working on another app of mine and hit a little obstacle here, i don't want the generic way of simple bar charts and line charts to be showing data

Or better yet, where to make maps that have a lot of templates I can look through?

- I visualize travel content for my agency (specifally safaris)

- Need something that isn't overwhelming or too expensive (so premium tools won't work for me)

- Ideally it has hover features where I roll the mouse over and see total population and can input the amount of hotels/national parks in the area.

I know a lot of you use more advanced platforms, so I'm hoping for an in-between?

What an interestingly specific sub…. Well. If you’ve got a Homelab and docker installed… CTRoadmap is a map making tool that also takes on the info & documentation you include and puts it into a “handbook” format for ya.

https://www.github.com/NoobCity99/CTRoadmap

Something I've had in my head since 1999 but couldn't build until now. Each image sits in a quadrant that can hold four children, forming a tree you navigate spatially. Built iteratively with Codex, no framework, no database — just a JSON tree and a PHP admin. Best experienced on desktop.

I’ve studied Quantum Mechanics and Special Relativity quite a bit and I’m wanting to stress test a "graphing calculator" that I’m working on. Give me scenarios to visualize so that I can make it better and I’ll publish a screen recording of the result

Hey Fam, I have a case that is ongoing in High Court. I need someone good in creating Graphical Analysis of the entire Case. I have generated structure using AI but a clear and structured case analysis is needed for story telling our case and which will be displayed on our website.

Hi everyone! I created this fun website where the toss-up Senate elections can be tracked using needles similar to New York Times. It currently uses a combination of polling, candidate baselines, and partisan lean of each state to build the current needles. On election night, they will live-update as results come in. Feel free to play around, you can also simulate the election at the bottom. Hopefully yall enjoy :)

I’ve been working with agricultural physicists and agronomists here at ICAR, and we were discussing about how visualisation or simulation is being handled in today's research scenario. I would say all standard tools we use are great for data output and backend math, but they suck it when it comes to intuitive, 3D visual simulation of growth progress, disease spread, or soil-water flux over time.

For those of you running these kinds of simulations, how do you handle the visualization component? Do you rely on static charts, or have you ever felt the need for a live, 3D 'digital twin' environment where you could scrub through time-series data to see how physiological factors are affecting the canopy and field in real-time?

I am currently working on a way to integrate this into the Python data science stack, and I’m curious if this level of visual interactivity would actually change your research workflow, or if you prefer sticking to the traditional table/graph-based analysis. I strongly think that such a tool which allows for full freedom and visualisation impacting every crop would genuinely revolutionize Agricultural Research.

Created a free site that shows Median Home Prices by counties and cities.

Kinread.ca - interactive site that lets you plot your literary tastes against 703K other users.

Data source: UCSD Goodreads dataset (Wan & McAuley), ~703K users, ~103M ratings. Tools: Python — weighted Pearson correlation for the similarity graph, Louvain community detection (~600 communities/reader clusters with an additional 505 sub communities/clusters for the larger groups), UMAP for the 2D projection. Rendered with deck.gl (WebGL) — ScatterplotLayer for the ~703K reader points, TextLayer for the cluster labels.

I just finished this website last week! Each dot is one reader, fully zoomed out they blend together into a mass of colours so I’ve included some progressive zoom shots to show how it looks close up. Distance roughly means taste similarity (though distance in the projection is non-linear and becomes increasingly distorted the farther you go).

The big central multicoloured mass is the connected mainstream of English-language fiction, and the isolated islands are genuinely separate reading communities (the teal blob on the far left that’s detached from the main plot is a cluster of readers of Arabic-language titles, who share almost no books with the main cohort for example).

Background: I've been wanting to build this for ten years — my first version was an Excel VBA scraper making scatter plots of rating alignment between Goodreads profiles. This year I finally built it properly: kinread.ca lets you paste your own library export (Goodreads, StoryGraph, or LibraryThing) and see where you land on this map, it also serves book recommendations based on what other readers who read and rate things like you enjoyed. It’s different from other recommendation algorithms because it doesn’t just serve books that are similar to what you’ve read previously, but it takes into account all the books you’ve ever rated— not just the ones you loved but also the ones you hated or were indifferent about. Also; it works really well for people with eclectic tastes— if you love non-fiction books about quantum computing, 18th century French poetry and books about time traveling wizards while eschewing pop psych books or stories about teenage vampires then it’ll find the people with similar readings tastes to you (if they exist).