// data = {
// map.update(stinky.length > 0 ? stinky : [])
// return d3.select(map).selectAll("circle").data();
// }
stinky = {
// https://observablehq.com/@mbostock/fetch-error-handling
const url='https://raw.githubusercontent.com/ds5110/stinky2/main/sample_data/smc_data.csv';
const response = await fetch(url);
if (!response.ok) {
return []
// throw new Error("sorry about that...unable to fetch");
}
return d3.csvParse(await response.text()).map(d => [+d.longitude, +d.latitude]);
}
data = {
const wind = {N:0, NE:45, E:90, SE:135, S:180, SW:225, W:270, NW:315};
const csv = await d3.csv('https://raw.githubusercontent.com/ds5110/stinky2/main/sample_data/merged_data.csv');
return csv.map(d => [new Date((+d.date.slice(0,4)), +d.date.slice(5,7)-1,+d.date.slice(8,10)), wind[d.wind_direction], [+d.longitude, +d.latitude]]
);
}
styling = {
d3.select(brush).select(".x-axis").attr("font-size", 15);
d3.select(brush).select(".y-axis").attr("font-size", 15);
}
url = (x, y, z) => `https://${"abc"[Math.abs(x + y) % 3]}.basemaps.cartocdn.com/rastertiles/voyager/${z}/${x}/${y}${devicePixelRatio > 1 ? "@2x" : ""}.png`
// url = (x, y, z) => `https://${"abc"[Math.abs(x + y) % 3]}.basemaps.cartocdn.com/light_all/${z}/${x}/${y}${devicePixelRatio > 1 ? "@2x" : ""}.png`
x = d3.scaleLinear(d3.extent(data, d => d[0]), [margin.left, width - margin.right])
margin = ({top: 30, right: 50, bottom: 30, left: 80})
height = 500
// initialCenter = [-69.4455, 45.2538] // Maine is 45.2538° N, 69.4455° W -- use with initial scale 1 << 15
initialCenter = [-70.2568, 43.645] // Portland, Maine 43.6591° N, 70.2568° W
initialScale = 1 << 21
features = d3.json("https://cdn.jsdelivr.net/npm/us-atlas@3/states-10m.json").then(topology => topojson.feature(topology, topology.objects.states))
topojson = require("topojson-client@3")
//import {viewof chart} with {data, title, x, margin} from "@pbogden/click-to-recenter-brush-iii"
import {viewof chart} with {data, title, margin} from "@pbogden/click-to-recenter-brush-iii"
d3 = require("d3@6", "d3-tile@1")
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.