Exploratory data analysis using R / Ronald K. Pearson.
By: Pearson, Ronald K.
Series: Chapman & Hall/CRC data mining and knowledge discovery, 45.Publisher: Boca Raton : CRC Press/Taylor & Francis Group, 2018Description: xiii, 547 pages : illustrations ; 24 cm.ISBN: 9781498730235 (pbk. : acidfree paper); 9781138480605 (hardback : acidfree paper); 9781315382111(ebook).Subject(s): Data mining -- Computer programs | R (Computer program language)DDC classification: 006.312 Online resources: eBook Single File Summary: "This textbook will introduce exploratory data analysis (EDA) and will cover the range of interesting features we can expect to find in data. The book will also explore the practical mechanics of using R to do EDA. Based on the author's course at the University of Connecticut, the book assumes no prior exposure to data analysis or programming, and is designed to be as non-mathematical as possible. Exercises are included throughout, and a Solutions Manual will be available. The author will also provide a supplemental R package through the Comprehensive R Archive Network that will include implementations of some of the features in this book, along with data examples, tools, and datasets"-- Provided by publisher.| Item type | Current location | Call number | URL | Status | Date due | Barcode |
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Internet | 006.312 PEA (Browse shelf) | https://doi.org/10.1201/9781315382111 | Available | NB3348 |
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| 005.824 ADV Advances of DNA computing in cryptography / | 006.22 SIN Arduino-based embedded systems : | 006.25 SOF Soft computing in wireless sensor networks / | 006.312 PEA Exploratory data analysis using R / | 006.312 ROG Data science and analytics with Python / | 006.45 HIL Audio and speech processing with MATLAB / | 006.6 BIL Image Processing and Pattern Recognition Based on Parallel Shift Technology |
"A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc."
Includes bibliographical references and index.
"This textbook will introduce exploratory data analysis (EDA) and will cover the range of interesting features we can expect to find in data. The book will also explore the practical mechanics of using R to do EDA. Based on the author's course at the University of Connecticut, the book assumes no prior exposure to data analysis or programming, and is designed to be as non-mathematical as possible. Exercises are included throughout, and a Solutions Manual will be available. The author will also provide a supplemental R package through the Comprehensive R Archive Network that will include implementations of some of the features in this book, along with data examples, tools, and datasets"-- Provided by publisher.
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