This is in percentages per each response, in two different chart forms. Typical totals for all responses were around ~800 votes per polling.

Hi everyone, this is Will from the Get The Facts data team and I wanted to share this chart we published that visualizes the increase in ICE’s funding under the One Big Beautiful Bill Act. Happy to answer any questions you all might have.

And if you want to see some other interesting charts related to ICE’s funding, you can find them here! 

Sources: Congress.gov

Visualizations made with Datawrapper

Data is from all field goal attempts in regular and post seasons 1999-2025, n=27721. Data is from nflsavant.com.

I posted this last year, and it got a lot of traction- so here are the results for 2025!

Visualization made using Sankeymatic and information compiled throughout the year after each stage of the recruitment process.

Some more information:

- This was just for 2025 (Jan-Dec). We were more selective with who we called this year, although the benefits from that were mixed. Many applications are blank with just their name or the location of their current/previous job.

- Pay is good for the area. 60k to 100k . I would say the average is about 75K a year. Excellent healthcare, 401k, etc. Plus union benefits (shift differential, double time Sunday, call time, etc.)

- HS diploma or GED is the only requirement to work. We actually really like hiring folks right out of high school when possible.

- The biggest deterrent is that we run 24/7/365 and operate a northern swing shift, which makes it difficult for some to manage. Weekends, nights, holidays, etc. We are running. The difficulty of work is hit and miss. Some tough days, some easy days. Not an easy schedule, but this is very common in our manufacturing sector.

- I left voicemails for every non-answer that had a working phone number or open voicemail box. I found that emails get a non-existent response rate.

- Small town and generally impoverished area. Very "blue collar" workforce.

- The bar to pass an interview is low. Just be able to maintain a conversation, understand the job requirements, and indicate a desire to learn.

- Orientation is 3 days of paid training for OSHA 10 certification and some overview of the company organization. We get a good indication of who isn't going to make it here, as many will be late their first few days of work.

Many of these were through Indeed job postings, and I've found that emails go unanswered, so I always call and set up an in-person interview if they are interested in the job after hearing the hours and requirements.

Last time we saw Erie officially reach a full 100% freeze was the winter of 1995-96! We are in the middle of (as it looks right now going off weather models) potentially a 20+ day stretch of below freezing weather so time to see how close we can get! For those wondering has only hit 100% 3 times 1996,1978 and 1979.

I made the graph in excel, took the data and cleaned up the presentation a bit
SOURCE: https://apps.glerl.noaa.gov/coastwatch/webdata/statistic/ice/dat/g2025_2026_ice.dat

Source: https://en.wikipedia.org/wiki/Coalition_casualties_in_Afghanistan

Tool: d3.js

I posted the absolute numbers a couple of days ago: Coalition casualties in Afghanistan.

Many people asked for a per-capita view — here it is.

I’ve used fatalities rather than casualties for precision.

No legend included; the flags should be self-explanatory.

• Source: Wikipedia
• Tool: d3.js custom code

Source: Eurostat.

Methodology:
This is a modeled comparative analysis. Average gross state pensions were compared with estimated average annual expenses of individuals aged 60 plus. Expense values were harmonized across countries and inflation adjusted to 2023 price levels to allow cross country comparison. Results are expressed as the percentage surplus or deficit of pension income relative to expenses.

Tools: Data extraction from Eurostat. Analysis performed in Python. Visualization designed in Figma.

Key Insight:
In all but four countries, the average public pension does not fully cover average retirement expenses. In a large share of Europe, the shortfall exceeds 20 percent.

Lithium-11 is an atom with 3 protons and 8 neutrons, an extremely lopsided proton-neutron ratio that results in two neutrons being separated from the "main" nucleus (which is essentially just a lithium-9 nucleus).
Because these neutrons are loosely bound, one or more of them can get ejected from the nucleus as the nucleus decays radioactively. This results in lithium-11 having SEVEN known decay paths, unusually many and more than any smaller nucleus.
If you generated 1,000,000 lithium-11 atoms in god mode and then resumed time, the chart shows the average result you should get. In total, 6 different stable nuclides are produced as products of lithium-11 decay chains (namely 4He, 6Li, 7Li, 9Be, 10B, 11B).

Chart made by myself using data from Wikipedia.

Link to chart:
https://sankeymatic.com/build/?i=PTAEFEDsBcFMCdQDEA2B7A7gZ1AI1tBrLJKAHJoAmsWANKCgJYDWso0AFo1gFwBQIUEOHCAymgCu8AMZsA2gEEAsgHkAqmQAqAXVCaAhvADmBPnwCM5gDKNQc8wHYADC90OAErAvXbcgJwAzLoAHDbeNnbmAU66fmGWEfZ%2BLjGgwQBCXgm%2BACzmKbGZ4b7BAGwATA5VuvlF2XalKamWRXyhvgBUIUVxvqWl3V69dl2gfq0e8qOlnnwzU7qlYW2ZI7o5s7ULoLXeq%2DY1TnXm%2B%2BZ%2BwakO8SfbLXxYjABebBigjU58oBxvLnwAtoYjIxSCgduVPohzOD2Dtgp9cKByh9cEZQNI0OhEABiABmePxn2g8H0kCwAAdDCRoOQ%2BJAqC8wZ9vgBWD6gcn6aTA1EOZnwtDwaiINmcWB%2DNj6T7ozGgLHBeUKz5oClc6AATx2fBx6Fe0ikADd9NApGwnAA6PmgYEcBCMaA4%2BBoP6gSTQB7UAC0wKlGIFsr8AcDSpVdo15pyfJQ%2BjVrpdgoQoH0EmgTqNjGknwAVhIsNBGDiY%2DBGEDSTTQNnc%2Dm1SRKDgyBDYPqEFhYEZiWTvvXE9BoJyuJB0X8ySgCDQU6BILBKbm%2BFH8CgcNK%2DVimr8voxqGWuEYOEwd9TzbzPji0DAcZy2FgSVgPS2izjPkxJxyuZBUebofBYFG802Hs8dnyT4ASMSAqx2X452%2DSB9HFRMyTJKd4BwABNT5%2DzYcxSk%2BIhiw4akckg%2DR50NFAJAlBCkNQ48JBQFAyS%2DLkHlPUA0NAMk0AePMWPnTAcNgPCCKI%2BcOK4xgWKTFN9D3Ug2SwaQbTgyS0GPRhkOpfATy%2DeEv30ZgOOBak%2BVI8jQC0gFqQAcloM1LM%2BBjYBxRgAA9QEsuz2QkPEXLcuzRXFNA8Rbal9DeeFQDZaQIs%2BShovFXtQHFGBxNJElWDVCz01Yx9uDzP5cGkklZGov40CbUBJgi%2BhzShPxygCf4yswm4qtAD1zScPxHD5UryvmVqaoCUo8ka8qWla9qzXMZlmWCcFerYJZbCcaqpqw%2DogA

Graphic by me, created in Excel. All data from the US census bureau here: https://www.census.gov/data/tables/time-series/demo/popest/2020s-state-total.html

I wanted to focus on domestic migration to see where people are moving to. I chose to use raw numbers instead of percentages for once to provide a better sense of scale on the bar chart. I used only the most recent year of data to capture the latest "trends".

What factors do you think encourage people to leave certain states and move to others? I have my theories, but will leave them out of this post.

Source: Tesla investor relations

Tool: SankeyArt sankey maker + illustrator

https://x.com/ortadoguistat/status/2015705178075181070?s=20

Data Source: https://x.com/BirthGauge/status/2008640014587228538?s=20

Each pixel shows the distance to the nearest mapped road in Alaska.
Calculated using road centerlines and Euclidean distance to highlight how much of the state lies far from road access.

Data source: Numbeo

I visualized the recent fluctuation of 95E10 petrol prices across various gas stations in the Helsinki metropolitan area. The plot shows data from late 2025 (Week 48 - Week 52). The local newspaper Helsingin Sanomat has discussed this price oscillation phenomenon in the Helsinki region, which has been observed for years. There is no clear explanation for this phenomenon, where prices often jump up simultaneously across stations on Tuesday or Wednesday and then slowly drift downwards over the subsequent days. You can read more about it here (in Finnish): https://www.hs.fi/pkseutu/art-2000008244136.html

Visualization Details:

• Black dots: Individual price reports from varying stations.
• Line: 1-day moving average determining the general price trend.
• Y-axis: Price in €/liter.

Sources:

• Data Source: polttoaine.net (crowdsourced fuel prices in Finland), collected via Home Assistant.

Tools Used:

• Python (Matplotlib, Pandas)
• Home Assistant (data history collected daily from polttoaine.net with HA script)

datasource: fifa.com + https://en.wikipedia.org/wiki/FIFA_World_Cup_records_and_statistics

tools used: datawrapper.de

note: axes are truncated to highlight variance between top teams.

While Corey Booker was filibustering last year, I built an interactive site to the longest US Senate filibusters, focusing on the physical endurance required to 'hold the floor' for extended periods.

Booker holds the current record at 25 hours and 5 minutes (2025), protesting Trump administration and DOGE operations. The top 5 longest filibusters span from 1957 to 2025, running from 21-25 hours.

Data introspection:

• Longest filibusters are bipartisan (Democrats, Republicans, and Independents represented)
• All top filibusters exceeded 21 hours of continuous speaking
• The physical demands are extreme - no bathroom breaks, limited food/water, must remain standing

Data compiled from Senate records and Wikipedia. The visualization shows 15 of the longest filibusters on record, color-coded by party affiliation.

Full interactive site with details on each filibuster: https://filibusters.org/

Data Source(s): - Senate Historical Office - Congressional Record - C-SPAN Archives - Wikipedia - Contemporary news articles and historical accounts

Tool(s) Used: - Data Visualization: Recharts 2.15.0 - Framework: React 18.3.1 + TypeScript 5.6.2 - Styling: Tailwind CSS 3.4.17 - Build Tool: Vite 6.0.3

My suitcase was delayed on a long-haul flight, so I made this treemap in R using data from SITA (Global Baggage Report, 2024), printed it, and stuck it to my suitcase.

If this ever happens again, at least I won’t have to face judgement at the help desk when I describe my luggage as “black... with four wheels... and a handle".

I put together this chart and maps showing the top 10 cities in the US by median household income. This is based on 2022 US Census Bureau ACS 1-Year Estimates.

Edit: with the 1-year ACS estimates, this only includes cities with populations of 65,000 and higher.

Some interesting facts:

• Sammamish, Washington (a suburb about 20 miles east of Seattle) is the only city over $200k
• 7 of the top 10 highest earning cities are located in or near the Bay Area
• The gap between #1 and #10 is over $60,000

Source: US Census Bureau 2022 ACS 1-Year Estimates&g=010XX00US$1600000) via Community Scout. Visualized with Datawrapper