# Context Pokemon has been around for the majority of my life. I obsessed over it as a child and enjoy seeing the success it carries still today. I figure that I can give the Pokemon Company a nod by applying my passion for data science to their datasets. # Content This is compiled data from two websites that I will acknowledge soon. As for the data, the primary variables are id, name, attack, defense, health, and cp. Other variables include tankiness, potentialdamage, basicdps, attackbasicdps (damage per second with strongest basic attack*attack), chargedps, oneshotpotential (damage per second with strongest charge attack*attack), and various rankings in each category as well as growth rates for each ranking (this variable only makes sense when sorted by each variable's ranking). # Acknowledgements I have to pay tribute to two websites: serebii.net and pokemongodb.net // these two pages allowed me to find the data that helped best explore the Pokemon Go universe. Thank you very much. # Inspiration The data makes it pretty clear what plays into a Pokemon's CP. But, I am curious to know what hidden gems you might find when going through this data. For example, is Dragonite really the powerhouse we think it is?