https://github.com/malintha-induwara/python-for-ds
This repository contains my personal notes, exercises, and examples for Python
https://github.com/malintha-induwara/python-for-ds
numpy pandas python webscraping
Last synced: about 2 months ago
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This repository contains my personal notes, exercises, and examples for Python
- Host: GitHub
- URL: https://github.com/malintha-induwara/python-for-ds
- Owner: malintha-induwara
- Created: 2024-11-07T08:11:53.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-07T15:01:57.000Z (over 1 year ago)
- Last Synced: 2025-04-02T06:16:48.753Z (about 1 year ago)
- Topics: numpy, pandas, python, webscraping
- Language: Python
- Homepage:
- Size: 60.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Python for Data Science Learning Repository
This repository contains my personal notes, exercises, and examples as I learn Python for Data Science.
## Repository Structure
### Notes
The `Notes` directory contains chronological entries organized by date, covering key concepts and insights:
- **Basics of Python** - Variables, data types, and operators
- **Data Collections** - Lists, tuples, sets, and dictionaries
- **Functions** - Parameters, arguments, lambda functions
- **Data Handling** - CSV files, structured data
- **NumPy** - Multi-dimensional arrays and matrix operations
- **Web Scraping** - Extracting data from websites
### Exercises
The `Exercises` directory contains practical examples covering various Python concepts:
1. **Basic Python** - Variables, conditionals, loops
2. **Data Structures** - Lists, tuples, and operations
3. **Functions & Lambda** - Function definitions, arguments, lambda expressions
4. **Object-Oriented Programming** - Classes, inheritance, encapsulation
5. **File Operations** - Reading and writing files
6. **Advanced Topics** - Recursion, decorators
7. **Data Science Libraries** - NumPy, Pandas examples
#### Special Exercise Directories
- **Extra** - Contains advanced algorithm implementations like binary search and fibonacci
### Environment Setup
- The `Env` directory contains environment variables and configuration
- `.gitignore` file to exclude unnecessary files from version control
## Key Concepts Covered
- Python fundamentals and best practices
- Data structures and their applications
- Functional and Object-Oriented Programming
- Data manipulation and analysis
- Algorithm implementation
- File handling and data persistence
## Getting Started
To run these examples:
1. Clone this repository
2. Make sure you have Python installed (preferably Python 3.6+)
3. Install required packages:
```
pip install numpy pandas python-dotenv
```
4. Navigate to specific exercise directories to run examples