Happy New Year to one and all! As data scientists/analysts/researchers/programmers/anything else on that crazy data science Venn diagram, I’m assuming all of our new years resolutions involve visualising our data with more sophistication and finesse. So with that in mind, I thought it was high time for a post about the joys of modularizing your shiny app code.

New Year, new improved workflows with emphasis on efficiency & reproducibility, amiright?
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There’s been some great animated maps in the data viz world of late. Most notably this stunner by John Muyskens for the Washington Post, showing the diverted flight paths of planes getting themselves into the line of the recent solar eclipse. What’s more it was made with R and ggplot2! Have a look here: Hundreds of aircraft flocked to the moon’s shadow during Monday’s eclipse. Animation by @JohnMuyskens Data courtesy of @flightradar24 pic.
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Background I really liked this blogpost by Peter Ellis that was recently brought to my attention by everyone’s favourite #rstats tweeter, Mara Averick: ???? code-through: “Inter-country inequality and the World Development Indicators” by @ellis2013nz https://t.co/zIjgqjPqKc #rstats #dataviz pic.twitter.com/h1sUfO2PPJ — Mara Averick (@dataandme) July 22, 2017 In the post, Peter recreates some of the charts from Branko Milanovic’s highly acclaimed book ‘Global Inequality: A New Approach for the Age of Globalization’ using World Development Indicator data from the World Bank.
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TL;DR If you’re looking for a tool to scrape all the posts in facebook page/group with a link and have the data presented to you in a searchable, filterable table then check out the shiny app I made for this purpose by clicking on the image below (very niche market, I know).

If however, that’s not why you’re here, and would like to look at some interesting ways of visualising social media data (or any kind of events over time data), please read on.
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UPDATE: We’ve just done an update to this tutorial on our new blog using R Spatial’s new simple features package! It’s a much nicer workflow than the one below so head over to Multivariate Dot-Denisty Maps in R with sf and ggplot2 now to check it out. Cheers! Background I recently came across Eric Fisher’s brilliant collection of dot density maps that show racial and ethnic divisions within US cities.
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CULTURE OF INSIGHT

Data Consultancy

London