Level 5: Montages

August 30, 2022

Welcome back!

Over the summer we've been touring around collaborating with other community projects, check out our previous challenges with:

And all the new datasets added to the #GamesNightViz Data Archive 💾

For our next theme,
"The hours approaching, just give it your best
You've got to reach your prime.
That's when you need to put yourself to the test,
And show us a passage of time,
We're gonna need a montage!"
Montage by Team America OST

Yes, our theme is montages, which is all about improving, gaining new skills and overcoming difficulties. For our games:

  • Video game montage, showing off your skills
  • Getting good against challenging bosses
  • Going from a beginner to a pro with the best strategies

There are three challenges to choose from.

Challenge 1: Viz your montage

Visualising your montage! with datasets ranging from Elden Ring boss fights to top Fortnite 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:

  • Are there games that you’ve played that were challenging to start with?
  • What games competitions have you seen? Were there any strategies you tried in your next playthrough?
  • Are there any gamers you admire for their skill or creativity in a game you enjoy?

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

Challenge 2: Layout Containers

Getting some space - exploring whitespace and padding

Create a visualization but take some time to remove, amend and optimise the layout containers used to display your work. Where do I find layout containers?

In Tableau, on a dashboard, in the left-hand side menu, at the top you’ll see a tab for “Layout”, and at the bottom of that section, you’ll see “Item hierarchy” which you can expand to see all the layout containers used when creating your dashboard.

After your build, review this section:

  • Are there any redundant containers? I.e. containers that are meant to be there, you may find repeated cases of containers within other containers that when removed don’t change the viz
  • Is the layout easy for someone else to understand? Rename containers to show what they are doing or containing
  • Would any containers work better if they were collapsible? A common use case is to put “how to” instructions in a container and then make it collapsible.

Here are a few blogs and tutorials from the community:

Here are some great vizzes from the Tableau community to give you an idea what can be done with containers!

People Overview by Katie Wagner

Influence of Tech on Music by Samuel Parsons

Using Layout Containers to Hide/Reveal Sheets in Your Dashboard by Stuart Davis

Workbook thumbnail
Violent Crimes in Baltimore by Louis Yu

Challenge 3: Elden Ring Weapons!

Cleaning weapons data - from Elden Ring

Over the last few months, the team have been playing Elden Ring which has inspired this challenge. We’re looking for the highest damaging weapons we can use throughout our playthrough. Using data tables from https://eldenring.wiki.fextralife.com/Weapons we have the base stats for all the melee weapons however, it’s a little messy!

Task

The goal is to create an output of the highest damaging weapon by its required level.

  1. Load the dataset
  2. Split the dataset into two tables:
  • Damage Stats: 1 containing: Name, Category, Phy, Mag, Fire, Ligh, Holy
  • Level Requirements: 1 containing: Name, Str, Dex, Int, Fai, Arc

For Damage Stats, if you look at the data in Phy, Mag, Fire, Ligh, Holy:

  • the first value shows the attack damage
  • the second value shows the damage resistance
  • A dash “-” means 0, i.e. no damage

For Level Requirements, for Str, Dex, Int, Fai, Arc:

  • the first value shows the level required
  • the second value shows the weapon scaling rating
  • A dash “-” means 0, i.e. no requirement or scaling
  1. Pivot the two datasets: For Damage Stats,1 column containing Phy, Mag, Fire, Ligh, Holy and 1 for the values For Level Requirements,1 column containing Str, Dex, Int, Fai, Arc and 1 for the values
  2. Split the pivot values into 2 columns for both tables: For Damage Stats label the first column “Attack Damage”, and the second “Damage Resistance” For Level Requirements label the first column “Required Attribute”, and the second “Attribute Scaling”
  3. Replace the “-” values with zero in the columns: “Attack Damage”, “Damage Resistance”, “Required Attribute” and change the datatype to whole numbers (integer)
  4. Find the total “Attack Damage” and total “Required Attribute” for all weapons and join the datasets together.
  5. Rank the weapons by total attack damage, grouped by the total required attribute.
  6. Filter for the number 1 rank and output the data

Bonus

Following up on my Tableau Prep TUG talk, I spoke about improving prep flows by reducing the complexity and avoiding repeated steps.

If you’ve followed the guide above you would have split the dataset into two datasets, and then performed similar data transformations to both datasets.

Can you think of a way you could avoid splitting the dataset? By doing so you’ll avoid creating duplicated calculations a join?

I faced a similar problem in my Iron Viz rebuild, in which I repeated calculations transformation for different streams in my Tableau Prep workflow, you can see how I removed the complexity here: https://youtu.be/fAGFYm9gWng?t=3801

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.

Rocket League Data by Matt Miller

What does it take to become a successful Call of Duty team? by Luke Todd

DEAL OR NO DEAL (Mini Version) by Srinivasa Reddy Vattigunta

Halo the Legacy Match Collection by Will Sutton

Halo Infinite Content Analysis by Devesh Dalmia

Madden 22 Player Ratings Ternary Plot by Will Strouse

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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