Learn to master data analysis with Pandas, covering Python basics to advanced techniques, including data cleaning, preprocessing, and visualization.

Key Features

Comprehensive coverage of Python basics and Pandas

Practical examples and code samples for hands-on learning

Detailed sections on data preprocessing, statistical concepts, and data visualization

Book Description

This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher. Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly. By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.

What you will learn

Learn to install and configure Python and Pandas

Perform data preprocessing and cleaning tasks

Understand statistical concepts and their application

Create data visualizations with Matplotlib and Seaborn

Handle missing data and outliers effectively

Utilize Pandas for advanced data manipulation

Who this book is for

The ideal audience for this book is software developers with a solid background in programming, specifically in Python. Complete beginners might not find this book very helpful. Readers should have a basic understanding of programming concepts.