Work out your pandas skills against dozens of real-world challenges, each carefully designed to build an intuitive knowledge of essential pandas tasks.

In Pandas Workout you’ll learn how to:
 

• Clean your data for accurate analysis
• Work with rows and columns for retrieving and assigning data
• Handle indexes, including hierarchical indexes
• Read and write data with a number of common formats, such as CSV and JSON
• Process and manipulate textual data from within pandas
• Work with dates and times in pandas
• Perform aggregate calculations on selected subsets of data
• Produce attractive and useful visualizations that make your data come alive

 Pandas Workout hones your pandas skills to a professional-level through two hundred exercises, each designed to strengthen your pandas skills. You’ll test your abilities against common pandas challenges such as importing and exporting, data cleaning, visualization, and performance optimization. Each exercise utilizes a real-world scenario based on real-world data, from tracking the parking tickets in New York City, to working out which country makes the best wines. You’ll soon find your pandas skills becoming second nature—no more trips to StackOverflow for what is now a natural part of your skillset.

About the technology

 Python’s pandas library can massively reduce the time you spend analyzing, cleaning, exploring, and manipulating data. And the only path to pandas mastery is practice, practice, and, you guessed it, more practice. In this book, Python guru Reuven Lerner is your personal trainer and guide through over 200 exercises guaranteed to boost your pandas skills.

About the book

 Pandas Workout is a thoughtful collection of practice problems, challenges, and mini-projects designed to build your data analysis skills using Python and pandas. The workouts use realistic data from many sources: the New York taxi fleet, Olympic athletes, SAT scores, oil prices, and more. Each can be completed in ten minutes or less. You’ll explore pandas’ rich functionality for string and date/time handling, complex indexing, and visualization, along with practical tips for every stage of a data analysis project.

What's inside

• Clean data with less manual labor
• Retrieving and assigning data
• Process and manipulate text
• Calculations on selected data subsets

About the reader

 For Python programmers and data analysts.