For the past view years, Jason Snell at Six Colors has conducted a survey of people who write about Apple. He asks a series of questions about the company and its products and presents a report of people’s answers. This year’s report has al... [Read more...]

When we want to see how something varies across categories, the trellis or small multiple plot is a good friend. We repeatedly draw the same graph once for each category, lining them up in a way that makes them comparable. Here’s an example from ... [Read more...]

I’m continuing to update the covdata package in anticipation of a Data Visualization for Social Science course I’ll teach next semester. I revisited the Partisan Trajectories graph, as it seems there’s more that could be done with it.... [Read more...]

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I updated the covdata package for the first time in a while, as I’ll be using it to teach in the near future. As a side-effect, I ended up taking a look at what the ongoing polarization or divergence of the COVID experience is like in different p... [Read more...]

Recently I came across a question where someone was looking to take a bunch of CSV files, each of which contained numerical columns, and (a) get them into R, (b) calculate the mean and standard deviation of every column in every CSV file, and (c) calculate some overall summary like ... [Read more...]

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People have been talking about this PNAS paper by Matthew Killingsworth: “Experienced well-being rises with income, even above $75,000 per year”. Here’s the abstract: Past research has found that experienced well-being does not incre... [Read more...]

Data from the Short Term Morality Fluctuations dataset compiled by the Human Mortality Database continues to be very interesting. When thinking about how to interpret the 2020 data in a cross-national and longitudinal context, it’s clear that the... [Read more...]

Although yesterday’s excess deaths plots by cause graph was for the whole of the United States only, the table we made did the same calculations on the whole CDC dataset, so the resulting df_excess table has numbers for all U.S. states and several other jurisdictions, such as ... [Read more...]

As I was saying the other day, calculating excess deaths can be a tricky business, especially if your focus is on understanding counterfactuals like how many people died of some cause who would not have died due to some other competing risk over the period of interest. Moreover, even setting ... [Read more...]

The other day I was looking to make a bunch of graphs showing some recent data from the CDC about excess mortality due to COVID-19. The idea was to take weekly counts of deaths over the past few years, both overall and from various important causes, and then show how ... [Read more...]

Following up on yesterday’s post on within-state variation in deaths in the United States, here’s a quick look at all-cause mortality rates across twenty countries, courtesy of the excellent work of the demographers who maintain the Human M... [Read more...]

The CDC recently released some new data on mortality counts by state and cause of death in the U.S., allowing us to get a look at excess mortality patterns due to the COVID-19 pandemic. I’ve folded the data into the covdata package. As an illustr... [Read more...]

I had a very nice chat recently about data visualization with Brian Fannin, a research actuary with the CAS. We covered a variety of topics from R and ggplot in particular, to how to think about data visualization in general, and what the dataviz commu... [Read more...]

If you’re teaching statistics, data analysis, or data visualization with R this semester, especially in the social sciences, I’ve pulled together various bits of data into packages that I use in my own teaching. You might find them useful o... [Read more...]

I’ve been maintaining covdata, an R package with a variety of COVID-related datasets in it. That means I’ve been pulling down updated files from various sources every couple of days. Most of these files are at static locations. While their internal structure may change occasionally, and maybe they’... [Read more...]

My post about Apple’s mobility data from a few days ago has been doing the rounds. (People have been very kind.) Unsurprisingly, one of the most thoughtful responses came from Dr. Drang, who wrote up a great discussion about the importance of choosing the right baseline if you’re ... [Read more...]

Apple recently released a batch of mobility data in connection with the COVID-19 pandemic. The data is aggregated from requests for directions in Apple Maps and is provided at the level of whole countries and also for a selection of large cities around the world. I folded the dataset into ... [Read more...]

The other day Nature reported some preliminary results from a study of COVID-19 symptoms that’s being carried out via a phone app. The report noted that loss of sense of smell (or “Anosmia”) seemed to be a common symptom. The report was accompanied by this graphic, showing the co-occurrence ... [Read more...]