The aim of this project is to create a more nuanced understanding of the interactions between socio-demographic characteristics, in-game behaviours, and global-scale environmental consciousness.
The dataset used contains a wide range of information, including socio-demographic details, responses to world events, environmental viewpoints, gaming habits, in-game activities, and player emotional experiences. This dataset is a significant resource for investigating the global convergence of virtual gaming, environmental awareness, and human actions. The dataset used in this project is got from Science data bank.
Our methodology is divided into three stages:
- Data quality checks - The aim of data quality assessment is to ensure the accuracy, consistency, and reliability of the dataset by identifying and rectifying discrepancies.
- Data characterization - The data characterization phase seeks to provide a comprehensive overview of key characteristics, patterns, and trends within the dataset.
- Detailed analysis objectives - The detailed analysis is for conducting an in-depth examination of the dataset, extracting valuable insights and conclusions.
In order to get the complete analysis and conclusion, please refer to this documentation.
- Python
Team members who made this project possible
- Priyanka Singh
- Omkar pawar
- Akshay Deshmukh