/Pokemon-Prediction

Practice to use the Kaggle Dataset.

Primary LanguageJupyter Notebook

Pokemon-Prediction

Practice to use the Kaggle Dataset.

使用環境 Envirmental

  • Jupyter Notebook
  • windows 10

需要使用的套件版本我放在requirements.txt裡面了
Windows 10 用戶會需要額外的套件我放在wheel裡面了
All the needed module had been listed in the requirements.txt.
Windows 10 users will need to install some bouns module which I put them into the wheel folder.

Data Image

內部呈現的是我針對多種資料視覺化的圖所做的練習
The images inside this folder are the maps that I used to practice to illustrate many kinds of data visualization.

  1. Scatter Map [ "Type1" vs all feature ]
  2. Pairplot [all feature vs all feature ]
  3. BoxPlots [all feature vs all "Type 1"]
  4. Heat Map

Data sets

裡面放的是我在 Kaggle 裡載的資料集
Kaggle Data set

  • 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 2
  • 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