An interactive legend color picker is coming to the next release of R's mapgl package. Specify a list of color ramp functions when you generate your palette for mapping; your data will automatically re-style with no need for Shiny. Learn more: walker-data.com/mapgl/articl...

Lots of new features landing in R's mapgl package as it approaches an 0.5.0 release. Today's drop: - An interactive color ramp picker for your legends - Native bivariate choropleth mapping Learn more: walker-data.com/mapg...

Not "flashy" for social media, but some useful quality-of-life features have landed in the development version of R's mapgl package: - Bezier curves and Bezier polygons in the draw control; - A coordinates control to track your mouse position (decimal or DMS);

In geospatial right now there's so much focus on AI and automating our work. But I still think there's room for hands-on exploration and careful, expert-guided spatial analysis. Just recorded this quick walkthrough on some brand-new features in mapgl. riverside.com/shared/expor...

spopt, an R package for spatial optimization, is now in general release on CRAN. spopt-r is inspired by the Python package of the same name. Features include: - Regionalization algorithms for building contiguous districts / territories; - Facility location solvers;

Putting Codex 5.5 through its paces today. Some really cool (and useful) features, like interactive attribute editing, will be landing in #rstats's mapgl shortly...

Mapping healthcare jobs clusters in Texas cities. Explore and filter the data yourselves: walker-data.com/free...

Clustering is a highly effective technique for visualizing dense geospatial point data. With freestiler, you can build cluster-aware tilesets that intelligently aggregate points until you hit a desired max cluster zoom level. Shown here: visualizing 5 million points smoothly with clustering.

146 million US jobs. Styled by category on a fast, filterable interactive map. Explore it here: walker-data.com/freestiler/l... The map is powered by {freestiler}, a Rust-powered vector tiling tool that is now available in general release on CRAN.

Visualizing a time-series of Texas mining, quarrying, and oil & gas extraction jobs (NAICS21) by Census tract between 2002 and 2023 in 3D. Featuring a native slider control for R's mapgl package, currently in development.

A new release of the mapgl R package (0.4.6) is now on CRAN. Get your hands on some major updates: - Static map helpers for image output / inclusion in Quarto reports; - Support for categorical rasters; - The latest @Mapbox GL JS with native PMTiles support

Facility and route optimization on road network graphs can solve countless problems across many industries. However, these solvers often require expensive software to set up and run them, or expensive, rate-limited travel-time matrix APIs. The spopt-r R package offers a solution.

🎯 [TIP de R - RECURSO 📚] ¿Mapas interactivos sin servidores externos? Con {freestiler} creá archivos PMTiles desde R, ¡súper rápido y sin dependencias! Ideal para Shiny/Quarto. Más info: walker-data.com/freestiler/a... ✍🏽 @kylewalker.bsky.social #RStats #RStatsES #Rtips #DataScience

The Huff model is the classic algorithm in retail spatial analysis - and you can now use it in R. Predict: - Which store a customer is likely to visit - Sales potential per location - How new stores reshape the competitive landscape Learn more: walker-data.com/spop...

New in spopt-r: optimized corridor routing on cost surfaces. Vignette: how to optimize a route for a produced water pipeline in Appalachia. Build a friction raster from inputs like terrain & land cover, then find the least cost path and evaluate diverse scenarios. walker-data.com/spopt-r/arti...

An important tech use-case for LLMs that isn’t pure coding is deploying and managing cloud services For example, Google Cloud Platform is powerful but a total maze to navigate LLMs help me work through the menus, understand the CLIs, and prep deployment scripts

Just implemented: support for categorical {terra} rasters in R's mapgl. Shown here: 7.6 million 300m x 300m grid cells across Texas derived from the 2024 NLCD, running fast natively in MapLibre. Closes a 2-year-old issue - was one that was more difficult to figure out than it seemed!

Teaching Gemma 4 (26b MoE) how to map Census data in R via OpenCode & oMLX in the Zed IDE. It's the first local LLM I've used that gets me real-time responsiveness. Running on a MacBook Pro M2 MAX, 64GB RAM. Not as smart as the frontier models - but it's running for free on my own hardware.

Set up Gemma 4 (26b MoE) via OpenCode and omlx for agentic coding on my MacBook It’s no Opus 4.6, but this is the first local model I’ve used that is actually capable of real work on my laptop

Can AI map land data in survey plats? Absolutely, if you set it up right. Shown here: extracting the surface hole, penetration point, and bottom hole coordinates from a permit plat PDF and plotting them with the lateral on an interactive map.

The freestiler R / Python package has been around for a month now, and it's proving to be one of the most useful tools I've built. Vector tiles are a must for high-performance visualization of large geospatial datasets, but creating vector tiles has long been tricky without specialized expertise.

New in the R mapgl package: static maps! I developed mapgl to bring my favorite interactive mapping libraries to R. But - interactive maps are by definition hard to share in non-interactive formats. I'm rolling out a couple new functions I'm already finding useful:

I'm struggling with an answer to "Can you share the code?" I've always been a big believer in open source software. I built my career on it. When I post a cool project / demo, inevitably I get the question "can you share the code?"

850,000 parcels in New York City. All visualized on an interactive map in 3D by estimated market value per square foot. Filtered dynamically in the browser with an interactive legend.

Our beloved Claude - even with access in this case to multiple years of conversations with me about mapping - defaults to a year-and-a-half-old release of MapLibre. A large percentage of people using AI uncritically are actually 18 months behind. Use this to your advantage.

A personal and professional goal of mine is to always be using and developing tools that Claude doesn’t know about yet by default

This is why I'm so excited about my new R/Python package, {freestiler}. I connect to a 146M row @duckdb.org database; generate vector tiles for 2.8 million jobs in CO from a query; serve the tiles and visualize on a @maplibre.org map. All in seconds! Get started: walker-data.com/freestiler

I work with AI agents daily. It is becoming more and more difficult to tell between when answers look right and are right, and when they look right and are wrong. Even more difficult: when answers look right but are suboptimal. Take the human out of the loop at your own risk.

An irony that's not lost on me: My older R packages that I wrote by hand have limited to no test coverage, in large part because of how time consuming it is to write tests, whereas; My newer, LLM-assisted R packages have comprehensive test coverage

Another update to R's spopt-r package: you can specify "required" and "candidate" facilities in max coverage / location-allocation solvers Brief demo: choosing the best new fire stations from candidate points in Fort Worth Same functionality here as ArcGIS's Network Analyst

I tend to be a CRAN-appreciator. But wow, R-Universe is such a useful project. As a developer, I can: - Experiment with new and creative approaches that would never get accepted on CRAN; - Have cross-platform binaries for my packages built within an hour (usually) of a GitHub push

New in the spopt-r #rstats package: route optimization. Solve the classic Traveling Salesman Problem for a single driver or optimize a fleet by solving the Vehicle Routing Problem. Written in Rust so they solve fast. Read the vignette which covers r5r integration: walker-data.com/spop...

If you are using AI the right way, it should make your job harder, not easier.

All 8.1 million US Census blocks. Visualized smoothly in 3D. Instant population and housing totals from a lasso selection. All running seamlessly in the browser, no traditional backend. While everyone’s talking about AI, it’s an incredible time for geospatial tech.

368,000 miles of Texas pipelines across nearly 500,000 line segments visualized in @maplibre.org as vector tiles. With {freestiler}, the tiling process took under 15 seconds. Infrastructure data meets modern geospatial tooling.

Incredible day 1 response and feedback to my new vector tile engine, freestiler. Several of you asked for an easier way to serve and map vector tiles. freestiler now has a built-in local tile server along with a new mapping vignette. Check it out: walker-data.com/free...

Announcing {freestiler}: a high-performance vector tiling engine for R and Python. Generate vector tiles for your maps directly from R/Python spatial data, @duckdb queries, and local spatial files. Check out the docs here: walker-data.com/free... Some highlights:

640,000 parcels in Dallas County Texas, visualized in 3D by appraised value per square foot. The data prep? Vector tiles generated in 15 seconds directly from a @duckdb.org database using my latest geospatial tool, {freestiler}. Package announcement coming tomorrow!

With OpenClaw, you can have on-demand location intelligence in your pocket. I taught my bot how to pull demographic data and do drive-time analytics for any address using validated pipelines; It then formats a branded PDF report and delivers to me by Telegram, ready to share.

This week on What's New in R: ✅ Tutorial on visualizing biking data w/elevation profiles ✅ {typeR} package for simulating live typing in demos ✅ @kylewalker.bsky.social's guide to creating travel-time matrices for spatial analysis Read the issue: buff.ly/T7DqdIw @fgazzelloni.bsky.social #rstats

With Claude Code as my dev partner, I'm getting close to releasing the most technically impressive geospatial package I've ever created. This one will have both R and Python bindings - I think you'll like it. It is an incredible time to be building things.

For me, Gemini is the #1 LLM for several use-cases including document extraction and image generation. But it doesn't get nearly the hype of its competitors as the Gemini CLI is a distant third for agentic coding. For us users - it pays off to know the best tool for the job.

Next step....getting {calcite} to work with {mapgl} 👆🏼 it already does, i just need to make an example :P New release coming in the next week or so! github.com/r-arcgis/cal... #rstats

spopt-r brings powerful spatial optimization algorithms for regionalization, facility location, and market analysis to R with a blazing-fast Rust backend. Use them for analyses in energy, retail, logistics, sales, real estate, and more. Get started: walker-data.com/spopt-r

We live in a magical time for #dataviz. This map is just a static html page served on GitHub pages 🤯 It uses the incredible {pmtiles} #rstats package by @kylewalker.bsky.social to quickly filter through ~21M rows of data hosted on Cloudflare vehicletrends.github.io/hhi-map/

New in R's mapgl: native support for Esri basemap styles! Build your maps and apps in R & Shiny, display your data over your favorite Esri styles that you use in ArcGIS Pro / Online. Just grab your ArcGIS API token and use `esri_style()` for dozens of choices.

How I map millions of features without breaking the bank: - Data prep: R - Data tiling: tippecanoe, PMTiles - Deployment: Cloudflare R2 / Workers - Mapping: MapLibre / R / mapgl Lightning-fast with edge caching, minimal hosting costs See it in action: personal.tcu.edu/kylewalker/m...

OpenClaw + R = custom maps and insights sent to my phone. I think there’s a huge opportunity in custom analytics bots for businesses with differentiated context and data.

I’m teaching my OpenClaw bot how to do mapping and spatial analysis. Location intelligence is now just a Telegram message away!

I joined Matt Forrest on the "Spatial Stack" podcast's latest episode. We discussed the importance of open data; why I use R for my geospatial work; why I'm enthusiastic about AI; and more. Watch / listen here: