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Column Chart
Raw
.block
license: mit
Raw
README.md

An example of a column chart visualising NSS scores per question at Imperial.

This is part of a series of visualisations called My Visual Vocabulary which aims to recreate every visualisation in the FT's Visual Vocabulary from scratch using D3.

Raw
index.html
<!DOCTYPE html>
<head>
<meta charset="utf-8">
<script src="https://d3js.org/d3.v4.min.js"></script>
<style>
body { margin:0;position:fixed;top:0;right:0;bottom:0;left:0; }
text {
font-family: monospace;
}
.outline {
fill: none;
}
.below-bar {
fill: #d7191c;
}
.eq-bar {
fill: #c9c9c9;
}
.above-bar {
fill: #2c7bb6;
}
.legend-label {
font-size: 11px;
}
</style>
</head>
<body>
<script>
var margin = {top: 100, right: 200, bottom: 100, left: 100};
var width = 960 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;
var svg = d3.select("body").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 + ")");
function getValues(d) {
for (var i = 1; i <= 27; i++) {
d[i] = +d[i];
}
return d;
}
var englandMode = true;
var x = d3.scaleBand()
.range([0, width])
.padding(0.2);
var y = d3.scaleLinear()
.range([height, 0]);
d3.csv("nss-results.csv", getValues, function(error, results) {
if (error) throw error;
var englandAverage = results[results.length - 2],
imperialAverage = results[results.length - 1];
results = results.slice(0, -2);
results.forEach(d => {
var eng = [],
imp = [];
for (var i = 1; i <= 27; i++) {
eng[i - 1] = (d[i] - englandAverage[i]).toPrecision(2);
imp[i - 1] = (d[i] - imperialAverage[i]).toPrecision(2);
}
d.englandAvgDiff = eng;
d.imperialAvgDiff = imp;
});
var resultsByQuestion = d3.range(27);
resultsByQuestion = resultsByQuestion.map(d => c = {
belowEng: 0,
equalEng: 0,
aboveEng: 0,
belowImp: 0,
equalImp: 0,
aboveImp: 0
});
results.forEach(d => {
d.englandAvgDiff.forEach((x, i) => {
if (x > 0) resultsByQuestion[i].aboveEng++;
if (x < 0) resultsByQuestion[i].belowEng++;
if (x == 0) resultsByQuestion[i].equalEng++;
})
d.imperialAvgDiff.forEach((x, i) => {
if (x > 0) resultsByQuestion[i].aboveImp++;
if (x < 0) resultsByQuestion[i].belowImp++;
if (x == 0) resultsByQuestion[i].equalImp++;
})
});
x.domain(d3.range(27));
y.domain([0, results.length]);
var title = svg.append("g")
.attr("transform", "translate(" + [width / 2, -30] + ")");
title.append("text")
.attr("text-anchor", "middle")
.text("No. of Departments w/ Scores Above or Below England Avg Per Question");
var legend = svg.append("g")
.attr("transform", "translate(" + [width + margin.right / 5, 0] + ")");
legend.selectAll("rect")
.data(["above-bar", "eq-bar", "below-bar"])
.enter().append("rect")
.attr("class", d => d)
.attr("y", (d, i) => (height / 3) * i)
.attr("height", d => height / 3)
.attr("width", x.bandwidth());
legend.append("rect")
.attr("class", "outline")
.attr("height", height)
.attr("width", x.bandwidth());
legend.selectAll("text")
.data(["Above", "Equal", "Below"])
.enter().append("text")
.attr("class", "legend-label")
.attr("y", (d, i) => (height / 3) * i)
.attr("x", x.bandwidth())
.attr("dx", 10)
.attr("dy", height / 6)
.text(d => d)
var yAxisGroup = svg.append("g")
.attr("class", "y-axis-group");
var yAxis = yAxisGroup.append("g")
.attr("class", "y-axis")
.call(d3.axisLeft(y).tickSize(0));
yAxis.attr("transform", "translate(" + [-5, 0] + ")");
yAxis.select(".domain").style("opacity", 0);
var xAxisGroup = svg.append("g")
.attr("class", "x-axis-group")
.attr("transform", "translate(" + [0, height] + ")")
var xAxis = xAxisGroup.append("g")
.attr("class", "x-axis")
.call(d3.axisBottom(x).tickSize(0).tickFormat(d => d + 1));
xAxis.attr("transform", "translate(" + [0, 5] + ")")
xAxis.select(".domain").style("opacity", 0);
var xLabel = xAxisGroup.append("text")
.attr("transform", "translate(" + [width / 2, margin.bottom / 2] + ")")
.attr("text-anchor", "middle")
.text("Question Number")
var barGroups = svg.append("g")
.attr("class", "bar-groups")
.selectAll("g")
.data(resultsByQuestion)
.enter().append("g")
.attr("class", "bar-group")
.attr("transform", (d, i) => "translate(" + [x(i), 0] + ")")
var aboveBars = barGroups.append("rect")
.attr("class", "above-bar")
.attr("y", d => y(d.belowEng + d.equalEng + d.aboveEng))
.attr("height", d => height - y(d.belowEng + d.equalEng + d.aboveEng))
.attr("width", x.bandwidth());
var eqBars = barGroups.append("rect")
.attr("class", "eq-bar")
.attr("y", d => y(d.equalEng + d.belowEng))
.attr("height", d => height - y(d.equalEng + d.belowEng))
.attr("width", x.bandwidth());
var belowBars = barGroups.append("rect")
.attr("class", "below-bar")
.attr("y", d => y(d.belowEng))
.attr("height", d => height - y(d.belowEng))
.attr("width", x.bandwidth());
var outlines = barGroups.append("rect")
.attr("class", "outline")
.attr("height", d => y(0))
.attr("width", x.bandwidth());
d3.select("svg").on("click", switchBetween);
function switchBetween() {
function newY(d) {
var aY, eY, bY;
if (englandMode) {
aY = y(d.belowImp + d.equalImp + d.aboveImp),
eY = y(d.equalImp + d.belowImp),
bY = y(d.belowImp);
} else {
aY = y(d.belowEng + d.equalEng + d.aboveEng),
eY = y(d.equalEng + d.belowEng),
bY = y(d.belowEng);
}
return [aY, eY, bY];
}
aboveBars
.transition()
.attr("y", d => newY(d)[0])
.attr("height", d => height - newY(d)[0]);
eqBars
.transition()
.attr("y", d => newY(d)[1])
.attr("height", d => height - newY(d)[1]);
belowBars
.transition()
.attr("y", d => newY(d)[2])
.attr("height", d => height - newY(d)[2]);
if (englandMode) {
title.select("text")
.text("No. of Departments w/ Scores Above or Below Imperial Avg Per Question");
} else {
title.select("text")
.text("No. of Departments w/ Scores Above or Below England Avg Per Question");
}
englandMode = !englandMode;
}
});
</script>
</body>
Raw
nss-results.csv
department 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
Medicine 0.88 0.82 0.91 0.80 0.75 0.82 0.93 0.73 0.76 0.56 0.55 0.85 0.74 0.72 0.76 0.77 0.75 0.88 0.93 0.91 0.78 0.91 0.93 0.80 0.72 0.75 0.90
Other Med 0.88 0.74 0.89 0.86 0.80 0.77 0.70 0.50 0.68 0.35 0.59 0.73 0.68 0.59 0.35 0.53 0.59 0.71 0.84 0.85 0.64 0.88 0.92 0.83 0.64 0.56 0.70
Biology 0.87 0.84 0.89 0.82 0.83 0.81 0.71 0.75 0.62 0.71 0.48 0.85 0.66 0.67 0.72 0.86 0.75 0.88 0.82 0.86 0.52 0.89 0.87 0.69 0.62 0.47 0.81
Other Bio 0.90 0.78 0.83 0.82 0.83 0.86 0.80 0.66 0.64 0.70 0.52 0.82 0.58 0.62 0.67 0.86 0.86 0.78 0.85 0.86 0.51 0.89 0.88 0.74 0.74 0.51 0.83
Chemistry 0.84 0.75 0.89 0.75 0.80 0.74 0.82 0.51 0.56 0.59 0.53 0.75 0.60 0.52 0.52 0.74 0.67 0.85 0.84 0.89 0.57 0.78 0.79 0.63 0.48 0.53 0.73
Phys & Astro 0.82 0.73 0.86 0.71 0.71 0.68 0.60 0.47 0.43 0.46 0.56 0.82 0.56 0.62 0.57 0.70 0.70 0.78 0.81 0.87 0.45 0.76 0.82 0.54 0.50 0.40 0.67
Geology 0.99 0.97 0.96 0.93 0.93 0.94 0.97 0.93 0.87 0.97 0.94 0.97 0.97 0.99 0.99 0.91 0.99 1.00 0.96 1.00 0.89 0.94 0.99 0.99 0.97 0.86 0.97
Maths & Stats 0.87 0.76 0.83 0.79 0.85 0.70 0.62 0.57 0.69 0.53 0.55 0.87 0.68 0.68 0.76 0.73 0.81 0.91 0.82 0.91 0.59 0.70 0.88 0.78 0.67 0.52 0.78
Computing 0.82 0.79 0.94 0.82 0.85 0.87 0.91 0.54 0.79 0.54 0.63 0.90 0.78 0.64 0.74 0.74 0.87 0.92 0.89 0.93 0.71 0.98 0.95 0.85 0.80 0.66 0.86
Gen Eng 0.92 0.91 0.97 0.86 0.91 0.97 0.85 0.57 0.74 0.77 0.66 0.91 0.80 0.69 0.86 0.82 0.85 0.80 0.81 0.91 0.85 0.94 0.92 0.94 0.83 0.57 0.97
Mech Eng 0.91 0.83 0.93 0.87 0.91 0.90 0.88 0.77 0.81 0.78 0.83 0.90 0.87 0.88 0.85 0.83 0.92 0.85 0.88 0.89 0.74 0.99 0.99 0.84 0.89 0.57 0.86
Aero Eng 0.71 0.67 0.81 0.75 0.72 0.77 0.74 0.65 0.67 0.43 0.57 0.86 0.73 0.59 0.70 0.70 0.75 0.90 0.87 0.87 0.57 0.96 0.86 0.61 0.57 0.53 0.78
E&E Eng 0.88 0.81 0.92 0.85 0.88 0.89 0.86 0.75 0.71 0.60 0.65 0.86 0.69 0.68 0.80 0.79 0.88 0.89 0.88 0.97 0.72 0.96 0.92 0.80 0.85 0.66 0.86
Civ Eng 0.93 0.81 0.94 0.88 0.86 0.89 0.93 0.69 0.75 0.87 0.69 0.96 0.90 0.82 0.90 0.90 0.90 0.96 0.96 0.94 0.85 0.97 0.94 0.92 0.79 0.77 0.94
Chem Eng 0.86 0.79 0.88 0.94 0.88 0.87 0.86 0.75 0.70 0.61 0.68 0.95 0.74 0.74 0.84 0.82 0.95 0.80 0.84 0.86 0.70 0.96 0.94 0.85 0.92 0.58 0.84
Materials 0.85 0.78 0.85 0.73 0.91 0.90 0.73 0.54 0.69 0.65 0.69 0.79 0.71 0.73 0.66 0.82 0.77 0.94 0.89 0.98 0.72 0.91 0.85 0.80 0.65 0.71 0.87
Business 0.79 0.64 0.71 0.67 0.69 0.76 0.76 0.57 0.67 0.50 0.55 0.79 0.57 0.59 0.62 0.69 0.79 0.81 0.83 0.88 0.56 0.88 0.80 0.69 0.66 0.59 0.66
England Average 0.89 0.83 0.85 0.82 0.84 0.85 0.82 0.72 0.73 0.73 0.74 0.86 0.79 0.75 0.71 0.79 0.77 0.83 0.87 0.86 0.72 0.86 0.84 0.76 0.62 0.58 0.84
Imperial Average 0.87 0.80 0.89 0.82 0.83 0.83 0.82 0.66 0.69 0.62 0.62 0.87 0.73 0.70 0.74 0.78 0.81 0.87 0.87 0.91 0.68 0.90 0.90 0.78 0.73 0.61 0.84
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