Data Analysis with Python

Overview

This repository contains Jupyter Notebook files that demonstrate data analysis techniques using four popular Python libraries: NumPy, Pandas, Matplotlib, and Seaborn. Each notebook provides examples and explanations of how to use these libraries effectively for data manipulation and visualization.

Libraries Used

• NumPy: A library for numerical computing in Python, providing support for arrays and a variety of mathematical functions.
• Pandas: A powerful data manipulation and analysis library that offers data structures like DataFrames for handling structured data.
• Matplotlib: A plotting library for creating static, animated, and interactive visualizations in Python.
• Seaborn: A statistical data visualization library based on Matplotlib that provides a high-level interface for drawing attractive graphics.

Installation

To run the notebooks, ensure you have Jupyter Notebook installed, and then install the required libraries using:

pip install numpy pandas matplotlib seaborn

Usage

Open the Jupyter Notebook files in your browser and follow along with the examples provided. Each notebook contains code snippets and explanations to help you understand the concepts.

Conclusion

Feel free to explore the notebooks and experiment with the code. Happy coding and data analysis!

Contributor

Rituparna Das