You’re looking at volume here when you need to be looking at efficiency. Players who throw more pass for more yards. This needs to be done as yards per attempt if you’re trying to glean anything meaningful out of this. And you would benefit in using a sample size of more than one season. For Example Russell Wilson’s 2023 is absolutely not indicative of the QB he has been throughout his career. Same with Tua. You’ve got an again Joe Flacco listed at 1,000 yards because he’s done, he has one foot out the door and his 2023 shouldn’t be the data used to judge his effective as it relates to his height. This is extremely flawed for so many reasons. If you aren’t looking at a players efficiency (again, not volume) over a longer period of time, you’re going to be led to a wrong conclusion.

So negative 1foot of snow depth?

I have no idea how to read this

Edit. Nevermind it's a video that takes 10 seconds to load on my phone, sorry

3D just obscures the depth. 2D color chart would be more comprehensible.

Lmao, good argument.

Arguing about something obviously stupid thing and making much more out of it then necessard... Sorry, I am blocking stupid people.

I think they actively plan on using floods to replenish the lost water now!

It’s ok that things are different. I’m just letting you know.

How does the height of the bar go above the back axis? It seems like you are really dedicated to not communicating the data with this visualization.

Source several french web housing market portals. I have done the plot with pandas and matplotlib in Python 3. The full article you can find here : https://damovs.com/rental-market-of-apartments-in-paris-in-2023/

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Do Utah next. Record breaking year.

Beautiful? This is a poor visualization.

This should be a top view map, contour, not 3D. I have no idea what the totals are, where they are, no legend, bad colors etc.

What does the news show when explaining snowfall totals? Not this. Reproduce what others do, while this may look cool, it’s a bad visualization for understanding data.

The ONLY time I saw a 3D isometric work was when it was showing real time by minute #of tweets based on location during the World Cup. When a goal was scored, the bars shot up like cheering. This was the ONLY time this map ever made sense to use.

Seems this is mostly relevant if you're asking, "What's important for QB success?", in which case you want a series of measures, like what are their times in the 40? Weight? QB rating? Etc.

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My takeaway from the comment section is that the people who are complaining that it doesn't effectively convey information are correct, but I also agree with OP that it looks kind of cool.

350 million people write dates that way. You are going to fight all of them??

Why is height a part of this graph?

I remember learning that as a lil kid in Ca. Huh. Cool beans. Thanks for the random memory pop up.

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It's in english and it says there are 84 million families. Not guaranteed to be US national statistics but it would be a stellar guess.

This is a terrible visual

I’m confused- the starting point for each line is at a different height but all the rest of the measurements are at equal heights- it makes any information under the 0 line impossible to interpret

Id rather not get shot

shame honestly, I feel like this will allow people to kick the can down the road and not face reality

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You made a chart that shows the more people try to do a thing, the more that thing happens? Of course it does. The more darts I throw the more that hit the board. The more I step on the gas the more miles my car goes. This is absurd, particularly because it’s an attempt to one up my chart that you ripped yesterday.

If your goal is to find outliers, you simply use a table or bar chart of quarterbacks’ yards per attempt. (Y/A, NY/A, or ANY/A)