Try this mapgl trick for #30DayMapChallenge Day 11: Minimal:
library(mapgl)
mapboxgl(
config = list(
basemap = list(
theme = "monochrome"
)
)
)
Add `lightPreset = "night"` for a dark basemap!
Try this mapgl trick for #30DayMapChallenge Day 11: Minimal:
library(mapgl)
mapboxgl(
config = list(
basemap = list(
theme = "monochrome"
)
)
)
Add `lightPreset = "night"` for a dark basemap!
Use the `set_fog()` function to change the color of the sky on your @Mapbox map. Visualize the glow of the Northern Lights - or whatever you can come up with!
Use the `set_fog()` function to change the color of the sky on your @Mapbox map. Visualize the glow of the Northern Lights - or whatever you can come up with!
For a "classic" look on your mapgl MapLibre maps, load a parchment paper image (or whatever you'd like) and override the basemap.
Here's how to do it: gist.github.com/walkerke/648...
For a "classic" look on your mapgl MapLibre maps, load a parchment paper image (or whatever you'd like) and override the basemap.
Here's how to do it: gist.github.com/walkerke/648...
The default Mapbox Standard Style with `mapboxgl()` gets you 3D buildings - with rendered landmarks - out of the box.
Using MapLibre? Try `maplibre(style = openfreemap_style("liberty"))` for 3D OSM buildings!
The default Mapbox Standard Style with `mapboxgl()` gets you 3D buildings - with rendered landmarks - out of the box.
Using MapLibre? Try `maplibre(style = openfreemap_style("liberty"))` for 3D OSM buildings!
Today's tip: calculate access from a location in one line of code with `mb_isochrone()` in the mapboxapi R package.
Then, visualize creatively with a comparison slider in mapgl.
Learn how: walker-data.com/posts/time-a...
Today's tip: calculate access from a location in one line of code with `mb_isochrone()` in the mapboxapi R package.
Then, visualize creatively with a comparison slider in mapgl.
Learn how: walker-data.com/posts/time-a...
Learn how to do it: walker-data.com/posts/mapgl-...
Learn how to do it: walker-data.com/posts/mapgl-...
Visualize your spatial data in 3D with `add_fill_extrusion_layer()`!
The key is `fill_extrusion_height`; map a column of heights here or use a helper like `interpolate()` to control how you extrude your polygons.
Visualize your spatial data in 3D with `add_fill_extrusion_layer()`!
The key is `fill_extrusion_height`; map a column of heights here or use a helper like `interpolate()` to control how you extrude your polygons.
I've published the app here for you to try out: walkerke-restaurant-finder-app.share.connect.posit.cloud
For #rstats devs, I've also published the source code here: gist.github.com/walkerke/4a1...
I've published the app here for you to try out: walkerke-restaurant-finder-app.share.connect.posit.cloud
For #rstats devs, I've also published the source code here: gist.github.com/walkerke/4a1...
Today's tip: in #rstats mapgl, use `mapboxgl(style = mapbox_style("standard-satellite"))` to get @mapbox.com high-quality imagery on an interactive globe in one line of code.
Even better - you get 3D terrain out of the box!
Today's tip: in #rstats mapgl, use `mapboxgl(style = mapbox_style("standard-satellite"))` to get @mapbox.com high-quality imagery on an interactive globe in one line of code.
Even better - you get 3D terrain out of the box!
- Find your location, draw a buffer (or isochrone, etc.) around it;
- Query a massive tileset (64 million places from Overture Maps) to find nearby places;
- Deliver that information to your app users.
- Find your location, draw a buffer (or isochrone, etc.) around it;
- Query a massive tileset (64 million places from Overture Maps) to find nearby places;
- Deliver that information to your app users.
Click to fly to your location; in Shiny, use `input$MAPID_geolocate` to get the coordinates.
Great for building apps designed for use in the field!
#30DayMapChallenge Day 4: My Data
Click to fly to your location; in Shiny, use `input$MAPID_geolocate` to get the coordinates.
Great for building apps designed for use in the field!
#30DayMapChallenge Day 4: My Data
Lasso wells on the map, download the data instantly.
From selection to export in seconds.
(By the way, this is powered by Shiny and #rstats)
Lasso wells on the map, download the data instantly.
From selection to export in seconds.
(By the way, this is powered by Shiny and #rstats)
Explored over satellite imagery in a single line of code.
Modern geospatial technology can take your land & ownership mapping to the next level.
#30DayMapChallenge Day 3: Polygons
Explored over satellite imagery in a single line of code.
Modern geospatial technology can take your land & ownership mapping to the next level.
#30DayMapChallenge Day 3: Polygons
Use `show_measurements = TRUE` to interactively measure line distances (and polygon areas) on your map.
#rstats
Use `show_measurements = TRUE` to interactively measure line distances (and polygon areas) on your map.
#rstats
Intelligently clustered and smoothly displayed on a map with click-to-zoom.
mapgl tip: use `cluster_options()` on a circle or symbol layer, no extra configuration required!
#30DayMapChallenge Day 1: Points
Intelligently clustered and smoothly displayed on a map with click-to-zoom.
mapgl tip: use `cluster_options()` on a circle or symbol layer, no extra configuration required!
#30DayMapChallenge Day 1: Points
Pay attention to this hashtag if you love maps - there will be tons of creative examples from around the world.
Pay attention to this hashtag if you love maps - there will be tons of creative examples from around the world.
However - you can push mapgl quite a ways without tiles!
In this post, I cover how to map all 85,000+ Census tracts in the US without pre-tiling, along with performance tips.
walker-data.com/post...
However - you can push mapgl quite a ways without tiles!
In this post, I cover how to map all 85,000+ Census tracts in the US without pre-tiling, along with performance tips.
walker-data.com/post...
And I'll freely admit that it would not exist without the help of LLMs.
I'm speaking tomorrow about my experiences with LLM-assisted R development.
Register here: docs.google.com/forms/d/e/1F...
And I'll freely admit that it would not exist without the help of LLMs.
I'm speaking tomorrow about my experiences with LLM-assisted R development.
Register here: docs.google.com/forms/d/e/1F...
My most recent blog post helps you get started. Use this reproducible workflow to learn how to create, explore, and visualize PMTiles.
walker-data.com/post...
My most recent blog post helps you get started. Use this reproducible workflow to learn how to create, explore, and visualize PMTiles.
walker-data.com/post...
Learn how to use the ellmer and shinychat R packages to integrate chat into your Shiny apps.
Check it out: walker-data.com/posts/ai-loc...
Learn how to use the ellmer and shinychat R packages to integrate chat into your Shiny apps.
Check it out: walker-data.com/posts/ai-loc...
Of course, I had to try this out in R.
Check it out: all 242,000 US Census block groups dynamically served as vector tiles from a DuckDB database, displayed on a MapLibre map from R in Positron.
Of course, I had to try this out in R.
Check it out: all 242,000 US Census block groups dynamically served as vector tiles from a DuckDB database, displayed on a MapLibre map from R in Positron.
The magic tech: MapLibre + PMTiles.
The glue: R + Shiny.
Seriously.
The magic tech: MapLibre + PMTiles.
The glue: R + Shiny.
Seriously.
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.
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.
Since 2021, Miami's median household income grew over 26 percent. Orlando and Tampa weren't far behind.
Among the US's largest metros, Seattle (10.5 percent) and Minneapolis (12 percent) have lagged.
Since 2021, Miami's median household income grew over 26 percent. Orlando and Tampa weren't far behind.
Among the US's largest metros, Seattle (10.5 percent) and Minneapolis (12 percent) have lagged.
But rush hour isn't average.
Your "15-minute service area" might be 25 minutes when it actually matters—when patients need care, employees commute, emergencies happen.
Learn how to handle this: walker-data.com/posts/time-a...
But rush hour isn't average.
Your "15-minute service area" might be 25 minutes when it actually matters—when patients need care, employees commute, emergencies happen.
Learn how to handle this: walker-data.com/posts/time-a...