The Data Analysis and Visualization with Python project aims to explore and analyze datasets using Python's popular data science libraries such as: Pandas, NumPy, and Matplotlib. The project focuses on providing hands-on experience with real-world datasets, - demonstrating various data manipulation and visualization techniques, and showcasing the power of Python for data analysis tasks.
To set up the project environment and install the necessary dependencies, follow these steps:
1: Clone the Repository: Start by cloning this repository to your local machine: git clone https://github.com/jumarubea/data_science_projects.git
2: Navigate to the Project Directory: Move into the project directory: cd data_analysis_project
3: Install Dependencies: Once the virtual environment is activated, install the project dependencies using pip: pip install pandas numpy matplotlib
4: Verify Installation: After the installation is complete, you can verify that the dependencies were installed correctly: pip list
5: Run the Project: You're now ready to run the project! python investigating_netflix_movies.py
Python (version = 3.12.1) pandas (version = 2.2.1) numpy (version = 1.26.4) matplotlib (version = 3.8.3)
Thank you for considering contributing to the Data Analysis and Visualization with Python project! Contributions are welcome and encouraged. Below are some guidelines for contributing to the project:
Reporting Issues If you encounter any issues or have suggestions for improvement, please feel free to open an issue on GitHub. When reporting issues, please provide as much detail as possible, including:
A clear and descriptive title. A detailed description of the issue or suggestion. Steps to reproduce the issue (if applicable). Any relevant screenshots or error messages. You can open a new issue here.
Submitting Pull Requests If you'd like to contribute code to the project, you can do so by submitting a pull request. Here's how to submit a pull request:
1: Fork the repository to your GitHub account. 2: Create a new branch for your feature or bug fix: git checkout -b feature-branch 3: Make your changes and commit them to your branch: git add . git commit -m "Your commit message here" 4: Push your changes to your forked repository: git push origin feature-branch 5: Open a pull request on GitHub. Be sure to provide a clear title and description for your pull request, explaining the changes you've made and why they're necessary.
Code Style When contributing code to the project, please follow the existing code style and conventions. This to maintaining a consistent coding style throughout the project.
Code Reviews All pull requests will undergo code review before being merged. During the code review process, feedback may be provided on your changes, and you may be asked to make revisions. Please respond promptly to any feedback and address any requested changes.