Blog Archives

Mid-year R Packages Update Summary

July 24, 2016
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I been updating some existing packages and github-releasing new ones (before a CRAN push). Most are “cyber”-related, but there are some general purpose ones. Here’s a quick overview: docxtractr (CRAN, now, v0.2.0) was initially designed to make it easy to get data tables out of MS Word (docx) documents. The update removes use of a... Continue reading...

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Slaying CIDR Orcs with Triebeard (a.k.a. fast trie-based ‘IPv4-in-CIDR’ lookups in R)

July 12, 2016
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The insanely productive elf-lord, @quominus put together a small package (triebeard) that exposes an API for radix/prefix tries at both the R and Rcpp levels. I know he had some personal needs for this and we both kinda need these to augment some functions in our iptools package. Despite triebeard having both a vignette and... Continue reading →

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CRAN Packages on GitHub (and some CRAN DESCRIPTION observations)

July 10, 2016
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Just about a week ago @thosjleeper posited something on twitter w/r/t how many CRAN packages had associations with GitHub (i.e. how many used GitHub for development). The DESCRIPTION file (that comes with all R packages) has some fields that can house this information and most folks who do use GitHub for development of R seem... Continue reading →

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Bridging The Political [Polygons] Gap with ggplot2

July 7, 2016
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Bridging The Political [Polygons] Gap with ggplot2

The @pewresearch folks have been collecting political survey data for quite a while, and I noticed the visualization below referenced in a Tableau vis contest entry: Those are filled frequency polygons, which are super-easy to replicate in ggplot2, especially since Pew even kind of made the data available via their interactive visualization (it’s available in... Continue reading →

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A Simple Prediction Web Service Using the New fiery Package

July 5, 2016
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fiery is a new Rook/httuv-based R web server in town created by @thomasp85 that aims to fill the gap between raw http & websockets and Shiny with a flexible framework for handling requests and serving up responses. The intent of this post is to provide a quick-start to using it setup a prediction API service.... Continue reading →

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Making “Time Rivers” in R

June 28, 2016
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Making “Time Rivers” in R

Once again, @albertocairo notices an interesting chart and spurs pondering in the visualization community with his post covering an unusual “vertical time series” chart produced for the print version of the NYTimes: I’m actually less concerned about the vertical time series chart component here since I agree with TAVE* Cairo that folks are smart enough... Continue reading →

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A Call to Arms[list] Data Analysis!

June 19, 2016
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A Call to Arms[list] Data Analysis!

The NPR vis team contributed to a recent story about Armslist, a “craigslist for guns”. Now, I’m neither pro-“gun” or anti-“gun” since this subject, like most heated ones, has more than two sides. What I am is pro-data, and the U.S. Congress is so deep in the pockets of the NRA that there’s no way... Continue reading →

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Your data vis “Spidey-sense” & the need for a robust “utility belt”

June 16, 2016
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Your data vis “Spidey-sense” & the need for a robust “utility belt”

@theboysmithy did a great piece on coming up with an alternate view for a timeline for an FT piece. Here’s an excerpt (read the whole piece, though, it’s worth it): Here is an example from a story recently featured in the FT: emerging- market populations are expected to age more rapidly than those in developed... Continue reading →

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On Whether Y-axis Labels Are Always Necessary

June 12, 2016
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On Whether Y-axis Labels Are Always Necessary

The infamous @albertocairo blogged about a nice interactive piece on German company tax avoidance by @ProPublica. Here’s a snapshot of their interactive chart: Dr. Cairo (his PhD is in the bag as far as I’m concerned :-) posited: Isn’t it weird that the chart doesn’t have a scale on the Y-axis? It’s not the first... Continue reading →

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Global Temperature Change in R & D3 (without the vertigo)

May 14, 2016
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Global Temperature Change in R & D3 (without the vertigo)

This made the rounds on social media last week: Spiraling global temperatures from 1850-2016 (full animation) https://t.co/YETC5HkmTr pic.twitter.com/Ypci717AHq— Ed Hawkins (@ed_hawkins) May 9, 2016 One of the original versions was static and was not nearly as popular, but—as you can see—this one went viral. Despite the public’s infatuation with circles (I’m lookin’ at you, pie... Continue reading →

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