This comprehensive but easy-to-follow deep dive into data analysis and visualization in the Python programming language is packed with practical examples and exercises that use real-world datasets.

This book is an in-depth guide to best practices for data analysis and visualization in Python. It focuses on various Python libraries, showing you how to optimize their performance with the most up-to-date syntax. After learning the basics of the pandas library, you’ll dive into how to use it for conducting nearly any kind of data analysis—complete with exercises in every chapter that test your newfound skills on real-world datasets, like tracking Chicago bikers. You’ll also explore the matplotlib and seaborn libraries, and try out some of the most common tasks during data analysis, including selecting subsets of the data and performing calculations on single or multiple columns.

Learn to:

• Apply operations to independent groups within a dataset
• Observe data over a period of time
• Tidy your data and display it in a reader-friendly way
• Join multiple datasets to work with them at the same time
• Set up a robust environment on your system to do data science

Master Data Analysis with Python is a masterclass in the best practices, libraries, and techniques for collecting, analyzing, and visualizing data with the world’s most popular, easy-to-learn language.