UPI Data Analysis is an open-source repository for performing and developing solutions for UPI (Unified Payments Interface) data analysis. This repository allows you to explore various types of testing, data analysis, and prediction on datasets from different contexts related to UPI transactions.
To get started with UPI Data Analysis, make sure you have the following libraries installed:
- pandas: To work with data efficiently.
pip install pandas
- [matplotlib]: For data visualization.
pip install matplotlib
- [other-libraries]: You may also need additional libraries for advanced data analysis and
visualization. Please refer to the documentation for specific requirements.
To perform data analysis and visualization, follow these steps:
-
git clone https://github.com/yourusername/UPI-data-analysis.git
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cd UPI-data-analysis/inference-data
Create a folder for your specific analysis, naming it <operationPerformed_day-month-year.format_type>. For example, exploratory_analysis_10-april-2023.png.
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mkdir exploratory_analysis_2023
Add the results of your analysis in the form of images, text files, or Jupyter Notebooks within the created folder.
Contributions to UPI Data Analysis are welcome! Here's how you can contribute:
Fork the repository. Create a new branch for your work.
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git checkout -b feature/my-contribution
Make your changes and commit them. Push your changes to your forked repository. Create a pull request to the main repository.
This project is licensed under the MIT License.
Acknowledgments for libraries, data sources, or collaborators would be mentioned here.
Feel free to reach out to me at [email protected] for any questions or feedback.