It's tempting to create a "top 10" style report and call it quits, often times it is more useful to understand the relative ranking of movement based on a time period; like how popular was this item last month vs last year?
The end result is something like this, high information density in an easy to read format. You can see that adidas has been growing steadily for a year or that Levi's has not moved from it's top spot (at the time of this post!)
Explore Data in Full Screen
There are a few table calculations, filters and pivots happening in the background.
- rank: this gives us the position of the item
- date filter: this gives us the last 2 complete months and then this month last year
12 months ago for 1 month,2 months ago for 2 months
- pivot on month: this gives us a pivot by time period (make sure to sort them so that your pivot_index works)
- ranks for time periods: this lets us extract the rank from each time period
- period over period: this lets us find the relative movements in ranks
- markers: these help visualize positive and negative changes
- hidden measures: keep the visualization clean by hiding the intermediate calculations
Of course you can also do a lot of this in LookML and get pretty fancy with the html output - table calculations is only one of the ways to do rankings in Looker!