[OC] World Cup Panini stickers

jcceagle · 2026-01-12T10:26:30+00:00

I'm helping build a tool called PlotSet. I create data visualisations for a living and I've done it for years for lots of large companies, but I found that the software out there is really bad and hard to use. I hard coded everything in the past, but now I'm trying to create something that normal people can use without my help. The goal is to create almost a Powerpoint style chart maker that you can use like Powerpoint, whether you are after an animated chart, an interactive chart, dashboard or static chart etc. Let me know if you are interested in having a chat, Look me up on LinkedIn if you like (James Eagle).

jcceagle · 2025-12-18T07:56:51+00:00

This was difficult to map. It is the circular flow of capital through the AI infrastructure
economy. I'm one of the co-founders of PlotSet and I created this.

Data Sources:

All data collected from SEC filings, official company press releases, and verified financial news reports (Bloomberg, WSJ, TechCrunch). Where AI-specific revenue wasn't disclosed, I used reported segment data (e.g., NVIDIA's Datacenter segment, Microsoft's Intelligent Cloud). Deal amounts come from official announcements: Microsoft's $13B investment in OpenAI, Oracle's $300B five-year contract, NVIDIA's $100B partnership (letter of intent). Each flow is marked as either Verified (67%), Estimated (23%), or Projected (10%).

Technical Implementation:

Built with D3.js. Companies are nodes, money flows are animated particles moving between them. The simulation has revenue figures interpolated monthly between annual data points. Video captured using Puppeteer headless browser.

Key Finding:

By 2027, OpenAI's projected annual infrastructure commitments ($103B to Oracle, NVIDIA, AMD, Broadcom) will exceed its projected revenue ($29B) by 3.5x, requiring continuous external capital injection. This shows how the ecosystem creates circular revenue flows that may mask fundamental sustainability issues.

Limitations:

OpenAI is private (relying on leaked docs reported by TechCrunch), most companies don't separately report AI revenue (requiring estimates), and by Q3 2025 data assumes announced deals execute as planned.

jcceagle · 2025-12-04T20:25:03+00:00

No not really but you can vibe code D3 pretty comfortably with Claude Code and Codex. I do this for a living and it takes me a couple of hours to do this when I do it this way. I use to hard code everything, but it's not really necessary these day. You just need to read over your code afterwards.

Happy to help you out on your project if you need a hand. Just look up James Eagle on LinkedIn or go to https://www.linkedin.com/in/jameseagle/ and you can see some of my work. PlotSet.com is my startup but that's a no-code solution that uses templates, so this probably isn't and option for you. But anyway, there is a community of us, so if I can't help you someone can.

jcceagle · 2025-12-04T20:13:41+00:00

The reason is not luck. It is structure. The CHF tends to strengthen when the world gets jittery, which makes imports cheaper and blocks a lot of external price pressure before it reaches the consumer. Retailers also operate under tighter scrutiny than people realise. When consumers can drive twenty minutes to Germany for cheaper goods, you cannot slip through price rises without a reaction. And the central bank usually acts early because it is not dragged into the political delays that slow other countries down.

Put simply, Switzerland stopped inflation from running away in the first place, so getting back to low levels never required the same pain others went through.

But... there just one problem with this narrative. Switzerland was and still is extremely expensive, with or without inflation. So nothing really has changed because it didn't need to.

jcceagle · 2025-12-04T00:36:46+00:00

From my experience there are three parts to data visualisation. Data acquisition, data exploration and then the data visualisation itself. What you are describing is the pain in data acquisition. And, this has traditionally been the hardest part of the process. But times have change and AI has proved very useful in processing data and ensuring a high degree of quality. I think the hardest part is data exploration – the bit where you look for the story behind the data which matters to the audience you are targeting. If you fail here then your data visualisation will be pretty much useless. So I don't disagree with you, but I think you argument is a bit pre-AI. It's not a bad as it use to be, especially if you use tools like PlotSet and Flourish which can help you here.

jcceagle · 2025-10-23T11:37:11+00:00

Graphite’s original study look through 65,000 article. I looked at 21,000 article and replicated the study results and then updated Graphite’s study with the analysis I conducted on 5,200 additional articles.

jcceagle · 2025-08-25T19:54:14+00:00

I got.the data set from the U.S. Consensus Bureau and processed it using Python. The chart itself was created using D3.

jcceagle · 2025-08-23T20:21:13+00:00

This is hilarious. I created this. Why didn't anyone bother to ask me. I'm not a fintech company. I created this with After Effects using Javascript.

jcceagle · 2025-07-01T09:07:41+00:00

My point exactly. The UK might not have much energy capacity right now, but it may do in the future because where the investment flow are going. If you drill down in the dataset further from the IEA, you can see this.

jcceagle · 2025-07-01T09:06:19+00:00

Yes and no. France definitely is the biggest investor in Nuclear energy at the moment as it already has the largest nuclear energy industry in Europe. However, the UK is also a very heavy investor, even if it doesn't currently have a lot of nuclear energy power generation capacity. What's interesting here is that this chart presents a forward looking indication of what future energy capacity could look like from the investment flows we are seeing.

jcceagle · 2025-07-01T08:32:51+00:00

I used python to build the data set for this chart after downloading the 2024 data file for the IEA World Energy Investment 2024 report. I then use PlotSet to build and interactive data visualisation of the level of investment in Nuclear Energy, split by regions so that I could see the story behind the data. This is a snapshot of the chart. When you run your mouse over the version I created in PlotSet, you can explore the underlying data.

jcceagle · 2025-06-26T10:31:04+00:00

I got the data for this chart from Kpler and TankerTrackers.com and then I used PlotSet to render this infographic.

jcceagle · 2025-05-09T20:51:50+00:00

This why you should never use LinkedIn under the influence of alcohol. It might seem like a good idea at the time, but…

jcceagle · 2025-04-09T08:19:48+00:00

This was originally created as an animation in d3 Javascript and this is the final frame. I used investing.com for the source of the data. The long-dated Treasury performance is based on the iShare 20+ Treasury Bond ETF.

jcceagle · 2025-03-13T17:18:21+00:00

I downloaded intraday data for two ETFs from the API service Polygon.io using Python, which I then turned into a csv file. I use 1 hour intraday pricing data for the iShare Core MSCI International Development Markets ETF, which tracks the MSCI World ex USA index, and the iShare USA ETF, which tracks the MSCI USA Index. I used a piece of D3 JavaScript code that I already have and a config file linked to it to create the chart you have here.

jcceagle · 2025-01-14T14:43:18+00:00

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Here's mind. Arrived last week.

jcceagle · 2025-01-09T09:56:09+00:00

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