data = d3.csv(
'https://gist.githubusercontent.com/radovankavicky/3a963cad5df48c94794a5d6dca7b383a/raw/c768cb9438ee9678161850cea551c0ac3abd9fa2/johnsnow_dataset_deaths.csv'
)
exampleOfData = [51.5, 0.12, 0.5]
normalize = d3
.scaleLinear()
.domain([0, d3.max(data.map(d => d['Number of deaths']))])
.range([0, 2]) // increase this number to change final scale values
choleraPoints = data.map(d => {
return [
+d['X coordinate'],
+d['Y coordinate'],
+normalize(d['Number of deaths'])
];
})
md`### Find the center of the map`
xCenter = d3.mean(d3.extent(data.map(d => d['X coordinate'])))
yCenter = d3.mean(d3.extent(data.map(d => d['Y coordinate'])))
choleraMap = {
// You'll often see Leaflet examples initializing a map like L.map('map'),
// which tells the library to look for a div with the id 'map' on the page.
// In Observable, we instead create a div from scratch in this cell, so it's
// completely self-contained.
let container = DOM.element('div', {
style: `width:${width}px;height:${width / 1.6}px`
});
// Note that I'm yielding the container pretty early here: this allows the
// div to be placed on the page. This is important, because Leaflet uses
// the div's .offsetWidth and .offsetHeight to size the map. If I were
// to only return the container at the end of this method, Leaflet might
// get the wrong idea about the map's size.
yield container;
// Now we create a map object and add a layer to it.
let map = L.map(container).setView([xCenter, yCenter], 17);
let osmLayer = L.tileLayer(
'https://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}@2x.png',
{
attribution:
'© <a href="http://osm.org/copyright">OpenStreetMap</a> contributors'
}
).addTo(map);
let choleraLayer = heatLayer(choleraPoints).addTo(map);
}
md`# Appendix`
html`<link href='${resolve(
'leaflet@1.2.0/dist/leaflet.css'
)}' rel='stylesheet' />`
L = require('leaflet@1.2.0')
heatLayer = (L, require('leaflet.heat').catch(() => L.heatLayer))
d3 = require('d3')
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
