I am working on creating a Treemap from a csv file.
The data in the csv file is hierarchical, as a result I used d3.nest()
.
However, the resulting JSON is in the form of {key:"United States", values:[...]}
.
The zoom-able treemap requires hierarchy as {name:"United States", children:[...]}
.
I have tried replacing name and children to key and values in the example, but it doesn't work.
If anyone has already looked into using key and values on a zoomable treemap, please help. I am new to D3 and I don't know whether d.children means structure or value from the data.
This is the code to convert World Continents, Regions, and Countries from CSV to a hierarchy using d3.
$ d3.csv("../Data/WorldPopulation.csv", function (pop) {
var treeData= { "key": "World", "values": d3.nest()
.key(function (d) { return d.Major_Region; })
.key(function (d) { return d.Region; })
.key(function (d) { return d.Country; })
.entries(pop)
};
The first few lines of the result is:
`[{"key":"AFRICA","values":[{"key":"Eastern Africa","values"
[{"key":"Burundi","values":[.........`
I can not use the zoomable treemap because it requires name and children labels in json rather than key and values.
The best way to convert a nest to a treemap is specifying children accessor function with Treemap.children().
In the zoomable treemap example , it requires not only "children" but also "name" and "size". You can do either:
1)change the accessor functions of those properties so that keep using "key" and "value".
Let's change the source code.
1.1)line 79 & 86:
.style("fill", function(d) { return color(d.parent.name); });
.text(function(d) { return d.name; })
Replace ".name" with ".YOUR_NAME_KEY"(i.e. ".key")
.style("fill", function(d) { return color(d.parent.YOUR_NAME_KEY); });
.text(function(d) { return d.YOUR_NAME_KEY; })
1.2)line 47:
var treemap = d3.layout.treemap()
.round(false)
.size([w, h])
.sticky(true)
.value(function(d) { return d.size; });
Append a line to specify children accessor function.(i.e ".values")
var treemap = d3.layout.treemap()
.round(false)
.size([w, h])
.sticky(true)
.value(function(d) { return d.YOUR_SIZE_KEY; })
.children(function(d){return d.YOUR_CHILDREN_KEY});
1.3)line 97 & 51:
function size(d) {
return d.size;
}
Replace ".size" with ".YOUR_SIZE_KEY"(you didn't mention in your resulting JSON)
function size(d) {
return d.YOUR_SIZE_KEY;
}
P.S. Maybe something omitted, you need verify it yourself.
2)convert your JSON structure to fit the example with Array.map().
I completely agree with @Anderson that the easiest approach to this issue is to use the treemap children(function)
and .value(function)
methods to specify the names of the properties within the nested dataset.
However, a duplicate question has recently been posted in which the questioner specifically asks for help using an Array.map
approach. So here it is:
The array map(function)
method creates a new array where each element in the array is the result of running the specified function on each element of the original array. Specifically, the function is run with up to three arguments: the element from the original array, the index of that element, and the original array as a whole. For the purposes of manipulating the property names, we only need the first argument.
The nested data in the original post has three levels, equivalent to the three key functions. Therefore, we're going to need a three-level mapping function:
var treeData = {
"key": "World",
"values": d3.nest()
.key(function(d) {
return d.Major_Region;
})
.key(function(d) {
return d.Region;
})
.key(function(d) {
return d.Country;
})
.entries(pop)
};
var treeData2 = {
"name": "World",
"children": treeData.values.map(function(major) {
return {
"name": major.key,
"children": major.values.map(function(region) {
return {
"name": region.key,
"children": region.values.map(function(country) {
return {
"name": country.key,
"children": country.values
};
}) //end of map(function(country){
};
}) //end of map(function(region){
};
}) //end of map(function(major){
}; //end of var declaration
You could also probably implement this with a recursive function, which would be especially useful if you had many more levels of nesting.
Since d3-collection
has been deprecated in favor of d3.array
, we can use d3.rollups
to achieve what used to work with d3.nest
:
var input = [
{ "Continent": "Europe", "Country": "Spain", "City": "Madrid", "value": "3" },
{ "Continent": "Europe", "Country": "Spain", "City": "Barcelona", "value": "30" },
{ "Continent": "Europe", "Country": "France", "City": "Paris", "value": "243" },
{ "Continent": "America", "Country": "Argentina", "City": "Buenos Aires", "value": "300" },
{ "Continent": "America", "Country": "Argentina", "City": "Buenos Aires", "value": "250" },
{ "Continent": "America", "Country": "Argentina", "City": "Rosario", "value": "200" }
];
// Nesting:
var rolled_up = d3.rollups(
input, // The array on which to apply the rollup
vs => d3.sum(vs, v => +v.value), // The reducing function to apply on rollups' leafs
d => d.Continent, // A first level of nesting
d => d.Country // A second level of nesting
);
// Formatting:
var output = {
key: "World",
values: rolled_up.map(x => ({
key: x[0], // continent
values: x[1].map(x => ({
key: x[0], // country
values: x[1]
}))
}))
}
console.log(output);
<script src="https://d3js.org/d3-array.v2.min.js"></script>
This:
d3.rollups
:
d3.rollups
take 3 parameters: the input array, a reducing function and a variable number of mappers for the different levels of nestingvs => d3.sum(vs, v => +v.value)
) takes the values associated to the grouped countries, cast them to int and sum them (using d3.sum
)Continent
and then on the Country
Here is the intermediate result produced by d3.rollups
(before formatting):
var input = [
{ "Continent": "Europe", "Country": "Spain", "City": "Madrid", "value": "3" },
{ "Continent": "Europe", "Country": "Spain", "City": "Barcelona", "value": "30" },
{ "Continent": "Europe", "Country": "France", "City": "Paris", "value": "243" },
{ "Continent": "America", "Country": "Argentina", "City": "Buenos Aires", "value": "300" },
{ "Continent": "America", "Country": "Argentina", "City": "Buenos Aires", "value": "250" },
{ "Continent": "America", "Country": "Argentina", "City": "Rosario", "value": "200" }
];
var rolled_up = d3.rollups(
input,
vs => d3.sum(vs, v => +v.value),
d => d.Continent,
d => d.Country
);
console.log(rolled_up);
<script src="https://d3js.org/d3-array.v2.min.js"></script>
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