Learning pandas: Get to grips with pandas - a versatile and high-performance Python library for data manipulation, analysis, and discovery

Key Features* Employ the use of pandas for data analysis closely to focus more on analysis and less on programming * Get programmers comfortable in performing data exploration and analysis on Python using pandas * Step-by-step demonstration of using Python and pandas with interactive and incremental examples to facilitate learning Book DescriptionThis learner's guide will help you understand how to use the features of pandas for interactive data manipulation and analysis. This book is your ideal guide to learning about pandas, all the way from installing it to creating one- and two-dimensional indexed data structures, indexing and slicing-and-dicing that data to derive results, loading data from local and Internet-based resources, and finally creating effective visualizations to form quick insights. You start with an overview of pandas and NumPy and then dive into the details of pandas, covering pandas' Series and DataFrame objects, before ending with a quick review of using pandas for several problems in finance. With the knowledge you gain from this book, you will be able to quickly begin your journey into the exciting world of data science and analysis. What You Will Learn* Install pandas on Windows, Mac, and Linux using the Anaconda Python distribution * Learn how pandas builds on NumPy to implement flexible indexed data * Adopt pandas' Series and DataFrame objects to represent one- and two-dimensional data constructs * Index, slice, and transform data to derive meaning from information * Load data from files, databases, and web services * Manipulate dates, times, and time series data * Group, aggregate, and summarize data * Visualize techniques for pandas and statistical data About the Author**Michael Heydt** is an independent consultant, educator, and trainer with nearly 30 years of professional software development experience, during which time, he focused on Agile software design and implementation using advanced technologies in multiple verticals, including media, finance, energy, and healthcare. Since 2005, he has specialized in building energy and financial trading systems for major investment banks on Wall Street and for several global energy-trading companies, utilizing .NET, C#, WPF, TPL, DataFlow, Python, R, Mono, iOS, and Android. His current interests include creating seamless applications using desktop, mobile, and wearable technologies, which utilize high-concurrency, high-availability, and real-time data analytics; augmented and virtual reality; cloud services; messaging; computer vision; natural user interfaces; and software-defined networks. He is the author of numerous technology articles, papers, and books. He is a frequent speaker at .NET user groups and various mobile and cloud conferences, and he regularly delivers webinars and conducts training courses on emerging and advanced technologies. Table of Content1. A Tour of pandas 2. Installing pandas 3. Numpy for pandas 4. The pandas Series Object 5. The pandas Dataframe Object 6. Accessing Data 7. Tidying up Your Data 8. Combining and Reshaping Data 9. Grouping and Aggregating Data 10. Time-series Data 11. Visualization 12. Applications to Finance

About This Book

• Learn to manipulate, visualize, and analyze a wide range of financial data with the help of built-in functions and programming in R
• Understand the concepts of financial engineering and create trading strategies for complex financial instruments
• Explore R for asset and liability management and capital adequacy modeling

Who This Book Is For

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.

About This BookEmploy the use of pandas for data analysis closely to focus more on analysis and less on programmingGet programmers comfortable in performing data exploration and analysis on Python using pandasStep-by-step demonstration of using Python and pandas with interactive and incremental examples to facilitate learningWho This Book Is ForIf you are a Python programmer who wants to get started with performing data analysis using pandas and Python, this is the book for you. Some experience with statistical analysis would be helpful but is not mandatory.