Book Image

Simulation for Data Science with R

By : Matthias Templ
Book Image

Simulation for Data Science with R

By: Matthias Templ

Overview of this book

Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. The book will provide a computational and methodological framework for statistical simulation to the users. Through this book, you will get in grips with the software environment R. After getting to know the background of popular methods in the area of computational statistics, you will see some applications in R to better understand the methods as well as gaining experience of working with real-world data and real-world problems. This book helps uncover the large-scale patterns in complex systems where interdependencies and variation are critical. An effective simulation is driven by data generating processes that accurately reflect real physical populations. You will learn how to plan and structure a simulation project to aid in the decision-making process as well as the presentation of results. By the end of this book, you reader will get in touch with the software environment R. After getting background on popular methods in the area, you will see applications in R to better understand the methods as well as to gain experience when working on real-world data and real-world problems.
Table of Contents (18 chapters)
Simulation for Data Science with R
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Visualizing information


In many chapters, results are visualized using the graphics capabilities of R. Thus, we will give a very short introduction to the base graphics package, plus a short introduction to the package ggplot2 (Wickham, 2009).

The reader will learn briefly about the graphical system in R, different output formats for traditional graphics system, customization and fine tuning of standard graphics, and the ggplot2 package.

Tip

Other packages such as ggmap, ggvis, lattice, or grid are not touched on here. Interactive graphics are also beyond the scope of this book (Google Charts, rgl, iplots, JavaScript, and R).

The graphics system in R

Many packages include methods to produce plots. Generally, they either use the functionality of the base R package called graphics or the functionality of the package grid.

For example, the package maptools (Bivand and Lewin-Koh, 2015) includes methods for mapping; with this package one can produce maps. It uses the capabilities of the graphics package...