walkerke

# Day 25: Hexagons - US Wind Energy Infrastructure
# Multi-resolution H3 hexagonal aggregation of 72,000+ wind turbines
# Aggregating total installed capacity (MW) per hexagon
# Points fade in at high zoom for individual turbine exploration

library(mapgl)
library(h3o)
library(sf)
library(dplyr)
library(readr)

walkerke

library(mapgl) # Get the new features: pak::pak("walkerke/mapgl")
library(tidycensus)
library(sf)
library(tidyverse)
sf_use_s2(FALSE)

tx_bgs <- get_acs(
  geography = "block group",
  variables = "B01001_001",
  state = "TX",

walkerke

# DuckDB Vector Tiles with mapgl Example
# This script demonstrates how to serve vector tiles from DuckDB using ST_AsMVT()
# and display them in a mapgl map using httpuv

library(mapgl)
library(duckdb) # Requires the latest DuckDB version (>= 1.4.0)
library(httpuv)
library(sf)
library(duckspatial)
library(tigris)

walkerke

# remotes::install_github("walkerke/mapgl")
library(mapgl)

# CYBERPUNK 2125 - Ultra-striking neon palette
# Deep blacks + electric neons for that Blade Runner / Akira vibe
cyberpunk_2125 <- c(
  "#000000", # Pure black (shadows)
  "#0a0e27", # Deep space blue (dark areas)
  "#1a1a2e", # Dark navy (buildings)
  "#16213e", # Midnight blue

walkerke

# remotes::install_github("walkerke/mapgl")
library(mapgl)
library(sf)
library(dplyr)

# Set seed for reproducibility
set.seed(42)

# Define the bounding box for Dallas (approximately)
dallas_bbox <- st_bbox(c(

walkerke

library(tidycensus)
library(tigris)
library(tidyverse)
options(tigris_use_cache = TRUE)

# Grab the data
us_income <- get_acs(
  geography = "puma",
  variables = "B19013_001",
  year = 2023,

walkerke

library(mapgl)

pmtiles <- "https://r2-public.protomaps.com/protomaps-sample-datasets/cb_2018_us_zcta510_500k.pmtiles"

maplibre(center = c(-97, 35), zoom= 3) |>
 set_projection("globe") |> 
 add_vector_source("pmtiles_source",
          url = paste0("pmtiles://", pmtiles)
 ) |>
 add_fill_layer(

walkerke

library(tidyverse)
library(tidycensus)

# Get the data
pyramid_data <- get_estimates(
  geography = "state",
  product = "characteristics",
  breakdown = c("AGEGROUP", "SEX"),
  breakdown_labels = TRUE,
  vintage = 2024,

walkerke

# Day 26: Transport - US Electric Power Transmission Lines
# Visualizing America's invisible highway: 700,000+ miles of power lines
# Dynamic line widths by voltage class, glowing effect for the energy flow

library(mapgl)
library(sf)
library(dplyr)

# Load transmission lines from HIFLD (Homeland Infrastructure Foundation-Level Data)
# This is a large dataset - we'll use direct URL for the GeoJSON

walkerke

# Day 27: Boundaries - World Time Zones
# Shows current time in each timezone

library(mapgl)
library(sf)
library(dplyr)
library(lubridate)

# Get user's current timezone and time
user_tz <- Sys.timezone()