Pokemon Data Analysis

mpmartins1970
2016-08-27

Data Products
Coursera Data Science Specialization

Executive Summary

  • This project analyze a pokemon data set that includes 721 Pokemon and their attributes: HP, Attack, Defense, Special Attack, Special Defense and Speed.

  • A shiny application is used to demonstrate the data analysis

  • Shiny application:
    • Input:
      • X, Y Attributes
      • Number of Top Pokemons
    • Output:
      • Summary of X, Y Attributes
      • Scatter Plot
      • Data Table

Understanding Pokemon Dataset

The data as described by Myles O'Neil is:

  • Name: Name of each pokemon
  • Type 1: Each pokemon has a type, this determines weakness/resistance to attacks
  • 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 (eg. 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

Exploratory Data Analysis

str(pkData[c(5:11)])

'data.frame':   800 obs. of  7 variables:
 $ Total  : int  318 405 525 625 309 405 534 634 634 314 ...
 $ HP     : int  45 60 80 80 39 58 78 78 78 44 ...
 $ Attack : int  49 62 82 100 52 64 84 130 104 48 ...
 $ Defense: int  49 63 83 123 43 58 78 111 78 65 ...
 $ SpAtk  : int  65 80 100 122 60 80 109 130 159 50 ...
 $ SpDef  : int  65 80 100 120 50 65 85 85 115 64 ...
 $ Speed  : int  45 60 80 80 65 80 100 100 100 43 ...

Frequency of Pokemons per Type

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