Published
Edited
Feb 29, 2020
Importers
working_memory = {
const svg = d3.create('svg')
.attr('viewBox', [0, 0, width, height]);
const wrapper = svg.append('g')
.attr('transform', `translate(${margin.left}, ${margin.top})`);
wrapper.append('g')
.call(xAxis);
const yAxis = wrapper.append('g')
.attr('class', 'y-axis')
.call(yAxisGenerator);
const grids = wrapper.append('g')
.call(grid);
var rects = wrapper.append('g')
.attr('class', 'bars')
.selectAll('rect')
.data(mydata[0].data)
.join('rect')
.attr('x', d => x(d.group))
.attr('y', d => y(d.mean))
.attr('fill', (d, i) => colorScale[i])
.attr('fill-opacity', 0.99)
.attr('stroke', '#3D4852')
.attr('height', d => y(y.domain()[0]) - y(d.mean))
.attr('width', x.bandwidth())
.on('click', changeYScale)
.style("cursor", "pointer");
// Draw confidence intervals
wrapper.append('g')
.attr('class', 'confInt')
.selectAll('line')
.data(mydata[0].data)
.join('line')
.attr('y1', d => y(d.cl_lower))
.attr('y2', d => y(d.cl_upper))
.attr('x1', d => x(d.group)+ x.bandwidth() / 2)
.attr('x2', d => x(d.group) + x.bandwidth() / 2)
.attr('stroke', 'black');
// Draw top whiskers
wrapper.append('g')
.attr('class', 'topWhiskers')
.selectAll('line')
.data(mydata[0].data)
.join('line')
.attr('y1', d => y(d.cl_upper))
.attr('y2', d => y(d.cl_upper))
.attr('x1', d => x(d.group) + (x.bandwidth()/2) - (x.bandwidth() / 20))
.attr('x2', d => x(d.group) + (x.bandwidth()/2) + (x.bandwidth() / 20))
.attr('stroke', 'black');
// Draw bottom whiskers
wrapper.append('g')
.attr('class', 'bottomWhiskers')
.selectAll('line')
.data(mydata[0].data)
.join('line')
.attr('y1', d => y(d.cl_lower))
.attr('y2', d => y(d.cl_lower))
.attr('x1', d => x(d.group) + (x.bandwidth()/2) - (x.bandwidth() / 20))
.attr('x2', d => x(d.group) + (x.bandwidth()/2) + (x.bandwidth() / 20))
.attr('stroke', 'black');
function changeYScale() {
let yDomain = y.domain();
let tickValues = d3.range(28, 36, 1);
if (y.domain()[0] == 0) {
y.domain([28, 35]);
tickValues = d3.range(28, 36, 1);
} else {
y.domain([0, 35]);
tickValues = d3.range(0, 36, 5);
}
// Update yAxis
yAxis.transition(t)
.call(d3.axisLeft(y)
.ticks(tickValues)
.tickSize(3)
.tickValues(tickValues)
.tickFormat(d3.format(',.0f')))
.call(g => g.selectAll('.tick text')
.attr('font-size', '0.8rem'));
// Update Bars
svg.select('.bars')
.selectAll('rect')
.transition(t)
.attr('y', d => y(d.mean))
.attr('height', d => y(y.domain()[0]) - y(d.mean));
// Update confidence interval
svg.select('.confInt')
.selectAll('line')
.transition(t)
.attr('y1', d => y(d.cl_lower))
.attr('y2', d => y(d.cl_upper))
.attr('stroke', 'black');
// Update whiskers top
svg.select('.topWhiskers')
.selectAll('line')
.transition(t)
.attr('y1', d => y(d.cl_upper))
.attr('y2', d => y(d.cl_upper));
svg.select('.bottomWhiskers')
.selectAll('line')
.transition(t)
.attr('y1', d => y(d.cl_lower))
.attr('y2', d => y(d.cl_lower));
}
return svg.node();
}
html`
<style>
.bars rect:hover {
fill-opacity: 0.92;
transition: fill-opacity 0.2s;
}
</style>
`
t = d3.transition()
.duration(700)
.ease(d3.easeLinear);
colorScale = ['#BCDEFA', '#6CB2EB', '#3490DC']
grid = g => g
.attr('stroke', '#B8C2CC')
.attr('stroke-opacity', 0.5)
.call(g => g.append('g')
.selectAll('line')
.data(d3.range(28, 36, 1))
.join('line')
.attr("x1", x(0))
.attr("x2", (width - margin.left - margin.right))
.attr("y1", d => y(d))
.attr("y2", d => y(d)))
.call(g => g.select('line:last-child').remove());
xAxis = g => g
.attr('transform', `translate(0, ${height - margin.top - margin.bottom})`)
.call(d3.axisBottom(x).tickSizeOuter(0))
.call(g => g.selectAll('.tick line').remove())
.call(g => g.selectAll('.tick text')
.attr('font-size', '0.8rem'));
yAxisGenerator = g => g
.call(d3.axisLeft(y)
.ticks(d3.range(28, 36, 1))
.tickSize(3)
.tickValues(d3.range(28, 36, 1))
.tickFormat(d3.format(',.0f')))
.call(g => g.select('.tick:last-of-type text').clone()
.attr('x', 10)
.attr('y', 0)
.attr('font-size', '0.5rem')
.attr('text-anchor', 'start')
.text("↑ Arbeitsgedächtnis (OSpan Score)"))
.call(g => g.selectAll('.tick text')
.attr('font-size', '0.8rem'));
x = d3.scaleBand()
.domain(mydata[0].data.map((d) => d.group))
.range([0, width - margin.left - margin.right])
.padding(0.2);
y = d3.scaleLinear()
.domain([28, 35])
.range([height - margin.bottom - margin.top, 0])
height = 400;
margin = ({top: 30, left: 30, bottom: 70, right: 30})
mydata = [{av: "Working Memory Capacity",
y: "OSpan Score",
x: "Phone Location",
data: [{group: "Schreibtisch", mean: 30.5, cl_lower: 29.7, cl_upper: 31.4},
{group: "Tasche", mean: 31.2, cl_lower: 30.2, cl_upper: 32.1},
{group: "Anderer Raum", mean: 33.9, cl_lower: 33, cl_upper: 34.9}]},
{av: "Fluid Intelligence",
y: "Correctly Solved Matries (out of 10)",
x: "Phone Location",
data: [{group: "Schreibtisch", mean: 7.8, cl_lower: 7.7, cl_upper: 7.96},
{group: "Tasche", mean: 8.24, cl_lower: 8.1, cl_upper: 8.37},
{group: "Anderer Raum", mean: 8.36, cl_lower: 8.2, cl_upper: 8.5}]}]
d3 = require("d3@5")
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.