Blog Archives

52 Vis Week 1 Winners!

April 13, 2016
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52 Vis Week 1 Winners!

The response to 52Vis has exceeded expectations and there have been great entries for both weeks. It’s time to award some prizes! Week 1 – Send in the Drones I’ll take this week in comment submission order (remember, the rules changed to submission via PR in Week 2). NOTE: WordPress seems to have “eaten” the... Continue reading →

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Beating lollipops into dumbbells

April 12, 2016
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Beating lollipops into dumbbells

Shortly after I added lollipop charts to ggalt I had a few requests for a dumbbell geom. It wasn’t difficult to do modify the underlying lollipop Geoms to make a geom_dumbbell(). Here it is in action: library(ggplot2) library(ggalt) # devtools::install_github("hrbrmstr/ggalt") library(dplyr)   # from: https://plot.ly/r/dumbbell-plots/ URL <- "https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv" fil <- basename(URL) if (!file.exists(fil)) download.file(URL, fil)... Continue reading →

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Clandestine DNS lookups with gdns

April 10, 2016
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Clandestine DNS lookups with gdns

Google recently announced their DNS-over-HTTPS API, which “enhances privacy and security between a client and a recursive resolver, and complements DNSSEC to provide end-to-end authenticated DNS lookups”. The REST API they provided was pretty simple to wrap into a package and I tossed in some SPF functions that I had lying around to bulk it... Continue reading →

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geom_lollipop() by the Chartettes

April 8, 2016
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geom_lollipop() by the Chartettes

I make a fair share of bar charts throughout the day and really like switching to lollipop charts to mix things up a bit and enhance the visual appeal. They’re easy to do in ggplot2, just use your traditional x & y mapping for geom_point() and then use (you probably want to call this first,

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52Vis Week 2 (2016 Week #14) – Honing in on the Homeless

April 6, 2016
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52Vis Week 2 (2016 Week #14) – Honing in on the Homeless

Why 52Vis? In case folks are wondering why I’m doing this, it’s pretty simple. We need a society that has high data literacy and we need folks who are capable of making awesome, truthful data visualizations. The only way to do that is by working with data over, and over, and over, and over again.

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iptools 0.4.0 released into the wild (i.e. is hitting the CRAN mirrors today)

April 4, 2016
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The iptools package—a toolkit for manipulating, validating and testing IP addresses and ranges, along with datasets relating to IP addresses—is flying through the internets and hitting a CRAN mirror near you, soon. What’s fixed? Tim Smith fixed a bug in ip_in_range() that occurred when the netmask was /32 (thanks, Tim!). What’s new? The range_boundaries() function

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Introducing a Weekly R / Python / JS / etc Vis Challenge!

March 30, 2016
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Introducing a Weekly R / Python / JS / etc Vis Challenge!

Per a suggestion, I’m going to try to find a neat data set (prbly one from @jsvine) to feature each week and toss up some sample code (99% of the time prbly in R) and offer up a vis challenge. Just reply in the comments with a link to a gist/repo/rpub/blog/etc (or post directly, though

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Easier Composite U.S. Choropleths with albersusa

March 29, 2016
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Easier Composite U.S. Choropleths with albersusa

Folks who’ve been tracking this blog on R-bloggers probably remember this post where I showed how to create a composite U.S. map with an Albers projection (which is commonly referred to as AlbersUSA these days thanks to D3). I’m not sure why I didn’t think of this earlier, but you don’t need to do those

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Nuclear Animations in R

March 26, 2016
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@jsvine (Data Editor at BuzzFeed) cleaned up and posted a data sets of historical nuclear explosions earlier this week. I used it to show a few plotting examples in class, but it’s also a really fun data set to play around with: categorial countries; time series; lat/long pairs; and, of course, nuclear explosions! My previous

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Using ProPublica “statefaces” in ggplot2

March 19, 2016
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Using ProPublica “statefaces” in ggplot2

I’m a huge fan of ProPublica. They have a super-savvy tech team, great reporters, awesome graphics folks and excel at data-driven journalism. Plus, they give away virtually everything, including data, text, graphics & tools. I was reading @USATODAY’s piece on lead levels in drinking water across America and saw they had a mini-interactive piece included

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