Data Engineer and aspiring Data Visualization Journalist, you can reach me at rjhontomin@gmail.com
{
const svg = d3.create("svg").attr("viewBox", [0, 0, width+margin.left+margin.right, height + margin.top + margin.bottom]).style("background", "#efefe7")
const wrapper = svg.append("g").attr("transform", `translate(${margin.left}, ${margin.top})`)
// Geo Projection
let projection = d3.geoMercator().fitSize([innerWidth, innerHeight], phl_regions2)
let geoGenerator = d3.geoPath().projection(projection)
let regions = wrapper.selectAll('region').data(phl_regions2.features)
let areas = regions.enter().append("path").attr("class", "areas").attr("d", d => geoGenerator(d)).attr("fill", "gray").attr("stroke", "white").attr("stroke-width", 1)
const circles = wrapper.selectAll('circle').data(data).join('circle').attr("transform", d => `translate(${d.x}, ${d.y})`).attr("r", 2).attr("fill", "red")
return svg.node()
}
_philvolcs = FileAttachment("2021_philvolcs.csv").csv()
phl_regions2 = FileAttachment("phl_regions2.geojson").json()
parseDate = d3.utcParse("%Y-%m-%d") //2021-01-31
height = 900
width = 600
margin = ({"top":100, "bottom":50, "left":30, "right":30})
innerHeight = height - margin.top - margin.bottom
innerWidth = width - margin.left - margin.right
projection = d3.geoMercator().translate([margin.left, margin.top]).fitSize([innerWidth, innerHeight], phl_regions2)
pathGenerator = d3.geoPath(projection)
data = ( await FileAttachment("2021_philvolcs.csv").csv()).map(d => {
let geoJsonPoint = {
type: "Point",
coordinates: [d.lat, d.long]
}
let t = projection([parseFloat(d.long), parseFloat(d.lat)]);
console.log(d.lat, d.long, t)
return {...d, "x": t[0], "y":t[1], date: parseDate(d.date)}
}).sort((a, b) => a.date - b.date)
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.