Color-balancing vote margins and vote totals in the US election map (opens in new tab)

Depends on the purpose. If you want to show the nuances, then, yes, it is effective. But, if I didn't know the results of the election, I don't think I could even take a guess looking at that map.

I don't believe there is a Grand Unified Theory of Election Maps. Use different maps to convey different facets of information.

you can really see the urban blue centers surrounded by grey suburbs surrounded by red exurbs. East and mid atlantic show this in several metro areas. US is not red state / blue state, but blue core / red rings.

But the county-level results aren't what's important in the election. For showing results, it makes sense to show all of Texas in red as soon as it's confirmed to have gone 50.1% to Trump, or whatever.

This map is useful in visualizing demographics and expected voter distribution. It's more valuable for showing election predictions than newsworthy results.

thank you =)

I was thinking the same thing. According to Wikipedia, the county areas vary by three orders of magnitude, from San Bernardino County, California (51,947 km^2) to Kalawao County, Hawaii (31 km^2), so it seems it can be very misleading.

For example, North Carolina and California have similiar population densities (80 people/km^2 versus 95 people/km^2), but on the "muddy" map North Carolina looks almost unpopulated while California is very emphasised---I guess this is because North Carolina is divided into smaller counties.

I guess in the case of San Bernardino it's a giant grey rectangle, so that particular one doesn't shift the red-blue impression very much, but still... :)

I've seen maps showing population rather than area in several places in recent British elections.

Here's a recent example: https://odileeds.org/projects/hexmaps/constituencies/

And here, where the first graphic is from 1895 and uses this approach: https://www.geog.ox.ac.uk/research/transformations/gis/paper... ... and Figure 31 (p28) has an American example.

Yeah, I'm on the same page. An idea for a follow-up map has been to do votes per thousand. I'm curious to find out what that resulting map would look like

My thoughts exactly. Giving the same color to the same population over different areas seems like a mistake, or at least a missed opportunity to provide more useful information.

EC-weighted, too.

I guess I'm really talking about the "lightness", not saturation

In my experience of reporting data to non-data-saavy people, I've learned people love maps. Maybe because they like finding their home state/county/city. For whatever reason, they love maps.

I've also learned the hardest part of my job is getting people to read and remember the data. Replacing their preconceived notions is difficult. I'll use any cheap trick (short of showing data inaccurately) to do this. So I make them the maps they love. I use the colors they expect. If I show tables, they're used by experts for further analysis and ignored by the people who actually make decisions.

>The saturated red and blue colors have an almost astrological meaning to people, it's got nothing to do with information.

That meaning is information. Is it the best thing for a nuanced data graphic? No. But showing a nuanced graphic is like handing somebody Principia Marhematica when they ask what 1 + 1 is. Sure, it had the answer. And sure, it's great for people with mathematical skill. But it's overkill most of the time.

I can tell you that in pretty much every presentation context a graph (no matter what graph) beats a table. We are much more accustomed to visually processing things than through numbers. I mean take the example of the given map (and let's keep it to the "simple" winner takes all map), the table for this map would definitely be so big that you could not easily tell which party won more counties. With the map it would be one glance.

Yes as the author points out it does not tell you anything about the number of people in the county, but trying to convey information in graphics well is difficult (and when people get it right it can be truly amazing, i.e. take Roslings talks, which really visualised public health effects and enabled many people to understand for the first time). However, everyone who regularly has to present data to people should invest time into learning about how to graph and visualise your data.

Thanks for the comment. Yep Alaska was a tough one. Although Alaska is separated by boroughs, their voting data is not. Researchers come up estimates for how each borough likely voted, but there can be different estimates depending on the methods used. Because of this, it felt more accurate to go with the concrete data that we had, even if it was not at the borough level. Although, I think there is merit to the argument that borough estimates should be used, even if they may not be accurate down to the last recorded vote.

Exactly. It'd only make sense when 2 counties, each with area S and N votes would have same color as a county with area 2 * S and 2 * N votes.

One party has the numbers they need because they need those numbers to be competitive in the current system and have made whatever concessions they needed to to achieve them. If the demographics changed then the parties would adapt so that again they both just barely have what they need. The parties would adapt by campaigning to different groups of voters or changing their policies to attract the other party's voters. It's a waste of resources and concessions to gain more voters than are useful for winning.

Third quartile plus 1.5 times the interquartile range (Q3 - Q1). The Q1, Q2, Q3 quartiles correspond to the 25th, 50th, and 75th percentiles. Q2 is also known as the median.

It’s only capping the saturation, so that counties with > 60000 residents are shown in brightest color. The color itself though still varies from red to blue based on percentage vote margin. In my mind, this is a great tradeoff, with the only exception that dark Grey counties (large counties with roughly 50:50 split) are way more important than they look since humans tend to de emphasize greys. I would have preferred a brown or something. Purple is not used as it has an imbalanced perceptual effect.

As the author of the OP explains, those counties are shown with 100% saturation. Moreover, the author also shows a map without the upper fence[a] and explains why he thinks that map is misleading.

[a] https://stemlounge.com/content/images/2019/10/muddy_no_upper...

As the article describes, the 'artificial' ceiling is the standard quantity known in statistics as the 'upper fence':

https://en.wikipedia.org/wiki/Outlier#Tukey's_fences

I agree that it would be nice to have a scaled version of the top few counties - maybe an area-corrected inset of the most populous counties over the Pacific, Atlantic, Gulf, or Lake Michigan.

Would Cook county fit in the lake, or would it need to overlay Canada? It's half the population of the state of Michigan...

Regardless, hoping this gets updated for 2020.

I've got just the thing. An Ohio State economics student made this adaptation: https://tuttlepower.github.io/VotingMap/?fbclid=IwAR0McVXHOI...