The holidays are upon us, and that means it’s time for best-of lists, Data@Urban included. We’ve published a blog post every two weeks since March, for a total of 22, including this one. What started as an experiment to share our behind-the-scenes work has exceeded our expectations. The number of views and shares has astonished us, and we are glad so many people find these topics as interesting as we do.
Content on Data@Urban has also expanded in ways we didn’t foresee. We assumed there would be posts on tools like Excel, JavaScript, and R. But driven by your interest and feedback, we also published content that showed you how we created new packages, new data tools, and data agreements that we are building as we help Urban conduct its in-depth, cutting-edge research.
We want to say thank you. Thank you for your interest in going behind the scenes at Urban. Thank you for visiting our blog. And thank you for providing your time and feedback. We appreciate it, and we look forward to many great posts next year. This couldn’t have been a success without you, and we hope you have a great holiday season!
Here are the top five Data@Urban posts of 2018, ranked by number of views.
1. How to Create State and County Maps Easily in R: By far our most popular, this blog post, written by Housing Finance Policy Center researcher Sarah Strochak, introduces readers to Urban’s urbnmapr R package, which allows R programmers to create state and county chloropleth (i.e., colored by value) maps easily with just a few lines of code.
2. Three Ways to Annotate Your Graphs: Our second-most-popular post, written by data visualization expert Jon Schwabish, walks readers through three tips that will help you create more effective data visualizations.
3. Fortran and Docker: How to Combine Legacy Code with Cutting-Edge Components: If your company has old code, odds are it’s written in the Fortran programming language, or something similar, like COBOL. This post, written by director of research programming Jessica Kelly, provides an introduction to using Docker to modernize the way Fortran code is run and called from other applications.
4. Why the Urban Institute Visualizes Data with ggplot2: R is the Urban Institute’s most rapidly growing programming language. In this post, Income and Benefits Policy Center researcher and R Users Group leader Aaron Williams details why Urban has adopted ggplot2 for a wide variety of data visualizations (including the state and county maps in post #1).
5. 3 Exciting Possibilities for Combining Data Science and Social Science: In this post, Chief Data Scientist Graham MacDonald describes three of the most exciting opportunities at the intersection of data science and public policy. As his thinking has evolved, he has written another post with our Chief Information Officer, Khuloud Odeh, and recorded a podcast with Odeh and Jessica Kelly with his updated thoughts on this topic.
-The Data@Urban team:
