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src=\"uPlot.svg\" alt=\"uPlot logo\" height=\"36\" align=\"top\"\u003e μPlot\u003c/h2\u003e\n\nA small ([~50 KB min](https://github.com/leeoniya/uPlot/tree/master/dist/uPlot.iife.min.js)), [fast](#performance) chart for time series, lines, areas, ohlc \u0026 bars _(MIT Licensed)_\n\n---\n### Introduction\n\nuPlot is a [fast, memory-efficient](#performance) [Canvas 2D](https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D)-based chart for plotting [time series](https://en.wikipedia.org/wiki/Time_series), lines, areas, ohlc \u0026 bars. From a cold start it can create an [interactive chart containing 166,650 data points](https://leeoniya.github.io/uPlot/bench/uPlot.html) in 25ms, scaling linearly at [~100,000 pts/ms](https://leeoniya.github.io/uPlot/bench/uPlot-10M.html) afterwards. In addition to fast initial render, the zooming and cursor performance is by far the best of any similar charting lib; at ~50 KB, it's likely the smallest and fastest time series plotter that doesn't make use of [context-limited](https://bugs.chromium.org/p/chromium/issues/detail?id=771792) WebGL shaders or WASM, both of which have much higher startup cost and code size.\n\nIn most sane cases, you can live-stream data with uPlot at 60fps, though it may begin to struggle beyond 100k in-view points.\nWhen [updating 3,600 points at 60fps](https://leeoniya.github.io/uPlot/demos/sine-stream.html), uPlot uses 10% CPU and 12.3MB RAM.\nThe next fastest Canvas-based libs (Chart.js and ECharts) use [40% / 77MB](https://leeoniya.github.io/uPlot/bench/Chart.js4-sine-stream.html) and [70% / 85MB](https://leeoniya.github.io/uPlot/bench/ECharts5-sine-stream.html), respectively.\nIf you need to stream, give [unclog your rendering pipeline](#unclog-your-rendering-pipeline) a try.\nIf that does not help, consider reducing the update frequency or switch to a WebGL/WebGPU solution, like [danchitnis/webgl-plot](https://github.com/danchitnis/webgl-plot), [huww98/TimeChart](https://github.com/huww98/TimeChart), [epezent/implot](https://github.com/epezent/implot).\n\n---\n![uPlot Chart](uPlot.png \"uPlot Chart\")\n\n---\n### Features\n\n- Multiple series w/toggle\n- Multiple y-axes, scales \u0026 grids\n- Temporal or numeric x-axis\n- Linear, uniform or [logarithmic](https://leeoniya.github.io/uPlot/demos/log-scales.html) scales\n- Line \u0026 Area styles (stroke, fill, width, dash)\n- Pluggable path renderers [linear, spline, stepped, bars](https://leeoniya.github.io/uPlot/demos/line-paths.html)\n- Zoom with auto-rescale\n- Legend with live values\n- Support for [IANA Time Zone Names](https://en.wikipedia.org/wiki/List_of_tz_database_time_zones) \u0026 DST\n- [Support for missing data](https://leeoniya.github.io/uPlot/demos/missing-data.html)\n- [Cursor sync for multiple charts](https://leeoniya.github.io/uPlot/demos/sync-cursor.html)\n- [Focus closest series](https://leeoniya.github.io/uPlot/demos/focus-cursor.html)\n- [Data streaming (live update)](https://leeoniya.github.io/uPlot/demos/stream-data.html)\n- [High / Low bands](https://leeoniya.github.io/uPlot/demos/high-low-bands.html)\n- A lean, consistent, and powerful API with hooks \u0026 plugins\n\n---\n### Non-Features\n\nIn order to stay lean, fast and focused the following features will not be added:\n\n- No data parsing, aggregation, summation or statistical processing - just do it in advance. e.g. [simples-statistics](https://simple-statistics.github.io/), https://github.com/leeoniya/uDSV\n- No transitions or animations - they're always pure distractions.\n- No collision avoidance for axis tick labels, so may require manual tweaking of spacing metrics if label customization significiantly increases default label widths.\n- No stacked series: see [\"Stacked Area Graphs Are Not Your Friend\"](https://web.archive.org/web/20221208193656/https://everydayanalytics.ca/2014/08/stacked-area-graphs-are-not-your-friend.html) and a [horrific demo](https://leeoniya.github.io/uPlot/demos/stacked-series.html). While smooth spline interpolation is available, its use is strongly discouraged: [Your data is misrepresented!](http://www.vizwiz.com/2011/12/when-you-use-smoothed-line-chart-your.html). Both visualizations are terrible at accurately communicating information.\n- No built-in drag scrolling/panning due to ambiguous native zoom/selection behavior. However, this can be added externally via the plugin/hooks API: [zoom-wheel](https://leeoniya.github.io/uPlot/demos/zoom-wheel.html), [zoom-touch](https://leeoniya.github.io/uPlot/demos/zoom-touch.html).\n\n---\n### Documentation (WIP)\n\nThe docs are a perpetual work in progress, it seems.\nStart with [/docs/README.md](https://github.com/leeoniya/uPlot/tree/master/docs) for a conceptual overview.\nThe full API is further documented via comments in [/dist/uPlot.d.ts](https://github.com/leeoniya/uPlot/blob/master/dist/uPlot.d.ts).\nAdditionally, an ever-expanding collection of runnable [/demos](https://leeoniya.github.io/uPlot/demos/index.html) covers the vast majority of uPlot's API.\n\n---\n### Third-party Integrations\n\n- [React, Vue.js and Svelte](https://github.com/skalinichev/uplot-wrappers) (Sergey Kalinichev)\n- [Python](https://github.com/stephane-caron/uplot-python) (Stéphane Caron)\n\n---\n### Performance\n\nBenchmarks done on this hardware:\n\n- Date: 2023-03-11\n- AMD Ryzen 7 PRO 5850U @ 1.9GHz, 32GB RAM\n- EndeavourOS/Arch (KDE/Plasma), Chrome 113.0.5638.0 (64-bit)\n- 4K display scaled to 1440p (1.5 devicePixelRatio)\n\n![uPlot Performance](perf.png \"uPlot Performance\")\n\nFull size: https://leeoniya.github.io/uPlot/demos/multi-bars.html\n\nRaw data: https://github.com/leeoniya/uPlot/blob/master/bench/results.json\n\n\u003cpre\u003e\n| lib                    | size    | done    | js,rend,paint,sys | heap peak,final | mousemove (10s)     |\n| ---------------------- | ------- | ------- | ----------------- | --------------- | ------------------- |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/uPlot.html\"\u003euPlot v1.6.24\u003c/a\u003e          | 47.9 KB |   34 ms |   51   2   1   34 |  21 MB   3 MB   |  218  360  146  196 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/Chart.js4.html\"\u003eChart.js v4.2.1\u003c/a\u003e        |  254 KB |   38 ms |   90   2   1   40 |  29 MB  10 MB   | 1154   46  165  235 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/Flot.html\"\u003eFlot v3.0.0\u003c/a\u003e            |  494 KB |   60 ms |  105   5   1   52 |  41 MB  21 MB   | ---                 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/ECharts5.html\"\u003eECharts v5.4.1\u003c/a\u003e         | 1000 KB |   55 ms |  148   3   1   35 |  17 MB   3 MB   | 1943  444  203  208 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/dygraphs.html\"\u003edygraphs v2.2.1\u003c/a\u003e        |  132 KB |   90 ms |  163   2   1   33 |  88 MB  42 MB   | 1438  371  174  268 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/LightningChart.html\"\u003eLightningChart® v4.0.2\u003c/a\u003e | 1300 KB |  --- ms |  250   2   1   33 |  33 MB  13 MB   | 5390  120  128  325 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/CanvasJS.html\"\u003eCanvasJS v3.7.5\u003c/a\u003e        |  489 KB |  130 ms |  266   4   1   35 |  98 MB  69 MB   | 1030  445   90  246 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/dvxCharts.html\"\u003edvxCharts v5.1.0\u003c/a\u003e       |  373 KB |  160 ms |  264  23   1   62 | 100 MB  61 MB   |  687  779  206  197 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/Highcharts.html\"\u003eHighcharts v10.3.3\u003c/a\u003e     |  413 KB |  --- ms |  416   7   1   38 |  97 MB  55 MB   | 1286  824  205  242 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/Plotly.js.html\"\u003ePlotly.js v2.18.2\u003c/a\u003e      | 3600 KB |  310 ms |  655  14   1   40 | 104 MB  70 MB   | 1814  163   25  208 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/ApexCharts.html\"\u003eApexCharts v3.37.1\u003c/a\u003e     |  503 KB |  685 ms |  694   9   1   33 | 175 MB  46 MB   | 1708  421  106  207 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/ZingChart.html\"\u003eZingChart v2.9.10\u003c/a\u003e      |  871 KB |  681 ms |  717   7   1  105 | 290 MB 195 MB   | 9021  305   41   71 |\n| \u003ca href=\"https://leeoniya.github.io/uPlot/bench/amCharts5.html\"\u003eamCharts v5.3.7\u003c/a\u003e        |  625 KB |  --- ms | 1601   3   3   46 | 147 MB 121 MB   | 9171   71  460  167 |\n\u003c/pre\u003e\n\n- libs are sorted by their initial, cold-start, render performance (excluding network transfer time to download the lib)\n- `size` includes the lib itself plus any dependencies required to render the benchmark, e.g. Moment, jQuery, etc.\n- Flot does not make available any minified assets and all their examples use the uncompressed sources; they also use an uncompressed version of jQuery :/\n\nSome libraries provide their own performance demos:\n\n- https://echarts.apache.org/next/examples/en/index.html\n- https://github.com/sveinn-steinarsson/flot-downsample/\n- https://dygraphs.com/tests/dygraph-many-points-benchmark.html\n- https://www.chartjs.org/docs/latest/general/performance.html\n- https://dash.plotly.com/performance\n- https://www.highcharts.com/docs/advanced-chart-features/boost-module\n- https://danchitnis.github.io/webgl-plot-examples/vanilla/\n- https://huww98.github.io/TimeChart/docs/performance\n- https://www.arction.com/lightningchart-js-performance/\n\nTODO (all of these use SVG, so performance should be similar to Highcharts):\n\n- Chartist.js\n- d3-based\n  - C3.js\n  - dc.js\n  - MetricsGraphics\n  - rickshaw\n\n---\n### Unclog your rendering pipeline\n\nYour browser's performance is highly dependent on your hardware, operating system, and GPU drivers.\n\nIf you're using a Chromium-based browser, there are some hidden settings that can unlock significant performance improvements for Canvas2D rendering.\nMost of these have to do with where and how the rasterization is performed.\n\nHead over to https://leeoniya.github.io/uPlot/demos/sine-stream.html and open up Chrome's DevTools (F12), then toggle the Performance Monitor.\n\n![Chrome DevTools Peformance Monitor](img/chrome-perf-monitor.png \"Chrome DevTools Peformance Monitor\")\n\nFor me:\n\n- On Windows 10 Desktop, Core i7-8700, 16GB RAM, AMD RX480 GPU, 2048 x 1080 resolution = 57% CPU usage\n- On Manjaro Laptop (Arch Linux), AMD Ryzen 7 PRO 5850U, 48GB RAM, AMD Radeon RX Vega 8 (integrated GPU), 4K resolution = **99% CPU usage**\n\nIf your CPU is close to 100%, it may be rasterizing everything in the same CPU process.\n\nPop open `chrome://gpu` and see what's orange or red.\n\n![Chrome gpu](img/chrome-gpu.png \"Chrome gpu\")\n\nThen open `chrome://flags` and search for \"raster\" to see what can be force-enabled.\n\n![Chrome flags](img/chrome-flags.png \"Chrome flags\")\n\n- On my Manjaro/Ryzen/Integrated GPU setup, force-enabling `Canvas out-of-process rasterization` resulted in a dramatic framerate improvement.\n- On my Windows/i7/Dedicated GPU setup, toggling the same flags moved the work to another process (still good), but did not have a significant framerate impact.\n\nYMMV!\n\n---\n### Acknowledgements\n\n- Dan Vanderkam's [dygraphs](https://github.com/danvk/dygraphs) was a big inspiration; in fact, my stale [pull request #948](https://github.com/danvk/dygraphs/pull/948) was a primary motivator for μPlot's inception.\n- Adam Pearce for [#15 - remove redundant lineTo commands](https://github.com/leeoniya/uPlot/issues/15).\n","funding_links":["https://github.com/sponsors/leeoniya"],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleeoniya%2Fuplot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fleeoniya%2Fuplot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleeoniya%2Fuplot/lists"}