mutable inspectData =''
mutable inspectSelector = ''
byDepartmentClassification = d3.nest()
.key(d => d.department)
.key(d => d.classification)
.entries(rowdata)
// Pass thingy into hierarchy
hier = d3.hierarchy(prepped_tree, funcChildren)
treemap = data => d3.treemap()
.tile(d3[tile])
.size([width, height])
.padding(vPadding)
.paddingTop(vPaddingTop)
.round(true)
(d3.hierarchy(data, funcChildren)
// running .sum in this way will count the nodes, similar to .count
// ideally we want to filter...
// .sum(d => (d.children ? d.parent : 1)).value
// changed sum -> count, counting leaves to generate values
// for now this didn't do much, just changing the output graph a little, rectangles fill up properly
.count(d => 1)
)
// When we run treemap, this function wraps up stuff
// and mutates the input, computing values that
// will be passed into root for the chart all the way above...
// The code below is called in chart but you can remove it from this here.
// This line is only included so we can inspect the output above...
treemap(prepped_tree);
// There is probably an easier way to do this in JS
// but this way uses a constructor
obj = function(name, children) {
this.name = name;
this.values = children; }
prepped_tree = new obj("metStuff", byDepartmentClassification);
// This function is used to choose where the children are located
funcChildren = d => d.values
funcChildren(prepped_tree)
2000
height = 900
format = d3.format(",d")
color = d3.scaleSequential([8, 0], d3.interpolateViridis)
d3 = require("d3@5")
mutable objectSecondaryImg = [];
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
