9781491910399-1491910399-R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

ISBN-13: 9781491910399
ISBN-10: 1491910399
Edition: 1
Author: Hadley Wickham, Garrett Grolemund
Publication date: 2017
Publisher: O'Reilly Media
Format: Paperback 518 pages
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Book details

ISBN-13: 9781491910399
ISBN-10: 1491910399
Edition: 1
Author: Hadley Wickham, Garrett Grolemund
Publication date: 2017
Publisher: O'Reilly Media
Format: Paperback 518 pages

Summary

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (ISBN-13: 9781491910399 and ISBN-10: 1491910399), written by authors Hadley Wickham, Garrett Grolemund, was published by O'Reilly Media in 2017. With an overall rating of 3.5 stars, it's a notable title among other Data Processing (Databases & Big Data, Mathematical & Statistical, Software) books. You can easily purchase or rent R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (Paperback, Used) from BooksRun, along with many other new and used Data Processing books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $5.81.

Description

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:

  • Wrangle—transform your datasets into a form convenient for analysis
  • Program—learn powerful R tools for solving data problems with greater clarity and ease
  • Explore—examine your data, generate hypotheses, and quickly test them
  • Model—provide a low-dimensional summary that captures true "signals" in your dataset
  • Communicate—learn R Markdown for integrating prose, code, and results
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