A few key practices for data preprocessing leveraging the tidyverse, more amazing wins with open source to process high-dimensional USDA geospatial data sets, and an infinitely fascinating look at how recursion and infinite data structures can be used in your R adventures. Episode Links <ul> <li>This week&#39;s curator: Jon Carroll - <a href="https://twitter.com/carroll_jono" rel="nofollow">@carroll_jono</a> (Twitter) &amp; <a href="https://fosstodon.org/@jonocarroll" rel="nofollow">@jonocarroll@fosstodon.org</a> (Mastodon)</li> <li><a href="https://www.jumpingrivers.com/blog/best-practices-data-cleaning-r/" rel="nofollow">Best Practices for Data Cleaning and Preprocessing</a></li> <li><a href="https://blog.ketchbrookanalytics.com/posts/2023-08-09-geoparquet-for-usda-crop-maps/geoparquet-for-usda-crop-maps" rel="nofollow">Analyzing new USDA data using open source tools</a></li> <li><a href="https://jcarroll.com.au/2023/08/18/taking-from-infinite-sequences/" rel="nofollow">Taking from Infinite Sequences</a>+ Entire issue available at <a href="https://rweekly.org/2023-WXX.html" rel="nofollow">rweekly.org/2023-WXX</a></li> </ul> Supplement Resources <ul> <li>janitor package by Sam Firke <a href="https://sfirke.github.io/janitor" rel="nofollow">https://sfirke.github.io/janitor</a> </li> <li>CRAN task view on missing data <a href="https://cran.r-project.org/web/views/MissingData.html" rel="nofollow">https://cran.r-project.org/web/views/MissingData.html</a></li> <li>Tidy modeling with R <a href="https://www.tmwr.org/" rel="nofollow">https://www.tmwr.org/</a></li> </ul> Supporting the show <ul> <li>Use the contact page at <a href="https://rweekly.fireside.fm/contact" rel="nofollow">https://rweekly.fireside.fm/contact</a> to send us your feedback</li> <li><a href="https://podcastindex.org/podcast/1062040" rel="nofollow">R-Weekly Highlights on the Podcastindex.org</a> - You can send a boost into the show directly in the Podcast Index. First, top-up with <a href="https://getalby.com/" rel="nofollow">Alby</a>, and then head over to the R-Weekly Highlights podcast entry on the index.</li> <li>A new way to think about value: <a href="https://value4value.info" rel="nofollow">https://value4value.info</a> </li> <li>Get in touch with us on social media <ul> <li>Eric Nantz: <a href="https://twitter.com/theRcast" rel="nofollow">@theRcast</a> (Twitter) and <a href="https://podcastindex.social/@rpodcast" rel="nofollow">@rpodcast@podcastindex.social</a> (Mastodon)</li> <li>Mike Thomas: <a href="https://twitter.com/mike_ketchbrook" rel="nofollow">@mike_ketchbrook</a> (Twitter) and <a href="https://fosstodon.org/@mike_thomas" rel="nofollow">@mike_thomas@fosstodon.org</a> (Mastodon)</li> </ul></li> </ul>

Eric Nantz

The R Weekly podcast offers a quick description of the latest highlighted stories and other stories from the latest R Weekly issue, as curated by the R Weekly team and R community.

Issue 2026-W19 Highlights

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A few key practices for data preprocessing leveraging the tidyverse, more amazing wins with open source to process high-dimensional USDA geospatial data sets, and an infinitely fascinating look at how recursion and infinite data structures can be used in your R adventures.