xBris18

xBris18 t1_j2drtix wrote

Reply to [OC] Weekly Plastic and Metallic waste from a 150 Seat Diner (lbs) by Hi_its_GOD

I'm honestly surprised by the amount of polystyrene waste. What country is your diner in if I may ask? In most parts of Europe PS has virtually disappeared for the end consumer and - afaik - is also mostly replaced by other materials where possible in the commercial sector. But I might be wrong. Again, really surprised to see so much of it in your graph.

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xBris18 t1_j1qr4dl wrote

Reply to comment by fred_fotch in [OC] State by State Housing Price Growth since 1975 by fred_fotch

Sure, no worries. What makes a "good design" is highly subjective of course, but I think there are a couple of things that are super easy to do in less than a minute that would greatly improve the quality of this graph: First of all, edit the axes: Give both of them a solid black line and change the scale to start at zero. I would also add some tick marks. For this particular graph, I'd change the y-axis to start at zero and end at 2500 %. I'd set the main interval to 500 % and set the minor interval to half that (and make sure to enable both tick marks). I'd also change the width of the bars by setting the gap width to 50 % (standard is - for some reason - 219 %). I would also add tick marks to the x-axis. Maybe increase text size by at least 1 point and definitely change the text colour to solid black. If you feel fancy, change the font. Maybe add labels to the axes as well. A lot of these things are personal preference, but a good litmus test is to look at your graph at half or even quarter the size and see if you can still make out its meaning. If you can't, it's probably a bad graph.

So while I didn't find the exact data set you used, I found a similar one that I put together in literally two minutes: https://i.imgur.com/xIZbXCy.png - I do however like that you use the full names of the states, instead of the abbreviations I used - I just couldn't be bothered to look them up ;)

Also, maybe a map would have been the best format for this data. Also also, I honestly don't really understand the numbers in this. Is 2500 % a lot or not? I think the data should be in some form of context - compare it to inflation or purchasing power in general - something that puts it into perspective. 2500 % looks impressive, but maybe it isn't really. Humans aren't super great at estimating numbers over these kinds of time scales.

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