Exploratory data analysis using R /
Material type: TextSeries: Chapman & Hall/CRC data mining and knowledge discoveryPublication details: Boca Raton CRC Press 2018Description: xiii, 547 pages : illustrationsISBN: 9781498730235 (pbk. : acidfree paper); 9781138480605 (hardback : acidfree paper)Subject(s): Data mining | R (Computer program language)DDC classification: 006.312 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"--Item type | Current library | Call number | Status | Date due | Barcode |
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BK | Stack | 006.312 PEA/E (Browse shelf (Opens below)) | Available | 49701 |
Browsing Kannur University Central Library shelves, Shelving location: Stack Close shelf browser (Hides shelf browser)
006.312 LIN/D Data mining technique : for marketing, sales and customer relationship management | 006.312 PAL/P Pattern recognition algorithms for data mining | 006.312 PEA/E Exploratory data analysis using R | 006.312 PEA/E Exploratory data analysis using R / | 006.312 PUJ/D Data mining techniques | 006.312 PUJ/D Data mining: techniques | 006.312 ROG/D Data science and analytics with Python / |
"A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc."
"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"--
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