R for data science : Import, tidy, transform, visualize and model data
By: Wickham, Hadley
.
Contributor(s): Grolemund, Garrett
.
Publisher: Sebastopol O'Reilly Media, Inc. 2017Edition: 1st.Description: xxiv, 492p. | Binding - Paperback | 22.2*15.5 cm.ISBN: 9789352134977.Subject(s): Computer Engineering![](/opac-tmpl/bootstrap/images/filefind.png)
Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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School of Engineering & Technology Reference Section | Reference | 006.312 WIC/GRO (Browse shelf) | Not For Loan | E14607 | ||
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School of Engineering & Technology General Stacks | Circulation | 006.312 WIC/GRO (Browse shelf) | Available | E14608 |
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006.312 PUJ Data mining techniques | 006.312 PUJ Data mining techniques | 006.312 VAN Python data science handbook | 006.312 WIC/GRO R for data science | 006.32 CAL Essence Of Neural Networks | 006.32 CAL Essence Of Neural Networks | 006.32 CAL Essence Of Neural Networks |
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way.
You'll learn how to:
WrangleÃtransform your datasets into a form convenient for analysis
ProgramÃlearn powerful R tools for solving data problems with greater clarity and ease
ExploreÃexamine your data, generate hypotheses, and quickly test them
ModelÃprovide a low-dimensional summary that captures true ""signals"" in your dataset
CommunicateÃlearn R Markdown for integrating prose, code, and results.
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