Data is Beautiful

Very detailed article here: https://www.reaktor.com/articles/why-ive-tracked-every-single-piece-of-clothing-ive-worn-for-three-years

!football@lemmy.world

Learning about the death of the last player who played the Final of 1958, I wanted to know how many of his teammates were still alive and doing it, I learned that the first 1990 World Champion has recently died, so I decided to create this to display this information : visually show how many Football/Soccer World Champions are still alive.

Brazil 1958 is the last team with living players. Brazil 1994 is the oldest with all living players.

The first World Champion to die was Umberto Caligaris for Italy in 1940.

In a couple of months between 1973/1974 saw the first players of Uruguay's 1950, West Germany's 1954 and Brazil's 1970 teams to pass away.

There are no longer any Uruguayan World Champions that are alive. It's the only country in this case.

Source: https://old.reddit.com/r/dataisbeautiful/comments/1fm42h6/oc_football_world_cup_winner_that_are_still_alive/

cross-posted from: https://feddit.org/post/3142575

Source.

Source: https://old.reddit.com/r/dataisbeautiful/comments/1fneq6s/the_tides_of_europe_oc/

Creator: https://old.reddit.com/r/dataisbeautiful/comments/1fm0m2t/oca_map_showing_africa_climate_range_based_on/

cross-posted from: https://sh.itjust.works/post/25337532

Best of luck to Mozilla. Their line on the chart may end soon if they lose funding from Google.

Source: https://eylenburg.github.io/browser_engines.htm

Author: https://old.reddit.com/r/dataisbeautiful/comments/1fhtwgv/oc_north_american_video_game_consoles_release/

cross-posted from: https://qoto.org/users/mapto/statuses/113147786737843592

Friends don't let friends...

Quite good list of good practices for basic graph charting
https://github.com/cxli233/FriendsDontLetFriends
@dataisbeautiful

Source.

Source: https://v-dem.net/documents/44/v-dem_dr2024_highres.pdf page 7

Source: https://v-dem.net/documents/44/v-dem_dr2024_highres.pdf page 9

Source: https://v-dem.net/documents/44/v-dem_dr2024_highres.pdf on page 14

cross-posted from: https://lemmy.dbzer0.com/post/27579423

This is my first try at creating a map of lemmy. I based it on the overlap of commentors that visited certain communities.

I only used communities that were on the top 35 active instances for the past month and limited the comments to go back to a maximum of August 1 2024 (sometimes shorter if I got an invalid response.)

I scaled it so it was based on percentage of comments made by a commentor in that community.

Here is the code for the crawler and data that was used to make the map:

https://codeberg.org/danterious/Lemmy_map

My chart shows population density in all urban areas that have over half a million people. "Urban area" basically means the built up area in and around a city, including its suburbs. The chart would be way too busy if it included labels for each city, so instead I opted to group them by the part of the world they are located in. This shows the striking difference in urban density across different parts of the world.

My data source for both population and population density came from Demographia World Urban Areas, 19th Annual: 2023.08_. This is a regularly updated collection of statistics for urban areas that include population and land area. I made this chart using Google Sheets and edited it with Inkscape.

If you're interested in diving deeper into this data, I put together a spreadsheet of the data and a detailed version of the map with city labels (which is still very cluttered). Enjoy!

Source: https://old.reddit.com/r/dataisbeautiful/comments/1fbbuer/population_density_in_900_urban_areas_across_the/

Collected US 2024 tech job postings from Indeed and embedded them with Open AI text embedding large. Reduced dimensionality and clustered via UMAP and HDBSCAN. Topic modeled with Open AI chat API. Visualized with DataMapPlot. Github pages https://hazondata.github.io/ has full interactive map. I also have real-time insights into tech job postings on my site hazon.fyi

https://old.reddit.com/r/dataisbeautiful/comments/1fakvwv/oc_clustering_250k_tech_job_postings_in_2024/

Source

https://www.chefspencil.com/the-worlds-late-night-dining-capitals/

"Live link: https://perthirtysix.com/tool/birthday-paradox

I built a sandbox that lets you simulate and understand the birthday paradox and few related problems. The birthday paradox tells us that in a room of 23 people, there are 50/50 odds that 2 people will have the same birthday (assuming a non-leap year and that birthdays are totally random, which they aren’t exactly).

I’ve always found these types of problems really interesting and counterintuitive. The “aha” moment for me was realizing that any two people sharing a birthday satisfies the problem, and at 23 people there are 253 different combinations of pairs between them.

I hope you enjoy messing around with the tool!

Built using Vue and p5.js, with probability formulas adapted from Wikipedia."

Source: https://old.reddit.com/r/dataisbeautiful/comments/1f80chg/oc_i_built_an_interactive_simulation_of_the/

Source: https://www.vegansociety.com/get-involved/research/empathy-index

Source: https://www.vegansociety.com/get-involved/research/empathy-index