I’m very pleased to announce the release of ggplot2 2.1.0, scales 0.4.0, and gtable 0.2.0. These are set of relatively minor updates that fix a whole bunch of little problems that crept in during the last big update. The most important changes are described below. When mapping an aesthetic to a constant the default guide
This post comes hot off the heels of the nigh-feature-complete release of vegalite (virtually all the components of Vega-Lite are now implemented and just need real-world user testing). I’ve had a few and seen a few questions about “why Vega-Lite”? I think my previous post gave some good answers to “why”. However, Vega-Lite and Vega
Recently, Jeff Leek at Simply Statistics discussed why he does not use ggplot2. He notes “The bottom line is for production graphics, any system requires work.” and describes a default plot that needs some work: To break down what is going on, here is what R interprets (more or less): Make a container for data
We were doing some exploratory data analysis on some attacker data at work and one of the things I was interested is what were “working hours” by country. Now, I don’t put a great deal of faith in the precision of geolocated IP addresses since every geolocation database that exists thinks I live in Vermont
If you’ve read my blog, taken one of my classes, or sat next to me on an airplane, you probably know I’m a big fan of Hadley Wickham’s ggplot2 package, especially compared to base R plotting.
Not everyone agrees. Among the anti-ggplot2 crowd is JHU Professor Jeff Leek, who yesterday wrote up his thoughts on the Simply Statistics...
High resolution and SVG versions of the new R logo are finally available. I converted the SVG to WKT (file here) which means we can use it like we would a shapefile in R. That includes plotting! Here’s a short example of how to read that WKT and plot the logo using ggplot2: library(sp) library(maptools)
Learn how to produce meaningful and beautiful data visualizations with DataCamp’s ggplot2 course series. Be introduced to the principles of good visualizations and the grammar of graphics plotting concept implemented in the ggplot2 package. Learn yourself how to make complex exploratory plots, and be able to make a custom plotting function to explore a large data set, combining...
In a post a few months ago I built a new ggplot2 statistical transformation (“stat”) to provide X13-SEATS-ARIMA seasonal adjustment on the fly. With certain exploratory workflows this can be useful, saving on a step of seasonally adjusting many different slices and dices of a multi-dimensional time series during data reshaping, and just drawing it for you...
Introduction The purpose of this blog post is to inform R users of a website that I created to track and list ggplot2 extensions. The site is available at: http://ggplot2-exts.github.io. The purpose of this site is to help other R users easily find ggplot2 extensions that are coming in “fast and furious” from the R community. If you