http://www.simplyapproximate.com/categories/r/ Recent content in R on Simply Approximate Hugo -- gohugo.io en-us Fri, 08 Jun 2018 00:00:00 +0000 http://www.simplyapproximate.com/posts/sods18-lesson-plan/ Fri, 08 Jun 2018 00:00:00 +0000 http://www.simplyapproximate.com/posts/sods18-lesson-plan/ The goal of week 2 of #SoDS18 is to narrow down all of the plans made during the brainstorming sessions from week 1 and plan out how to accomplish those goals. I’ve decided to narrow it down to three main goals to be completed over the 3 months of #SoDS18. These goals are: Build an R Shiny app/dashboard Complete a machine learning competition (and implement multiple models) Learn about deep learning and implement a deep learning model I've got my week 2 plan for #SoDS18 done! http://www.simplyapproximate.com/posts/what-makes-a-good-r-vignette/ Wed, 18 Apr 2018 00:00:00 +0000 http://www.simplyapproximate.com/posts/what-makes-a-good-r-vignette/ A month ago I asked the #rstats community on Twitter what their favorite package vignette was. While working on a “getting started” vignette myself I realized that I wanted to increase the number of examples I could reference. After not getting much in the way of responses, I thought it would be a great time to put together my own list of favorite R package vignettes. As described by Hadley Wickham in R Packages: http://www.simplyapproximate.com/posts/towards-reproducible-research/ Tue, 09 Jan 2018 00:00:00 +0000 http://www.simplyapproximate.com/posts/towards-reproducible-research/ In December, I came across a guide to reproducible code in ecology and evolution published by the British Ecological Society. While my background is in physics research, I think the guide is incredibly useful for scientists of all disciplines. Reading through this guide also got me thinking about reproducibility in general and my own journey towards creating reproducible research. The British Ecological Society’s guide comes at a time when researchers across the various scientific disciplines are discussing the importance of reproducibility. http://www.simplyapproximate.com/posts/playing-with-the-xray-package/ Tue, 02 Jan 2018 00:00:00 +0000 http://www.simplyapproximate.com/posts/playing-with-the-xray-package/ After seeing an announcement about it on R-Bloggers, I decided to test out the new xray package using the Titanic data set. The xray package provides a few functions for quickly getting a summary of anomalies and distributions of the variables in a data set. For anomalies, the anomalies() function outputs the number and percentage of NA’s, zeroes, empty strings, and infinities while also giving some useful information about distinct observations and variable class. http://www.simplyapproximate.com/posts/how-i-started-using-computational-essays-on-accident/ Tue, 05 Dec 2017 00:00:00 +0000 http://www.simplyapproximate.com/posts/how-i-started-using-computational-essays-on-accident/ Recently, I came across a blog post by Tony Hirst on computational essays and how they can be used to facilitate learning. Hirst was reflecting on an earlier blog post by Stephen Wolfram on what defines a computational essay. Computational essays are, as paraphrased from Hirst and Wolfram, a mixture of plain language, computer input, and computer output allowing the user to interweave narrative with code and the output from that code. http://www.simplyapproximate.com/posts/datacamp-r-courses/ Mon, 20 Nov 2017 00:00:00 +0000 http://www.simplyapproximate.com/posts/datacamp-r-courses/ Back in September I finished the Data Scientist (with R) career path from DataCamp. This career path is a series of 23 online courses that start with a general introduction to R, introduce the important functions and packages for modern R usage, and give a sampling of machine learning techniques. Along the way, these courses introduce data analysis concepts that go beyond the specifics of how to code in R.