Stack Overflow Analysis Guidelines

👨‍💻 Demo Video

Final.video.mp4

👇 Prerequisites

Before installation, please ensure you have the following tools installed:

• Git - Learn Git step-by-step by following the instructions provided here.
• Anaconda
• Jupyter Package

🛠️ Installation Steps

1. Fork the project: Fork the sanjay-kv/Stackoverflow-Analysis repository. Follow these instructions on how to fork a repository.
2. Clone the project: git clone [email protected]:your-username/Stackoverflow-Analysis.git
3. Download the original data from the drive link
4. Open Jupyter Notebook and place the file in the project folder. Make sure you're selecting the correct path.

Development

We welcome contributions from all levels of experience. If you think the community would benefit from being walked through the steps you're going through, please share! ❤️

Finding Insights from Stack Overflow Developer Survey

Stack Overflow is a professional community for developers, conducting a survey annually. Analyzing the dataset professionally using modern tools can enable us to answer real-world questions effectively. The dataset covers 275 questions in total.

Project Goals:

1. Perform Analysis on the last 3 years' Stack Overflow Dataset to extract insights.
2. Analyze the impact of higher education, experience, and responsibilities on salary and gender inequalities.
3. Investigate participation rates based on ethnicity and differences in income between men and women.
4. Explore the popularity of programming languages and predict their growth based on survey responses.

Data Source and Background

The dataset comes from the annual Stack Overflow developer survey, covering responses from developers in 180 countries. The data are available in CSV format, ranging from 40 to 150 MB, with responses from 1.5 Lakh survey participants.

Data Format

The data is in a CSV file format with 252,199 observations and 62 variables.

Expected Work

Data wrangling tasks include handling null values and converting data for analysis. Techniques such as ML algorithms and data visualization will be employed.

👨‍💻 Contributing

• Contributions are greatly appreciated. Check out our contribution guidelines (yet to be updated) for more information.

🛡️ License

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

💪 Thanks to all Contributors

Thanks to all contributors for helping this project grow! 🍻

🙏 Support

Don't forget to leave a star ⭐️ for this project!

Crafted with ♥ by @sanjay-kv.