https://github.com/smusab9152/pokemon_data_analysis
This repo that explores and analyzes a dataset of Pokémon attributes. The analysis includes data cleaning, exploratory data analysis (EDA), and visualizations .
https://github.com/smusab9152/pokemon_data_analysis
analytics data-analysis data-visualization exploratory-data-analysis jupyter-notebook matplotlib numpy pandas pokemon python seaborn statistical-analysis
Last synced: 4 months ago
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This repo that explores and analyzes a dataset of Pokémon attributes. The analysis includes data cleaning, exploratory data analysis (EDA), and visualizations .
- Host: GitHub
- URL: https://github.com/smusab9152/pokemon_data_analysis
- Owner: smusab9152
- Created: 2025-09-23T17:02:33.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-10-02T19:02:00.000Z (4 months ago)
- Last Synced: 2025-10-02T21:07:53.081Z (4 months ago)
- Topics: analytics, data-analysis, data-visualization, exploratory-data-analysis, jupyter-notebook, matplotlib, numpy, pandas, pokemon, python, seaborn, statistical-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 25.4 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Pokemon Data Analysis
This repository explores and analyzes a dataset of Pokémon attributes. The analysis includes data cleaning, exploratory data analysis (EDA), and visualizations to derive insights about Pokémon characteristics across generations and types.
## Overview
This project provides a comprehensive analysis of Pokémon data, focusing on:
- Statistical comparisons across generations
- Type-based performance analysis
- Legendary vs. non-Legendary Pokémon statistics
- Distribution and frequency of types and type combinations
- Correlations among key attributes
All analysis is performed in a Jupyter Notebook using Python libraries such as pandas, numpy, and matplotlib.
## Analysis Questions
The notebook addresses the following questions:
- **General Analysis**
- How do the average stats (HP, Attack, Defense, Sp. Atk, Sp. Def, Speed) compare across generations?
- Which Pokémon type has the highest and lowest average Attack stat?
- Is there a significant difference in total stats between Legendary and non-Legendary Pokémon?
- What is the distribution of Pokémon types and combinations?
- **Comparative and Relationship Analysis**
- Is there a correlation between Speed and Attack?
- How do stats compare between dual-type and single-type Pokémon?
- Which Pokémon has the highest stat in each category?
- **Specific Analysis**
- How many Pokémon are present in each generation?
- What is the most common type combination?
- How do average stats vary among Pokémon types?
## Dataset
The dataset (`pokemon_data.csv`) contains 800 Pokémon and the following attributes:
- Number, Name, Type 1, Type 2
- HP, Attack, Defense, Sp. Atk, Sp. Def, Speed
- Generation, Legendary status
## Project Structure
```
Pokemon_Data_Analysis/
│
├── Pokemon_Data_Analysis.ipynb # Main analysis notebook
├── pokemon_data.csv # Dataset file
└── README.md # Project documentation
```
## Getting Started
1. **Clone the repository**
```bash
git clone https://github.com/smusab9152/Pokemon_Data_Analysis.git
```
2. **Install dependencies**
- Python 3.x
- Jupyter Notebook
- pandas, numpy, matplotlib
Install with pip:
```bash
pip install pandas numpy matplotlib
```
3. **Open the notebook**
```bash
jupyter notebook Pokemon_Data_Analysis.ipynb
```
## Key Insights
Some of the results from the analysis include:
- **Generational Stats:** Average stats vary across generations, with certain generations showing higher HP or Attack.
- **Type Analysis:** Dragon-type Pokémon have the highest average Attack; Bug-type Pokémon have the lowest.
- **Legendary Comparison:** Legendary Pokémon have significantly higher stats compared to non-Legendaries.
- **Type Frequency:** Water and Normal types are the most common; Flying and Fairy are among the least.
- **Stat Leaders:** Pokémon like Blissey, Mewtwo (Mega forms), and Deoxys hold records for highest individual stats.
## License
This project is licensed under the MIT License.