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Summarizing rstudio::conf 2019 Summaries with Tidy Text Techniques

January 26, 2019
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Summarizing rstudio::conf 2019 Summaries with Tidy Text Techniques

To be honest, I planned on writing a review of this past weekend’s rstudio::conf 2019, but several other people have already done a great job of doing that—just check out Karl Broman’s aggregation of reviews at the bottom of the page here! (More on this in a second.) In short, my thoughts on the whole experience are captured perfectly by Nick Strayer’s tweet the day after...

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A Newbie’s Guide to Making A Pull Request (for an R package)

January 19, 2019
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A Newbie’s Guide to Making A Pull Request (for an R package)

I had the wonderful opportunity to participate in the {tidyverse} Developer Day the day after rstudio::conf2019 officially wrapped up. 1One of the objectives of the event was to encourage open-source contributor newbies (like me 😄) to gain some experience, namely through submitting pull requests to address issues with {tidyverse} packages. Having only ever worked with my own packages/repos before, I found this was to be perfect opportunity to...

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Re-creating a Voronoi-Style Map with R

December 21, 2018
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Re-creating a Voronoi-Style Map with R

Introduction I’ve written some “tutorial”-like content recently—see here, here, and here—but I’ve been lacking on ideas for “original” content since then. With that said, I thought it would to try to re-create something with R. (Not too long ago I saw that Andrew Heiss did something akin to this with Charles Minard’s well-known visualization of Napoleon’s 1812.) The focus of my re-creation here is the price contour map shown...

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Converting nested JSON to a tidy data frame with R

October 19, 2018
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In this “how-to” post, I want to detail an approach that others may find useful for converting nested (nasty!) json to a tidy (nice!) data.frame/tibble that is should be much easier to work with. 1 For this demonstration, I’ll start out by scraping National Football League (NFL) 2018 regular season week 1 score data from ESPN, which involves lots of nested data in its raw form....

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The Split-Apply-Combine Technique for Machine Learning with R

August 4, 2018
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The Split-Apply-Combine Technique for Machine Learning with R

Introduction Much discussion in the R community has revolved around the proper way to implement the “split-apply-combine”. In particular, I love the exploration of this topic in this blog post. It seems that the “preferred” approach is dplyr::group_by() + tidyr::nest() for splitting, dplyr::mutate() + purrr::map() for applying, and tidyr::unnest() for combining. Additionally, many in the community have shown implementations of the “many models” approach in {tidyverse}-style pipelines, often also using...

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Fuzzy Matching with Texas High School Academic Competition Results and SAT/ACT Scores

August 3, 2018
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Introduction As a follow-up to a previous post about correlations between Texas high school academic UIL competition scores and SAT/ACT scores, I wanted explore some of the “alternatives” to joining the two data sets—which come from different sources. In that post, I simply perform a an inner_join() using the school and city names as keys. While this decision ensures that the data integrity is “high”, there are...

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Visualizing Texas High School SAT Math Scores with Bubble Grids

July 21, 2018
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Visualizing Texas High School SAT Math Scores with Bubble Grids

Two awesome things inspired this post: {ggplot2}’s version 3.0 release on CRAN, including full support for the {sf} package and new functions geom_sf() and coord_sf(), which make plotting data from shapefiles very straightforward. Jonas Scholey’s blog post discussing the use of “bubble grid” maps as an alternative to choropleth maps, which seem to be used more prevalent. As Jonas implies, using color as a visual encoding is not always the best...

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Correlations Between Texas High School Academic Competition Results and SAT/ACT Scores

July 20, 2018
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Correlations Between Texas High School Academic Competition Results and SAT/ACT Scores

Introduction I wanted to do a follow-up on my series of posts about Texas high school University Interscholastic League (UIL) academic competitions to more closely evaluate the relationship between the school performance in those competitions with school-wide SAT) and ACT scores. For those who may not be familiar with these tests, these are the two most popular standardized tests used for college admission in the United States. In my introduction...

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An Analysis of Texas High School Academic Competition Results, Part 4 – Schools

May 19, 2018
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An Analysis of Texas High School Academic Competition Results, Part 4 – Schools

Having investigated individuals elsewhere, let’s now take a look at the schools. NOTE: Although I began the examinations of competitions and individuals by looking at volume of participation (to provide context), I’ll skip an analogous discussion here because the participation of schools is shown indirectly through those analyses.) School Scores Let’s begin by looking at some of the same metrics shown for individual students, but aggregated...

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An Analysis of Texas High School Academic Competition Results, Part 1 – Introduction

May 19, 2018
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An Analysis of Texas High School Academic Competition Results, Part 1 – Introduction

NOTE: This is part of a series of write-ups discussing my findings of Texas high school academic University Interscholastic Scholarship (UIL) competitions. To keep this and the other write-ups concise and to focus reader attention on the content, I have decided not to show the underlying code (especially that which is used to create the visuals). Nonetheless, the full code can be viewed on...

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