The Pandas Workshop E-Book

Blaine Bateman

• Herausgeber: Packt Publishing
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 642

Veröffentlichungsjahr: 2022

Beschreibung

The Pandas Workshop will teach you how to be more productive with data and generate real business insights to inform your decision-making. You will be guided through real-world data science problems and shown how to apply key techniques in the context of realistic examples and exercises. Engaging activities will then challenge you to apply your new skills in a way that prepares you for real data science projects.
You’ll see how experienced data scientists tackle a wide range of problems using data analysis with pandas. Unlike other Python books, which focus on theory and spend too long on dry, technical explanations, this workshop is designed to quickly get you to write clean code and build your understanding through hands-on practice. As you work through this Python pandas book, you’ll tackle various real-world scenarios, such as using an air quality dataset to understand the pattern of nitrogen dioxide emissions in a city, as well as analyzing transportation data to improve bus transportation services.
By the end of this data analytics book, you’ll have the knowledge, skills, and confidence you need to solve your own challenging data science problems with pandas.

Leseprobe

The Pandas Workshop

A comprehensive guide to using Python for data analysis with real-world case studies

Blaine Bateman

Saikat Basak

Thomas V. Joseph

William So

BIRMINGHAM—MUMBAI

The Pandas Workshop

Copyright © 2022 Packt Publishing

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First published: June 2022

Production reference: 1270522

Published by Packt Publishing Ltd.

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B3 2PB, UK.

ISBN 978-1-80020-893-3

www.packt.com

To my wife Cynthia, who steadfastly supports me in these efforts and is a constant source of inspiration.

-Blaine Bateman

“To all my friends, who couldn’t believe I wrote a book about panda(s).”

-William So

To my mother Marykutty, and to the memory of my father V. T. Joseph, for laying the foundation of what I am. To my wife Anu, for being the pillar of support in all my endeavors. My children Joe and Tess, for reminding me that life is not all about Data Science.

-Thomas V. Joseph

Contributors

About the authors

Blaine Bateman has more than 35 years of experience working with various industries, from government R&D to start-ups to $1 billion public companies. His experience focuses on analytics, including machine learning and forecasting. His hands-on abilities include Python and R coding, Keras/TensorFlow, and AWS and Azure machine learning services. As a machine learning consultant, he has developed and deployed actual machine learning models in industry.

Saikat Basak is a data scientist and a passionate programmer. Having worked with multiple industry leaders, he has a good understanding of problem areas that can potentially be solved using data. Apart from being a data guy, he is also a science geek and loves to explore new ideas on the frontiers of science and technology.

Thomas V. Joseph is a data science practitioner, researcher, trainer, mentor, and writer with more than 19 years of experience. He has extensive experience in solving business problems using machine learning toolsets across multiple industry segments.

William So is a Data Scientist with both a strong academic background and extensive professional experience. He is currently the Head of Data Science at Douugh and also a Lecturer for Master of Data Science and Innovation at the University of Technology Sydney.

During his career, he successfully covered the end-end spectrum of data analytics from ML to Business Intelligence helping stakeholders derive valuable insights and achieve amazing results that benefits the business.

William So is a co-author of the "The Applied Artificial Intelligence Workshop" published by Packt.

About the reviewer

Vishwesh Ravi Shrimali graduated from BITS Pilani, where he studied mechanical engineering, in 2018. He also completed a masters in machine learning and AI at LJMU in 2021. He authored Machine Learning for OpenCV (2nd edition) and Computer Vision Workshop and Data Science for Marketing Analytics (2nd edition), both available from Packt. When he is not writing blogs or working on projects, he likes to go on long walks or play his acoustic guitar.

ii Preface

To get the most out of this book iii

iv Preface

Get in touch v

Part 1 – Introduction to pandas

This section will serve as a brief introduction to the world of pandas, its functionalities, and its history. It also covers the various data structures that are used in pandas and how they can be used for data analysis and machine learning. We will also see how to efficiently access data from various sources, as well as the various data types that pandas uses for its various operations.

This section contains the following chapters:

Chapter 1, Introduction to pandasChapter 2, Data StructuresChapter 3, Data I/OChapter 4, pandas Data Types