3 September 2021
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 parts of the United States. Here I use county-level data to draw out some of the trends. The idea is to take the time series of COVID-19 deaths and split it into deciles by some county-level quantity of interest.
4 May 2021
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 the mean of all the means and the mean of all the standard deviations.
I already know how to use map_dfr() to read a lot of CSVs with the same structure into a nice tidy tibble.
24 February 2021
Updated on April 29th, 2021.
The CDC continues to update its counts of deaths by cause for 2020 as data comes in from the jurisdictions that report to it. The data are by now fairly complete, though there are still significant gaps in several states due to delayed reporting. North Carolina, in particular, has yet to report almost any deaths for the entire final quarter of 2020. But I haven’t updated my gallery since last October.
26 January 2021
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 increase above incomes of $75,000/y. This finding has been the focus of substantial attention from researchers and the general public, yet is based on a dataset with a measure of experienced well-being that may or may not be indicative of actual emotional experience (retrospective, dichotomous reports).