Data Analysis with Python

Welcome to the Python Course Notes repository! This repository contains resources, lecture notes, and datasets used in a short course aimed at introducing Python libraries like Pandas, Matplotlib, Seaborn, and NumPy for data analysis. The course was conducted at the University of Nairobi, Department of Mathematics.

Table of Contents

• Course Overview
• Course Materials
• Datasets
• How to Use This Repository
• Contributions
• License

Course Overview

This course introduces the fundamental Python libraries essential for data analysis, including:

• Pandas: For data manipulation and analysis.
• Matplotlib: For data visualization.
• Seaborn: For statistical data visualization.
• NumPy: For numerical computing.

Course Materials

The repository contains lecture notes and Jupyter notebooks organized by days and weeks:

• Week 1: Introduction to Python

  • Day 1: Introduction to Python (PDF)
  • Day 2: Introduction to Python (PDF)
  • Notebook
  • PDF

• Week 2: Advanced Python Topics

  • Day 1: PDF
  • Day 2: Notebook
  • PDF

...and so on for subsequent weeks.

Datasets

• GOOG.csv
• Sales Data.csv
• Pokemon.csv

These datasets are used for practical exercises throughout the course.

How to Use This Repository

1. Clone the repository:

   git clone https://github.com/Isaakkamau/python-course-notes.git

2. Navigate to the desired files and open the Jupyter notebooks or PDF lecture notes.

3. Explore the datasets and try out the Python code provided in the notebooks.

Contributions

Contributions are welcome! If you find any issues or would like to add new content, feel free to open an issue or submit a pull request.

License

This repository is licensed under the MIT License. See the LICENSE file for more details.