Data Visualization and Exploration with R A Practical Guide to Using R RStudio and Tidyverse for Data Visualization Exploration and Data Science Applications

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Today, data science is an indispensable tool for any organization, allowing for the analysis and optimization of decisions and strategy. R has become the preferred software for data science, thanks to its open source nature, simplicity, applicability to data analysis, and the abundance of libraries for any type of algorithm. This book will allow the student to learn, in detail, the fundamentals of the R language and additionally master some of the most efficient libraries for data visualization in chart, graph, and map formats. The reader will learn the language and applications through examples and practice. No prior programming skills are required. We begin with the installation and configuration of the R environment through RStudio. As you progress through the exercises in this hands-on book you’ll become thoroughly acquainted with R’s features and the popular tidyverse package. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, charts, and maps, and create publication-ready documents using real world data. The detailed step-by-step instructions will enable you to get a clean set of data, produce engaging visualizations, and create reports for the results. What you will learn from this book Introduction to the R programming language and R Studio Using the tidyverse package for data loading, transformation, and visualization Get a tour of the most important data structures in R Learn techniques for importing data, manipulating data, performing analysis, and producing useful data visualization Data visualization techniques with ggplot2 Geographic visualization and maps with ggmap Turning your analyses into high quality documents, reports, and presentations with R Markdown. Hands on case studies designed to replicate real world projects and reinforce the knowledge you learn in the book

Author(s): Eric Pimpler
Publisher: Geospatial Training Services
Year: 2018

Language: English
Pages: 238
Tags: Data Science, Exploratory Data Analysis, R, RStudio, Tidyverse