Hillebrand J. - Mastering RStudio - Develop, Communicate, and Collaborate with R
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RStudio helps you to manage small to large projects by giving you a multi-functional integrated development environment, combined with the power and flexibility of the R programming language, which is becoming the bridge language of data science for developers and analyst worldwide. Mastering the use of RStudio will help you to solve real-world data problems.This book begins by guiding you through the installation of RStudio and explaining the user interface step by step. From there, the next logical step is to use this knowledge to improve your data analysis workflow. We will do this by building up our toolbox to create interactive reports and graphs or even web applications with Shiny. To collaborate with others, we will explore how to use Git and GitHub with RStudio and how to build your own packages to ensure top quality results. Finally, we put it all together in an interactive dashboard written with R.What You Will Learn:
Discover the RStudio IDE and details about the user interface;
Communicate your insights with R Markdown in static and interactive ways;
Learn how to use different graphic systems to visualize your data;
Build interactive web applications with the Shiny framework to present and share your results;
Understand the process of package development and assemble your own R packages;
Easily collaborate with other people on your projects by using Git and GitHub;
Manage the R environment for your organization with RStudio and Shiny server;
Apply your obtained knowledge about RStudio and R development to create a real-world dashboard solution.Discover the multi-functional use of RStudio to support your daily work with R code.
Learn to create stunning, meaningful, and interactive graphs and learn to embed them into easy communicable reports using multiple R packages.
Develop your own R packages and Shiny web apps to share your knowledge and collaborate with others.Who This Book Is For:
This book is aimed at R developers and analysts who wish to do R statistical development while taking advantage of RStudios functionality to ease their development efforts. R programming experience is assumed as well as being comfortable with Rs basic structures and a number of functions. iPAD Amazon Kindle, PC , Cool Reader (EPUB), Calibre (EPUB, MOBI, AZW3), Adobe Digital Editions (EPUB), FBReader (EPUB, MOBI, AZW3).
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Copyright 2015 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: November 2015
Production reference: 1251115
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78398-254-7
www.packtpub.com
Authors
Julian Hillebrand
Maximilian H. Nierhoff
Reviewer
Nicholas A. Yager
Commissioning Editor
Kartikey Pandey
Acquisition Editor
Tushar Gupta
Content Development Editor
Anish Dhurat
Technical Editor
Mohita Vyas
Copy Editor
Angad Singh
Project Coordinator
Harshal Ved
Proofreader
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Indexer
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Graphics
Abhinash Sahu
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Melwyn Dsa
Cover Work
Melwyn Dsa
Julian Hillebrand studied international business marketing management at the Cologne Business School in Germany. His interest in the current questions of the business world showed him the importance of data-driven decision-making. Because of the growing size of available inputs, he soon realized the great potential of R for analyzing and visualizing data. This fascination made him start a blog project about using data science, especially for social media data analysis, which can be found at http://thinktostart.com/. He managed to combine his hands-on tutorials with his marketing and business knowledge.
Julian is always looking for new technological opportunities and is also interested in the emerging field of machine learning. He completed several digital learning offerings to take his data science capabilities to the next level.
Maximilian H. Nierhoff is an analyst for online marketing with more than half a decade of experience in managing online marketing channels and digital analytics. After studying economics, cultural activities, and creative industries, he started building online marketing departments and realized quickly that future marketing forces should also have programming knowledge. He has always been passionate about everything related to the topics of data, marketing, and customer journey analysis. Therefore, he has specialized in using R since then, which is his first-choice language for programming, data science, and analysis capabilities. He considers himself a lifelong learner and is an avid user of MOOCs, which are about R and digital analytics.
Nicholas A. Yager is a biostatistician and software developer researching statistical genomics, image analysis, and infectious disease epidemiology. With an education in biochemistry and biostatistics, his experience in analyzing cutting-edge genomics data and simulating complex biological systems has given him an in-depth understanding of scientific computing and data analysis. Currently, Nicholas works for a personalized medicine company, designing medical informatics systems for next-generation personalized cancer tests. Aside from this book, Nicholas has reviewed Unsupervised Learning with R , Packt Publishing .
I would like to thank my friends, Lauren and Matt, and my mentor, Dr. Gregg Hartvigsen, for their help in reviewing this book.
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Data analysis, visualization, and the handling of complex statistical issues was reserved just for universities and very few organizations for a long time. In fact, an easy-to-use and free environment to make the concept of data analysis available to a broader audience was not available.
But in the early nineties, R saw the light of day, and since then, it has been on a meteoric rise. R has shaped the landscape of data science in recent years like no other programing language. Because of its open source nature, it became widely known and is often referred to as the lingua franca of data analysis. Another reason for this huge success is the availability of a sophisticated Integrated Development Environment (IDE) named RStudio.
The development of RStudio started in 2010, and now, it is the de facto, go-to IDE for everybody working with R. The mission statement of RStudio is "to provide the most widely used open source and enterprise-ready professional software for the R statistical computing environment . "
But RStudio offers more than just a handy way to create R scripts; it grew to a real ecosystem by providing a variety of functionalities like package, application, interactive reporting creation, and more. Walking this way, RStudio has managed to bring data analysis to a broader audience. And because of its continuous desire to innovate R and its possibilities, it can be seen as a further development of the R language. RStudio combines the strong statistical power of R, the community, and open source spirit with cutting edge technologies of user interface development.
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