R Tutorial: Inspecting choice data

Want to learn more? Take the full course at https://learn.datacamp.com/courses/choice-modeling-for-marketing-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- One thing that trips up new choice modelers is that choice data doesn't fit into the usual format we use for predictive modeling. So, let's take a look at how choice data is structured. We usually organize data in rows where each row represents one observation. For the data here, each row is an observation of sales at a store and we have some information about the characteristics of each store. In this data, the number of rows is the number of observations. In a typical choice dataset, we observe someone making a choice from a set of options that have common features. It's convenient to stack up the options for one choice observation into multiple rows where each row describes one of the alternatives. For instance, the first three rows of this data describe a choice from among three different sports cars. The first car was a 2-seater with a manual transmission for thirty-five thousand dollars. The second two options were both automatic 5-seaters with one at 40 thousand and the other at 30 thousand. To keep track of which rows belong to which observations, we have columns called ques - short for question - and alt - short for alternative. The first three values of ques are all 1s indicating that these three rows all belong to question 1. The values of alt are 1, 2 and 3 indicating that these are the three alternatives the customer chose from. The choice is recorded in the column labeled choice as a 0 or 1 for each option and, of course, only one option was chosen for each observed choice. In question 1, the third option was chosen. The second three rows describe another choice. It also has three alternatives, but that doesn't have to be the case - some of the observed choices may have four or five or more options. The important thin