Phil Seamark has an interesting problem:
The requirement was simple enough. Take the following dataset and, for any given day, produce a count of each possible State using the last known State for any given TestID. The dataset contains six unique Test IDs (A through F). At any given point in time, we first want to establish the last State for each TestID. We also want to group this by day and produce a count value for each possible State. Note, a given TestID can have more than one event in a day, and we only care about the last one.
I’m particularly interested in this because I find a lot of merit in the event-based structure in Phil’s input dataset, but it can be tricky going from that to data in a shape the customer likes.