Data Engineer and aspiring Data Visualization Journalist, you can reach me at rjhontomin@gmail.com
lol_dataset
{
const svg = d3.create('svg').attr('viewBox', [0,0,width, height]).style('background', "#463152")
const wrapper = svg.append('g').attr("transform", `translate(${margin.left},${margin.top})`)
const node = wrapper.selectAll('g').data(lol_dataset.nodes).join('g').attr('transform', function(d) { return `translate(${d.x},${ d.y})`}).call(create_node)
// init simulation
const simulation = d3.forceSimulation();
simulation.nodes(lol_dataset.nodes);
// annotations and descriptions
const desc_group = svg.append('g').attr('transform', `translate(30,30)`)
desc_group.append('text').text("Red side vs Blue Side Pick Rate, Patch(11.13 and 11.14)").attr('fill', "white")
desc_group.append('text').attr('transform', `translate(${0}, ${30})`).text(`Region ${curr_region}`).attr('fill', "white").attr('font-size', 30)
wrapper.append("g").attr('transform', `translate(${0},${margin.top})`).call(xAxis)
wrapper.append('line')
.attr('stroke', 'white')
.attr('opacity', 0.8)
.style('stroke-dasharray', '5,5')
.attr('fill', 'white')
.attr('x1', x(0.5))
.attr('y1', 0)
.attr('x2', x(0.5))
.attr('y2', innerHeight)
wrapper.append('text').attr('transform', `translate(${x(0.5)}, ${40})`).text('50% pickrate').attr('fill', 'white').attr('align-text', 'center')
// simulation force
simulation.force("charge", d3.forceManyBody())
.force('y', d3.forceY().y(y('All')).strength(0.1))
.force('x', d3.forceX().x(d => x(parseFloat(d.data[curr_region].red_weight))).strength(1))
.force('collide',d3.forceCollide().radius(function(d) { return r(d.data[curr_region].totalpickrate) + 15}))
simulation.alpha(1).alphaDecay(0.01).velocityDecay(0.36)
simulation.on('tick', () => {
node.transition().duration(700).ease(d3.easeLinear).attr('transform', function(d) {
return `translate(${d.x},${ d.y})`})
})
return Object.assign(svg.node(), {
update(curr_region) {
simulation.alpha(1).alphaDecay(0.01).velocityDecay(0.36 ).restart()
}
});
}
lol_dataset
create_node = (node) => {
node.append('defs').append("clipPath") // define a clip path
.attr("id", d => `circle-clip-${d.champion}`) // give the clipPath an ID
.append("rect") // shape it as an ellipse
.attr("x", v => r(v.data[curr_region].totalpickrate) - 1 * r(v.data[curr_region].totalpickrate) * 2 * calculate_circular_segment(v.data[curr_region].red_weight)) // position the x-centre
.attr("y", v => {return (-r(v.data[curr_region].totalpickrate))}) // position the y-centre
.attr("width", v => calculate_circular_segment(v.data[curr_region].red_weight) * r(v.data[curr_region].totalpickrate) * 2) // set the x radius
.attr("height", v => r(v.data[curr_region].totalpickrate) * 2)
node.append('circle').attr('r', v => r(v.data[curr_region].totalpickrate)).attr('fill', "#5496d0")
node.append('circle').attr('r', v => r(v.data[curr_region].totalpickrate)).attr('clip-path', d => `url(#circle-clip-${d.champion})`).attr('fill', "#f51641")
node.append('text').attr('text-anchor', 'middle').text(v => v.champion).attr('font-size', 15).attr('y', v => r(v.data[curr_region].totalpickrate) > 10 ? 0 : -12).attr('fill', "whitesmoke")
node.attr('opacity', 0.9)
}
calculate_circular_segment = (f) => {
// From Mike Bostock Wonderful Notebook https://observablehq.com/@mbostock/circular-segment
let h = f;
if (h > 0 && h < 1) {
let t0,
t1 = Math.pow(12 * h * Math.PI, 1 / 3);
for (let i = 0; i < 10; ++i) {
t0 = t1;
t1 =
(Math.sin(t0) - t0 * Math.cos(t0) + 2 * h * Math.PI) /
(1 - Math.cos(t0));
}
h = (1 - Math.cos(t1 / 2)) / 2;
}
return h;
}
lol_dataset = FileAttachment("lol_dataset.json").json()
margin = ({"top":50, "bottom":50, "left":150, "right":150})
height = 1200
width = 800
innerHeight = height-margin.top-margin.bottom
innerWidth = width-margin.left-margin.right
y = d3.scaleBand().domain(["All"]).range([0, innerHeight]).padding(1)
r = d3.scaleLinear().domain([0,1]).range([5, width/20])
x = d3.scaleLinear()
.domain([0,1])
.range([0, innerWidth])
xAxis = g => g
.call(d3.axisTop(x).ticks(0))
.call(g => g.select('.text').remove())
.call(g => g.selectAll('.tick line').remove())
.call(g => g.select('.domain').remove())
.call(g => g.append('text')
.attr('x', -10)
.attr('y', 0)
.attr('font-weight', 'bold')
.attr('font-size', "0.65rem")
.attr('fill', 'white')
.attr('text-anchor', 'end')
.text('← Blue Pick Rate'))
.call(g => g.append('text')
.attr('x', x(1)+10)
.attr('y', 0)
.attr('font-weight', 'bold')
.attr('font-size', "0.65rem")
.attr('fill', 'white')
.attr('text-anchor', 'start')
.text('Red Pick Rate →'))
yAxis = g => g
.call(d3.axisLeft(y) .tickFormat(d => `${d} `).ticks(0))
.call(g => g.select('.text').remove())
.call(g => g.append('text')
.attr('x', 0)
.attr('y', 0)
.attr('font-weight', 'bold')
.attr('font-size', "0.87rem")
.attr('fill', 'white')
.attr('text-anchor', 'start')
.text('50% Pick Rate'))
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.