Introduction to Exploratory Data Analysis (EDA)

Exploratory Data Analysis (EDA) is a crucial step in the data analysis process. It involves visually and statistically summarizing and interpreting data to uncover patterns, trends, and insights. The "Hands on EDA" repository is a practical resource inspired by the book "Hands-On Exploratory Data Analysis with Python" by Suresh Kumar Mukhiya and Usman Ahmed.

About the Book

"Hands-On Exploratory Data Analysis with Python" provides a comprehensive guide to EDA techniques using Python. This repository follows the book's principles and best practices, offering a hands-on approach to mastering EDA.

Navigating the Repository

All the Notebooks below demand at least basic Python, NumPy, Pandas, ScikitLearn, Matplotlib, and Machine Learning knowledge.

1. Basics of NumPy: A quick look on the basics of NumPy.
2. Basics of Pandas: A quick look on the basics of Pandas.

Getting Started

1. Clone the repository: git clone https://github.com/DeepNets-US/Hands-on-EDA.git

2. Explore the folders and files mentioned above to enhance your EDA skills.

3. Refer to the book for an in-depth understanding of EDA with Python.

Happy exploring! 🚀