Here's a question:
Can Haskell be used to analyze data published by, say @KingdomInformed, on, say: @DefiKingdoms heroes for sale?
Answer: welp, let's find out.
We'll answer the above question by posing then answering smaller, simpler questions.
Question 1: can I look at only Serendale heroes?
Answer: yes! https://dfkanalytics.vercel.app/hero select Serendale Realm on filters.
Question 2: can I download the stats for Serendale?
Answer: yes! Yes, I can, via the 'export'-link.
Parsing DFK Heroes-for-sale Data
Question 3: can I parse this file?
Answer: YES! ... but this is divided into simpler questions.
Question 3.a: What are the relevant hero data from the CSV file?
Answer: These are, ...
... which we capture in this Haskell data-type.
Question 3.b: Do I want per-line error reporting?
Answer: yeup.
Question 3.c: Does that mean I need to create a language around the DFK hero knowledge-base?
Answer: But of course!
Okay, before we get into the guts of the parser: can we parse in the DFK hero sales data?
What do heroes sale data look like when parsed?
Alrighty, then. What does the parser look like?
What does 'parsing at a low level' look like?
Answer: It looks like this. We match each column of CSV to each datum in the Hero-structure, capturing if we can't at each datum as errors which we report out.
Fortunately, there were no errors, this parse. 😅🎉
Constructing the individual parsers was a reductive exercise, fortunately. Why?
1. First, I constructed a Language of Parsing DFK heroes.
Once you shape a language of the problem, the solution simply falls out.
2. and I constructed the generic `parseT` higher-order function.
Distribution Analyses
That's great! I can parse DFK data!
Who cares? (I do) 🥺
That's a valid question. Data are to be analyzed.
So, what analyses can we do?
1. We can compute distributions along any dimension of the hero-vectors.
Say: "What are the distribution of levels of heroes for sale?"
Okay, but all that work for just heroes for sale-by-level?
Nupe.
We can do heroes-for-sale by x, where x is any dimension of the Hero-vector.
Let's say, heroes-by-generation? How do we code that?
Easy!
> count gen hs
How about "Heroes for sale-by-(primary)-class"?
Answer: np
> count class1 hs
Once we've parsed the data into our SVM, we can query any dimension's distribution simply.
"What dark majick't is this `count`-function, geophf?" you demand vociferously.
"So, ya gon' be a d!ck? Or are you gon' share your source code, huh, geophfrmeisterG?"
Me: "...yes?" 🤓😎
Postlude and teaser
These are simple analyses. Useful? Sure!
But!
How about analyses considering several, or all, vectors?
How about the question: "Given 'a priori'-data, how much can I sell my hero, x, for?"
Would you like an answer for that question?
I would.
CrystalVale Hero Data
p.s.: "How many changes did I have to make to my system to parse DFK CrystalVale heroes-for-sale data?"
Answer: none.
