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May 4, 2019 03:01
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basic density plot
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| license: mit |
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| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <!-- Load d3.js --> | |
| <script src="https://d3js.org/d3.v4.js"></script> | |
| <!-- Create a div where the graph will take place --> | |
| <div id="my_dataviz"></div> | |
| <script> | |
| // set the dimensions and margins of the graph | |
| var margin = {top: 30, right: 30, bottom: 30, left: 50}, | |
| width = 460 - margin.left - margin.right, | |
| height = 400 - margin.top - margin.bottom; | |
| // append the svg object to the body of the page | |
| var svg = d3.select("#my_dataviz") | |
| .append("svg") | |
| .attr("width", width + margin.left + margin.right) | |
| .attr("height", height + margin.top + margin.bottom) | |
| .append("g") | |
| .attr("transform", | |
| "translate(" + margin.left + "," + margin.top + ")"); | |
| // get the data | |
| d3.csv("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/1_OneNum.csv", function(data) { | |
| // add the x Axis | |
| var x = d3.scaleLinear() | |
| .domain([0, 1000]) | |
| .range([0, width]); | |
| svg.append("g") | |
| .attr("transform", "translate(0," + height + ")") | |
| .call(d3.axisBottom(x)); | |
| // add the y Axis | |
| var y = d3.scaleLinear() | |
| .range([height, 0]) | |
| .domain([0, 0.01]); | |
| svg.append("g") | |
| .call(d3.axisLeft(y)); | |
| // Compute kernel density estimation | |
| var kde = kernelDensityEstimator(kernelEpanechnikov(7), x.ticks(40)) | |
| var density = kde( data.map(function(d){ return d.price; }) ) | |
| // Plot the area | |
| svg.append("path") | |
| .attr("class", "mypath") | |
| .datum(density) | |
| .attr("fill", "#69b3a2") | |
| .attr("opacity", ".8") | |
| .attr("stroke", "#000") | |
| .attr("stroke-width", 1) | |
| .attr("stroke-linejoin", "round") | |
| .attr("d", d3.line() | |
| .curve(d3.curveBasis) | |
| .x(function(d) { return x(d[0]); }) | |
| .y(function(d) { return y(d[1]); }) | |
| ); | |
| }); | |
| // Function to compute density | |
| function kernelDensityEstimator(kernel, X) { | |
| return function(V) { | |
| return X.map(function(x) { | |
| return [x, d3.mean(V, function(v) { return kernel(x - v); })]; | |
| }); | |
| }; | |
| } | |
| function kernelEpanechnikov(k) { | |
| return function(v) { | |
| return Math.abs(v /= k) <= 1 ? 0.75 * (1 - v * v) / k : 0; | |
| }; | |
| } | |
| </script> |
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