Simple time series data modeling composed of a trend, seasonality and random component with dataseries.js.
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December 12, 2015 07:48
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Simple time series data modeling with dataseries.js.
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| <!doctype html> | |
| <meta charset="utf-8"/> | |
| <script src="http://d3js.org/d3.v3.js"></script> | |
| <script src="https://raw.github.com/metmajer/dataseries.js/master/dataseries.min.js"></script> | |
| <script src="https://raw.github.com/metmajer/dataseries.js/master/examples/lib/charts/line.js"></script> | |
| <style> | |
| body { | |
| font-family: Georgia; Arial; sans-serif; | |
| padding: 0; | |
| margin: 0; | |
| } | |
| #graph svg .axis path, | |
| #graph svg .axis line { | |
| fill: none; | |
| stroke: black; | |
| shape-rendering: crispEdges; | |
| } | |
| #graph svg .graph { | |
| fill: none; | |
| stroke: steelblue; | |
| stroke-width: 1.5px; | |
| } | |
| </style> | |
| <body> | |
| <div id="graph"></div> | |
| </body> | |
| <script type="text/javascript"> | |
| var data = ds.generators.f(function(x) { | |
| return ds.functions.linear(x, { a: 1, b: 1 }) | |
| + ds.functions.sin(x, { f: 0.5 }) | |
| + ds.random.rand(-0.2, 0.2); | |
| }) | |
| .inputs(ds.range(0, 1, 0.01)) | |
| .time(new Date(), ds.time.DAY) | |
| .transform(ds.transforms.point) | |
| .values(); | |
| line(d3.select("#graph")) | |
| .width(900) | |
| .height(500) | |
| .margin({top: 20, right: 20, bottom: 40, left: 60}) | |
| .data(data)(); | |
| </script> |
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