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. 

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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

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

 

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Publisher: Wiley
Date: March 2021
Pages: 416
ISBN: 978-1119712978
Print: 1119712971
Kindle: B08WZ2D7WC
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Rating: 3
Reviewer: Mike James
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Publisher: In Easy Steps
Date: July 2020
Pages: 480
ISBN: 978-1840788785
Print: 184078878X
Kindle: B08FBGXGF1
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Reviewer Mike James
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