Python project that uses linear regression model to train AI and converge through the data in given CSV file
This data set contains 721 unique Pokemons, including their number (ID), name, first and second type, and basic stats: HP, Attack, Defense, Special Attack, Special Defense, and Speed.
This are the raw attributes that are used for calculating how much damage an attack will do in the games.
The data as described is:
ID: ID for each pokemon
Name: Name of each pokemon
Type 1: Each pokemon has a type, this determines weakness/resistance to attacks
Type 2: Some pokemon are dual type and have two types
Total: sum of all stats that come after this, a general guide to how strong a pokemon is
HP: hit points, or health, defines how much damage a pokemon can withstand before fainting
Attack: the base modifier for normal attacks (e.g., Scratch, Punch)
Defense: the base damage resistance against normal attacks
SP Atk: special attack, the base modifier for special attacks (e.g., fire blast, bubble beam)
SP Def: the base damage resistance against special attacks
Speed: determines which pokemon attacks first each round
The data for this table has been acquired from several different sites, including:
pokemon.com
pokemondb
bulbapedia