R Tutorial: Introduction to spatial data

Want to learn more? Take the full course at https://learn.datacamp.com/courses/visualizing-geospatial-data-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Welcome to working with geosptial data in R. Perhaps your first question is: What makes makes data spatial? It's quite simple, whenever our data is associated with locations, we think about it as spatial. When those locations are on the Earth we'll often be a little more specific and call the data, geospatial. A location is most unambigously described by a set of coordinates and a description of what coordinate system is being used. You are already familiar with one coordinate reference system: geographical coordinates, the usual latitide longitude pairs we use to specify where something is on the globe. In this chapter you'll be working with house sales from 2015, where I live, a town called Corvallis. When a house sells, the most obvious data, is the price and the address of the house, but there may also be data on how big the house was, how many bedrooms it has, how many bathrooms, how much land and what condition it is in. All this data is associated with a house at a specfic location so we can consider this spatial data. Although the address specifies the location it isn't a set of coordinates. To work with these house sales we need to convert the address to a set of coordinates: latitude specifies the position North to South, and longitude the position East to West. Often the North/South and East/West abbreviations are dropped and instead we use positive numbers for one direction: North for latitude and East for longitude and negative numbers for the other direction: South for latitude and West for longitude. In math we are so used to specifying location in x and y, that you'll also often see longtude listed first, since it specifies the horizontal- or x-coordinate. Let's take a look at these house sales as you'll see them in a dat