Hands On Programming With R
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Hands On Programming With R
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Author : Garrett Grolemund
language : en
Publisher:
Release Date : 2014
Hands On Programming With R written by Garrett Grolemund and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Mathematical statistics categories.
Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.
Hands On Programming With R
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Author : Garrett Grolemund
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2014-06-13
Hands On Programming With R written by Garrett Grolemund 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 2014-06-13 with Computers categories.
Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools. RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time. Work hands-on with three practical data analysis projects based on casino games Store, retrieve, and change data values in your computer’s memory Write programs and simulations that outperform those written by typical R users Use R programming tools such as if else statements, for loops, and S3 classes Learn how to write lightning-fast vectorized R code Take advantage of R’s package system and debugging tools Practice and apply R programming concepts as you learn them
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
Introduction To Nfl Analytics With R
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Author : Bradley J. Congelio
language : en
Publisher: CRC Press
Release Date : 2023-12-19
Introduction To Nfl Analytics With R written by Bradley J. Congelio and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-19 with Sports & Recreation categories.
It has become difficult to ignore the analytics movement within the NFL. An increasing number of coaches openly integrate advanced numbers into their game plans, and commentators, throughout broadcasts, regularly use terms such as air yards, CPOE, and EPA on a casual basis. This rapid growth, combined with an increasing accessibility to NFL data, has helped create a burgeoning amateur analytics movement, highlighted by the NFL’s annual Big Data Bowl. Because learning a coding language can be a difficult enough endeavor, Introduction to NFL Analytics with R is purposefully written in a more informal format than readers of similar books may be accustomed to, opting to provide step-by-step instructions in a structured, jargon-free manner. Key Coverage: Installing R, RStudio, and necessary packages Working and becoming fluent in the tidyverse Finding meaning in NFL data with examples from all the functions in the nflverse family of packages Using NFL data to create eye-catching data visualizations Building statistical models starting with simple regressions and progressing to advanced machine learning models using tidymodels and eXtreme Gradient Boosting The book is written for novices of R programming all the way to more experienced coders, as well as audiences with differing expected outcomes. Professors can use Introduction to NFL Analytics with R to provide data science lessons through the lens of the NFL, while students can use it as an educational tool to create robust visualizations and machine learning models for assignments. Journalists, bloggers, and arm-chair quarterbacks alike will find the book helpful to underpin their arguments by providing hard data and visualizations to back up their claims.
Finite Element Computations In Mechanics With R
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Author : Khameel Bayo Mustapha
language : en
Publisher: CRC Press
Release Date : 2018-04-17
Finite Element Computations In Mechanics With R written by Khameel Bayo Mustapha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-17 with Science categories.
Finite Element Computations in Mechanics with R: A Problem-Centred Programming Approach provides introductory coverage of the finite element method (FEM) with the R programming language, emphasizing links between theory and implementation of FEM for problems in engineering mechanics. Useful for students, practicing engineers, and researchers, the text presents the R programming as a convenient easy-to-learn tool for analyzing models of mechanical systems, with finite element routines for structural, thermal, and dynamic analyses of mechanical systems, and also visualization of the results. Full-color graphics are used throughout the text.
Efficient R Programming
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Author : Colin Gillespie
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-08
Efficient R Programming written by Colin Gillespie 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 2016-12-08 with Computers categories.
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry—the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer
Data Science With R For Psychologists And Healthcare Professionals
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Author : Christian Ryan
language : en
Publisher: CRC Press
Release Date : 2021-12-22
Data Science With R For Psychologists And Healthcare Professionals written by Christian Ryan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-22 with Business & Economics categories.
This introduction to R for students of psychology and health sciences aims to fast-track the reader through some of the most difficult aspects of learning to do data analysis and statistics. It demonstrates the benefits for reproducibility and reliability of using a programming language over commercial software packages such as SPSS. The early chapters build at a gentle pace, to give the reader confidence in moving from a point-and-click software environment, to the more robust and reliable world of statistical coding. This is a thoroughly modern and up-to-date approach using RStudio and the tidyverse. A range of R packages relevant to psychological research are discussed in detail. A great deal of research in the health sciences concerns questionnaire data, which may require recoding, aggregation and transformation before quantitative techniques and statistical analysis can be applied. R offers many useful and transparent functions to process data and check psychometric properties. These are illustrated in detail, along with a wide range of tools R affords for data visualisation. Many introductory statistics books for the health sciences rely on toy examples - in contrast, this book benefits from utilising open datasets from published psychological studies, to both motivate and demonstrate the transition from data manipulation and analysis to published report. R Markdown is becoming the preferred method for communicating in the open science community. This book also covers the detail of how to integrate the use of R Markdown documents into the research workflow and how to use these in preparing manuscripts for publication, adhering to the latest APA style guidelines.
Geocomputation With R
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Author : Robin Lovelace
language : en
Publisher: CRC Press
Release Date : 2025-05-23
Geocomputation With R written by Robin Lovelace and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-23 with Mathematics categories.
Geocomputation with R is for people who want to analyze, visualize, and model geographic data with open source software. The book provides a foundation for learning how to solve a wide range of geographic data analysis problems in a reproducible, and therefore scientifically sound and scalable way. The second edition features numerous updates, including the adoption of the high-performance terra package for all raster data processing, detailed coverage of the spherical geometry engine s2, updated information on coordinate reference systems and new content on openEO, STAC, COG, and gdalcubes. The data visualization chapter has been revamped around version 4 of the tmap package, providing a fresh perspective on creating publication-quality maps from the command line. The importance of the book is also highlighted in a new foreword by Edzer Pebesma. The book equips you with the knowledge and skills necessary to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. The book is especially well-suited to: Data scientists and engineers interested in upskilling to handle spatial data. People with existing geographic data skills interested in developing powerful geosolutions via code. Anyone who needs to work with spatial data in a reproducible and scalable way. The book is divided into three parts: Foundations, Extensions, and Applications, covering progressively more advanced topics. The exercises at the end of each chapter provide the necessary skills to address various geospatial problems, with solutions and supplementary materials available at r.geocompx.org/solutions/.
Data Science Analytics And Machine Learning With R
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Author : Luiz Paulo Favero
language : en
Publisher: Academic Press
Release Date : 2023-01-23
Data Science Analytics And Machine Learning With R written by Luiz Paulo Favero and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-23 with Computers categories.
Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear. - Presents a comprehensive and practical overview of machine learning, data mining and AI techniques for a broad multidisciplinary audience - Serves readers who are interested in statistics, analytics and modeling, and those who wish to deepen their knowledge in programming through the use of R - Teaches readers how to apply machine learning techniques to a wide range of data and subject areas - Presents data in a graphically appealing way, promoting greater information transparency and interactive learning
Modeling Techniques In Predictive Analytics With Python And R
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Author : Thomas W. Miller
language : en
Publisher: FT Press
Release Date : 2014-09-29
Modeling Techniques In Predictive Analytics With Python And R written by Thomas W. Miller and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-29 with Business & Economics categories.
Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more