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Sumant Pattanaik
Published
Edited
Mar 8, 2021
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CAP 6737
Plotly slider use IPlotly slider usePlotly InteractionD3 Quick OverviewColor Solids: RGB and HSLHCL color modelCone Spectral Sensitivity PlotsColor Blind SimulatorColorBlindLibHSV and HSL Color ModelsColor from Wavelength, Correlated Temperature and HTML color pickerPlotly Color UsagePlotlyJS GeoVisualization
GeoVisualization
Visual Cluster AnalysisAssignment 4 Data and related computationWeather ForecastFetch Covid-19 dataWeb Scraping Table data from HTML file.1D Dataviz in PlotlyUS Baby NamesPlotly.Js: Getting Started with Old FaithfulData Fetch and Meta dataUseful Javascript Array functions.Useful D3 Functions for Data handlingIntroduction to Observable and PlotlyJSCAP 6737 Class Practice Notes
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Data Visualization Using D3 and Ploty.js
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AlcoholConsumptionRows
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{
const unpack = key =>
AlcoholConsumptionRows.map(function(row) {
return row[key];
});
const alcohol = AlcoholConsumptionRows.map(d => d.alcohol);
const bubbleSizeScale = d3
.scaleSqrt()
.domain(d3.extent(alcohol))
.range([1, 10]);
const bubbleSize = alcohol.map(d => bubbleSizeScale(d));

var data = [
{
type: 'scattergeo',
locationmode: 'country names',
locations: unpack('location'),
marker: {
size: bubbleSize
},
text: alcohol
}
];

var layout = {
title: 'Pure alcohol consumption<br>among adults (age 15+) in 2010',
height: 500,
width: 900,
geo: {
projection: {
type: projectionOption
}
}
};
const myDiv = DOM.element("div");
Plotly.newPlot(myDiv, data, layout);
return myDiv;
}
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{
const rows = populationRows;
const unpack = (rows, key) =>
rows.map(function(row) {
return row[key];
});
var data = [
{
type: 'choropleth',
locationmode: 'USA-states',
locations: unpack(rows, 'State').map(state => stateNameToPostal[state]),
z: unpack(rows, 'Population'),
text: unpack(rows, 'State'),
autocolorscale: true
}
];

var layout = {
title: '2014 US Popultaion by State',
geo: {
scope: 'usa'
}
};
const myDiv = DOM.element("div");
Plotly.newPlot(myDiv, data, layout);
return myDiv;
}
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mapbox(myRasterDiv,rasterStyle,0)
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mapbox = (div, style, vectorFlag) => {
const rows = EarthquateRows;
function unpack(rows, key) {
return rows.map(function(row) {
return row[key];
});
}

var data = [
{
lon: unpack(rows, 'Longitude'),
lat: unpack(rows, 'Latitude'),
radius: 10,
z: unpack(rows, 'Magnitude'),
type: "densitymapbox",
coloraxis: 'coloraxis',
hoverinfo: 'skip'
}
];

var layout = {
mapbox: { center: { lon: 0, lat: 0 }, style: style, zoom: 0.55 },
coloraxis: { colorscale: "Viridis" },
title: { text: "Earthquake Magnitude" },
width: 900,
height: 500,
margin: { t: 30, b: 0 }
};

var config = { mapboxAccessToken: yourToken };

Plotly.newPlot(div, data, layout, vectorFlag ? config : {});
//Plotly.newPlot(myDiv, data, layout);
return div;
}
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myVectorDiv = DOM.element("div");
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mapbox(myVectorDiv, vectorStyle, 1)
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locations
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medianIncome
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{
const data = [
{
type: 'choroplethmapbox',
locations: locations,
z: medianIncome,
geojson: fips_geojson,
coloraxis: 'coloraxis',
hoverinfo: 'skip'
}
];

const layout = {
mapbox: {
center: { lat: 37.0902, lon: -95.7129 },
style: "open-street-map", //"carto-positron", //"light", //
zoom: 3,
//colorscale: "Viridis",
zmin: 0,
zman: 12,
marker_opacity: 0.5
},

marker_opacity: 0.1,
marker_line_width: 0,

marker_line_width: 0,
title: { text: "Median_Income" },
width: 900,
height: 500,
margin: { t: 30, b: 0 }
};

const myDiv = DOM.element("div");
Plotly.newPlot(myDiv, data, layout, { mapboxAccessToken: yourToken });
return myDiv;
}
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{
const data = [
{
type: 'scattermapbox',
lat: lats,
lon: longs,
mode: 'markers',
marker: {
size: population.map(d =>
d3
.scaleSqrt()
.domain(d3.extent(population))
.range([3, 50])(d)
), //population.map(d=>d/100000).map(d=>d<3?3:d),
line: {
color: 'black',
width: 1
}
},
geojson: fips_geojson,
text: countyStatePopulation
}
];

const layout = {
mapbox: {
center: { lat: 37.0902, lon: -95.7129 },
style: "open-street-map",
zoom: 3
},
title: { text: "population" },
width: 900,
height: 500,
margin: { t: 30, b: 0 }
};

const myDiv = DOM.element("div");
Plotly.newPlot(myDiv, data, layout, { mapboxAccessToken: yourToken });
return myDiv;
}
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fips_geojson = d3.json("https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json")
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medianIncome = locations.map(d=>Math.random()*10000) // Random
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population = countyFIPSLatLong.map(d=>d.POPULATION)
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lats = countyFIPSLatLong.map(d=>+d.LATITUDE)
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longs = countyFIPSLatLong.map(d=>+d.LONGITUDE)
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countyStatePopulation = countyFIPSLatLong.map(d=>d.COUNAME + ", "+d.STNAME+" : "+d.POPULATION)
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countyFIPSLatLong = d3.csvParse(await FileAttachment("CenPop2010_Mean_CO.csv").text(), d3.autoType) // Data Source: https://www2.census.gov/geo/docs/reference/cenpop2010/county/
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md `## Using GeoJson`
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airlines = [...new Set(globalAirportTraffic.map(d => d.airline))]
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airlines.filter(d => d == "Delta")
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mutable feedback = ""
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zeroPad = (num, places) => String(num).padStart(places, '0') //https://stackoverflow.com/questions/2998784/how-to-output-numbers-with-leading-zeros-in-javascript
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