The avatar for @spattana
Sumant Pattanaik
Published
Edited
Sep 13, 2021
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Data Visualization Using D3 and Ploty.js
Introduction to Observable and PlotlyJSUseful Javascript Array functions.Plotly.Js: Getting Started with Old FaithfulUseful D3 Functions for Data handlingPlotly Color UsageGeoVisualizationGapminder data in PlotlySample US Wind Data VizPlotlyJS GeoVisualizationHCL color modelHSV and HSL Color ModelsColor Blind SimulatorColorBlindLibD3: IntroducingWebGL Volume RenderingColor from Wavelength, Correlated Temperature and HTML color pickerColor Solids: RGB and HSL2D Vector Field Visualization
1D Dataviz in Plotly
Stock Market Performance of Presidents Trump, Obama, W. Bush, Clinton, H.W. Bush, Reagan During their first term.SVG cheat sheetScales and AxesFetch Covid-19 data
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CAP 6737
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md `## Strip/Jitter Plot.`
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new Array(oneDdata.length).fill(1)
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viewof jitterScale = slider()
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stripPlotData = {
const data = new Array(oneDdata.length).fill(0);
if ( jitter=="true") return data.map(d=>jitterScale*(Math.random()-0.5));
else return data;
}
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binSize = {
const xExtent = dataExtent;
return (xExtent[1]-xExtent[0])/nBins
}
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xAxisLabel = dim==='eruptions'?'Eruption Duration':'Waiting Time'
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dataExtent = d3.extent(oneDdata);
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oneDdata = extract(dim)
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densityDataLength = 100
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delta = (dataExtent[1]-dataExtent[0])/densityDataLength
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densityX = new Array(densityDataLength+1).fill(0).map((d,i)=>dataExtent[0]+i*delta)
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kernel = kernels[kernelname](bandWidth)
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densityY = kde(kernel,densityX,oneDdata)
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function kde(kernel, Xs, data) {
return Xs.map(x => d3.mean(data, d => kernel(Math.abs(x - d)/bandWidth)/bandWidth));
}
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oldFaithful = d3.csvParse(await FileAttachment("faithful.csv").text(), d3.autoType);
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extract = attribute=>oldFaithful.map(d=>d[attribute]);
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//import {epanechnikov} from "@d3/kernel-density-estimation"
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kernels = ({
cosine: () => (x => x <= 1 ? (Math.PI/4)*Math.cos(x*Math.PI/2): 0),
epanechnikov: () => (x => x <= 1 ? (3/4) * (1 - x * x) : 0),
quartic: () => (x => x <= 1 ? (15/16)*((1 - x * x)**2) : 0),
triweight: () => (x => x <= 1 ? (35/32)*((1 - x * x)**3) : 0),
tricube: () => (x => x <= 1 ? (35/32)*((1 - x**3)**3) : 0),
uniform:() => (x => x <= 1 ? 0.5 : 0),
triangle: () => (x => x <= 1 ? (1 - x): 0)
})
// Chosen Kernels with finite extent from https://en.wikipedia.org/wiki/Kernel_(statistics)
// Note all the kernels are symmetric and are zero outside the range -1 to + 1.
// So input to these functions are values that are translated and scaled so that it is zero at the peak value of the function.
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Plotly = require("plotly.js-dist") //require("https://cdn.plot.ly/plotly-latest.min.js")
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import {radio, slider} from "@jashkenas/inputs"
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md`## D3 Based visualization`
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Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
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