Create maps that are beautiful as well as geospatially accurate. In this course, Geospatial Mapping with D3, you'll learn the concepts behind geospatial data and the world of cartography, which has been around for centuries! First, you'll gain an understanding of how maps are built, how the cartographers of the world use maps, and then you'll dig into functionally working with this data using open source tools to process your shapefiles into something you can draw in D3. Next, you'll learn how to convert files to various formats, clip files to a specific area, filter files down using SQL-like syntax, and simplify the output of files. Once you have our data pulled together and format ready to draw in D3, you'll dive into drawing maps with TopoJSON, combining data from a fictitious company's sale system and your topojson data. When you finish this course, you'll have the practical skills needed to make beautiful and useful maps in D3.
I work as a feedback mechanism for organizations and teams to help them understand what’s going on with their products and processes. I do this by collecting and organizing their data, visually exploring it, enriching it with other data and metrics, then presenting my findings using creative information design techniques. This leads to improved business performance and often sparks a data-driven culture throughout my clients organizations.
Working with Geospatial Data Hi, this is Ben Sullins with Pluralsight and welcome to this module on working with geospatial data. We're going to first talk about the concepts here and the different tools and everything we're going to be using, different formats of data and everything that we'll be going through in this module. Then we'll go into some exploratory work. We'll go put our investigator hat on and search the web and find some data for us to use in our visualization. Then we'll actually work with the data in GeoJSON. So this is one of the formats we'll be talking about here in a second. And then we'll actually start using TopoJSON, which is another format for us, which we'll actually use going forward for our final project. Let's get started. First, we can't forget who we're serving here, Cogsley Services Inc. This is our fictitious company that was founded in 2008. It's a technical consulting firm, if you recall, and the main goal of our project here was to help them understand their customer locations for their targeted marketing efforts. So the main things we're going to be trying to do here are take the exported CSV sales data and combine that with the map data. Mostly, what we'll be doing first is figuring out the different concepts and tools that we'll be using, playing with some map data and seeing how that works, and then we'll actually go through in the final step and merge that with our CSV sales data so we can actually use that for our final project. Let's get going.
Drawing Maps with D3 Hi this is Ben with bensullins. com and welcome to this module on drawing maps with D3. The first thing we're going to cover today are building choropleth maps. If you recall, choropleth maps are filled maps. It's where we take a geometry or an area and we fill it with a color. They're used quite often in voter turnouts and things like that as well as looking at different places around economic development or age or anything like that. Here we're going to go through a couple examples there that are pretty common that you probably come across in your work at a data visualization engineer. Next, we're going to go take a look at bubble maps. Bubble maps, unlike choropleth maps, require drawing a base map and then putting dots or circles in D3 objects where you want things to appear. In the final project we're going to go into we're going to use it to show profit by county and that is the last thing we're going to close off with here in this course actually is the final project map. If you recall from the very beginning, we took a sneak peak of what we were building and here we're going to actually finish that off and build that final map that you saw. We need to recall again that we're looking at Cogsley Services Inc. This is our fictitious company. They were founded in 2008, they're a technical consulting firm, and the whole point of what we're doing here or the thing we're trying to solve is that they need to understand their customer locations so that they can market to them more effectively and that's the idea. I wanted to give a realistic scenario, something you'll probably come across or probably have come across in your work as a data visualization engineer, that is going to help you translate what you learn here into the real world. Let's get going.