Learn Ggplot2 Using Shiny App
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Learn Ggplot2 Using Shiny App
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Author : Keon-Woong Moon
language : en
Publisher: Springer
Release Date : 2017-04-13
Learn Ggplot2 Using Shiny App written by Keon-Woong Moon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-13 with Computers categories.
This book and app is for practitioners, professionals, researchers, and students who want to learn how to make a plot within the R environment using ggplot2, step-by-step without coding. In widespread use in the statistical communities, R is a free software language and environment for statistical programming and graphics. Many users find R to have a steep learning curve but to be extremely useful once overcome. ggplot2 is an extremely popular package tailored for producing graphics within R but which requires coding and has a steep learning curve itself, and Shiny is an open source R package that provides a web framework for building web applications using R without requiring HTML, CSS, or JavaScript. This manual—"integrating" R, ggplot2, and Shiny—introduces a new Shiny app, Learn ggplot2, that allows users to make plots easily without coding. With the Learn ggplot2 Shiny app, users can make plots using ggplot2 without having to code each step, reducing typos and error messages and allowing users to become familiar with ggplot2 code. The app makes it easy to apply themes, make multiplots (combining several plots into one plot), and download plots as PNG, PDF, or PowerPoint files with editable vector graphics. Users can also make plots on any computer or smart phone. Learn ggplot2 Using Shiny App allows users to Make publication-ready plots in minutes without coding Download plots with desired width, height, and resolution Plot and download plots in png, pdf, and PowerPoint formats, with or without R code and with editable vector graphics
Scientific Data Analysis With R
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Author : Azizur Rahman
language : en
Publisher: CRC Press
Release Date : 2024-11-28
Scientific Data Analysis With R written by Azizur Rahman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-28 with Mathematics categories.
In an era marked by exponential growth in data generation and an unprecedented convergence of technology and healthcare, the intersection of biostatistics and data science has become a pivotal domain. This book is the ideal companion in navigating the convergence of statistical methodologies and data science techniques with diverse applications implemented in the open-source environment of R. It is designed to be a comprehensive guide, marrying the principles of biostatistics with the practical implementation of statistics and data science in R, thereby empowering learners, researchers, and practitioners with the tools necessary to extract meaningful knowledge from biological, health, and medical datasets. This book is intended for students, researchers, and professionals eager to harness the combined power of biostatistics, data science, and the R programming language while gathering vital statistical knowledge needed for cutting-edge scientists in all fields. It is useful for those seeking to understand the basics of data science and statistical analysis, or looking to enhance their skills in handling any simple or complex data including biological, health, medical, and industry data. Key Features: Presents contemporary concepts of data science and biostatistics with real-life data analysis examples Promotes the evolution of fundamental and advanced methods applying to real-life problem-solving cases Explores computational statistical data science techniques from initial conception to recent developments of biostatistics Provides all R codes and real-world datasets to practice and competently apply into reader’s own domains Written in an exclusive state-of-the-art deductive approach without any theoretical hitches to support all contemporary readers
R For Political Science Research
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Author : Jane L. Sumner
language : en
Publisher: Springer Nature
Release Date : 2025-01-30
R For Political Science Research written by Jane L. Sumner and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-30 with Political Science categories.
This text teaches basic R skills to political science students with no programming background. Intended specifically for the students who need to learn R for a class and who have no interest in R or may even be afraid of or hostile to it, this text builds an awareness of basics, confidence, and a skill set necessary to transition into more advanced texts. To that end, in addition to standard topics, this book includes three chapters specific to the new or reluctant learner. The Introduction explicitly sets expectations for how to use the book and discusses fixed and growth mentalities, and why a growth mentality is crucial for learning R. Chapter 1 includes some basic information on programming, R, and their place in political science research. Chapter 2 explicitly discusses errors, warnings, and methods of debugging. Further chapters build on this by including new errors or warnings that students may encounter as they progress. In service of the aim to give students a solid foundation in R and awareness of what it is and can do, this book teaches and uses both tidyverse and base R frameworks throughout. After completing the book, students should be prepared to learn more advanced materials.
Learning R Programming
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Author : Kun Ren
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-10-28
Learning R Programming written by Kun Ren and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-28 with Computers categories.
Become an efficient data scientist with R About This Book Explore the R language from basic types and data structures to advanced topics Learn how to tackle programming problems and explore both functional and object-oriented programming techniques Learn how to address the core problems of programming in R and leverage the most popular packages for common tasks Who This Book Is For This is the perfect tutorial for anyone who is new to statistical programming and modeling. Anyone with basic programming and data processing skills can pick this book up to systematically learn the R programming language and crucial techniques. What You Will Learn Explore the basic functions in R and familiarize yourself with common data structures Work with data in R using basic functions of statistics, data mining, data visualization, root solving, and optimization Get acquainted with R's evaluation model with environments and meta-programming techniques with symbol, call, formula, and expression Get to grips with object-oriented programming in R: including the S3, S4, RC, and R6 systems Access relational databases such as SQLite and non-relational databases such as MongoDB and Redis Get to know high performance computing techniques such as parallel computing and Rcpp Use web scraping techniques to extract information Create RMarkdown, an interactive app with Shiny, DiagramR, interactive charts, ggvis, and more In Detail R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset. Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques. Style and approach Developed to make learning easy and intuitive, this book comes packed with a wide variety of statistical and graphical techniques and a wealth of practical information for anyone looking to get started with this exciting and powerful language.
Generative Ai In R
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Author : Akansha Singh
language : en
Publisher: Springer Nature
Release Date : 2026-01-01
Generative Ai In R written by Akansha Singh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Computers categories.
Leverage Generative AI within the R programming environment and prepare for future directions and how new innovations can be applied in the R ecosystem. This pioneering book is designed to bridge the gap between the advanced realms of Generative AI and the practical, statistical computing power of R. You’ll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. You’ll then dive into the practicalities of implementing generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) in R. See how R, most known for its statistical analysis, can also be used for creative synthetic data, improving model robustness, and generating innovative insights from data. Additionally, this book addresses the demand for ethical AI by emphasizing the use of synthetic data to tackle privacy and data scarcity issues—concerns particularly relevant in healthcare, finance, and social research. We are at a pivotal moment in the evolution of AI and data science. With AI's growing importance, the book's focus on R makes advanced techniques more accessible, promoting ethical and innovative data science practice, preparing readers for upcoming trends. What You Will Learn Grasp the core concepts of Generative AI and its significance in the broader AI landscape. Implement various generative models in R, such as GANS and VAEs. Generate high-quality synthetic data. Apply advanced techniques for improving efficiency and effectiveness of models for different applications. Understand Gen AI ethical considerations. Who This Book Is For Data scientists and statisticians with intermediate R programming skills who want to expand into Generative AI for data analysis and problem-solving. AI enthusiasts and data analysts looking to apply Generative AI techniques in R to enhance their analytical capabilities.
An R Companion For Applied Statistics I
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Author : Danney Rasco
language : en
Publisher: SAGE Publications
Release Date : 2020-01-28
An R Companion For Applied Statistics I written by Danney Rasco and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-28 with Social Science categories.
An R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner′s Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.
Web Application Development With R Using Shiny
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Author : Chris Beeley
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-09-27
Web Application Development With R Using Shiny written by Chris Beeley and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-27 with Computers categories.
Shiny is an open source R package that provides an elegant and powerful web framework for building web applications using R. This guide takes a fresh approach to developing scalable web applications. It will enable you to create responsive, interactive web applications using the complete R Shiny suite.
Building Interactive Graphs With Ggplot2 And Shiny
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Author : Christophe Ladroue
language : en
Publisher:
Release Date : 2014
Building Interactive Graphs With Ggplot2 And Shiny written by Christophe Ladroue and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
"If you are a software programmer, application developer, or web developer with basic to intermediate knowledge of R programming and you want to build elegant graphs to display data that you can showcase to your clients, this course is for you. No knowledge of web technologies is required. Packt video courses are designed to cover the breadth of the topic in short, hands-on, task-based videos. Each course is divided into short manageable sections, so you can watch the whole thing or jump to the bit you need. The focus is on practical instructions and screencasts showing you how to get the job done. Following an example-driven approach, this course offers a practical way to learn how to build interactive graphs with ggplot 2 and Shiny with the help of easy-to-understand examples and step-by- step instructions."--Resource description page.
Mastering Shiny
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Author : Hadley Wickham
language : en
Publisher:
Release Date : 2021-04-13
Mastering Shiny written by Hadley Wickham and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-13 with categories.
Master the Shiny web framework--and take your R skills to a whole new level. Shiny helps you create fully interactive web apps for data analyses by letting you move beyond static reports, tables, and graphs. Your users will be able to jump between datasets, explore different subsets, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create complex Shiny apps. Shiny is easy to learn, but even intermediate users often wonder what they've missed. This in-depth introduction provides a learning path that you can follow with confidence. Getting started: Begin with a tutorial-style exploration of the basics Shiny in action: Explore Shiny functionality with a focus on code samples and example apps Best practices: Learn techniques for managing complexity and ensuring correctness, and explore ways to measure and improve your Shiny app's scalability Mastering reactivity: Learn the underlying theory of reactivity to improve your ability to reason about complex Shiny apps
Mastering Shiny
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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-04-29
Mastering Shiny written by Hadley Wickham and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Computers categories.
Master the Shiny web framework—and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant. Get started: Discover how the major pieces of a Shiny app fit together Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques Master reactivity: Go deep into the theory and practice of reactive programming and examine reactive graph components Apply best practices: Examine useful techniques for making your Shiny apps work well in production