Note: If the notebook is taking too long to render on github, head to https://nbviewer.org/github/finalys/Finalysis-Walkthrough/tree/main/.

Hi, I'm Finalys. You may know me as the author of Finalysis which started in 2020 as a personal project to learn about python.

Check out the very first Finalysis I tweeted.

Finalysis started off as a project to summarize and derive insights from Shadowverse tournaments, mainly SVO and JCG. Now that I've sort of achieved what I wanted to learn, it is time to share my knowledge as I try to understand how GitHub works (previously I've been doing everything on Jupyter). I hope to work with others in the future on GitHub :)

The purpose is to share my process of how I process data from Shadowverse Tournaments, which should be suitable for beginners like me. I am pretty sure there are better/efficient ways to perform such tasks. I'm not from a STEM background so results is what matters to me more. I'm not too concerned with the most time-optimal method since the data that we're working with isn't too large (pretty sure I gave the wrong justification but oh wells).

As this is my very first public repo, I will try my best to pick up good habits and make it very digestable for fellow beginners. I hope to inspire more people to take the very first step, ideally in something that interest you like how Shadowverse did to me.

Again, I reiterate that I still consider myself a beginner so if there are any improvements/suggestions please feel free to let me know!

Contact me via Discord Finalys#7064 and do follow me on Twitter!!

Calling the API, creating hashes

• File: ShadowverseAPI.ipynb
• Retrieving useful information for shadowverse-portal
• Cleaning the information
• Other utilities: Scraping image assets
• Output: SVCardInfo.xlsx

JCG Analysis

• Files: JCGAnalysis.ipynb, DeckClassify.py, SVExcelFormatter.py
• Scraping from the JCG website
• Cleaning and getting player information & decks
• Identify the deck archetypes brought by players & descriptive statistics
• Breakdown of each deck brought by players
• Matchup analysis
• Export file to Excel

SVO Analysis

• Files: SVOAnalysis.ipynb, DeckClassify.py, SVExcelFormatter.py
• Identify the deck archetypes brought by players & descriptive statistics
• Breakdown of each deck brought by players

V1.6.2

• Update for Academy of Ages (v4.1.1 nerfs)
• Update for JCGAnalysis.ipynb

V1.6.1:

• Update for DeckClassify.py for Academy of Ages. Introduced hybrid deck identifiers; if a deck fulfills multiple archetype identifiers, it will be classified as a hybrid of said archetypes instead of an overwrite.

V1.6:

• Major rehaul on SVOAnalysis.ipynb, SVExcelFormatter.py. Introduced more reliance on battlefy data to pull customFields to reduce manual checks across players' decklist and information.
• Notebook visuals for SVOAnalysis.ipynb are removed, to be updated in the future.
• SVExcelFormatter.py is now a standalone python file rather than a chunk of code in both SVOAnalysis.ipynb and JCGAnalysis.ipynb.

V1.5.2:

• SVO Analysis using battlefy and Zhiff's data in SVOAnalysis.ipynb
• Minor housekeeping, including Eightfold Abyss: Azvaldt Mini-Expansion

V1.5.1:

• Error fix for JCGAnalysis.ipynb for BYE situations.

V1.5:

• Updated SVCardInfo.xlsx for Eightfold Abyss: Azvaldt

V1.4:

• Added SVOAnalysis.ipynb.
• Updated DeckClassify.py for identification housekeeping.

V1.3.1:

• Updated SVCardInfo.xlsx for Celestial Dragonblade Genesis Artifact nerf

V1.3:

• Added image utitlies in ShadowverseAPI.ipynb
• Added 2 new sections to JCGAnalysis.ipynb: Brackets Page, Matchup Analysis
• Updated SVCardInfo.xlsx for Celestial Dragonblade Bat Usher nerf

V1.2:

• Added 3 new sections to JCGAnalysis.ipynb: Deck Classification & Summarization, Deck Breakdown, Exporting the results
• Added DeckClassify.py as part of Deck Classification & Summarization
• Added more visuals to JCGAnalysis.ipynb, more gifs!
• Updated SVCardInfo.xlsx for Celestial Dragonblade expansion

V1.1:

• Added JCGAnalysis.ipynb

V1.0:

• My first GitHub commit!