Exploratory Data Analysis Using R (CRC Press)
Thursday, 06 September 2018

This book provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. Author Ronald K. Pearson also introduces the mechanics of using R to explore and explain data. Alongside a detailed overview of data, exploratory analysis, and R, the book also covers graphics in R., working with external data, linear regression models, and crafting data stories. The second part of the book focuses on developing R programs, including good programming practices and examples, working with text data, and general predictive models. 

<ASIN:149873023X>

 

Author: Ronald K. Pearson
Publisher: Chapman & Hall
Date: Sept 2018
Pages: 562
ISBN: 978-1498730235
Print: 149873023X
Kindle: B07CYQ7LQM
Audience: Developers working with data
Level: Intermediate
Category: Data Science

expdatausingr

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

 

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Modern Software Engineering (Addison-Wesley)

Author: David Farley
Pages: 256
ISBN: 978-0137314911
Print:0137314914
Kindle: B09GG6XKS4
Audience: Software Engineers
Rating: 3.5
Reviewer: Kay Ewbank

This book is subtitled 'doing what works to build better software faster' - does it teach you how to achieve that?



Killer ChatGPT Prompts (Wiley)

Author: Guy Hart-Davis
Publisher: Wiley
Pages: 240
ISBN: 978-1394225255
Print: 1394225253
ASIN: B0CF3WFTWM
Audience: Everyone
Rating: 5
Reviewer: Ian Stirk

This book aims to get optimal answers to your questions from ChatGPT, how does it fare? 


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