Published
Edited
Sep 16, 2019
Importers
4 stars
chart = {
const svg = d3.select(DOM.svg(width, height));
svg.append("g").call(xAxis)
svg.append("g").call(yAxis)
svg.append("g")
.call(setTitle, "Scatter Chart is Good")
const dots = svg.append("g")
.call(addCircles, groceries.slice(0,15), mint, 5)
const dots2 = svg.append("g")
.call(addCircles, groceries.slice(16,50), "orange", 5)
svg.append("path")
.call(addLine, groceries, mint, 3)
return svg.node()
}
fittedLine = d3.line()
.x(d => x(d.x))
.y(d => y(d.y))
x = d3.scaleLinear()
.domain([d3.min(groceries, d=>parseFloat(d.Grocery)),d3.max(groceries, d=>parseFloat(d.Grocery))])
.range([30, width-30])
y = d3.scaleLinear()
.domain([d3.min(groceries, d=>parseFloat(d.Health)),d3.max(groceries, d=>parseFloat(d.Health))])
.range([height-30, 30])
xAxis = svg => svg
.attr("transform", `translate(0,${height - 30})`)
.call(d3.axisBottom(x))
yAxis = svg => svg
.attr("transform", `translate(${30},0)`)
.call(d3.axisLeft(y))
md`# Appendix`
tooltip = d3.select("body").append("div").attr("class", "toolTip");
groceries = Object.assign(await d3.csv("https://gist.githubusercontent.com/muvic08/e532c9644e219a2b35bfdd5818aa80ad/raw/80efedc6f19299212cad72669259bc32cc79f4fd/groceries.csv"))
regressionPoints2 = [
{x: 106, y: 91},
{x: 71, y: 114}
]
regressionPoints3 = [
{
x: x.domain()[1],
y: y.domain()[1]
},
{
x: x.domain()[0],
y: y.domain()[0]
}
]
regressionPoints = {
const firstX = d3.min(groceries.map(d => parseFloat(d.Grocery)));
const lastX = d3.max(groceries.map(d => parseFloat(d.Grocery)));
const xCoordinates = [firstX, lastX];
return xCoordinates.map(d => ({
x: d,
y: linearRegressionLine(d)
}));
}
linearRegressionLine2 = function(x) {
return params.M*x + params.C
}
linearRegressionLine = ss.linearRegressionLine(linearRegression)
linearRegression = ss.linearRegression(
groceries.map(d => [parseFloat(d.Grocery), parseFloat(d.Health)]))
params = ({M:1.2, C: 100})
d3 = require("d3@5")
ss = require('simple-statistics')
x.domain()
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.