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Creating a map

The topics that we will cover in this chapter include:

  1. Creating a map
  2. Define GeoJSON
  3. Use a projection
  4. Generate a <path> using a projection and the GeoJSON data

In this section we'll generate <path> elements from GeoJSON data that will draw a map of the world

Define GeoJSON

GeoJSON is just JSON data that has specific properties that are assigned specific data types. Here's an example:

{
    "type": "Feature",
    "geometry": {
        "type": "Point",
        "coordinates": [125.6, 10.1]
    },
    "properties": {
        "name": "Dinagat Islands"
    }
}

In this example, we have one Feature who's geometry is a Point with the coordinates [125.6, 10.1]. It has "Dinagat Islands" as its name. Each Feature follows this general structure:

{
    "type": STRING,
    "geometry": {
        "type": STRING,
        "coordinates": ARRAY
    },
    "properties": OBJECT
}

We can also have a Feature Collection which is many Features grouped together in a features array:

{
    "type": "FeatureCollection",
    "features": [
        {
            "type": "Feature",
            "geometry": {
                "type": "Point",
                "coordinates": [102.0, 0.5]
            },
            "properties": {
                "prop0": "value0"
            }
        },
        {
            "type": "Feature",
            "geometry": {
                "type": "LineString",
                "coordinates": [
                    [102.0, 0.0], [103.0, 1.0], [104.0, 0.0], [105.0, 1.0]
                ]
            },
            "properties": {
                "prop0": "value0",
                "prop1": 0.0
            }
        },
        {
            "type": "Feature",
            "geometry": {
                "type": "Polygon",
                "coordinates": [
                    [
                        [100.0, 0.0], [101.0, 0.0], [101.0, 1.0],
                        [100.0, 1.0], [100.0, 0.0]
                    ]
                ]
            },
            "properties": {
                "prop0": "value0",
                "prop1": { "this": "that" }
            }
        }
    ]
}

This basically follows the form:

{
    "type": "FeatureCollection",
    "features": ARRAY
}

The features property is an array of feature objects which we've defined previously.

Set up the HTML

Let's set up a basic D3 page:

<!DOCTYPE html>
<html lang="en" dir="ltr">
<head>
    <meta charset="utf-8">
    <title></title>
    <script src="https://d3js.org/d3.v5.min.js" charset="utf-8"></script>
    <script src="https://cdn.rawgit.com/mahuntington/mapping-demo/master/map_data3.js" charset="utf-8"></script>
</head>
<body>
    <svg></svg>
    <script src="app.js" charset="utf-8"></script>
</body>
</html>

The only thing different from the setup that we've used in previous chapters is this line:

<script src="https://cdn.rawgit.com/mahuntington/mapping-demo/master/map_data3.js" charset="utf-8"></script>

This just loads an external javascript file which sets our GeoJSON data to a variable. Here's what the beginning of it looks like:

var map_json = {
    type: "FeatureCollection",
    features: [
        {
            type: "Feature",
            id: "AFG",
            properties: {
                name: "Afghanistan"
            },
            geometry: {
                type: "Polygon",
                coordinates: [
                    //lots of coordinates
                ]
            }
        }
        // lots of other countries
    ]
}

Note that the map_json variable is just a JavaScript object that adheres to the GeoJSON structure (it adds an id property which is optional). This is very important. If the object didn't adhere to the GeoJSON structure, D3 would not work as it should.

In production, you would probably make an AJAX call to get this data, or at the very least, create your own geoJSON file similar to the one being hosted on rawgit.com. The setup above was created to make learning easier by decreasing the complexity associated with AJAX.

Use a projection

Now let's start our app.js file:

var width = 960;
var height = 490;

d3.select('svg')
    .attr('width', width)
    .attr('height', height);

At the bottom of app.js let's add:

var worldProjection = d3.geoEquirectangular();

This generates a projection, which governs how we're going to display a round world on a flat screen. There's lots of different types of projections we can use: https://github.com/d3/d3-geo/blob/master/README.md#azimuthal-projections

The line above tells D3 to create an equirectangular projection (https://github.com/d3/d3-geo/blob/master/README.md#geoEquirectangular)

Generate a <path> using a projection and the GeoJSON data

Now that we have our projection, we're going to generate <path> elements for each data element in the map_json.features array. Then we set the fill of each element to #099. Add this at the end of app.js:

d3.select('svg').selectAll('path')
    .data(map_json.features)
    .enter()
    .append('path')
    .attr('fill', '#099');

Here's what it should look like at the moment if we open index.html in Chrome and view the elements tab in the developer tools:

We created the path elements, but they each need a d attribute which will determine how they're going to drawn (i.e. their shape).

We want something like:

d3.selectAll('path').attr('d', function(datum, index){
    //somehow use datum to generate the value for the 'd' attributes
});

Writing the kind of code described in the comment above would be very difficult. Luckily, D3 can generate that entire function for us. All we need to do is specify the projection that we created earlier. At the bottom of app.js add the following:

var dAttributeFunction = d3.geoPath()
    .projection(worldProjection);

d3.selectAll('path').attr('d', dAttributeFunction);

geoPath() generates the function that we'll use for the d attribute, and projection(worldProjection) tells it to use the worldProjection var created earlier so that the path elements appear as an equirectangular projection like this (This is helpful because we can use different projects to view a round world on a flat screen in different ways):

Conclusion

In this section we've covered how to use D3 to create a projection and render GeoJSON data as a map, and we've learned about using different projects to visualize the world. This can be helpful when displaying populations or perhaps average rainfall of various regions. Congratulations! You've made it to the end of this book. Now go off and create amazing visualizations.