https://github.com/abhay-kanwasi/datalearning

In this repository I will be learning libraries like numpy, pandas and regex
https://github.com/abhay-kanwasi/datalearning

Last synced: about 1 month ago
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In this repository I will be learning libraries like numpy, pandas and regex

• Host: GitHub
• URL: https://github.com/abhay-kanwasi/datalearning
• Owner: Abhay-Kanwasi
• Created: 2024-07-01T10:31:56.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-07-31T18:04:56.000Z (5 months ago)
• Last Synced: 2024-07-31T22:14:47.851Z (5 months ago)
• Language: Python
• Homepage:
• Size: 4.88 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
**About**

This repository is dedicated to my learning journey with popular Python libraries, including NumPy, Pandas, and Regex (Regular Expressions). It serves as a collection of projects, exercises, and examples that demonstrate my understanding and application of these powerful tools.

### Libraries Covered:

1. **NumPy**:

   - Fundamental array and matrix operations

   - Advanced mathematical and statistical functions

   - Efficient data manipulation and analysis

2. **Pandas**:

   - Data structures: Series and DataFrames

   - Data loading, cleaning, and preprocessing

   - Data exploration, transformation, and visualization

3. **Regex (Regular Expressions)**:

   - Pattern matching and text manipulation

   - Advanced string operations

   - Integration with Python for powerful text processing

### Project Structure:

The repository is organized into folders, each dedicated to a specific library:

- `numpy/`: Contains projects and examples showcasing the use of NumPy for numerical computing.

- `pandas/`: Includes projects and exercises that demonstrate the capabilities of the Pandas library for data analysis and manipulation.

- `regex/`: Features projects and examples that explore the power of Regular Expressions for text processing and pattern matching.

Within each library-specific folder, you'll find Jupyter Notebooks, Python scripts, and other supporting files that guide you through the learning process.

### Getting Started:

1. **Clone the Repository**:

   ```bash

   git clone 

   cd your-repo-name

   ```

2. **Set up the Environment**:

   - Ensure you have Python and the necessary libraries (NumPy, Pandas, Regex) installed.

   - You can use a virtual environment or a tool like Conda to manage your dependencies.

3. **Explore the Content**:

   - Navigate to the respective library folders and dive into the projects and examples.

   - Follow the instructions and explanations provided in the Jupyter Notebooks or Python scripts.

### Contributions:

Feel free to contribute by opening issues, submitting pull requests, or suggesting new projects and exercises. Your feedback and contributions are highly valuable for enhancing the learning experience.

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This "About" section provides a comprehensive overview of the repository, outlining the key libraries covered, the project structure, and instructions for getting started. It sets clear expectations for users interested in learning these essential Python libraries.