Applied Data Visualization with R and ggplot2 introduces you to the world of data visualization by taking you through the basic features of ggplot2. To start with, you’ll learn how to set up the R environment, followed by getting insights into the grammar of graphics and geometric objects before you explore the plotting techniques.You’ll discover what layers, scales, coordinates, and themes are, and study how you can use them to transform your data into aesthetical graphs. Once you’ve grasped the basics, you’ll move on to studying simple plots such as histograms and advanced plots such as superimposing and density plots. You’ll also get to grips with plotting trends, correlations, and statistical summaries.By the end of this book, you’ll have created data visualizations that will impress your clients.

This book addresses the needs of researchers and students using R to analyze spatial data across a range of disciplines and professions. The book is co-authored by a group involved in the Comprehensive R Archive Network.

This book addresses the needs of researchers and students using R to analyze spatial data across a range of disciplines and professions. The book is co-authored by a group involved in the Comprehensive R Archive Network.

If you are looking to create custom data visualization solutions using the R programming language and are stuck somewhere in the process, this book will come to your rescue. Prior exposure to packages such as ggplot2 would be useful but not necessary. However, some R programming knowledge is required.

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and th...(展开全部)

This book provides an introduction to the R system for users with a background in economics. It covers a variety of regression models (beginning with the classical linear regression model estimated by ordinary least quares,) regression diagnostics and robustness issues, the nonlinear models of microeconomics (Logit, Probit, Tobit, and further models), time series and time serie...(展开全部)

This book provides an introduction to the R system for users with a background in economics. It covers a variety of regression models (beginning with the classical linear regression model estimated by ordinary least quares,) regression diagnostics and robustness issues, the nonlinear models of microeconomics (Logit, Probit, Tobit, and further models), time series and time serie...(展开全部)

Budding data scientists and data analysts who are new to the concept of data analysis, or who want to build efficient analytical models in R will find this book to be useful. No prior exposure to data analysis is needed, although a fundamental understanding of the R programming language is required to get the best out of this book.

The R language provides a rich environment for working with data, especially data to be used for statistical modeling or graphics. Coupled with the large variety of easily available packages, it allows access to both well-established and experimental statistical techniques. However techniques that might make sense in other languages are often very ine?cient in R, but, due to R’...(展开全部)

This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner.