R Tutorial: Getting to know your vector data

Want to learn more? Take the full course at https://learn.datacamp.com/courses/spatial-analysis-with-sf-and-raster-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- In this lesson we'll dig a little deeper into the properties of a vector spatial object in the sf package. One of the huge innovations of the sf package over the older sp package is that spatial objects are stored as data frames. So we have one row per feature and we can use the standard functions for working with data frames including tools like those in the dplyr package. In addition to the standard data frame properties, sf data frames have a few special properties. One difference with non-spatial data frames is that sf data frames store metadata about the spatial object and you can see this metadata here by using the head function. In addition, geometry is stored in what are called list columns. List columns are not unique to spatial data but are used extensively in sf to store geometry. So let me show you a quick example of a non-spatial list column so you can get a sense of how they operate. To illustrate a list column in this example I'm manually creating a non-spatial data frame and I'm also separately creating a new list. So we have d as the data frame and new_list as the list with three elements. Here you see that I'm adding the list as a new variable to the data frame. The list has 3 elements, one for each row, but within each element we can store as much information as we want. This is the idea behind a list column. Note that I'm only using the function tbl_df() so d is printed nicely to the console and you can see that variable c is a list. So when you look at an sf object in the console you can see that there is a print out of the metadata followed by the variables. In this example, there are two standard variables, tree_id and species. And then we have the geometry which is stored as a list-column. Here we use is d