Advanced R 4 Data Programming and the Cloud

Using Postgresql, Aws, and Shiny
2. Auflage 2020
ISBN: 978-1-4842-5972-6
Verlag: Apress

Buch, Englisch, 433 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 837 g

Program for data analysis using R and learn practical skills to make your work more efficient. This revised book explores how to automate running code and the creation of reports to share your results, as well as writing functions and packages. It includes key R 4 features such as a new color palette for charts, an enhanced reference counting system, and normalization of matrix and array types where matrix objects now formally inherit from the array class, eliminating inconsistencies.
Advanced R 4 Data Programming and the Cloud is not designed to teach advanced R programming nor to teach the theory behind statistical procedures. Rather, it is designed to be a practical guide moving beyond merely using R; it shows you how to program in R to automate tasks.
This book will teach you how to manipulate data in modern R structures and includes connecting R to databases such as PostgreSQL, cloud services such as Amazon Web Services (AWS), and digital dashboards such as Shiny. Each chapter also includes a detailed bibliography with references to research articles and other resources that cover relevant conceptual and theoretical topics.
What You Will Learn

- Write and document R functions using R 4
- Make an R package and share it via GitHub or privately
- Add tests to R code to ensure it works as intended
- Use R to talk directly to databases and do complex data management
- Run R in the Amazon cloud
- Deploy a Shiny digital dashboard
- Generate presentation-ready tables and reports using R
Who This Book Is For

Working professionals, researchers, and students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to take their R coding and programming to the next level.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Wiley, Matt

Wiley, Joshua F

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Mathematik | Informatik Mathematik Stochastik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software

Inhaltsverzeichnis

Programming1.Programming Basics2.Programming Utilities3.Loops, flow control, and *apply functions4.Writing Functions5.Writing Classes and Methods6.Writing a PackageData Management7.Data Management using data.table8.Data Munging With data.table9.Other Tools for Data Management10.Reading Big Data(bases)Cloud Computing11.Getting a Cloud12.Ubuntu for Windows Users13.Every Cloud has a Shiny lining… 14.Shiny Dashboard Sampler 15.Dynamic Reports and the CloudReferences (backmatter)

Über Autor(innen)

Matt Wiley is a tenured, associate professor of mathematics with awards in both mathematics education and honor student engagement. He earned degrees in pure mathematics, computer science, and business administration through the University of California and Texas A&M systems. He serves as director for Victoria College’s quality enhancement plan and managing partner at Elkhart Group Limited, a statistical consultancy. With programming experience in R, C++, Ruby, Fortran, and JavaScript, he has always found ways to meld his passion for writing with his joy of logical problem solving and data science. From the boardroom to the classroom, Matt enjoys finding dynamic ways to partner with interdisciplinary and diverse teams to make complex ideas and projects understandable and solvable.

Joshua F. Wiley is a lecturer in the Monash Institute for Cognitive and Clinical Neurosciences and School of Psychological Sciences at Monash University and a senior partner at Elkhart Group Limited, a statistical consultancy. He earned his PhD from the University of California, Los Angeles, and his research focuses on using advanced quantitative methods to understand the complex interplay of psychological, social, and physiological processes in relation to psychological and physical health. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. Through consulting at Elkhart Group Limited and former work at the UCLA Statistical Consulting Group, he has supported a wide array of clients ranging from graduate students, to experienced researchers, and biotechnology companies. He also develops or co-develops a number of R packages including varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.