Preppin' Data

Challenge by: Will Sutton In this week's Preppin' Data we're collaborating with #GamesNightViz on their latest challenge Power Ups . We'll be diving into the Pokédex to explore how Pokémon combat stats change when they evolve. Inputs pkmn_stats  pkmn_evolutions  Requirements Import the data (excel file) From pkmn_stats dataset remove the columns height, weight and evolves from Pivot (wide to long) pkmn stats so that hp, attack, defense, special_attack, special_defense, and speed become a column called 'combat_factors' Using the evolutions data look up the combat_factors for each Pokémon at each stage, making sure that the combat_factors match across the row, i.e. we should be able to see the hp for Bulbasaur, Ivysaur and Venusaur on one row Remove any columns for 'pokedex_number' and 'gen_introduced' that were from joins at Stage 2 & 3 If a Pokémon doesn't evolve remove it from the dataset Find the combat power values relating to the Po...

Challenge By: Jenny Martin Often our stakeholders can have very niche knowledge and their requests may baffle us. Luckily, as data preppers we have the tools to tackle any dataset, no matter how bizarre. Yes, Carl and Tom have allowed me to create another Pokémon challenge! The idea came from a  YouTube video that I stumbled across: Who Is Pokemon’s LEAST Favorite Pokémon? The logical steps applied in the video felt like they were screaming out for a Preppin' Data challenge to verify the results! But be warned, the answer to this challenge will differ from the conclusion of the video, due to differing datasets. Inputs We have multiple inputs for this challenge: Gen 1 Pokémon (from Pokémon Database ) Evolution Group (from Bulbapedia - also see Preppin' Data 2021 week 10 )  Evolutions (Bulbapedia) Mega Evolutions (Pokémon DB) Alolan Pokémon (Pokémon DB) Galarian Pokémon (Pokémon DB) Gigantamax Pokémon (from IGN ) Unattainable Pokémon in Sword & Shield (Pokémon DB) Ani...

Challenge By: Jenny Martin I can hear the hesitancy already surrounding this challenge. "I know nothing about Pokémon, how can I participate?" Well, rest assured, you don't need to understand the data in order to work with it and complete this challenge. In fact, I believe this challenge could help with most hierarchical data.  The aim of this challenge is to group Pokémon into Evolution Groups. Why? So that when we select any Pokémon, we can see all the information about what they evolved from, what they will evolve to etc. In the example below, Bulbasaur evolves into Ivysaur, who then evolves into Venusaur. Choose another Pokémon like Flareon and we can see it evolves from Eevee, who has multiple evolution possibilities. See full dashboard here How is this applicable to other hierarchical data? Well imagine that a Pokémon that has a null in the Evolves From field is similar to an employee at Work Level 1 in an organisation. Their manager would then sit in the Evolv...