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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/11/strings-in-r.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>The RStudio team has created another very useful <a rel="nofollow" href="https://www.rstudio.com/resources/cheatsheets/" target="_blank">cheat sheet for R</a>: <em>Working with Strings</em>. This cheat sheet provides an example-laden menu of operations you can perform on strings (character verctors) in R using the <a rel="nofollow" href="https://github.com/tidyverse/stringr#stringr-" target="_blank">stringr package</a>. While base R provides a solid set of string manipulation functions, the stringr package functions are simpler, more consistent (making them easy to use with the pipe operator), and more like the Ruby or Python way of handling string operations.</p>
<p>The back page of the cheat sheet also provides a handy guide to regular expressions a useful (if often frustrating) tool for extracting substrings according to a pattern you define with codes like these:</p>
<p><a rel="nofollow" href="https://github.com/rstudio/cheatsheets/raw/master/strings.pdf" target="_blank"><img border="0" alt="Stringr" title="Stringr" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01bb09d38b76970d-800wi"></a></p>
<p>You can pick up the <em>Working with Strings</em> cheat sheet, and others from the series, at the link below.</p>
<p>RStudio: <a rel="nofollow" href="https://www.rstudio.com/resources/cheatsheets/" target="_blank">Cheat Sheets</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://blog.revolutionanalytics.com/2017/11/strings-in-r.html"> Revolutions</a></strong>.</div>
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