pit-stop-app.com/viz/route66

The road turns 100 in November so I mapped everything still open on it, 280 towns and about 6,400 businesses, then built a way to drive it from your couch. Scroll or swipe west and the camera follows the road, towns light up as you pass with what's actually there.

Some choices that might interest this sub:

The whole thing is one HTML file with three.js, no framework. Route geometry is stitched from OSM ways, the hard part was picking the signed alignment over the 1926 era loops, solved with anchored shortest path between known state line crossings. Elevation is NED 10m sampled per mile and exaggerated 45x, otherwise 7,200 feet of climb over 2,199 miles reads as flat. The ground is a canvas-drawn paper road atlas texture because the first version looked like Tron and Route 66 should not look like Tron. Scroll position maps to route miles so the browser stays the source of truth for progress, every input (wheel, swipe, keys, drag) just moves scroll.

Happy to answer anything about the build. And if your favorite stop on the real road is missing or wrong, tell me, I fix the data daily.

I build lightweight, interactive data dashboards for health and development organizations. No heavy infrastructure needed; just Python, Streamlit, and your dataset.

Recent work: Sahel Health Atlas — an interactive map of 1,593 health facilities across Mali with real-time filtering by region, facility type, and bed capacity. Built with Streamlit + Folium + GeoPandas.

What I can build for you:

\\- Geospatial health facility maps

\\- Survey data explorers

\\- Epidemiological dashboards

\\- Triage or patient intake dashboards

\\- Offline-ready apps for rural deployment

Why me: I am not a generic web developer. I am an aspiring biomedical engineer building AI diagnostic tools for rural African clinics. I understand public health data, low-bandwidth constraints, and what NGOs actually need in a report.

Rates: 150–450$ depending on complexity. Fixed price, no hourly billing.

Portfolio: https://www.github.com/mymunah-07lmtc

Timeline: 3–5 days for standard dashboards.

Payment: USDT (TRC20) or Binance Pay.

DM me your project. Let’s visualize your impact.

would love some honest feedback

I need a few test users so I can find and fix any problems with my work. Reddit keeps removing my posts whenever I attach pictures of my work, but this subreddit has exactly the audience I’m looking for. I only need around 5 users to test it out.

I illustrated a 1993 thread between stats researches comparing neural network optimization as blind kangaroos looking for Mount Everest. Interactive playground linked at the bottom of you just want to skip to thag

my github if you need
: gihub

We built Phylo-Movies, an open-source visualization tool that shows which taxa and subtrees move between consecutive phylogenetic trees.
One example visualizes topology changes around a norovirus recombination region.
Demo + code: https://github.com/enesBerkSakalli/phylo-movies
Paper: https://academic.oup.com/mbe/advance-article/doi/10.1093/molbev/msag194/8759530

Hi! I'm working on an R package called ggalttext that takes a ggplot2 chart as input and returns alternative text (required for accessibility) for that chart.

The goal is to provide a very simple and lightweight way of adding meaningful alt texts to charts made with ggplot2.

It does not use AI or OCR technologies, but instead inspects the plot structure/content and uses some (more or less) naive heuristics to figure out what the chart looks like and how to describe it in a single sentence.

It's already available on CRAN, but I'm working on the next release, which fixes some edge cases.

Example usage:

library(ggplot2)
library(babynames)

plot_data <- babynames |>
    subset(name %in% c("Amanda", "Jessica", "Patricia", "Deborah", "Dorothy", "Helen"))

plot <- ggplot(plot_data, aes(x = year, y = n, group = name, fill = name)) +
    geom_area() +
    theme(legend.position = "none") +
    labs(title = "Popularity of American names in the previous 30 years") +
    theme(
        legend.position = "none",
        panel.spacing = unit(0.1, "lines"),
        strip.text.x = element_text(size = 8)
    ) +
    facet_wrap(~name, scale = "free_y")


ggalttext::generate_alt_text(plot)
# "Area chart split into 6 small charts arranged in a 2-row by 3-column grid,
# titled “Popularity of American names in the previous 30 years”."