Git-For-Geeks in as open source contribution event conducted by Geeks-for-Geeks Chapter of Shri Ramdeobaba College of Engineering and Management, Nagpur.
Data science is using data to make better decisions with analysis for insight, statistics for causality, and machine learning for prediction.
A Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data. These insights can be used to guide decision making and strategic planning.
Read more: Data Science
- Numpy
- Pandas
- Matplotlib
- Seaborn
- Create a Exploratory data analysis on any Dataset of your choice.
- Find statistics and conclusion from the dataset like Trends, Future Outcome, etc.
- Apply Data Visualization techniques to elaborate your conclusion.
Some sample datasets here
For more datasets: Visit here
You can use any of the datasets but you should apply proper data visualization techniques that end up in finding the conclusion that can be drawn after visualizing the data. Mention the conclusion in your Collab or Python Notebooks.
Find Issue to work on, comment on that issue and wait till you are assigned. Once assigned, start resolving the issue.
1. Fork this repository.
2. Clone your forked copy of the project.
git clone https://github.com/<your_github_user_name>/Data_Science_Tools
3. Navigate to the project directory.
cd Data_Science_Tools
4. Make changes in source code and stage.
git add .
5. Stage your changes and commit
git commit -m "<your_commit_message>"
6. Push your local commits to your repository.
git push origin main
7. Create a PR to main repository.
- All contributors must follow the contribution rules in order to get their PRs merged.
- The codes must have comments to explain them. Simply copy pasting is not allowed.
- If you are referring resources, make sure to avoid copy pasting the code. Plagiarism will be checked.