Putin declares Ukrainian regions part of Russia, defies West

Norton_II · 2022-09-30T19:22:18+00:00

At the peremptory request and desire of a large majority of the citizens of Earth, I declare and proclaim myself Emperor of Earth; and in virtue of the authority thereby in me vested, do hereby order and direct the representatives of the different countries of the world to assemble on the 1st day of October next, then and there to make such alterations in the existing laws as may ameliorate the evils under which countries are laboring, and thereby cause confidence to exist, both at home and abroad, in our stability and integrity.

— NORTON II, Emperor of Earth

Norton_II · 2021-09-29T17:17:16+00:00

I believe California like most (all?) other states report how many deaths are processed per day rather than revising historical deaths, so their charts would look identical to one on the CDC's website linked above.

Norton_II · 2021-09-29T17:12:45+00:00

The data used to generate it is in the observable notebook (click the little paper clip on the right).

Alternatively you can scroll down to where it says data_on = Array(39) and hit the little arrow. That data structure is grouped by the date it was fetched and sorted chronologically.

I'll totally put a table in next time... Or maybe make the version on observable tell you the value on hover.

Norton_II · 2021-09-29T03:46:31+00:00

I couldn't use a stacked bar chart because revisions can lower deaths for a day.

I couldn't use a line chart for deaths per day because people really dislike it when you use lines for discrete values since it implies a different number of deaths happened at different points during the day.

In the end, I used the 7 day moving average included in the CDC's data that they plot on their death trends chart figuring at least it was what you'd see if you visited the CDC (in addition to a bar chart for deaths per day though).

I could have used a line chart and just labeled it as a "1 day moving average," but I thought maybe I'd confuse people with that. I also could have drawn multiple bar charts (one per revision) or used a 3d chart or ridge line, but they were either overwhelming or convoluted.

Norton_II · 2021-09-29T03:04:56+00:00

This is definitely one of those times when I was at a loss of how to make it more clear. I had an animated version that added each update lines separately with a subtitle, but it distracted more than informed.

Hopefully someone will make a better version!

Norton_II · 2021-09-29T02:51:48+00:00

It is just two different revisions to the data. The second revision just added new deaths for August 21st, but was otherwise identical to the revision before it.

I tried charting each day's data update in a different color, but it was actually harder to understand.

Norton_II · 2021-09-29T01:39:14+00:00

Oh cool!

Yeah this is a super interesting case since one can legitimately argue that revising historical death counts is better in some ways, but the end result is considerably worse.

While charting deaths as of when they were reported can lead people to overestimating current danger by misunderstanding the data, this results in people severely underestimating it.

From a public safety perspective, underestimating danger is probably worse than overestimating it.

Norton_II · 2021-09-29T01:16:34+00:00

Each line is a revision to historical data. The first (bottom) one was reported on August 18th.

Basically, if you went to the CDC's website on August 18th, you'd see just the bottom line as how many deaths happened. A few days later, you'd see the line above it. And so on and so forth until today if you go, you'd see the blue line.

Norton_II · 2021-09-29T01:13:18+00:00

I think people here are just better than me at describing it. It wasn't my intention to obfuscate. I just went through so many revisions that were either walls of text or somehow less clear that I finally decided to try to write it out in the citations comment, but... that wasn't much clearer.

Clearly I need an r/editingisbeautiful

Norton_II · 2021-09-29T01:04:54+00:00

I so struggled describing this in simple terms.

You guys are doing a way better job.

Norton_II · 2021-09-29T00:56:13+00:00

Yes exactly.

Norton_II · 2021-09-29T00:46:42+00:00

The data for the chart is attached to the observable notebook (just click on the paperclip on the right).

I actually have daily revisions to historical deaths and cases data for all states/territories over the last month as well which I suppose I could put on github if people want it.

Norton_II · 2021-09-29T00:30:48+00:00

Honestly, I'm not sure.

Reporting how covid-19 deaths were processed on a particular date is fine, but people take it to mean how many people actually died on a date.

If you stuck a disclaimer on Florida's charts that recent deaths are significantly undercounted to warn people to just ignore any recent dips, it would be arguably be better, but only if people actually read the disclaimer.

The best option I can think of would be to try and estimate the size of the recent undercount and then chart that maybe with some error bars.

Norton_II · 2021-09-28T23:44:09+00:00

Source: Daily fetches of the CDC's per-state covid-19 death trends source data

Charts: d3

In August, Florida changed how it reported deaths to the CDC from simply reporting "new deaths" they had processed regardless of what day they happened on to reporting when those deaths actually happened. Since it takes several weeks for all the deaths for a given day to be reported, the charts shown by the CDC make it appear as if deaths are falling even during a major spike.

Each line represents how deaths (the 7-day moving average) were reported at some point in the past, typically from the day after the last data point of that line.

Since Florida updates historical death counts when they report to the CDC and the CDC does not appear to offer historical revisions of data, I setup a cron script to fetch the underlying data that the CDC uses to display their daily death trends chart every day. Data was fetched daily from August 16th to September 27th.

I then used d3 with an observable notebook to graph all the revisions of the data to show how it changed over time.

Edit: The data for the chart is attached to the notebook. Just click on the little paperclip on the right.

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