Preface

This book is about learning to use pandas, an open source library for Python, which was created to enable Python to easily manipulate and perform powerful statistical and mathematical analyses on tabular and multidimensional datasets. The design of pandas and its power combined with the familiarity of Python have created explosive growth in its usage over the last several years, particularly among financial firms as well as those simply looking for practical tools for statistical and data analysis.

While there exist many excellent examples of using pandas to solve many domain-specific problems, it can be difficult to find a cohesive set of examples in a form that allows one to effectively learn and apply the features of pandas. The information required to learn practical skills in using pandas is distributed across many websites, slide shares, and videos, and is generally not in a form that gives an integrated guide to all of the features with practical examples in an easy-to-understand and applicable fashion.

This book is therefore intended to be a go-to reference for learning pandas. It will take you all the way from installation, through to creating one- and two-dimensional indexed data structures, to grouping data and slicing-and-dicing them, with common analyses used to demonstrate derivation of useful results. This will include the loading and saving of data from resources that are local and Internet-based and creating effective data visualizations that provide instant ability to visually realize insights into the meaning previously hidden within complex data.