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Practical Data Wrangling

You're reading from   Practical Data Wrangling Expert techniques for transforming your raw data into a valuable source for analytics

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787286139
Length 204 pages
Edition 1st Edition
Languages
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Author (1):
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Allan Visochek Allan Visochek
Author Profile Icon Allan Visochek
Allan Visochek
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Table of Contents (10) Chapters Close

Preface 1. Programming with Data FREE CHAPTER 2. Introduction to Programming in Python 3. Reading, Exploring, and Modifying Data - Part I 4. Reading, Exploring, and Modifying Data - Part II 5. Manipulating Text Data - An Introduction to Regular Expressions 6. Cleaning Numerical Data - An Introduction to R and RStudio 7. Simplifying Data Manipulation with dplyr 8. Getting Data from the Web 9. Working with Large Datasets

Introducing R and RStudio


R is a programming language and environment for statistical computing and graphics. R differs from Python in that it is specialized for statistical computing and contains a number of features in addition to the programming language. The R project website lists the features of R as:

  • An effective data handling and storage facility
  • A suite of operators for calculations on arrays - in particular, matrices
  • A large, coherent, integrated collection of intermediate tools for data analysis
  • Graphical facilities for data analysis and display either onscreen or on hard copy
  • A well-developed, simple and effective programming language that includes conditionals, loops, user-defined recursive functions, and input and output facilities

The most common way of using R is through RStudio, an IDE for interfacing with the R programming language and environment. RStudio combines several components to centralize and facilitate the process of working with data. These include:

  • A console for executing...

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