--- name: echarts-63ac64e35396 description: >- Creates interactive data visualizations with Apache ECharts, the open-source JavaScript charting library. Use when a user asks to build charts, dashboards, or data-driven graphics using ECharts in React, Vue, or vanilla JavaScript applications, render a chart to SVG on the server, or upgrade from ECharts 5 to 6. license: Apache-2.0 compatibility: "ECharts 6.x (checked against 6.1.0) in modern browsers, or Node.js for server-side SVG. React: echarts-for-react 3.0.6. Vue: vue-echarts 8 (Vue 3.3+, ECharts 6 only)." metadata: author: terminal-skills version: "1.1.0" category: data-ai tags: "charts, interactive, canvas, dashboard, analytics" repository: https://github.com/apache/echarts --- # ECharts — Enterprise Data Visualization ## Overview Apache ECharts is an open-source (Apache-2.0) JavaScript charting library. A chart is one plain `option` object passed to `chart.setOption()`: line, bar, pie, scatter, heatmap, tree, sankey, geographic and custom series, with tooltips, zooming, animation and themes built in. It draws on Canvas (the default) or SVG, and in Node.js it can produce an SVG string without a browser. ECharts 6 changed the default theme and added runtime theme switching plus chord, beeswarm, broken-axis and matrix-layout charts. ## Instructions ### Installation ```bash npm install echarts # Vanilla JS npm install echarts echarts-for-react # React npm install echarts vue-echarts # Vue 3 ``` ### Vanilla JavaScript ```javascript import * as echarts from "echarts/core"; import { BarChart, LineChart } from "echarts/charts"; import { DatasetComponent, GridComponent, LegendComponent, TooltipComponent } from "echarts/components"; import { CanvasRenderer } from "echarts/renderers"; // Tree-shakeable imports: register what the chart uses. A renderer is always required. echarts.use([BarChart, LineChart, DatasetComponent, GridComponent, LegendComponent, TooltipComponent, CanvasRenderer]); const el = document.getElementById("revenue-chart"); // the element needs a CSS width and height const chart = echarts.init(el); chart.setOption({ tooltip: { trigger: "axis" }, legend: {}, dataset: { source: [ ["month", "Revenue", "Costs"], ["Jan", 42000, 31000], ["Feb", 46500, 32500], ["Mar", 51200, 34100], ], }, xAxis: { type: "category" }, yAxis: {}, series: [{ type: "bar" }, { type: "line" }], // each series takes the next dataset column }); // The chart does not follow its container: call resize() yourself const observer = new ResizeObserver(() => chart.resize()); observer.observe(el); // On teardown: observer.disconnect(); chart.dispose(); ``` `import * as echarts from "echarts"` registers everything and needs no `use()` call: simpler, but a much larger bundle. ### React Integration ```tsx // Using echarts-for-react wrapper import { useEffect, useRef } from "react"; import ReactECharts from "echarts-for-react"; function SalesChart({ data }) { const option = { title: { text: "Monthly Sales", left: "center" }, tooltip: { trigger: "axis", formatter: (params) => { return params.map(p => `${p.seriesName}: $${p.value.toLocaleString()}`).join("
"); }, }, legend: { bottom: 0, data: ["Revenue", "Costs", "Profit"] }, xAxis: { type: "category", data: data.map(d => d.month) }, yAxis: { type: "value", axisLabel: { formatter: "${value}" } }, series: [ { name: "Revenue", type: "bar", data: data.map(d => d.revenue), color: "#4f46e5" }, { name: "Costs", type: "bar", data: data.map(d => d.costs), color: "#ef4444" }, { name: "Profit", type: "line", data: data.map(d => d.profit), color: "#22c55e", smooth: true, areaStyle: { opacity: 0.1 } }, ], toolbox: { feature: { saveAsImage: {}, // Download as PNG dataZoom: {}, // Zoom into data restore: {}, // Reset view }, }, dataZoom: [{ type: "slider", start: 0, end: 100, bottom: 30 }], // Range slider above the legend grid: { bottom: 90 }, }; return ; } // Donut chart; onEvents receives ECharts events such as a click on a slice function CategoryBreakdown({ data, onSelect }) { const option = { tooltip: { trigger: "item", formatter: "{b}: {c} ({d}%)" }, series: [{ type: "pie", radius: ["40%", "70%"], // Donut chart avoidLabelOverlap: true, itemStyle: { borderRadius: 8, borderColor: "#fff", borderWidth: 2 }, label: { show: true, formatter: "{b}\n{d}%" }, emphasis: { label: { fontSize: 16, fontWeight: "bold" } }, data: data.map(d => ({ value: d.count, name: d.category })), }], }; return onSelect(e.name) }} />; } // Real-time streaming chart: update the instance directly instead of re-rendering React function LiveMetrics({ readLatency }) { const chartRef = useRef(null); const points = useRef([]); const baseOption = { animation: false, xAxis: { type: "time" }, yAxis: { type: "value", name: "ms" }, series: [{ type: "line", showSymbol: false, data: [] }], }; useEffect(() => { const interval = setInterval(() => { const chart = chartRef.current?.getEchartsInstance(); if (!chart) return; // Append new data point, keep the last 60 points.current = [...points.current, [Date.now(), readLatency()]].slice(-60); chart.setOption({ series: [{ data: points.current }] }); }, 1000); return () => clearInterval(interval); }, [readLatency]); return ; } ``` ### Vue Integration ```vue ``` ### Advanced Charts ```typescript // Sankey diagram (flow visualization) — every name used in links must be listed in data const sankeyOption = { series: [{ type: "sankey", data: [ { name: "Organic" }, { name: "Paid" }, { name: "Referral" }, { name: "Signup" }, { name: "Activation" }, { name: "Churned" }, { name: "Paid User" }, ], links: [ { source: "Organic", target: "Signup", value: 5000 }, { source: "Paid", target: "Signup", value: 3000 }, { source: "Referral", target: "Signup", value: 2000 }, { source: "Signup", target: "Activation", value: 6000 }, { source: "Signup", target: "Churned", value: 4000 }, { source: "Activation", target: "Paid User", value: 3500 }, ], }], }; // Heatmap (calendar-style, like GitHub contributions); dailyData = [{ date: "2026-03-14", commits: 7 }, ...] const calendarHeatmap = { visualMap: { min: 0, max: 100, type: "piecewise", orient: "horizontal", left: "center" }, calendar: { range: "2026", cellSize: ["auto", 15] }, series: [{ type: "heatmap", coordinateSystem: "calendar", data: dailyData.map(d => [d.date, d.commits]), }], }; ``` ### Upgrading from ECharts 5 to 6 `npm install echarts@6` needs no code changes in most projects, but charts look different: a new color palette, and the legend now sits at the bottom by default. ```javascript import * as echarts from "echarts"; import "echarts/theme/v5.js"; // keep the .js: "echarts/theme/v5" fails to resolve in Node const chart = echarts.init(el, "v5"); // version 5 colors and component positions chart.setOption(option); // New in 6: switch theme on a live chart (it has no effect before the first setOption) chart.setTheme(window.matchMedia("(prefers-color-scheme: dark)").matches ? "dark" : "v5"); ``` ## Examples ### Example 1: Render a chart to SVG on the server User: "Generate the weekly signups chart as an image for our email report, no browser." ```javascript // render-signups.mjs — run with: node render-signups.mjs import { writeFileSync } from "node:fs"; import * as echarts from "echarts"; const chart = echarts.init(null, null, { renderer: "svg", ssr: true, width: 800, height: 400 }); chart.setOption({ animation: false, title: { text: "Signups, week of 21 September" }, xAxis: { type: "category", data: ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"] }, yAxis: { type: "value" }, series: [{ type: "bar", data: [182, 205, 197, 241, 263, 118, 96], label: { show: true, position: "top" } }], }); writeFileSync("signups.svg", chart.renderToSVGString()); chart.dispose(); ``` Result: `signups.svg`, an 800×400 vector image of about 7 KB, written without a DOM. SSR mode needs `renderer: "svg"`, `ssr: true` and an explicit width and height. For PNG output, pass a `canvas` package (node-canvas) instance to `echarts.init` and call `canvas.toBuffer("image/png")`. ### Example 2: Plot 200,000 sensor readings without freezing the page User: "Our temperature chart has 200k points and the page locks up when it loads." ```javascript // readings: [[timestampMs, celsius], ...] with 200,000 rows chart.setOption({ animation: false, tooltip: { trigger: "axis" }, xAxis: { type: "time" }, yAxis: { type: "value", scale: true, name: "°C" }, dataZoom: [{ type: "inside" }, { type: "slider" }], series: [{ type: "line", showSymbol: false, // no marker per point sampling: "lttb", // downsample to what the pixels can show, keeping peaks data: readings, }], }); ``` Result: the line keeps its shape while far fewer segments are drawn (rendered to SVG at 1200 px wide, 200,000 points come to about 75 KB with `sampling: "lttb"`; without it the size depends on the data, from about 230 KB for a slow drift to over 2 MB for noisy readings), and zooming with the wheel or slider reveals detail again. ## Guidelines 1. **echarts-for-react for React** — Use the wrapper for lifecycle management; pass `option` as prop, and reach for `getEchartsInstance()` only for high-frequency updates 2. **Canvas for large data** — Canvas is the default renderer and the right one beyond roughly a thousand elements; use `sampling` on lines and `large: true` on bar and scatter series, and the `echarts-gl` extension (WebGL) for millions of points 3. **Toolbox for interaction** — Enable `saveAsImage`, `dataZoom`, `restore` in the toolbox; users expect to zoom and download 4. **Responsive resize** — Plain ECharts needs `chart.resize()` from a `ResizeObserver`; `echarts-for-react` resizes on its own (`autoResize`, on by default) and `vue-echarts` when the `autoresize` prop is set. The container must have a height 5. **Theme system** — Use ECharts themes for consistent styling across charts; create custom themes at https://echarts.apache.org/en/theme-builder.html and load them with `echarts.registerTheme(name, theme)` 6. **Updates in React** — A new `option` object is merged into the chart; set `notMerge={true}` when series are removed, or stale ones stay. `lazyUpdate={true}` postpones the redraw to the next frame 7. **Dataset for shared data** — Use ECharts `dataset` component when multiple series share the same data source 8. **Server-side rendering** — Use the built-in SVG SSR mode shown in Example 1 for reports and emails; `VChart` and `ReactECharts` render only in the browser 9. **Dispose charts** — Call `chart.dispose()` when the element is removed; undisposed instances keep memory and listeners 10. **Untrusted data** — A `tooltip.formatter` function returns raw HTML; escape user-supplied text with `echarts.format.encodeHTML()` before inserting it, or it is an XSS risk --- Source attribution: terminal-skills Original project: https://github.com/TerminalSkills/skills/blob/8a9852d489f274538be9bf1c9121aeb403750b1c/skills/echarts/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: terminal-skills Original project: https://github.com/TerminalSkills/skills/blob/8a9852d489f274538be9bf1c9121aeb403750b1c/skills/echarts/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering, Product Management, Marketing Roles: Data Analyst, Frontend Developer, Product Manager, Growth Marketer, Marketing Analyst Specialties: Frontend, API, Cross Platform Tools: Apache Echarts Country applicability: Country not specified Classification basis: Source category, role and specialization labels Instruction SHA-256: 23191a983642912fa755bb49107bfeceb869040574c6a22fc711db2ebb7e9dbd