Book description
Study data analysis and visualization to successfully analyze data with R
Key Features
 Get to grips with data cleaning methods
 Explore statistical concepts and programming in R, including best practices
 Build a data science project with realworld examples
Book Description
R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. To start with, you'll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops.
Once you have grasped the basics, you'll move on to studying data visualization and graphics. You'll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you'll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values.
By the end of this book, you'll have completed an entire data science project of your own for your portfolio or blog.
What you will learn
 Use basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow control
 Import data to R from various formats such as CSV, Excel, and SQL
 Clean data by handling missing values and standardizing fields
 Perform univariate and bivariate analysis using ggplot2
 Create statistical summary and advanced plots such as histograms, scatter plots, box plots, and interaction plots
 Apply data management techniques, such as factoring, pivoting, aggregating, merging, and dealing with missing values, on the example datasets
Who this book is for
R Programming Fundamentals is for you if you are an analyst who wants to grow in the field of data science and explore the latest tools.
Publisher resources
Table of contents
 Title Page
 Copyright and Credits
 Packt Upsell
 Contributors
 Preface
 Introduction to R
 Data Visualization and Graphics

Data Management
 Factor Variables
 Summarizing Data

Splitting, Combining, Merging, and Joining Datasets

Splitting and Combining Data and Datasets
 Splitting and Unsplitting Data with Base R and the dplyr Methods
 Splitting Datasets into Lists and Then Back Again
 Combining Data
 Combining Data with rbind()
 Combining Matrices of Objects into Dataframes
 Splitting Strings
 Using stringr Package to Manipulate a Vector of Names
 Combining Strings Using Base R Methods
 Activity: Demonstrating Splitting and Combining Data
 Merging and Joining Data
 Activity: Merging and Joining Data

Splitting and Combining Data and Datasets
 Summary

Solutions

Chapter 1: Introduction to R
 Activity: Installing the Tidyverse Packages
 Activity: Identifying Variable Classes and Types
 Activity: Creating Vectors, Lists, Matrices, and Dataframes
 Activity: Building Basic Loops
 Activity: Exporting and Importing the mtcars Dataset
 Activity: Exploring the Introduction to dplyr Vignette
 Chapter 2: Data Visualization and Graphics
 Chapter 3: Data Management

Chapter 1: Introduction to R
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Product information
 Title: R Programming Fundamentals
 Author(s):
 Release date: September 2018
 Publisher(s): Packt Publishing
 ISBN: 9781789612998
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