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 ...
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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.
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