Extending R
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Extending R
Up-to-Date Guidance from One of the Foremost Members of the R Core Team Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R. The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R. A 2017 Choice Outstanding Academic Title
Extending Excel with Python and R
Author: Steven Sanderson
language: en
Publisher: Packt Publishing Ltd
Release Date: 2024-04-30
Seamlessly integrate the Python and R programming languages with spreadsheet-based data analysis to maximize productivity Key Features Perform advanced data analysis and visualization techniques with R and Python on Excel data Use exploratory data analysis and pivot table analysis for deeper insights into your data Integrate R and Python code directly into Excel using VBA or API endpoints Purchase of the print or Kindle book includes a free PDF eBook Book Description– Extending Excel with Python and R is a game changer resource written by experts Steven Sanderson, the author of the healthyverse suite of R packages, and David Kun, co-founder of Functional Analytics. – This comprehensive guide transforms the way you work with spreadsheet-based data by integrating Python and R with Excel to automate tasks, execute statistical analysis, and create powerful visualizations. – Working through the chapters, you’ll find out how to perform exploratory data analysis, time series analysis, and even integrate APIs for maximum efficiency. – Both beginners and experts will get everything you need to unlock Excel's full potential and take your data analysis skills to the next level. – By the end of this book, you’ll be able to import data from Excel, manipulate it in R or Python, and perform the data analysis tasks in your preferred framework while pushing the results back to Excel for sharing with others as needed. What you will learn Read and write Excel files with R and Python libraries Automate Excel tasks with R and Python scripts Use R and Python to execute Excel VBA macros Format Excel sheets using R and Python packages Create graphs with ggplot2 and Matplotlib in Excel Analyze Excel data with statistical methods and time series analysis Explore various methods to call R and Python functions from Excel Who this book is for – If you’re a data analyst or data scientist, or a quants, actuaries, or data practitioner looking to enhance your Excel skills and expand your data analysis capabilities with R and Python, this book is for you. – The comprehensive approach to the topics covered makes it suitable for both beginners and intermediate learners. – A basic understanding of Excel, Python, and R is all you need to get started.
Extensions of Rings and Modules
Author: Gary F. Birkenmeier
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-07-19
The "extensions" of rings and modules have yet to be explored in detail in a research monograph. This book presents state of the art research and also stimulating new and further research. Broken into three parts, Part I begins with basic notions, terminology, definitions and a description of the classes of rings and modules. Part II considers the transference of conditions between a base ring or module and its extensions. And Part III utilizes the concept of a minimal essental extension with respect to a specific class (a hull). Mathematical interdisciplinary applications appear throughout. Major applications of the ring and module theory to Functional Analysis, especially C*-algebras, appear in Part III, make this book of interest to Algebra and Functional Analysis researchers. Notes and exercises at the end of every chapter, and open problems at the end of all three parts, lend this as an ideal textbook for graduate or advanced undergradate students.