Название: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter, 3rd Edition (Second Early Release)
Автор: Wes McKinney
Издательство: O’Reilly Media, Inc.
Год: 2021-09-09
Страниц: 173
Язык: английский
Формат: epub
Размер: 10.2 MB

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of Pandas, NumPy, and Jupyter in the process.

This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. My goal is to offer a guide to the parts of the Python programming language and its data-oriented library ecosystem and tools that will equip you to become an effective data analyst. While “data analysis” is in the title of the book, the focus is specifically on Python programming, libraries, and tools as opposed to data analysis methodology. This is the Python programming you need for data analysis.

Sometime after I originally published this book in 2012, people started using the term “data science” as an umbrella description for everything from simple descriptive statistics to more advanced statistical analysis and machine learning. The Python open source ecosystem for doing data analysis (or data science) has also expanded significantly since then. There are now many other books which focus specifically on these more advanced methodologies. My hope is that this book serves as adequate preparation to enable you to move on to a more domain-specific resource. Some might characterize much of the content of the book as “data manipulation” as opposed to “data analysis”. We also use the terms “wrangling” or “munging” to refer to data manipulation.