What this book covers
Chapter 1, pandas Foundations, introduces the main pandas objects, namely, Series, DataFrames, and Index.
Chapter 2, Selection and Assignment, shows you how to sift through the data that you have loaded into any of the pandas data structures.
Chapter 3, Data Types, explores the type system underlying pandas. This is an area that has evolved rapidly and will continue to do so, so knowing the types and what distinguishes them is invaluable information.
Chapter 4, The pandas I/O System, shows why pandas has long been a popular tool to read from and write to a variety of storage formats.
Chapter 5, Algorithms and How to Apply Them, introduces you to the foundation of performing calculations with the pandas data structures.
Chapter 6, Visualization, shows you how pandas can be used directly for plotting, alongside the seaborn library which integrates well with pandas.
Chapter 7, Reshaping DataFrames, discusses the many ways in which data can be transformed and summarized robustly via the pandas pd.DataFrame.
Chapter 8, Group By, showcases how to segment and summarize subsets of your data contained within a pd.DataFrame.
Chapter 9, Temporal Data Types and Algorithms, introduces users to the date/time types which underlie time-series-based analyses that pandas is famous for and highlights usage against real data.
Chapter 10, General Usage/Performance Tips, goes over common pitfalls users run into when using pandas, and showcases the idiomatic solutions.
Chapter 11, The pandas Ecosystem, discusses other open source libraries that integrate, extend, and/or complement pandas.
