Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio featureAbout This Book54 useful and practical tasks to improve working systemsIncludes optimizing performance and reliability or uptime, reporting, system management tools, interfacing to standard data ports, and so onOffers 10-15 real-life, practical improvements for each user typeWho This Book Is ForThis book is targeted at R statisticians, data scientists, and R programmers. Readers with R experience who are looking to take the plunge into statistical computing will find this Cookbook particularly indispensable.What You Will LearnFamiliarize yourself with the latest advanced R console featuresCreate advanced and interactive graphicsManage your R project and project files effectivelyPerform reproducible statistical analyses in your R projectsUse RStudio to design predictive models for a specific domain-based applicationUse RStudio to effectively communicate your analyses results and even publish them to a blogPut yourself on the frontiers of data science and data monetization in R with all the tools that are needed to effectively communicate your results and even transform your work into a data productIn DetailThe requirement of handling complex datasets, performing unprecedented statistical analysis, and providing real-time visualizations to businesses has concerned statisticians and analysts across the globe. RStudio is a useful and powerful tool for statistical analysis that harnesses the power of R for computational statistics, visualization, and data science, in an integrated development environment.This book is a collection of recipes that will help you learn and understand RStudio features so that you can effectively perform statistical analysis and reporting, code editing, and R development. The first few chapters will teach you how to set up your own data analysis project in RStudio, acquire data from different data sources, and manipulate and clean data for analysis and visualization purposes. Youll get hands-on with various data visualization methods using ggplot2, and you will create interactive and multidimensional visualizations with D3.js. Additional recipes will help you optimize your code; implement various statistical models to manage large datasets; perform text analysis and predictive analysis; and master time series analysis, machine learning, forecasting; and so on. In the final few chapters, youll learn how to create reports from your analytical application with the full range of static and dynamic reporting tools that are available in RStudio so that you can effectively communicate results and even transform them into interactive web applications.Style and approachRStudio is an open source Integrated Development Environment (IDE) for the R platform. The R programming language is used for statistical computing and graphics, which RStudio facilitates and enhances through its integrated environment.This Cookbook will help you learn to write better R code using the advanced features of the R programming language using RStudio. Readers will learn advanced R techniques to compute the language and control object evaluation within R functions. Some of the contents are:Accessing an API with RSubstituting missing values by interpolationPerforming data filtering activitiesR Statistical implementation for Geospatial dataDeveloping shiny add-ins to expand RStudio functionalitiesUsing GitHub with RStudioModelling a recommendation engine with RUsing R Markdown for static and dynamic reportingCurating a blog through RStudioAdvanced statistical modelling with R and RStudio