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Yeah i get that, but for me that would be the interesting part. Making a model is just one part, choosing if the model is correct is a whole different story :) And i still think that adjusting an inverse square model might be worth trying, no? The price is based on available space, and this correlates with a square and not an exponential function. Not sure why I feel so strongly about that, sorry:)

Yeah, I actually should. Have forgotten it here to mention in the plot.

And the two charts you link to were an effort to respond to my chart which started this parade of QB height scatter plots. https://www.reddit.com/r/dataisbeautiful/comments/121pvx7/oc_nfl_quarterbacks_of_passes_batted_down/?utm_source=share&utm_medium=ios_app&utm_name=iossmf

In my chart, which was not an attempt to evaluate QB effectiveness against height, but an attempt to evaluate one aspect of quarterbacking...batted balls.

There is widely assumed belief that shorter QBs will have their passes batted down more frequently which is proven to be false in my analysis. People point to players such as Baker Mayfield and Kyler Murray who are short and have passes batted down often, but these two commonly used examples are not the rule which is evident in my chart. That’s was the point of my analysis, to either prove or disprove that narrative wasn’t sure which way it would go when I started, but it was clear when I finished.

The person who created the other two weird and flawed charts was aggressively critical of my analysis and thought they would create something more meaningful. It’s clear that they don’t understand football or analytics. So here we are. Then this OP responded to them, and this OP gets it.

Well, the results looked much more off. But you are right, I should add some information on the mean squared error. In my article I didn't wanted to shock people with it, because it's kind of more informative post.

As a Californian how the fuck is this a shame, I don't think you understand how badly we needed this water. Don't 3000 IQ yourself here.

Californians have been living in drought conditions since maybe early-mid 2010s. At this point I'm pretty sure we're wired to be concerned about water levels. Especially since groundwater levels are still low. I assure you Californians and public agencies are still thinking about droughts, everyone knows we will eventually have some dry winters. That's just Californian climate. It's just a matter of when.

I read the article. What did not work? Or why do you think the exp formula in the article did work?

That's great, now scrap the "sheet" or "layer" like scale and we are getting beautifuler!

Yeah, I've tried and inverse square law didn't word well. On the original article you can find more info https://damovs.com/rental-market-of-apartments-in-paris-in-2023/

4-7 rooms means that these are offered apartments, which have between 4 and 7 rooms. It's up to you if you can afford and live alone or share it with other people. I do believe that 1-bed apartments are most expensive per square meter because 1) there is the highest demand (to use them within the week and go back to family on weekends), and 2) because you have fixed costs (council tax, ...) included, which are scaled by less square size. In France everything except gas and electricity is included already into the rent.

This is beautiful. Yes I saw the comments about the z axis but this isn’t about quants for me. As someone who doesn’t get to hear about northern Cali as much as southern Cali, I love it. I would have also loved if there was a sudden glitch and San Diego or LA got 2 inches.

Why is a 4-7 room apartment cheaper than a 1 room? Does 4-7 room mean it’s like communal living like a student dorm?

A coefficient of less than one half of one percent of variance...

Over 100 dams have been removed in California in the last 30 years. Resulting in historic flooding, mudslides, and the inability to capture the snow runoff before it reaches the pacific.

[removed]

Is that supposed to be feet or inches?

That's interesting. Can you supply some measure of performance (mean squared error, mean absolute error, ...) for those curve fits?

Yup, it ain’t the accepted standard. ISO8601.

One thing you could consider:

The dark purple is kind of hard to distinguish from the black "0 snow" value. For instance, it took watching a couple times through to see the snow total change in Southern California. You changed the color for 0 to white, and include an outline of the state, or perhaps some other light color that's not already used in your snow depth palette.

haha thank you 😘 it’s the 3d viewing angle - could definitely be done as 2d contour plot i just think it’s neat looking this way.

When you understand the context, you'll understand why this is beautiful. I was wishing someone would make this graph.

Two previous posts (https://www.reddit.com/r/dataisbeautiful/comments/122avg2/taller_american_football_players_tend_to_throw/ and https://www.reddit.com/r/dataisbeautiful/comments/122c5b2/american_football_starting_quarterback_pass/) put out weak evidence that QB height was correlated with passing performance. No R2 values, polynomial regressions where they are not needed, uninformative bubble sizes.

OP just put up the real analysts graph - a measure of passing performance that is acceptably unbiased for time on the field plotted against QB height, modeled linearly showing that height explains 0.3% of the variance in this metric. This graph is the hero we need, but not the one we deserve.

yeah other people have been saying that as well. I’m gonna try another state with a custom color scale with more range at the 0-5ft level

Will do!

The colours are pretty hard to read. At about 2 seconds in, the graph has some dark colour and the base is dark as well.

I had to crank up my display brightness

Would have loved to see the residuals of that exponential fit. They look a bit off even by eye? Not sure if this is the proper model since with the areal distance the area accessible to build houses raises with a square, so the simplest model I'd try is to use something with an inverse square law no?