GameVis

A Steam Game Data Visualization Project

This project visualizes Steam game data using a combination of front-end and back-end technologies.

Demo (Without Backend)

Website: GitPage

Prerequisites

• Node.js: Make sure you have Node.js installed. You can download it from Node.js.
• Yarn: Yarn is used for package management. Install it globally using:

  npm install -g yarn

• Conda: Ensure you have Conda installed. You can download it from Anaconda or Miniconda.

Setup Instructions

Clone the Repository

1. Clone the repository from GitHub:

   git clone https://github.com/whats2000/SteamVisualization.git
   cd SteamVisualization

Backend Setup

1. Create a Conda environment with Python 3.11:

   conda create -n steam-visualization python=3.11

2. Activate the Conda environment:

   conda init bash
   conda activate steam-visualization

3. Install the dependencies using pip:

   pip install -r requirements.txt

4. Run the backend server:

   python run.py

Frontend Setup

1. Open another terminal window of the project directory.

2. Navigate to the d3-ts-website directory:

   cd d3-ts-website

3. Install the dependencies using Yarn:

   yarn

4. Start the front-end development server:

   yarn start

Project Structure

SteamVisualization
│
├── .github
├── create_database
├── d3-ts-website
│   ├── dist
│   ├── node_modules
│   ├── src
│   ├── package.json
│   ├── tsconfig.json
│   ├── webpack.config.js
│   ├── yarn.lock
├── data_analysis
├── data_server
│   ├── __init__.py
│   ├── models.py
│   ├── routes.py
├── raw_data
│   ├── games_march2025_cleaned.csv
├── script
│   ├── analyze_and_merge_data.py
├── .gitattributes
├── .gitignore
├── .prettierignore
├── .prettierrc.yaml
├── config.py
├── LICENSE
├── README.md
├── requirements.txt
└── run.py

Usage

Once both the frontend and backend servers are running, open your browser and navigate to http://localhost:8080/ to view the application.

Dataset Reference

This project uses Steam game data from multiple sources, merged into a comprehensive dataset:

Current Data Source (March 2025)

• Primary Source: Steam Games Dataset by artermiloff
• Last Updated: March 2025
• Total Games: ~107,866 games
• Data Split: 20 JSON chunks for progressive loading

Previous Data Source

• Original Source: Steam Games Dataset by FronKongames
• Historical data merged with current source to preserve older game information

About the Dataset

These datasets are created using the Steam API and SteamSpy API. The data includes game metadata, statistics, pricing, player counts, reviews, and more.

Updating the Dataset

To merge new data:

1. Place the new CSV file in raw_data/ directory
2. Run analysis: python script/analyze_and_merge_data.py
3. Run merge: python script/analyze_and_merge_data.py --merge

The merge process preserves all existing game data and updates with new information where available.

License

This project is licensed under the MIT License - see the LICENSE file for details.