Visualising Generation One Pokemon Cards

Joti Gautam
5 min readSep 21, 2021

Recently, I published my Pokemon Viz on Tableau Public, I wanted to write about it, so, finally I got some time to write about it and I am here with why, when and how of the visualization. I have been inactive in my blogging from a few months as I was trying to put my whole energy in new job. But I really missed documenting my visualisations, so I will try to be regular at this.

Here is the final version of visualisation if you haven’t seen it yet and interactive version is just a click away. It basically depicts the characteristics, power and abilities of Generation One Pokemons with Pokedex number from One to Twenty.

Final Visualisation

How did I come across the idea of visualizing this topic?

When I was first introduced to map layers in Tableau, I was thinking about different ways to utilize this method in data visualisations. Initially I used it for some simple things such as creating points for shapes in horizontal and vertical manners in my interactive resume.

I wanted to use map layers in more ways. After that I came accross many visualisations in the community which were around providing many layers of information through one chart with the help of map layers. I was completly blown away by this powerful feature by Tableau. It was the same time I was getting interested in Pokemon animated tele series. Hence, came the idea to visualise Pokemon with the help of map layers.

Map layers learning resources:

Webinar by Adam McCann

How to use the new map layers feature -Data Coach

Game, Shape, Match -CJ Mayes

Data Preparation

Pokemon dataset is available in the Sample dataset resources on Tableau Public which made the process really easy as the dataset was clean and sorted. I didn’t had to do any cleanup.

https://public.tableau.com/en-us/s/resources

As I was interested in creating cards for Pokemon with Pokedex 1 to 20, I extracted the 20 Pokemon details from the whole dataset. After this, to define the place for each card on canvas, two columns ‘Name Row’ and ‘Name Col’ are added. They can differ in values as per placement you want for each card.

As we are creating 5 x 4 grid, Name Row defines the position of each row and Name Col defines the position of each card in those rows.

Shape Files

There are four shape files created and added to the Shapes folder in Tableau Repository: Pokemon Picture, Pokemon Name, PokeDex Number, Pokemon Types. Shapes are taken from Pokemon website and then modified in powerpoint. Below are some screenshots from work in progress.

Shape files added to Tableau Shapes folder
Pokemon Nameplates
Pokemon Types

Building the viz

The visualisation is based on a lot of makepoint functions. Simple explanation of makepoint is that it converts longitude and latitude values into x, y coordinate point on canvas (generally used in geospatial analysis). Below is screenshot of how it looks when we create makepoint of Name Row and Name Col after putting the background map to ‘None’

I have adjusted this makepoint accordingly to create different positions for different parts of card. I will not go deep into the details of that, as this will vary depending upon the placement you want for different objects. Workbook can be downloaded for understanding each layer. The best thing about using layers is that I was able to create tooltips for each object as shown below:

Below Tooltip was really fun as it has been created using Viz in Tooltip feature of Tableau. It is combination of multiple worksheets in tooltip. If you want to know more about tooltip usage then refer the workbook which was used in recent VizConnect session on Tooltips.

Visual Design and Legend

The overall Visual design and legend are created in Figma. I wanted to give it a look of playing cards used in various games. Hence came up with below design. When information is encoded in visuals on multiple layers, it is utmost to create the legend in a clear way for the ease of understanding.

To finish with, it was really fun working on this visualisation. I would keep exploring layers more as I believe they have potential to do much more.

I am really grateful to be part of the datafam for the learnings and push they provide to level up.

Cheers!

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Joti Gautam
Joti Gautam

Written by Joti Gautam

Passionate about data | Pushing my limits each day to learn more

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