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Pretty Good Hat

Tag: data

Destiny 2 Power leveling tool in R

The latest piece of my homebrew Destiny 2 toolset is Travelr, a power leveling tracking tool built with R and using a much simpler process than most of my prior nonsense. (Aside: I'm still using ArmoreR, but it has some key limitations that I haven't spent much time with, including a problem incorporating the authentication flow more fully into Shiny so that I could make it an app that others could use in a more friction-free way.)

The power climb is part of the game with each new Destiny season. A lot of this process is luck: A player can only get so many pinnacle drops per week and there's no guarantee that a given drop won't be in a duplicate category. But, some drops can be targeted to broad categories -- armor versus a weapon, for example -- and there is some efficiency across characters if you can strategically raise one category to increase the base level for all characters. 

I was inspired by a fantastic tool written by a member of the small Destiny 2 community I'm in, that identifies categories to target (or, try to target, anyway; a lot of it is still frustrating random luck, sometimes), and decided to try building my own version. It doesn't do anything unique, but it works and it's wonderfully satisfying to step through an R markdown notebook that authorizes me to the D2 API, retrieves all my equipment statistics, calculates my maximum power level and indicates which, if any, categories should be targeted.

For example, here's a screenshot from the beginning of the season, where every single equipment type would increase my total maximum power level:

A screenshot of a table of data showing lots of equipment categories that would increase power level to the next integer

... and later in the season:

Travelr screenshot showing a table of armor and equipment values, highlighting values that would increase the total maximum power level to the next highest integer

It's been great fun to have this small tool with me during the season's play. It's currently dependent on another small tool that grabs the equipment "manifest" file, and I'll be publishing the whole notebook to github when I finish incorporating that into the repository. 

Preparing to troll my team by visualizing time series data using a donut plot. This is going to be great.

We’ve been watching a lot of The Great Pottery Throwdown, and I’ve decided I want to get an apron for work. “Time to go sit at the data table. Better put on my apron. Could get messy.” Maybe get some for the whole team.

Had a great time hanging out, learning, and getting inspired by things at #csvconf the last couple of days. Go 🦙!

Calling R specifically and data folks in general: anybody using the M1 routinely with a broad analytics/data sci set of tools now? Things look pretty promising but I wonder if the day to day still relies on too much fiddling in/out of Rosetta to feel effective.

Likely not on the radar for most of my academic, stats and data sci friends: the Tableau conf is free and online this week. While the tool may not be in your wheelhouse, it’s almost certainly in your institutional/civic infrastructure. Good oppty to see the conversation here.