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(This article was first published on <strong><a href="http://www.win-vector.com/blog/2017/12/how-to-avoid-the-dplyr-dependency-driven-result-corruption/"> R – Win-Vector Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>In our <a rel="nofollow" href="http://www.win-vector.com/blog/2017/12/please-inspect-your-dplyrdatabase-code/" target="_blank">last article</a> we pointed out a dangerous silent result corruption we have seen when using the <a rel="nofollow" href="https://www.r-project.org/" target="_blank"><code>R</code></a> <a rel="nofollow" href="https://cran.r-project.org/package=dplyr" target="_blank"><code>dplyr</code></a> package with databases.</p>
<p>To systematically avoid this result corruption <a rel="nofollow" href="http://www.win-vector.com/blog/2017/09/my-advice-on-dplyrmutate/" target="_blank">we suggest breaking up your <code>dplyr::mutate()</code> statements to be dependency-free</a> (not assigning the same value twice, and not using any value in the same mutate it is formed). We consider these to be key and critical precautions to take when using <code>dplyr</code> with a database.</p>
<p>We would also like to point out we are also distributing <a rel="nofollow" href="https://winvector.github.io/seplyr/articles/MutatePartitioner.html" target="_blank">free tools to do this automatically</a>, and <a rel="nofollow" href="http://winvector.github.io/FluidData/DplyrDependencies.html" target="_blank">a worked example of this solution</a>.</p>
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