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Learning a computer language like R can be either frustrating, fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward for overcoming them. The book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. For students and professionals in the biological sciences, humanities and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a ...
Are you looking for a special book of endearing quick reads? Are you looking for a book of short stories to captivate you and stick in your mind forever? Here you go! Oh, oh! Look out! The flashes return! Along with some sparks and shorts too. An entire circuit of reading delight as Paul John Hausleben adds the fourth book of short pieces of fiction to the series “Flash Fiction, Thoughts, Essays, and Short Stories” by Mr. Paul John Hausleben. In the fourth book for the collection, the author once more mixes up the genres with his meditative thoughts on life with the various sparks, some religion, romance, along with doses of fantasy and emotional outpourings. When the author feels the st...
A Guide to British television programmes shown at Christmas time, throughout the years.
Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners. Key Features overview: breakdown of complex data science software stacks into core components applied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source software reader guidance: different entry points and rich references to deepen the understanding of selected aspects
A new idea can become an expensive flop for TV executives. So from the earliest days of television, the concept of a pilot episode seemed like a good idea. Trying out new actors; new situations and new concepts before making a series was good economical sense. It was also tax deductible. Sometimes these pilots were shown on television; sometimes they were so awful they were hidden from sight in archives; and sometimes they were excellent one-offs, but a series seemed elusive and never materialised. Chris Perry has always been fascinated by the pilot episode. So many pilots are made annually, but never seen by audiences. Only a handful appear on screen. It's a hidden world of comedy, variety, drama and factual programming. This volume attempts to lift the lid on the world of the TV pilot by revealing the many transmitted and untransmitted episodes made through the decades.
Outstanding User Interfaces with Shiny provides the reader with necessary knowledge to develop beautiful and highly interactive user interfaces. It gives the minimum requirements in HTML/JavaScript and CSS to be able to extend already existing Shiny layouts or develop new templates from scratch. Suitable for anyone with some experience of Shiny, package development and software engineering best practices, this book is an ideal guide for graduates and professionals who wish to bring their app design to the next level. Key Features: Provides a survival kit in web development to seamlessly get started with HTML/CSS/JavaScript Leverage CSS and Sass and higher-level tools like {bslib} to substant...
Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you’ll learn to specify tasks you want to do in a precise way and achieve programming goals within a domain-specific context. Domain-Specific Languages in R includes examples of DSLs including large data sets or matrix multiplication; pattern matching DSLs for application in computer vision; and DSLs for continuous time Markov chains and their applications in data science. After reading and using this book, you’ll understand how to write DSLs in R and have skills you can extrapolate to other programming languages. What You'll Learn Program with domain-specific languages using R Discover the components of DSLs Carry out large matrix expressions and multiplications Implement metaprogramming with DSLs Parse and manipulate expressions Who This Book Is For Those with prior programming experience. R knowledge is helpful but not required.
A Criminologist's Guide to R: Crime by the Numbers introduces the programming language R and covers the necessary skills to conduct quantitative research in criminology. By the end of this book, a person without any prior programming experience can take raw crime data, be able to clean it, visualize the data, present it using R Markdown, and change it to a format ready for analysis. A Criminologist's Guide to R focuses on skills specifically for criminology such as spatial joins, mapping, and scraping data from PDFs, however any social scientist looking for an introduction to R for data analysis will find this useful. Key Features: Introduction to RStudio including how to change user preference settings. Basic data exploration and cleaning – subsetting, loading data, regular expressions, aggregating data. Graphing with ggplot2. How to make maps (hotspot maps, choropleth maps, interactive maps). Webscraping and PDF scraping. Project management – how to prepare for a project, how to decide which projects to do, best ways to collaborate with people, how to store your code (using git), and how to test your code.