This week, a few projects went up on the internets about money and spending, each with different goals and approaches. In this issue of The Process, we look at each more closely.

Neal Agarwal used a money printing metaphor to depict differences in various wages. The higher the wage, the faster the money prints. Keep scrolling and you also see big company revenues, finished with a frantic U.S. deficit increase.

So good. [Thanks, Neal]

For The Upshot, Alicia Parlapiano and Quoctrung Bui scaled down the federal budget to something more relatable:

To better understand how federal spending has changed since Mr. Trump has taken office, we looked at the actual budget amounts for the 2020 fiscal year. We divided them by the U.S. population and sized the numbers proportionally to make their scale easier to visualize. Then we compared the numbers to the actual budget for the 2016 fiscal year, adjusting for inflation and population changes.

Federal budget visualizations usually aim to show big dollar values going to many different departments. You look at the breakdowns, and you can’t help but think, “That’s a lot of money.” For most of us, it’s hard to imagine billions of dollars, because the scale is so far beyond our own experiences.

So it’s interesting that this piece goes the other direction and scales everything down to match the values to something more familiar. The font size of each value also scales accordingly, which I think in the end is what you end up focusing on.

Reddit user quantum-kate used daily high and low temperatures in Denver in 1992 as the basis of this blanket. I feel like I should learn to knit crochet.

DR used a 3-D model to recreate King Frederick the 9th’s ink:

King Frederick the 9th was famous for his tattoos. But until recently — noone knew much about them. By examining hundreds of old photographs and films we have recreated the Kings’ ink in order to get a sence of who he was — both on the inside and the outside.

The scrolly touring works really well here. I went in knowing nothing about the king and came out more educated on the other side.

We hear about billionaires spending millions of dollars on ads, acquisitions, etc. It seems like a ridiculous amount of money, but that’s partially because us common folk think of the millions of dollars in the context of our own net worth. When Jeff Bezos spends a few multiples of what we will never make in a lifetime, it seems like a lot.

For The Washington Post, Michelle Ye Hee Lee and Youjin Shin made an interactive that instead looks at the spending as a percentage of net worth. The purchases suddenly seem less crazy (sort of).

It’s simple math but a nice way to make the spending scales more relatable.

From @haru_cchii on the Twitter:

Local German Gets Bored And Tries To Name All American States
i think i did pretty well

Seems right to me.

It wasn’t just issues with an app. There appears to be many more problems with the Iowa caucus results. The Upshot broke it down with a closer look at the data:

Some of these inconsistencies may prove to be innocuous, and they do not indicate an intentional effort to compromise or rig the result. There is no apparent bias in favor of the leaders Pete Buttigieg or Bernie Sanders, meaning the overall effect on the winner’s margin may be small.

But not all of the errors are minor, and they raise questions about whether the public will ever get a completely precise account of the Iowa results. With Mr. Sanders closing to within 0.1 percentage points with 97 percent of 1,765 precincts reporting, the race could easily grow close enough for even the most minor errors to delay a final projection or raise doubts about a declared winner.

When did voting get so complicated?

To increase anonymity in the Census records, the bureau is testing an algorithm that removes real people and inserts imaginary people in various locations. As you can imagine, this carries a set of challenges. Gus Wezerek and David Van Riper for New York Times Opinion ask what effects this could have on small towns. [Thanks, Gus]

Welcome to another episode of Misleading or Not? where we look at a chart and decide if it’s misleading or not.

For the Financial Times, Alan Smith and Steven Bernard traced the history of railroad construction in America and mapped it over time. Literally. Bernard used digitized versions of old maps and traced each new segment by hand. Tedious, but the result is impressive.

From Lusion, CineShader is a fun editor for those who are familiar with Shadertoy:

CineShader is a real-time 3D shader visualiser. It leverages the Shadertoy.com API to bring thousands of existing shader artworks into a cinematic 3D environment.

The whole project was started as an idea of using a web demo to explain what procedural noise is to our clients at Lusion. After sending out the demo to some of our friends, we were encouraged to add the live editor support and we decided to release it to the public.

Google Maps incorporates data from smartphones to estimate traffic in any given location. Artist Simon Weckert used this tidbit to throw the statistical models off the scent. With a wagon of 99 smartphones, he turned roads red on Google Maps just by walking around.

Nice.

Michael Keller released a new version of Layer Cake:

Layer Cake is a graphics framework built on top of Svelte. It measures your target div and your data and creates scales that stay synced on layout changes. Use these scales to organize multiple, mostly-reusable Svelte components, whether they be SVG, HTML, Canvas or WebGL. Since they all share the same coordinate space, you can build your graphic one layer at a time.

I’m intrigued. (And I feel like I need to learn more about this Svelte.)

I know you don’t get enough election coverage these days and are probably like, “I wish there was a way I could be reminded of who’s running with bouncing heads across my screen whenever I come back to my computer. That would be super.” Well, look no more. The Presidential Hopefuls screensaver by Robert Tolar Haining is what you’re looking for.

Every month I collect resources and tools to help you better visualize data. Here’s the good stuff for January 2020.

Flow Fields, a generative art tool by Michael Freeman, lets you adjust various parameters, such as color, smoothness, and fluctuations, and the flows just keep coming. Pretty.

The code is up on GitHub and is based on Daniel Shiffman’s Coding Train tutorials.

For ProPublica, Ellis Simani and Ken Schwencke compiled an interactive database that you can search:

ProPublica reporters spent months collecting the lists as they were originally released by each diocese. They then made them searchable via a public database in order to provide victims of clerical abuse and members of the public a way to search across all of the released lists.

More than 6,700 names are included in the database, and over 5,800 of them are unique. A little more than half of the people named were listed as being deceased. ProPublica did not have the data necessary to merge records with the same name across dioceses, though our reporting on specific clergy indicates that some have surfaced on as many as eight lists.

Unsettling.

The data is also available for download.

Noah Veltman just posted a dataset of 23,463 personalized license plate applications that were flagged for additional review by the state of California from 2015 to 2016. Casually scrolling through, for the plates people request and why they are flagged, this is a goldmine of amusement.

Veltman writes:

This data was parsed from a set of 458 Excel workbooks that the DMV prepared for someone else’s public records request. I received the files as a consolation prize in response to my own related records request, which I was told would cost $2,000 to fulfill otherwise.

Just on this information alone, I think we are obligated to do something with this dataset.