Python Notes

This repository contains a collection of Python notes, primarily focused on data analysis and general Python programming. The notes are based on several popular books and are organized in Jupyter notebooks for easy reference and interactive learning.

Some python notes. The initial motive is the interest group created by my teacher Richard Gu in 2024 April.

Overview

These notes were initially created as part of an interest group led by Richard Gu in April 2024. The project aims to provide a comprehensive resource for learning Python, with a particular emphasis on data analysis techniques and tools.

Main Features

• Detailed notes on Python fundamentals
• Coverage of data analysis libraries such as pandas, NumPy, and Matplotlib
• Interactive Jupyter notebooks for hands-on learning
• Examples and exercises from popular Python and data analysis books

Topics Covered

1. Python basics and data types
2. Control structures (loops, conditionals)
3. Functions and classes
4. NumPy library for numerical computing
5. pandas library for data manipulation and analysis
6. Data visualization with Matplotlib
7. Regular expressions
8. File handling
9. Useful Python tools and environment setup

Source Books

The notes are based on the following books:

1. Wes McKinney - Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter (O'Reilly Media, Inc., 2022)
2. Fabio Nelli - Python Data Analytics: With Pandas, NumPy, and Matplotlib, 3rd Edition (Apress, 2023)
3. Rob Mastrodomenico - The Python Book (John Wiley & Sons, 2022)

Setup Instructions

1. Clone this repository to your local machine:

   git clone https://github.com/your-username/python-notes.git
   

2. Ensure you have Anaconda or Miniconda installed on your system.

3. Create a new conda environment:

   conda create -n python-notes python=3.11
   

4. Activate the environment:

   conda activate python-notes
   

5. Install the required packages:

   conda install jupyter pandas numpy matplotlib
   pip install jupytext plotly resource-usage pyviz
   

6. Launch Jupyter Notebook:

   jupyter notebook
   

Usage

1. Open the desired notebook file (.ipynb) in Jupyter Notebook.
2. Read through the notes and run the code cells to see the examples in action.
3. Modify the code and experiment with different inputs to deepen your understanding.

Additional Tools

The useful_tools.ipynb notebook contains information on:

• Setting up Jupyter Notebook to work with multiple Python environments
• Installing additional useful packages
• Configuring Jupyter Notebook for improved usability

Contributing

If you find any errors or would like to add more content, please feel free to open an issue or submit a pull request.

License

This project is licensed under the GNU General Public License v3.0. See the LICENSE file for details.