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 real-world 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.
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
- Other Books You May Enjoy
Product information
- Title: R Programming Fundamentals
- Author(s):
- Release date: September 2018
- Publisher(s): Packt Publishing
- ISBN: 9781789612998
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