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Learning R

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Learning R Cover

 

Synopses & Reviews

Publisher Comments:

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.

The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what youve learned, and concludes with exercises, most of which involve writing R code.

  • Write a simple R program, and discover what the language can do
  • Use data types such as vectors, arrays, lists, data frames, and strings
  • Execute code conditionally or repeatedly with branches and loops
  • Apply R add-on packages, and package your own work for others
  • Learn how to clean data you import from a variety of sources
  • Understand data through visualization and summary statistics
  • Use statistical models to pass quantitative judgments about data and make predictions
  • Learn what to do when things go wrong while writing data analysis code

Synopsis:

If you have basic programming skills and do any kind of data analysis, you need R in your toolkit. This book teaches you how to be productive with this important programming language for statistics by covering everything about R you need to know, including:

  • Data gathering from different sources such as web scraping and databases
  • Data transformation/manipulation that can save you hours
  • Visualization that provides a great way of showing insights into datasets
  • Modelling that shows just how many different analyses can be done in R

About the Author

Richie is a data scientist with a background in chemical health and safety, and has worked extensively on tools to give non-technical users access to statistical models. He is the author of the R packages "assertive" for checking the state of your variables and "sig" to make sure your functions have a sensible API. He runs The Damned Liars statistics consultancy.

Table of Contents

PrefaceThe R LanguageChapter 1: IntroductionChapter 2: A Scientific CalculatorChapter 3: Inspecting Variables and Your WorkspaceChapter 4: Vectors, Matrices, and ArraysChapter 5: Lists and Data FramesChapter 6: Environments and FunctionsChapter 7: Strings and FactorsChapter 8: Flow Control and LoopsChapter 9: Advanced LoopingChapter 10: PackagesChapter 11: Dates and TimesThe Data Analysis WorkflowChapter 12: Getting DataChapter 13: Cleaning and TransformingChapter 14: Exploring and VisualizingChapter 15: Distributions and ModelingChapter 16: ProgrammingChapter 17: Making PackagesAppendixesBibliographyIndexColophon

Product Details

ISBN:
9781449357108
Author:
Cotton, Richard
Publisher:
O'Reilly Media
Subject:
analysis;data analysis;data modelling;math;programming;r;statistics
Copyright:
Edition Description:
Print PDF
Publication Date:
20130931
Binding:
TRADE PAPER
Language:
English
Pages:
400
Dimensions:
9.19 x 7 in

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Related Subjects

Computers and Internet » Computer Languages » The Attic
Computers and Internet » Computers Reference » General
Computers and Internet » Programming » Open Source
Engineering » Engineering » Inventions
Science and Mathematics » Mathematics » Software

Learning R New Trade Paper
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$34.99 In Stock
Product details 400 pages O'Reilly Media - English 9781449357108 Reviews:
"Synopsis" by ,

If you have basic programming skills and do any kind of data analysis, you need R in your toolkit. This book teaches you how to be productive with this important programming language for statistics by covering everything about R you need to know, including:

  • Data gathering from different sources such as web scraping and databases
  • Data transformation/manipulation that can save you hours
  • Visualization that provides a great way of showing insights into datasets
  • Modelling that shows just how many different analyses can be done in R

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