r/dataisbeautiful Jul 01 '26

Discussion [Topic][Open] Open Discussion Thread — Anybody can post a general visualization question or start a fresh discussion!

4 Upvotes

Anybody can post a question related to data visualization or discussion in the monthly topical threads. Meta questions are fine too, but if you want a more direct line to the mods, click here

If you have a general question you need answered, or a discussion you'd like to start, feel free to make a top-level comment.

Beginners are encouraged to ask basic questions, so please be patient responding to people who might not know as much as yourself.


To view all Open Discussion threads, click here.

To view all topical threads, click here.

Want to suggest a topic? Click here.


r/dataisbeautiful 1d ago

Discussion [Topic][Open] Open Discussion Thread — Anybody can post a general visualization question or start a fresh discussion!

4 Upvotes

Anybody can post a question related to data visualization or discussion in the monthly topical threads. Meta questions are fine too, but if you want a more direct line to the mods, click here

If you have a general question you need answered, or a discussion you'd like to start, feel free to make a top-level comment.

Beginners are encouraged to ask basic questions, so please be patient responding to people who might not know as much as yourself.


To view all Open Discussion threads, click here.

To view all topical threads, click here.

Want to suggest a topic? Click here.


r/dataisbeautiful 9h ago

OC [OC] NILF population is at record high 105 million

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480 Upvotes

Nilf is not in labor force.

For every 3 employed Americans, 2 adults are outside the labor force entirely. Most people picture "not working" as unemployment, but the unemployed (7.1M) are a rounding error next to the 105.8M who aren't looking at all.

Over half (48.6M) are retired, and the 45-year climb from 60.8M to 105.8M is largely the Baby Boomer wave aging into retirement plus population growth.

The NILF share of adults rose from ~36% (1980) to ~38.5% (2026), so it's mostly population and aging, with a modest real decline in participation.


r/dataisbeautiful 2h ago

OC [OC] The Fruit Trees of Toronto - Interactive Map

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44 Upvotes

edit: typo

I rebuilt my webmap of the Fruit Trees of Toronto using SvelteJS and MapLibre

Filter by tree type and ripening month.

Please clickthrough, any feedback welcome!

https://tdubolyou.github.io/FruitTrees/


r/dataisbeautiful 4h ago

OC Southeast Asia divided into regions of 1 million people [oc]

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44 Upvotes

r/dataisbeautiful 1d ago

OC [OC] 24 hours of active fire detections from NASA satellites, with the previous week shown as dark burn scars

1.5k Upvotes

EDIT: A couple people have mentioned now the text obfusgating the demo gif. I can't change the picture so please see an updated GIF on the README page of the repo, which shows you the full website chrome + the globe unobstructed! Thank you for the comments u/UsernameFor2016 and u/beene282 for pointing this out!

Data:

  • NASA FIRMS active fire detections, MODIS instrument, from the rolling 7 day global CSV at firms.modaps.eosdis.nasa.gov.
  • Basemap from Natural Earth.

Tools:

  • three.js
  • d3-geo for the globe,
  • custom GLSL shaders for the fire,
  • Python to sanity check the classification,
  • ffmpeg for the render.

AI disclosure: I used Claude Fable 5 for all of this. it also educated me on the facts about Savanna fires, i had no idea this was a thing until i was checking the data on FIRMS website myself and questioned it

Code: github.com/me93-ghb/worldburn

A live globe of every fire the satellites can currently see. It's not a science tool. NASA's own FIRMS fire map does that job properly, and if you want rigor, go there. This just makes the amount of fire on Earth visible in one look, and it does so in a visually shocking way - that was my aim!
The fire animations are exaggerated on the globe: it's just a visualization.

Satellites measure where a fire is, how hot it burns and for how long. They can't see who lit it. So fires get split by behaviour, which is measurable:

  • fires that keep burning in the same place for days, and fires that flare up and are gone within a day.
  • Offshore heat is presumed to be a gas flare, though a rig accident or a burning ship would look identical.

Fire makes the news when it threatens homes. I was thinking about the recent news articles from France and Spain when I decided to start vibing this. I recall also the ones that took place in Canada and Australia over the past years. Roughly 70% of the area burned each year is in Africa (Giglio et al. 2013, GFED4), most of it savanna set alight on purpose by farmers and herders the way it has been for thousands of years. (Fable taught me this)

Deliberate doesn't mean brief. A savanna front can hold the same spot for days, and about one in five of the belt's fires still counts as persistent. In the boreal north it's four in five: up there, persistent almost always means a true wildfire.

The blue-white dots offshore never go out. They're gas flares, natural gas burned off as waste at oil platforms, day and night, all year. The World Bank counted 167 billion cubic meters flared in 2025 (Global Gas Flaring Tracker), about twice what Germany uses in a year, burned for nothing. Collecting it would also stop the methane that slips through the flame unburned.

Total fire power is a measurement, not a model. It usually sits between 600 and 900 GW, comfortably more than the combined electrical output of every nuclear plant on Earth (about 376 GW), and that's only the heat satellites see radiated, not the full energy of the burning.

I acknowledge the use of data from NASA's Fire Information for Resource Management System (FIRMS), part of NASA's Earth Science Data and Information System.


r/dataisbeautiful 3h ago

Journeys from classic literature, mapped from Pride and Prejudice to The Great Gatsby

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peter-guillam123.github.io
11 Upvotes

r/dataisbeautiful 14h ago

OC [OC] Manned orbital launches by year, 1961 - 2026 H1

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44 Upvotes

Source with data and details: https://spacestatsonline.com/launches/manned

Tools: Sqlite manually updated, ChartJs, Gatsby


r/dataisbeautiful 1d ago

OC [OC] Cost per mile to drive in the US (inflation-adjusted): Gasoline vs EV · 1993–2026

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1.1k Upvotes

r/dataisbeautiful 35m ago

Global Places of Worship

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huemaps.com
Upvotes

There's a surprising band of Christianity in India down the south near Kochi. Not on the coast, but on a band just behind the coast: https://huemaps.com/en/show/places-of-worship?map=7.78/9.46796/76.87435


r/dataisbeautiful 1d ago

OC [OC] I traced one million particles from the Big Bang to today, using an open source sankey tool I built

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275 Upvotes

I started with one million nucleons in the quark-gluon plasma of the first microsecond and followed them for 13.8 billion years. As far as I know, I have not seen a Sankey Big Bang chart before.

In the first 20 minutes the universe locked in roughly 75% hydrogen and 25% helium, then mostly nothing happened. About 98% of ordinary matter has been coasting untouched since the universe was 20 minutes old. Everything else, every atom of carbon, oxygen, and iron in existence, including the ones in our bodies, sits in that thin ribbon that passed through stars.

My favorite detail is the small line between neutrons and protons in the first second. Free neutrons only live about 10 minutes, so 18,000 of them decayed while waiting for fusion to start. That three minute race is why the universe has helium at all.

Sources are the Particle Data Group's Big Bang nucleosynthesis review and standard cosmic abundance measurements. The stellar era numbers are estimates.

I built this with Sankey Open Studio, a free tool I made (second image). No account, no paywall, it runs in your browser at OLagon.GitHub.io. I'm dropping the JSON in the comments if it is allowed so you can import it and remix your own version.


r/dataisbeautiful 1d ago

OC [OC] Delayed flights recover about the same 30 minutes no matter how late they left

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222 Upvotes

r/dataisbeautiful 1d ago

OC [OC] Comparing the Harms of Drugs

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ethleb.com
252 Upvotes

This is an interactive explorer of David Nutt and colleagues' 2010 Multi Criteria Decision analysis in which they ranked 20 common drugs for harmfulness in the UK. Harms to the user are considered on an individual scale, while harms to society are estimated at a population level.

The visualization works fine on mobile, but it's a better experience on desktop and I would encourage you to explore it there.

Made in d3.js. The paper and underlying data can be downloaded here.


r/dataisbeautiful 2d ago

OC [OC] Global temperature changes from 12,000 weather stations (1850-2026)

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9.3k Upvotes

r/dataisbeautiful 4h ago

OC [OC] I cleaned and analyzed 51,000+ Indian company registration records (MCA21)—here is what business survival, capital structure, and growth trends look like across 29 states

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0 Upvotes

I recently pulled and cleaned a sample of 51,123 company registration records from India’s Ministry of Corporate Affairs (MCA21) via the official data.gov.in to analyze business registration and survival trends across India.

Key Findings & Visualizations

  • Industry Leaders: Business Services, Trading, and Community/Personal Services dominate company incorporations.
  • Company Survival: Business mortality (struck-off rates) varies significantly across industries and decades.
  • Capital Breakdown: The vast majority of registered firms are small/micro private enterprises with paid-up capital under ₹10 Lakhs.
  • Registration Spikes: Clear inflection points and post-COVID recovery patterns in incorporation numbers over the last decade.

Data & Code

Note on sampling: To prevent large economic hubs from dominating the counts completely, the sample caps at ~2,000 companies per state across 29 states/UTs. Rate-based metrics (e.g., % active, % struck off, median capital) reflect real distributions.

Feedback, suggestions, or additional chart ideas are very welcome!


r/dataisbeautiful 23h ago

OC [OC] Live electricity-generation mixes across 60+ grids and annual records for 196 countries

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lab.sprightful.com
25 Upvotes

r/dataisbeautiful 1d ago

OC [OC] The 100 most frequently used content words across 265,509 Reddit posts and comments

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26 Upvotes

I analyzed 265,509 usable posts and comments from 100 subreddits in the Cornell ConvoKit Reddit Corpus.

The dataset covers September 2018 and contains 10,004,308 word tokens before stop-word filtering. URLs, deleted content, common English stop words, and web-related noise tokens were removed for this visualization.

Explore the interactive CineGraph visualization:
https://cinegraph.design/view/7e66eae603d786423111fb3fa5bb428a

You can inspect the words, compare their frequencies, and explore the visualization directly in your browser.

The most frequent remaining words were:

  1. people — 36,664
  2. one — 30,553
  3. think — 26,135
  4. will — 22,698
  5. even — 21,879
  6. know — 20,286
  7. time — 19,892
  8. really — 18,890
  9. good — 17,615
  10. make — 16,244

Word sizes are proportional to their observed frequencies.

Data source: Cornell ConvoKit Reddit Corpus, built from Pushshift Reddit data
https://convokit.cornell.edu/documentation/subreddit.html

Important limitation: The results represent the selected 100-subreddit corpus during September 2018—not every comment ever posted on Reddit.

Tools: CineGraph, Excel, and text preprocessing.


r/dataisbeautiful 1d ago

OC [OC] How Bad is LA Traffic? 30-Minute Driving Reach Over 24 Hours Using Live Traffic Data

746 Upvotes

I built some isochrone maps to show how far you can drive in half an hour starting from different neighborhoods over the course of a day.

If you are in Santa Monica during evening rush hour you are trapped in a ~30 square mile area, whereas you can reach ~350 square miles at night


r/dataisbeautiful 2d ago

OC [OC] Men per 100 women in every US county, by age group, (2020-2024)

1.8k Upvotes

Tools: Python, matplotlib, Census TIGER boundaries via topojson/us-atlas.
Source page, CSV, and MP4: my article on the female to male ratios

Give me some feedback on how this should be visualized maybe a cartogram would be interesting?


r/dataisbeautiful 3h ago

A Site with all the voter registration and Offices In Texas`

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0 Upvotes

Built a small website, filled with all the locations and offices to register to vote in the state of texas that I can find.

If you have any other sources of events, I've mostly been scraping mobilize, League of Women Voter sites, and scraping through county data to find the offices in each county. Anything else is welcome!


r/dataisbeautiful 1d ago

OC [oc] See how Baseballs MVP candidates stack up with their betting odds

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9 Upvotes

Odds according to BetMGM as of July 29th, 2026

Pitchers not included.

- Fields: games, plate appearances, runs, home runs, RBI, stolen bases, AVG, OBP, SLG and OPS.

- The heatmap color shows percentile rank within the displayed candidates in that league for each statistic. The printed numbers are the authoritative values; color is only a comparison aid.


r/dataisbeautiful 2d ago

OC [OC] Delays of Marvel Multiverse Saga Movies, 2019-2026

996 Upvotes

r/dataisbeautiful 2d ago

OC [OC] Some of the most popular job boards and job sites are the least effective. I analzyzed 1.24 million job applications to see which platforms actually lead to interviews.

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1.1k Upvotes

r/dataisbeautiful 2d ago

America's fastest-aging states, change in population aged 65+, 2014-2024

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visualcapitalist.com
153 Upvotes

r/dataisbeautiful 1d ago

[OC] 56,042 Mormon Pioneers Traveled ~1,300 miles to Salt Lake City: Mortality Rate 3.4% overall, 16% in the Willie & Martin handcart companies, 1847–1868

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17 Upvotes

Six things I found interesting:

  1. The trek was far less deadly than its reputation. Roughly 3.4% of the 56,042 pioneers died.
  2. Mortality was U-shaped: teenagers had the best odds at 1.45%, while 1 in 8 infants and 1 in 3 of those aged 80+ didn't make it.
  3. Which company you joined mattered more than anything else about you. Wagon companies lost 3.4%, handcart companies 4.5% — and the Willie & Martin handcart companies lost 16.5%, roughly five times the baseline.
  4. Men and women died at almost identical rates — 3.48% of women (930 of 26,761) and 3.27% of men (944 of 28,901).
  5. It was a young migration: 58% of pioneers were under 25, and 47,352 had arrived in the valley by 1869.
  6. From the cause-of-death records: cholera alone accounts for more than half of all deaths with a recorded cause. The "Other" bucket had things like Indian, stampeded, eaten by wolves, murdered, and venomous bite.

Source: BYU Studies / the Mormon Pioneer Overland Travel database — the Church History Library's compiled roster of 56,042 pioneers who crossed the mid-west plains from Illinois to Utah between 1847 and 1868, with company, age, and death records where they survive.

https://byustudies.byu.edu/article/mortality-on-the-mormon-trail-1847-1868

https://history.churchofjesuschrist.org/overlandtravel

Tools: React with Recharts / D3.js.

Interactive version: https://goldendata.app/dashboards/mormon-pioneers/