This post describes how to build a very basic
stacked barplot
with d3.js. You can see many other examples in the
barplot section
of the gallery. Learn more about the theory of boxplots in
data-to-viz.com. This example works with d3.js v4
and v6
d3.stack()
function is used to stack the
data: it computes the new position of each subgroup on the Y
axis
d3.stack()
can be used to create
a set of rect
as for a normal barplot.
<!DOCTYPE html>
<meta charset="utf-8">
<!-- Load d3.js -->
<script src="https://d3js.org/d3.v4.js"></script>
<!-- Create a div where the graph will take place -->
<div id="my_dataviz"></div>
<!DOCTYPE html>
<meta charset="utf-8">
<!-- Load d3.js -->
<script src="https://d3js.org/d3.v6.js"></script>
<!-- Create a div where the graph will take place -->
<div id="my_dataviz"></div>
<script>
// set the dimensions and margins of the graph
var margin = {top: 10, right: 30, bottom: 20, left: 50},
width = 460 - margin.left - margin.right,
height = 400 - margin.top - margin.bottom;
// append the svg object to the body of the page
var svg = d3.select("#my_dataviz")
.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 + ")");
// Parse the Data
d3.csv("https://raw.githubusercontent.com/holtzy/D3-graph-gallery/master/DATA/data_stacked.csv", function(data) {
// List of subgroups = header of the csv files = soil condition here
var subgroups = data.columns.slice(1)
// List of groups = species here = value of the first column called group -> I show them on the X axis
var groups = d3.map(data, function(d){return(d.group)}).keys()
// Add X axis
var x = d3.scaleBand()
.domain(groups)
.range([0, width])
.padding([0.2])
svg.append("g")
.attr("transform", "translate(0," + height + ")")
.call(d3.axisBottom(x).tickSizeOuter(0));
// Add Y axis
var y = d3.scaleLinear()
.domain([0, 60])
.range([ height, 0 ]);
svg.append("g")
.call(d3.axisLeft(y));
// color palette = one color per subgroup
var color = d3.scaleOrdinal()
.domain(subgroups)
.range(['#e41a1c','#377eb8','#4daf4a'])
//stack the data? --> stack per subgroup
var stackedData = d3.stack()
.keys(subgroups)
(data)
// Show the bars
svg.append("g")
.selectAll("g")
// Enter in the stack data = loop key per key = group per group
.data(stackedData)
.enter().append("g")
.attr("fill", function(d) { return color(d.key); })
.selectAll("rect")
// enter a second time = loop subgroup per subgroup to add all rectangles
.data(function(d) { return d; })
.enter().append("rect")
.attr("x", function(d) { return x(d.data.group); })
.attr("y", function(d) { return y(d[1]); })
.attr("height", function(d) { return y(d[0]) - y(d[1]); })
.attr("width",x.bandwidth())
})
</script>
<script>
// set the dimensions and margins of the graph
const margin = {top: 10, right: 30, bottom: 20, left: 50},
width = 460 - margin.left - margin.right,
height = 400 - margin.top - margin.bottom;
// append the svg object to the body of the page
const svg = d3.select("#my_dataviz")
.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})`);
// Parse the Data
d3.csv("https://raw.githubusercontent.com/holtzy/D3-graph-gallery/master/DATA/data_stacked.csv").then( function(data) {
// List of subgroups = header of the csv files = soil condition here
const subgroups = data.columns.slice(1)
// List of groups = species here = value of the first column called group -> I show them on the X axis
const groups = data.map(d => (d.group))
// Add X axis
const x = d3.scaleBand()
.domain(groups)
.range([0, width])
.padding([0.2])
svg.append("g")
.attr("transform", `translate(0, ${height})`)
.call(d3.axisBottom(x).tickSizeOuter(0));
// Add Y axis
const y = d3.scaleLinear()
.domain([0, 60])
.range([ height, 0 ]);
svg.append("g")
.call(d3.axisLeft(y));
// color palette = one color per subgroup
const color = d3.scaleOrdinal()
.domain(subgroups)
.range(['#e41a1c','#377eb8','#4daf4a'])
//stack the data? --> stack per subgroup
const stackedData = d3.stack()
.keys(subgroups)
(data)
// Show the bars
svg.append("g")
.selectAll("g")
// Enter in the stack data = loop key per key = group per group
.data(stackedData)
.join("g")
.attr("fill", d => color(d.key))
.selectAll("rect")
// enter a second time = loop subgroup per subgroup to add all rectangles
.data(d => d)
.join("rect")
.attr("x", d => x(d.data.group))
.attr("y", d => y(d[1]))
.attr("height", d => y(d[0]) - y(d[1]))
.attr("width",x.bandwidth())
})
</script>
Wondering what chart type you should use? Check my
Data To Viz project! It is a
comprehensive classification of chart types organized by data
input format. Get a high-resolution version of the decision tree in your
inbox now!