chart = CandlestickChart(aapl, {
date: d => d.Date,
high: d => d.High,
low: d => d.Low,
open: d => d.Open,
close: d => d.Close,
yLabel: "↑ Price ($)",
width,
height: 500
})
aapl = FileAttachment("aapl-2.csv").csv({typed: true}).then(data => data.slice(-120))
// Copyright 2021 Observable, Inc.
// Released under the ISC license.
// https://observablehq.com/@d3/candlestick-chart
function CandlestickChart(data, {
date = d => d.date, // given d in data, returns the (temporal) x-value
open = d => d.open, // given d in data, returns a (quantitative) y-value
close = d => d.close, // given d in data, returns a (quantitative) y-value
high = d => d.high, // given d in data, returns a (quantitative) y-value
low = d => d.low, // given d in data, returns a (quantitative) y-value
title, // given d in data, returns the title text
marginTop = 20, // top margin, in pixels
marginRight = 30, // right margin, in pixels
marginBottom = 30, // bottom margin, in pixels
marginLeft = 40, // left margin, in pixels
width = 640, // outer width, in pixels
height = 400, // outer height, in pixels
xDomain, // array of x-values (defaults to every weekday)
xRange = [marginLeft, width - marginRight], // [left, right]
xPadding = 0.2,
xTicks, // array of x-values to label (defaults to every other Monday)
yType = d3.scaleLinear, // type of y-scale
yDomain, // [ymin, ymax]
yRange = [height - marginBottom, marginTop], // [bottom, top]
xFormat = "%b %-d", // a format specifier for the date on the x-axis
yFormat = "~f", // a format specifier for the value on the y-axis
yLabel, // a label for the y-axis
stroke = "currentColor", // stroke color for the daily rule
strokeLinecap = "round", // stroke line cap for the rules
colors = ["#4daf4a", "#999999", "#e41a1c"] // [up, no change, down]
} = {}) {
// Compute values.
const X = d3.map(data, date);
const Yo = d3.map(data, open);
const Yc = d3.map(data, close);
const Yh = d3.map(data, high);
const Yl = d3.map(data, low);
const I = d3.range(X.length);
const weeks = (start, stop, stride) => d3.utcMonday.every(stride).range(start, +stop + 1);
const weekdays = (start, stop) => d3.utcDays(start, +stop + 1).filter(d => d.getUTCDay() !== 0 && d.getUTCDay() !== 6);
// Compute default domains and ticks.
if (xDomain === undefined) xDomain = weekdays(d3.min(X), d3.max(X));
if (yDomain === undefined) yDomain = [d3.min(Yl), d3.max(Yh)];
if (xTicks === undefined) xTicks = weeks(d3.min(xDomain), d3.max(xDomain), 2);
// Construct scales and axes.
// If you were to plot a stock using d3.scaleUtc, you’d see distracting gaps
// every weekend. This chart therefore uses a d3.scaleBand whose domain is every
// weekday in the dataset. A few gaps remain for holiday weekdays, such as
// Christmas, but these are infrequent and allow the labeling of Mondays. As a
// band scale, we specify explicit tick values.
const xScale = d3.scaleBand(xDomain, xRange).padding(xPadding);
const yScale = yType(yDomain, yRange);
const xAxis = d3.axisBottom(xScale).tickFormat(d3.utcFormat(xFormat)).tickValues(xTicks);
const yAxis = d3.axisLeft(yScale).ticks(height / 40, yFormat);
// Compute titles.
if (title === undefined) {
const formatDate = d3.utcFormat("%B %-d, %Y");
const formatValue = d3.format(".2f");
const formatChange = (f => (y0, y1) => f((y1 - y0) / y0))(d3.format("+.2%"));
title = i => `${formatDate(X[i])}
Open: ${formatValue(Yo[i])}
Close: ${formatValue(Yc[i])} (${formatChange(Yo[i], Yc[i])})
Low: ${formatValue(Yl[i])}
High: ${formatValue(Yh[i])}`;
} else if (title !== null) {
const T = d3.map(data, title);
title = i => T[i];
}
const svg = d3.create("svg")
.attr("width", width)
.attr("height", height)
.attr("viewBox", [0, 0, width, height])
.attr("style", "max-width: 100%; height: auto; height: intrinsic;");
svg.append("g")
.attr("transform", `translate(0,${height - marginBottom})`)
.call(xAxis)
.call(g => g.select(".domain").remove());
svg.append("g")
.attr("transform", `translate(${marginLeft},0)`)
.call(yAxis)
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").clone()
.attr("stroke-opacity", 0.2)
.attr("x2", width - marginLeft - marginRight))
.call(g => g.append("text")
.attr("x", -marginLeft)
.attr("y", 10)
.attr("fill", "currentColor")
.attr("text-anchor", "start")
.text(yLabel));
const g = svg.append("g")
.attr("stroke", stroke)
.attr("stroke-linecap", strokeLinecap)
.selectAll("g")
.data(I)
.join("g")
.attr("transform", i => `translate(${xScale(X[i])},0)`);
g.append("line")
.attr("y1", i => yScale(Yl[i]))
.attr("y2", i => yScale(Yh[i]));
g.append("line")
.attr("y1", i => yScale(Yo[i]))
.attr("y2", i => yScale(Yc[i]))
.attr("stroke-width", xScale.bandwidth())
.attr("stroke", i => colors[1 + Math.sign(Yo[i] - Yc[i])]);
if (title) g.append("title")
.text(title);
return svg.node();
}
import {howto, altplot} from "@d3/example-components"
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.