>
<ol>
<li>Novelty <em>(potential danger: triviality)</em></li>
<li>Outlier <em>(spurious result; see also, p-hacking)</em></li>
<li>Archetype <em>(oversimplification)</em></li>
<li>Trend <em>(variance)</em></li>
<li>Debunking <em>(confirmation bias)</em></li>
<li>Forecast <em>(overfitting)</em></li>
</ol>
<div><strong><a target="_blank" rel="nofollow" href="https://www.blogger.com/blogger.g?blogID=6232819486261696035">Yihui Xie</a></strong> led a two-hour tutorial on <strong>advanced RMarkdown</strong>. You can see his <a target="_blank" rel="nofollow" href="https://slides.yihui.name/2017-rstudio-conf-rmarkdown-Yihui-Xie.html">slides here</a>. The <a target="_blank" rel="nofollow" href="https://github.com/rstudio/rticles">rticles package</a> has LaTeX Journal Article Templates for R Markdown for various journals. The <a target="_blank" rel="nofollow" href="https://github.com/rstudio/tufte">tufte package</a> now supports both PDF and HTML output. See an <a target="_blank" rel="nofollow" href="http://rstudio.github.io/tufte/">example here</a>. Yihui’s <a target="_blank" rel="nofollow" href="https://github.com/yihui/xaringan">xaringan package</a> ports the <a target="_blank" rel="nofollow" href="https://remarkjs.com/">remark.js</a> library for slideshows into R. Careful. Yihui warns that you may not sleep after learning about how cool remark.js is. Yihui showed an early version of the in-development <a target="_blank" rel="nofollow" href="https://github.com/rstudio/blogdown">blogdown package</a> that can build blog-aware static websites using the blazing-fast and well-documented <a target="_blank" rel="nofollow" href="http://gohugo.io/">Hugo</a> static site generator. Finally, the <strong><a target="_blank" rel="nofollow" href="https://github.com/rstudio/bookdown">bookdown package</a></strong> is just awesome. It takes multiple RMarkdown documents as input and renders into multiple output formats (screen-readable ebook, PDF, epub, etc.). It looks great for writing books and technical documentation with pushbutton publishing to multiple output formats with some nice built-in styles out of the box. Some examples:</div>
<ul>
<li><a target="_blank" rel="nofollow" href="https://bookdown.org/yihui/bookdown/">bookdown.org/yihui/bookdown</a> — The bookdown book, written in RMarkdown with bookdown. <em>(whoa, meta)</em></li>
<li><a target="_blank" rel="nofollow" href="http://r4ds.had.co.nz/">r4ds.had.co.nz</a> — Garrett Grolemund and Hadley Wickham’s <em>R for Data Science</em> book.</li>
<li><a target="_blank" rel="nofollow" href="http://tidytextmining.com/">tidytextmining.com</a> — Julia and David’s book on text mining</li>
<li><a target="_blank" rel="nofollow" href="http://moderndive.com/">moderndive.com</a> — an open-source introductory statistics class textbook</li>
</ul>
<div>Finally, a few gems from other talks that I jotted down:</div>
<ul>
<li><strong><a target="_blank" rel="nofollow" href="https://twitter.com/old_man_chester">Chester Ismay</a></strong> gave a great talk on teaching introductory statistics using R, with the <a target="_blank" rel="nofollow" href="http://moderndive.com/">open-source course textbook</a> written in RMarkdown using bookdown.</li>
<li><strong><a target="_blank" rel="nofollow" href="https://twitter.com/hrbrmstr">Bob Rudis</a></strong> talked about using pipes (<code>%>%</code>), and pipes within pipes, and best piping practices. See his <a target="_blank" rel="nofollow" href="https://twitter.com/hrbrmstr">slides here</a>.</li>
<li><strong><a target="_blank" rel="nofollow" href="https://twitter.com/hspter">Hilary Parker</a></strong> talked about the idea of an <em>analysis development</em>, (and analysis developers), drawing similarities to software development/developers. Hilary discussed this once before on the excellent <a target="_blank" rel="nofollow" href="https://soundcloud.com/nssd-podcast">podcast</a> that she and Roger Peng host, and you can probably find it in their <em><a target="_blank" rel="nofollow" href="https://leanpub.com/conversationsondatascience/">Conversations On Data Science</a></em> ebook that summarize and transcribe these conversations.</li>
<li><strong><a target="_blank" rel="nofollow" href="https://twitter.com/drsimonj">Simon Jackson</a></strong> introduced <strong><a target="_blank" rel="nofollow" href="https://cran.r-project.org/web/packages/corrr/vignettes/using-corrr.html">corrr package</a></strong> for exploring and manipulating correlations and correlation matrices in a tidy way.</li>
<li><strong><a target="_blank" rel="nofollow" href="https://twitter.com/gshotwell">Gordon Shotwell</a></strong> introduced the <strong><a target="_blank" rel="nofollow" href="https://github.com/GShotwell/easyMake">easymake</a></strong> package that generates Makefiles from a data frame using R.</li>
<li><strong><a target="_blank" rel="nofollow" href="https://twitter.com/_inundata">Karthik Ram</a></strong> quickly introduced several of the (many) <strong><a target="_blank" rel="nofollow" href="https://ropensci.org/packages/">rOpenSci packages</a></strong> related to data publication, data access, scientific literature access, scalable &amp; reproducible computing, databases, visualization, taxonomy, geospatial analysis, and many utility tools for data analysis and manipulation.</li>
</ul>
<hr>
<div>With split sessions I missed more than half the talks. Lots of people here are active on Twitter, and you can catch many more notes and tidbits on the <a target="_blank" rel="nofollow" href="https://twitter.com/search?q=%23rstudioconf">#rstudioconf</a> hashtag. The meeting was superbly organized, I learned a ton, and I enjoyed meeting in person many of the folks I follow on Twitter and elsewhere online. A few days of 80-degree weather in mid-January didn’t hurt either. I’ll definitely be coming again next year. Kudos to the rstudio::conf organizers and speakers!</div>
<div>All the talks were recorded and will supposedly find their way to <a target="_blank" rel="nofollow" href="https://www.rstudio.com/">rstudio.com</a> at some point soon. I’ll update this post with a link when that happens.</div>
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<div>Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.</div>
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