Tools: R, the GIMP

Data source: Tables from worldathletics.org

Background:

Dutch athletics has been growing by leaps and bounds over the last ten years or so. Two weeks ago another landmark was set by superstar Femke Bol, just before her 23rd birthday. At the humble Dutch national indoor championships Bol shattered the 41-year old 400m indoors world record, slingshotted by her close friend Lieke Klaver who herself improved her personal best and became the (at that moment) 15th fastest woman ever.

These two ladies just won gold and silver at the European indoor championships in Istanbul, and we made use of the occasion to plot Bol's record against the best performances of the last decades. The former record was set by Czech athlete Jarmila Kratochvílová in 1982.

Design:

I wanted to put annual traffic deaths into the context of other accidents and disasters. For example, the all-time worst aviation disaster caused 583 deaths which is a little less than 3.8 hours of average global traffic deaths. The range of values is huge and I didn't want to simply use a logarithmic scale on a bar chart, so I used this style which I've seen elsewhere on the sub a few times. If anyone knows what this kind of visualization is called, please let me know.

Notes:

All death counts rounded to nearest square.

When sources state a range, the maximum deaths are used.

Tools:

Draw.io

Sources:

https://www.who.int/publications/i/item/9789241565684

https://en.wikipedia.org/wiki/List_of_accidents_and_disasters_by_death_toll

https://en.wikipedia.org/wiki/List_of_avalanches_by_death_toll

https://en.wikipedia.org/wiki/List_of_costly_or_deadly_hailstorms

https://en.wikipedia.org/wiki/List_of_natural_disasters_by_death_toll

https://en.wikipedia.org/wiki/List_of_Pacific_hurricanes

https://en.wikipedia.org/wiki/List_of_tornadoes_causing_100_or_more_deaths

https://en.wikipedia.org/wiki/List_of_foodborne_illness_outbreaks_by_death_toll

https://en.wikipedia.org/wiki/List_of_volcanic_eruptions_by_death_toll

What general topic do you have expert knowledge about, just out of curiosity?

I was actually thinking “is this Switzerland or Italy?” before I googled it. I’m an Australian who has been to both countries, but I still didn’t quite know what I was looking at.

Yep. I googled it. But beautiful data is beautifully presented with simple clarity. It shouldn’t require most of its audience to go to google to try to work out what they are looking at.

> Pruitt has not literally pressed the 'edit' button 4.4 million times. One method he has used to achieve his astonishing numbers is a software tool that allows a user to make numerous identical edits simultaneously

Yeah i was expecting this.

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Does a low yield rate at a private school mean that the student could be in a better place in negotiating financial aid? I’m referring to the single digit of the private schools near the bottom of the chart. Or perhaps those schools don’t care about yield rates? Isn’t it the higher the yield rate the more points on a ranking system?

Doesn’t say that though.

My point is that the graph is concocted to make Latin American production appear more significant than it is. It’s not a careful analysis, it’s just spin.

You got production mixed up with consumption. Australia actually is the 4th largest consumer of cheese per capita in the world. We are behind EU (27 countries counted as 1), US and Canada. https://www.statista.com/statistics/527195/consumption-of-cheese-per-capita-worldwide-country/

Domestic production of cheese is limited by the amount of dairy farming land available.

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This isn't how such data is displayed. The wind industry uses SI units, m/s for wind speed. What's the red line representing? For normal power curves for turbines it would be the warranted power values from the OEM. It's a decent idea but the data is too noisy to properly show the correlation. It doesn't look like a strong correlation from the graph when wind speed cubed is directly correlated to power.

No. I went to a smaller state school. Nothing that usually makes national rankings.

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Thanks! Like I said, "dumb question" but I had to ask :)

University of Chicago has dramatically climbed this particular leaderboard over the past 10 years or so. They used to be high prestige but very low yield - essentially, they had a difficult time making themselves anyone’s first choice.

That seems to have changed.

Im using a poly fit function set to the third degree: https://numpy.org/doc/stable/reference/generated/numpy.polyfit.html

Yeah the wind turbines dont produce electricity until they reach their cut in speed which is around 15 to 20km/h I believe. Then they have a max output, somewhere around 55km/h. They also need to park at high wind speeds or risk getting damaged. You can see this more clearly here: https://imgur.com/a/GNR2M9c

Dumb question, but why is the red line between 10km/h and 20km/h plotted so much higher above the dense mass of dots below it?

Shouldn't the red line be coming in a bit lower and angling up a bit steeper along that part of the graph?

( or are all those low-density outliers above the red line causing it to appear higher up? )

This. +1. The wind speed is not uniform across the disc area of turbines. You need wind speed at several points in height. Although not sure what OP is really trying to determine here just avg power v wind speed but fit looks poor at lower end.

That number seems to be quite low if i may say so myself, I am making north of 140 an hour without ever touching the grounds of college.

Some of the top schools got caught coordinating some time ago, and the Feds came down hard on them. They don't do that any more.

Now they just need to invent a light bulb that lights in proportion with how much wind is blowing.

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