Level 1: Player Select

August 24, 2022

The theme for the first #GamesNightViz project is "Player Select", which follows the start of most games - choosing your character.

Picking the right character can be a tricky decision, and we may want to bring in some data to help us select the best character for the job, we may want to know:

  • What skills does this character have?
  • What makes them different from everyone else?
  • How likely are they to succeed based on past performances?

There are three challenges to choose from.

Challenge 1: Characters

Visualising data about our favourite CHARACTERS, with datasets ranging from gaming icons to top poker players

Pick one of the data sets below, or a data set you've found, and visualise it.

Casual Difficulty - For those new to data visualisation or with limited time available)

Normal Difficulty - A fair size data set that could create multiple data visualisations

Heroic Difficulty - A large data set for those with more time available

Legendary difficulty - Bring your own data or expand on the data provided by bringing new data to the project

For those considering the Legendary difficulty (bring your own data), here are a few ideas to get you started:

  • Do you have a favourite character?
  • Did they appear in multiple match/games or is there one particular match/game that was interesting?
  • Do they have particular strengths that gives them an advantage over others?

Looking for data sets? Check out Sarah Bartlett's Twitter thread for data sources

Stuck for Ideas? Here are some questions you could try to answer:

  • Iconic Characters: Are older video games characters more iconic than newer ones? Do good game sales make for an iconic character?
  • Pokemon: Are people's favourite Pokemon the strongest? Do people prefer certain pokemon types (e.g. Legendaries, Fire types, Final evolutions) over others?
  • Top Poker Players: The players are ranked by total earnings, are there other attributes we can explore to better understand their careers? For example, they've earned millions of dollars but was it all in one go? How many years have they been playing poker? How regularly do they win?

Challenge 2: Colors

Crafting designs to explore COLOUR, with tools to help you create a unique colour palette

Colour is one of the most powerful tools for a data visualisation to connect with its readers/users. Colour allows us to distinguish and emphasize important parts of our data visualisation and well as creating an atmosphere for the work.

Here's an example by Andy Cotgrave, a clever switch of colour to create the same charts different message.

Viz of the Day: Bringing back the CHARM! by Louis Yu


Using a colour palette tool create a unique colour scheme for a data visualisation. Some of our favourite colour tools:

For more on inspiration on colour tools, read this great article by Lisa Charlotte Muth, Your Friendly Guide to Colors in Data Visualisation. Also, consider accessibility when experimenting with colour, you can create more accessible visualisations:

Challenge 3: The best Mario Kart

Preparing data to find the BEST MARIO KART driver and kart combination, with steps to follow along the way

The holiday season is coming up, which means friends and relatives will be coming over and a chance you'll find yourself in a Mario Kart 8 tournament. To give me the best possibility of winning what's the best kart I could pick for my favourite character? Also, what's the best kart whether everything has been unlocked or not? For Mario Kart 8, at the start of the game you select:

  • A driver
  • Kart body
  • Kart tires
  • Kart glider

To work out the best combination of driver, body, tires and glider, we can source some data tables from MarioWiki.com

  1. Input the data
  2. Long pivot the Driver, Kart body, Tires and Gliders tabs so each attribute becomes a row with the attribute value.
  3. Join Driver, Kart body, Tires and Gliders together so we have 1 row per combination of driver, kart body, tires and glider
  4. Create a total value (sum of the driver, kart body, tires and glider values) for each attribute
  5. Drop the individual component values and create a wide pivot of the data spreading attributes into columns displaying the total values for each kart combination
  6. Simplify the attributes:
  • Sum all attributes as the overall total
  • Sum all attributes starting with "S" for the overall speed
  • Sum all attributes starting with "T" for the overall handling
  1. Determine which components (driver, kart body, tires and glider) are available at the start of the game
  2. Create a flag for any kart combination that requires an unlock, i.e. any components not available at the start of the game
  3. Create a rank for each driver and if an unlock is required, ordered by the highest overall total descending, then by speed descending and handling descending
  4. Filter the data so just the best kart for each driver and if an unlock is required, split any ties so we end with 1 kart per driver
  5. Optional: Join each component to an image so you know what to look out for in the game
  6. Output the data

Inspiration from the Tableau community

Your content may be different but focus on the choices the authors have made in presenting the data, what would you do differently? And what aspects would you like to emulate? Here are some vizzes to check out for inspiration.

Mario by Yuzo Tokutani

Winningest Poker Tournament Players by Kevin Flerlage

PokeMon: PokeDex (1-20) of Gen One by Joti Gautam

31 years of The Legend of Zelda by Marcus Grant

Videogame Female Characters by Fabio Fantoni

Fire Emblem Heroes Character Breakdown by SmirkyGraphs

Pac-Man - The Top Grossing Arcade Game of All Time by David Callies

Card Game Trick by Adrian Zinovei

Las Vegas Blackjack by Mark Bradbourne

How to Submit

Team GNV

This project focuses a monthly theme that you can participate to challenge either data preparation, data visualization or visual design. Existing datasets on video games will be readily available and comes with difficulty scales to help those newer or with limited time to practice. You can also bring data from your own favorite games too! We love all types of games: card games, board games, video games, party games, game shows, the list goes on!

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