Categories ▸ Visualization
ASA Section Membership and Revenues.
I taught a half-sized introductory seminar on data visualization last semester. It’s an introduction to some principles of data visualization for working social scientists, and is focused mostly on teaching people how to use ggplot effectively. I’ve made the (slightly rough-and-ready) course notes available as a website. The notes include numerous code samples, .Rmd files for every week, and there’s a GitHub repository containing all the material to build the site, including the datasets used to make the plots.
Continuing my nonremunerative career as an IT Analyst, I updated my Apple Sales plots to the most recent (end of 2015) round of quarterly data. These plots were originally inspired by Dr Drang, and the trend for the iPad (shown below) continues to confirm his views. I also took the opportunity to clean up the code a little, and to fix a small problem in the earlier versions. The x-axis of the “Remainder” panel didn’t line up properly with the line plots above and below it.
A few days ago, Matt Yglesias shared this tweet from Liz Ann Sonders, Chief Investment Strategist with Charles Schwab, Inc:
DailyShot: Here is a comparison of the monetary base with the S&P500 ... Coincidence? pic.twitter.com/QsdNhJdbRP
— Liz Ann Sonders (@LizAnnSonders) January 15, 2016 Matt remarked that “Friends don’t let friends use two y-axes”. It’s a good rule. The topic came up a couple of times during the data visualization short course I taught last semester.
While making the maps for yesterday’s post about the extent of US federal landownership, I noticed an odd checker-pattern in one part of it. It flowed through northern Nevada and Utah, and then out a ways into southern Wyoming. I did enough work to make sure it wasn’t a coding error on my part, but didn’t pursue it any further. This morning, JP Lien asked me about it on Twitter, and we both took a closer look.
The current occupation of a federal wildlife refuge building in rural Oregon prompted me to make a map of the land owned or administered by the US government. There are a few such maps floating around, but I wanted to see if I could draw one in R. The US Geological Survey makes a shapefile available containing the boundaries of federal lands, so I grabbed that and simplified the category codings a bit, to make the main classes of land a bit more tractable.
A few weeks ago the Irish Times ran an extensive supplement on secondary student transition to higher education in Ireland. They were interested mostly in a league-table exercise to identify the “best” schools in the country, but in the process they compiled some pretty good data on “feeder schools” together with some decent discussion of the broader trends associated with the move from secondary school to third-level education. They also made their full table of data available as an Excel spreadsheet.
Marissa Mayer’s performance as CEO of Yahoo has been criticized by various people. Yesterday, Eric Jackson, an investment fund manager, sent a 99-slide presentation to Yahoo’s board outlining his best case against Mayer. Paging through the presentation/hatchet-job gives some insight into what passes for analysis in the world of corporate investment and finance. I’m not too interested in the details. From a design and communication point of view, though, the slides are generally terrible.
Having recently revisited plots of some international comparative data on assault death rates in the OECD, here’s a quick update to the state- and region-level plots for assault deaths within the United States. CDC Wonder data now goes up to 2013, so if we query that for adjusted death rates due to assault (based on ICD-10 codes X85-Y09 and Y87.1) we can make some new plots. Here’s a boxplot of the yearly trends across states, with some high-rate outliers marked.
Another week, another mass shooting in the United States. I’ve linked before to my posts America is a Violent Country, and Assault Deaths Within the United States. I thought I would update the figures with the latest data from the OECD. The method and scope are the same as before. Here is the main figure, showing assault death rates for the US and 23 other OECD countries.
Assault Death rates in the US and other OECD countries, 1960-2013.
The other day, Jonathan Marshall posted a nice graphic showing population age profiles of electoral constituencies in New Zealand, ordered by their tendency to vote left or right. He put the data on github, and on a long transatlantic flight yesterday I ended up messing around with it a bit.
Almost the only bit of Demography I know is the old saw that women get sicker but men die quicker. So I thought I’d take a look at differences in the sex composition of age cohorts by constituency.
To be notified of updates, you can
subscribe to the RSS feed for the site.