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Hillebrand Julian - Mastering RStudio: develop, communicate, and collaborate with R: harness the power of RStudio to create web applications, R packages, markdown reports and pretty data visualizations

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Hillebrand Julian Mastering RStudio: develop, communicate, and collaborate with R: harness the power of RStudio to create web applications, R packages, markdown reports and pretty data visualizations
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Mastering RStudio: develop, communicate, and collaborate with R: harness the power of RStudio to create web applications, R packages, markdown reports and pretty data visualizations: summary, description and annotation

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Cover ; Copyright; Credits; About the Authors; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The RStudio IDE -- an Overview; Downloading and installing RStudio; Installing R; For Ubuntu; Using RStudio with different versions of R; Windows; Ubuntu; Updating RStudio; Getting to know the RStudio interface; The four main panes; The Source editor pane; Syntax highlighting; Code completion; Executing R Code from the source pane; Code folding; Debugging code; The Environment and History panes; History pane; Console pane.

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Mastering RStudio Develop, Communicate, and Collaborate with R

Mastering RStudio Develop, Communicate, and Collaborate with R

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

Credits

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

Safis Editing

Indexer

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Graphics

Abhinash Sahu

Production Coordinator

Melwyn Dsa

Cover Work

Melwyn Dsa

About the Authors

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.

About the Reviewer

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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Preface

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.

This made RStudio more than just a tool for statisticians; it became the platform for everybody who wants to generate insights from data and share them with others.

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