Metadata-Version: 2.1
Name: datasu
Version: 0.1.1
Summary: Essential utilities for data scientists
Home-page: https://github.com/danibcorr/data-scientist-utilities
Author: danibcorr (Daniel Bazo)
Keywords: python,data science,machine learning,deep learning,artificial intelligence
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: numba
Requires-Dist: ipywidgets
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: pandas
Requires-Dist: scikit-learn


# 🛠️ Data Scientist Utilities

## 🚀 Overview

Welcome to the **Data Scientist Utilities** repository! This repository is a carefully curated collection of tools and utilities that I've developed throughout my journey as a Data Scientist. Whether you're aiming to streamline data manipulation, elevate your data augmentation strategies, or craft stunning visualizations, you'll find valuable resources here to boost your productivity.

## 🎨 Repository Contents

Explore the core components of this repository:

- **`data_augmentation/`**: Scripts and methods for augmenting datasets, designed to improve model robustness and performance across various scenarios.
- **`data_manipulation/`**: A comprehensive set of tools for efficient data manipulation, including cleaning, transforming, and reshaping datasets to fit your needs.
- **`data_visualization/`**: A collection of visualization tools to help you explore, analyze, and present your data in insightful and compelling ways.

*Note: This repository is continuously evolving, with new tools and updates being added regularly. Be sure to check back often for the latest enhancements!*

## ✨ Getting Started

To start using these utilities, follow these steps:

1. Install the package via pip:

   ```bash
   pip install datasu
   ```

2. Explore the contents and integrate the tools into your projects to enhance your data science workflows.

## 🌟 Contributing

Your contributions are invaluable in making this toolbox more robust and versatile! Whether you've developed new tools, discovered bugs, or have ideas for enhancements, feel free to open an issue or submit a pull request. Let's work together to expand this collection and support the data science community!

## 🤖 License

This project is licensed under the [MIT License](LICENSE). You're free to use, modify, and share the code. Happy coding, experimenting, and data exploration!
