How Judaism, Christianity, Islam, Hinduism and Buddhism branched over 9,000 years, each split dated by its earliest surviving evidence.

A few days ago I posted which subreddits each age group is most overrepresented in (https://www.reddit.com/r/dataisbeautiful/comments/1xf6gt3/). The pushback I got most: people on Reddit lie about their age, self-reported data can't be verified, it's just noise.

Fair point. So instead of arguing, I checked.

Chart 1: do people age on schedule? If people made their ages up, there'd be no pattern over time. So I took everyone who stated their age in two posts or comments at least a year apart, 2.3 million people, and checked whether their age went up by the time that actually passed. 49% aged exactly on schedule and 68% were within a year. The outlined bars are the same people with their second age swapped for a random stranger's, which is what noise looks like: 3.5% and 7%. Gender too: 5.4M people stated it twice and 96% said the same thing both times.

First, what isn't a lie. Plenty of numbers look like ages and aren't: "I'm 99 farming" is a RuneScape skill level, "91F" is an army job code, "Female, 26, nurse" is someone guessing about another person. I filter that out wherever I can spot it, and nobody's age comes from one comment anyway: it's the middle of everything that person has said, so a stray number gets outvoted.

Chart 2: so where do everyday Redditors lie? I flagged every age claim 10+ years off from what that same person usually says, then read 20 random flagged posts in each of the 100 biggest everyday subreddits. Three AI reviewers per post, and a lie only counts when all three agree. Result: about 1 in 270 age claims is a lie. Even the "worst" one, r/indiasocial, is around 2%. When people do it, they mostly add years: 38 in the post, 26 everywhere else. Think a r/tifu story told by a 50-year-old from an account that's 27 in every other post, or 30-somethings saying they're 15 in r/teenagersnew.

Chart 3: where it spikes. Dating subs are even more honest than average (0.15%). Lying only takes off in a few adult subs: 8.4% of age claims in cheating and cuckold subs, 3.5% in "mature women" ones. 91% of those posts are written as a woman and 65% come with a Snapchat handle. Promo accounts posting as a 45-year-old woman, who are 28 in their other posts.

So: most people just say how old they are.

Full write-up with five more checks, where this method is weaker, and the CSVs: https://kissmypost.com/research/reddit-self-reported-age-gender-accuracy

Source and tools in the first comment.

carouselopedia.org
This is a fun project I spun up this weekend. It's a wiki-like site to collect data on carousels and what horses are lined up where.

Along the way, I came up with a cool diagram to indicate horses, other animals, and cups/chariots, as well as showing partial or missing data.

It's not open for public edits yet, but I'm excited to get it a lot more fleshed out when I do.

This is part of my overall analysis to find out whether companies that talk more about AI tend to perform better than their quieter peers in the stock market. Full interactive piece, with the rest of the analysis: https://milesmeters.com/form-10-k-ai/

Source: 2,438 annual reports (10-Ks) filed with the SEC - every S&P 500 company's last report before ChatGPT launched (Nov 30, 2022) plus every report since. I counted AI terms per 10,000 words and labeled each mention hopeful (selling, using, or investing in AI) or worried (risks like competition, regulation, and security).

Brussels is known as the chocolate capital of the world, so I wanted to know how many chocolatiers it actually has.

To count them I used the Google Places and OpenStreetMap API, merging the two and removing the duplicates, to give a total of 176 (in the Brussels Capital Region).

Each one is shaded by when the chocolatier was founded: dark chocolate for pre-1900, milk for 1900 - 2000, and white for post-2000. The 40 I couldn't find a founding year for are left off. For chains they're all coloured by the earliest founding year, not on a store-by-store basis.

I printed a base map of the Brussels-Capital Region on A0 paper, and used Belgian chocolate (Callebaut) callets as the data points.

This is one in a series of charts I'm making about chocolate, out of chocolate. The pièce de résistance (literally) is a chocolate bar that is also a chart. I'll share that here soon, and share the code for this map as part of the larger project.

Interactive live version with all updates

Sources:

• EPA ratings
• EIA prices: gas and diesel (week of Oct 19), home electricity (August 2026 residential, 18.16¢ a kWh)
• The 25 best-selling models from January to September 2026, from the carmakers' own sales reports, plus the next 5 best-selling EVs and the Prius for comparison. Each row is a version, not a model, so models sold as gas, hybrid, plug-in hybrid or diesel get a row for each. Plug-in hybrids split their miles between battery and gas by EPA's estimate for an owner who charges every night.

Tools: Kadoa for the data, Python, HTML and SVG for the chart. Claude did the car outlines from each model's published length, height and wheelbase.

EDIT:

• Prices vary a lot by state, so I added a state picker to the live version.
• The cities are only a ruler for distance/for scale.
• Added plug-in hybrids and the Prius. At 53 mpg the Prius goes 1,237 miles on $100, just behind the slowest EV (Rivian R1S, 1,278).
• Added a toggle for fast charging vs home charging
• metric units added

What you're looking at:

• Top: BepiColombo's path seen from above the Sun. The rings mark the flybys.
• Bottom: its distance from the Sun over time. The wobble getting tighter and dropping toward Mercury's orbit is the spacecraft working its way in.

Why "on average": Venus comes closer at its nearest, but it also spends long stretches on the far side of the Sun. Mercury never strays far from the Sun, so it never gets very far from us either.

And yet it's one of the hardest places to get to. Falling toward the Sun speeds you up, so the whole trip is about getting rid of speed. That took one flyby of Earth, two of Venus and six of Mercury itself, each one handing a little of the spacecraft's energy to the planet. Orbit insertion is planned for 21 November.

The Earth flyby was in April 2020, which makes BepiColombo one of the few visitors anyone had that spring. And even spacecraft run late: a thruster problem in 2024 added a year.

Interactive version, where you can drag the timeline and change the speed: https://dojo.amcharts.com/demos/bepicolombo/

How I ranked these

I took every residential block in the five boroughs with 4 or more homes that have their own front door (24,256 blocks; lobby buildings don't count, which is why Manhattan is so sparse) and gave each one four percentiles within its own borough, a quarter each: front doors per 100 m of street, owner occupied and single family homes, kids aged 5 to 14 per home, and few pedestrian crashes within 150 m. Brighter blocks score higher. Lime patches are groups of touching blocks in the top quarter of their own community district. The labels give each borough's district with the most top quarter blocks, and the spot locals name most often in old Reddit threads and local news.

Data

Homes and units: New York City's parcel records, with building heights for townhouse rows

Kids and ownership: US Census ACS 5 year estimates, 2020 to 2024

Pedestrian crashes: NYPD Motor Vehicle Collisions on NYC Open Data, a pedestrian injured or killed, since 2022 (Brooklyn since 2023)

Districts: NYC Planning's 2020 community districts; Staten Island uses its 16 neighborhoods because it has only 3 districts

Tool: MAIA, a mapping tool I work on

Caveats

obv the data doesn't account for door-to-door observations. (nor does it account for which apartments or businesses give the biggest candy bars)

Each borough is scored against itself, so Canarsie is Brooklyn's best, not the city's best.

Kids and ownership are area estimates for the blocks around a home, never one house.

Only 992 of Manhattan's 2,623 residential blocks have 4 or more front doors, so its map is mostly empty on purpose.

Marble Hill is counted with Washington Heights and Inwood.

The crash feed has nothing after June 11, 2026.

https://tpmblegal.com/chicago-halloween-pedestrian-crash-analysis/

Halloween was on a Friday last year, so it makes sense why the holiday's crash counts & pedestrian crashes spiked last year compared to its same-weekday average. However, this year Halloween falls on a Saturday, so I can only imagine what the #s would be like for this year. This is only for Chicago, but I would imagine a similar pattern of increased crash counts & pedestrian accidents will occur throughout the US, especially in major cities.

This had some counterintuitive findings. I expected cities like NY and SF to top the list. The conventional wisdom is that rent should be around 30% of one's gross (pre-tax) income.

Analysis: In 2024 the typical renter household in the Miami metro spent 38.6% of its income on rent and utilities, the most of the 25 US metros with the most renters (next: Orlando 35.8%, Tampa 35.6%). Nationally the figure barely moved, 31.6% in 2010 vs 30.9% in 2024, because median gross rent rose 74% ($855 to $1,487 a month) while median renter household income rose 78% ($30,671 to $54,446 a year). Rent took a bigger share of income in 9 of the 25 metros, most in Las Vegas (+3.7 points; rent +76% vs renter income +52%) and Houston (+3.1; +74% vs +55%), and a smaller share in 15, most in Detroit (−2.2) and Chicago (−2.1). Part of why renter incomes kept pace may be who rents: Harvard's Joint Center for Housing Studies (America's Rental Housing reports) has noted growth in higher-income renter households since 2010. This data can't separate that shift from raises for people who were already renting.

Caveats: the figure is a median over renter households paying cash rent, so half pay more and half less; it doesn't show how many renters are severely burdened. Each value is a survey estimate with a margin of error of up to about a point for a single metro (Miami ±0.7), so small changes may be noise. Dollar figures are current dollars, not adjusted for inflation. 2024 is the latest 1-year ACS release.

Sources: [US Census Bureau, American Community Survey 1-year estimates](census.gov/programs-surveys/acs), 2010 and 2024: tables B25071 (median gross rent as a percentage of household income), B25064 (median gross rent), B25119 (median household income by tenure) and B25003 (renter households), read from the public ACS summary files at www2.census.gov. The 25 metros are those with the most renter households in 2024 (Puerto Rico excluded), named by their first city. Hollow dot = 2010, filled dot = 2024; red = rent took a bigger share of income than in 2010.

Tool: Artio for the data pipeline and chart; the chart is SVG drawn in Python.

Link: https://www.artio.so/dataviz/pages/2026-10-26-rent-vs-income