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R Programming By Example
R Programming By Example

R Programming By Example: Practical, hands-on projects to help you get started with R

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Profile Icon Omar Trejo Navarro
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$19.99 per month
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (4 Ratings)
Paperback Dec 2017 470 pages 1st Edition
eBook
$41.39 $45.99
Paperback
$57.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Omar Trejo Navarro
Arrow right icon
$19.99 per month
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (4 Ratings)
Paperback Dec 2017 470 pages 1st Edition
eBook
$41.39 $45.99
Paperback
$57.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$41.39 $45.99
Paperback
$57.99
Subscription
Free Trial
Renews at $19.99p/m

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R Programming By Example

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Key benefits

  • Get a firm hold on the fundamentals of R through practical hands-on examples
  • Get started with good R programming fundamentals for data science
  • Exploit the different libraries of R to build interesting applications in R

Description

R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable.

Who is this book for?

This books is for aspiring data science professionals or statisticians who would like to learn about the R programming language in a practical manner. Basic programming knowledge is assumed.

What you will learn

  • * Discover techniques to leverage R's features, and work with packages
  • * Perform a descriptive analysis and work with statistical models using R
  • * Work efficiently with objects without using loops
  • * Create diverse visualizations to gain better understanding of the data
  • * Understand ways to produce good visualizations and create reports for the results
  • * Read and write data from relational databases and REST APIs, both packaged and unpackaged
  • * Improve performance by writing better code, delegating that code to a more efficient programming language, or making it parallel

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 22, 2017
Length: 470 pages
Edition : 1st
Language : English
ISBN-13 : 9781788292542
Category :
Languages :

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Product Details

Publication date : Dec 22, 2017
Length: 470 pages
Edition : 1st
Language : English
ISBN-13 : 9781788292542
Category :
Languages :

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Frequently bought together


Stars icon
Total $ 159.97
Modern R Programming Cookbook
$50.99
R Data Mining
$50.99
R Programming By Example
$57.99
Total $ 159.97 Stars icon

Table of Contents

11 Chapters
Introduction to R Chevron down icon Chevron up icon
Understanding Votes with Descriptive Statistics Chevron down icon Chevron up icon
Predicting Votes with Linear Models Chevron down icon Chevron up icon
Simulating Sales Data and Working with Databases Chevron down icon Chevron up icon
Communicating Sales with Visualizations Chevron down icon Chevron up icon
Understanding Reviews with Text Analysis Chevron down icon Chevron up icon
Developing Automatic Presentations Chevron down icon Chevron up icon
Object-Oriented System to Track Cryptocurrencies Chevron down icon Chevron up icon
Implementing an Efficient Simple Moving Average Chevron down icon Chevron up icon
Adding Interactivity with Dashboards Chevron down icon Chevron up icon
Required Packages Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(4 Ratings)
5 star 50%
4 star 0%
3 star 0%
2 star 0%
1 star 50%
John Beck Aug 29, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great content and very well explained. At first I was hesitating about buying it because of the other comment here, but I had heard good things about the book so I bought it, and I’m glad I did. Never had a problem with the data files or source code files. Easy to download and follow, and great material. Thanks! Definitely recommended.
Amazon Verified review Amazon
John Stewart Sep 06, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I know programming at an intermediate level, and I've recently started to focus in Data Science. This book was the right one for me! It does a great job at introducing R from a programmer's perspective, not only showing you how to do interesting Data Science projects, but actually explaining the underlying programming concepts which I had not seen well explained in other R books. Thanks!
Amazon Verified review Amazon
S N Jul 10, 2018
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Pros:-The book seems to have practical, detailed examples and quality instruction.Major Con:-The data files required to use the book are NOT available. The author only provides links to Git Hub "pointer files", which have to be downloaded via a separate command prompt utility (Git LFS). The author provides vague, incorrect instructions for how to download the files. You will need to spend several hours researching and troubleshooting just to figure out how to correctly run the utility and which commands to run. What's worse: once you get the utility commands to successfully execute, you'll get an error message indicating that the .csv files are not available on the server.-The publisher and author REFUSE to provide accessible links to the .csv files, or correct/detailed instructions for how to retrieve them. If you contact the publisher or author, the author will ignore your feedback about error messages and will simply copy/paste vague instructions from Errata which he posted previously on the publisher's website (i.e. indicating that previous people have complained).I cannot recommend this book at all until the author/publisher corrects this. Very unprofessional behavior.
Amazon Verified review Amazon
Amazon Customer Oct 22, 2018
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
R Programming By Example is not worth. Instead to buy this book we have somany alternate books which they explain very clear.
Amazon Verified review Amazon
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