Published
Edited
Nov 18, 2020
md`# PetDB - Entity Statistics`
format = d3.format(",.2r")
data = Object.entries(tempData).map(([key,val], i) => {
const fullData = []
let currentKey = key.replaceAll('_', ' ').toUpperCase()
return fullData[i] = {"name": currentKey, "value": val}
})
delete tempData.ts
tempData = jsonData['data'][0];
jsonData = d3.json("https://ecapi.earthchem.org/statistics/entitystatistics")
chartColor = d3.scaleLinear()
.domain([d3.median(data, d => d.value), d3.max(data, d => d.value)]).nice()
.range(["#d6706a", "#8a211b"])
x = d3.scaleLinear()
.domain([0, d3.max(data, d => d.value)])
.range([margin.left, width - margin.right])
y = d3.scaleBand()
.domain(data.map(d => d.name))
.range([margin.top, height - margin.bottom])
.padding(0.1)
xAxis = g => g
.attr("transform", `translate(0,${margin.top})`)
.call(d3.axisTop(x).ticks(width/80))
.call(g => g.select(".domain").remove())
yAxis = g => g
.attr("transform", `translate(${margin.left}, 0)`)
.call(d3.axisLeft(y).tickSizeOuter(0))
width = 500
height = data.length * 25 + margin.top + margin.bottom
margin = ({top: 20, right: 80, bottom: 20, left: 120})
d3 = require("d3@6")
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.
