Exploratory Data Analysis with R
Exploratory Data Analysis with R
About the Book
This book covers the essential exploratory techniques for summarizing data with R. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data you have. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing informative data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.
If you are interested in a printed copy of this book, you can purchase one at Lulu.
Some of the topics we cover are
- Making exploratory graphs
- Principles of analytic graphics
- Plotting systems and graphics devices in R
- The base and ggplot2 plotting systems in R
- Clustering methods
- Dimension reduction techniques
About the Author
Packages
The Book
This package contains just the book in PDF, EPUB, or MOBI formats.
PDF
EPUB
MOBI
WEB
English
The Book + Datasets + R Code Files
This package contains the book and R code files corresponding to each of the chapters in the book. The package also contains the datasets used in all of the chapters so that the code can be fully executed.
Includes:
Datasets
R Code Files
PDF
EPUB
MOBI
WEB
English
The Book + Lecture Videos (HD) + Datasets + R Code Files
This package includes the book, high definition lecture video files (720p) corresponding to each of the chapters, datasets and R code files for all chapters. The videos are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license.
Includes:
Datasets
R Code Files
Lecture Videos (HD)
PDF
EPUB
MOBI
WEB
English
Table of Contents
- 1. Stay in Touch!
- 2. Preface
-
3. Getting Started with R
- 3.1 Installation
- 3.2 Getting started with the R interface
-
4. Managing Data Frames with the
dplyrpackage- 4.1 Data Frames
-
4.2 The
dplyrPackage -
4.3
dplyrGrammar -
4.4 Installing the
dplyrpackage -
4.5
select() -
4.6
filter() -
4.7
arrange() -
4.8
rename() -
4.9
mutate() -
4.10
group_by() -
4.11
%>% - 4.12 Summary
-
5. Exploratory Data Analysis Checklist
- 5.1 Formulate your question
- 5.2 Read in your data
- 5.3 Check the packaging
-
5.4 Run
str() - 5.5 Look at the top and the bottom of your data
- 5.6 Check your “n”s
- 5.7 Validate with at least one external data source
- 5.8 Try the easy solution first
- 5.9 Challenge your solution
- 5.10 Follow up questions
-
6. Principles of Analytic Graphics
- 6.1 Show comparisons
- 6.2 Show causality, mechanism, explanation, systematic structure
- 6.3 Show multivariate data
- 6.4 Integrate evidence
- 6.5 Describe and document the evidence
- 6.6 Content, Content, Content
- 6.7 References
-
7. Exploratory Graphs
- 7.1 Characteristics of exploratory graphs
- 7.2 Air Pollution in the United States
- 7.3 Getting the Data
- 7.4 Simple Summaries: One Dimension
- 7.5 Five Number Summary
- 7.6 Boxplot
- 7.7 Histogram
- 7.8 Overlaying Features
- 7.9 Barplot
- 7.10 Simple Summaries: Two Dimensions and Beyond
- 7.11 Multiple Boxplots
- 7.12 Multiple Histograms
- 7.13 Scatterplots
- 7.14 Scatterplot - Using Color
- 7.15 Multiple Scatterplots
- 7.16 Summary
-
8. Plotting Systems
- 8.1 The Base Plotting System
- 8.2 The Lattice System
- 8.3 The ggplot2 System
- 8.4 References
-
9. Graphics Devices
- 9.1 The Process of Making a Plot
- 9.2 How Does a Plot Get Created?
- 9.3 Graphics File Devices
- 9.4 Multiple Open Graphics Devices
- 9.5 Copying Plots
- 9.6 Summary
-
10. The Base Plotting System
- 10.1 Base Graphics
- 10.2 Simple Base Graphics
- 10.3 Some Important Base Graphics Parameters
- 10.4 Base Plotting Functions
- 10.5 Base Plot with Regression Line
- 10.6 Multiple Base Plots
- 10.7 Summary
-
11. Plotting and Color in R
- 11.1 Colors 1, 2, and 3
- 11.2 Connecting colors with data
- 11.3 Color Utilities in R
-
11.4
colorRamp() -
11.5
colorRampPalette() - 11.6 RColorBrewer Package
- 11.7 Using the RColorBrewer palettes
-
11.8 The
smoothScatter()function - 11.9 Adding transparency
- 11.10 Summary
-
12. Hierarchical Clustering
- 12.1 Hierarchical clustering
- 12.2 How do we define close?
- 12.3 Example: Euclidean distance
- 12.4 Example: Manhattan distance
- 12.5 Example: Hierarchical clustering
- 12.6 Prettier dendrograms
- 12.7 Merging points: Complete
- 12.8 Merging points: Average
-
12.9 Using the
heatmap()function - 12.10 Notes and further resources
-
13. K-Means Clustering
- 13.1 Illustrating the K-means algorithm
- 13.2 Stopping the algorithm
-
13.3 Using the
kmeans()function - 13.4 Building heatmaps from K-means solutions
- 13.5 Notes and further resources
-
14. Dimension Reduction
- 14.1 Matrix data
- 14.2 Patterns in rows and columns
- 14.3 Related problem
- 14.4 SVD and PCA
- 14.5 Unpacking the SVD: u and v
- 14.6 SVD for data compression
- 14.7 Components of the SVD - Variance explained
- 14.8 Relationship to principal components
- 14.9 What if we add a second pattern?
- 14.10 Dealing with missing values
- 14.11 Example: Face data
- 14.12 Notes and further resources
-
15. The ggplot2 Plotting System: Part 1
-
15.1 The Basics:
qplot() - 15.2 Before You Start: Label Your Data
- 15.3 ggplot2 “Hello, world!”
- 15.4 Modifying aesthetics
- 15.5 Adding a geom
- 15.6 Histograms
- 15.7 Facets
- 15.8 Case Study: MAACS Cohort
- 15.9 Summary of qplot()
-
15.1 The Basics:
-
16. The ggplot2 Plotting System: Part 2
- 16.1 Basic Components of a ggplot2 Plot
- 16.2 Example: BMI, PM2.5, Asthma
- 16.3 Building Up in Layers
- 16.4 First Plot with Point Layer
- 16.5 Adding More Layers: Smooth
- 16.6 Adding More Layers: Facets
- 16.7 Modifying Geom Properties
- 16.8 Modifying Labels
- 16.9 Customizing the Smooth
- 16.10 Changing the Theme
- 16.11 More Complex Example
- 16.12 A Quick Aside about Axis Limits
- 16.13 Resources
-
17. Data Analysis Case Study: Changes in Fine Particle Air Pollution in the U.S.
- 17.1 Synopsis
- 17.2 Loading and Processing the Raw Data
- 17.3 Results
- 18. About the Author
Other books by this author
The Leanpub 45-day 100% Happiness Guarantee
Within 45 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.
See full terms
Do Well. Do Good.
Authors have earned$10,884,695writing, publishing and selling on Leanpub, earning 80% royalties while saving up to 25 million pounds of CO2 and up to 46,000 trees.
Learn more about writing on Leanpub
Free Updates. DRM Free.
If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).
Most Leanpub books are available in PDF (for computers), EPUB (for phones and tablets) and MOBI (for Kindle). The formats that a book includes are shown at the top right corner of this page.
Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.
Learn more about Leanpub's ebook formats and where to read them
Top Books
- #1
Functional event-driven architecture: Powered by Scala 3
Gabriel VolpeExplore the event-driven architecture (EDA) in a purely functional way, mainly powered by Fs2 streams in Scala 3!
Leverage your functional programming skills by designing and writing stateless microservices that scale, powered by stateful message brokers.
- #2
Book of Monads
Alejandro Serrano MenaIn functional programming, at the heart of input/output, failure, state, logic, and much more, lies a powerful abstraction called monad. This book provides a journey from the very first concepts, to the myriad of monads available to programmers, down to the categorical foundations.
- #3
Functional Programming Made Easier
Charles ScalfaniA Functional Programming book from beginner to advanced without skipping a single step along the way.
In my 40 years of programming, I've felt that programming books always let me down, especially Functional Programming books. So, I wrote the book I wish I had 5 years ago.
Functional Programming will never be easy, but it can be easier.
- #4
Ansible for DevOps
Jeff GeerlingAnsible is a simple, but powerful, server and configuration management tool. Learn to use Ansible effectively, whether you manage one server—or thousands.
- #5
Practical FP in Scala: A hands-on approach
Gabriel VolpeA practical book aimed for those familiar with functional programming in Scala who are yet not confident about architecting an application from scratch.
Together, we will develop a purely functional application using the best libraries in the Cats ecosystem, while learning about design patterns and best practices.
- #6
Introducing EventStorming
Alberto BrandoliniThe deepest tutorial and explanation about EventStorming, straight from the inventor.
- #7
入門 日本語自然言語処理
Masato Hagiwara and Paul O'Leary McCann日本語テキストを処理したい全てのプログラマ・エンジニアの方へ。分かち書きなどの基本から、自然言語生成などの最新の話題までをカバー。動かして学べるコードや、参照文献も付いています。言語学や機械学習の知識が無くても問題ありません。
- #8
Stratospheric
Tom Hombergs, Björn Wilmsmann, and Philip RiecksFrom Zero to Production with Spring Boot and AWS. All you need to know to get a Spring Boot application into production with AWS. No previous AWS knowledge required.
Go to stratospheric.dev for a tour of the contents.
- #9
C++20
Rainer GrimmC++20 is the next big C++ standard after C++11. As C++11 did it, C++20 changes the way we program modern C++. This change is, in particular, due to the big four of C++20: ranges, coroutines, concepts, and modules.
- #10
Building Virtual Machine Labs: A Hands-on Guide (Second Edition)
Tony RobinsonThe premise of this book is to provide students a hands-on, go-to resource for building a secure, customizable lab environment in order to enable their own specific pursuits.
Top Bundles
- #1
CCIE Service Provider Ultimate Study Bundle
2 Books
Piotr Jablonski, Lukasz Bromirski, and Nick Russo have joined forces to deliver the only CCIE Service Provider training resource you'll ever need. This bundle contains a detailed and challenging collection of workbook labs, plus an extensively detailed technical reference guide. All of us have earned the CCIE Service Provider certification... - #2
Modern C++ Collection
3 Books
Get All about Modern C++C++ Standard Library, including C++20Concurrency with Modern C++, including C++20C++20Each book has about 200 complete code examples. Updates are included. When I update one of the books, you immediately get the updated bundle. You can expect significant updates to each new C++ standard (C++23, C++26, .. ) and also... - #3
Software Architecture for Developers: Volumes 1 & 2 - Technical leadership and communication
2 Books
"Software Architecture for Developers" is a practical and pragmatic guide to modern, lightweight software architecture, specifically aimed at developers. You'll learn:The essence of software architecture.Why the software architecture role should include coding, coaching and collaboration.The things that you really need to think about before... - #4
The Indie Python Extravaganza
5 Books
The Indie Python Extravaganza! A collection of books that will help you to improve your knowledge of the Python programming language one page at a time. Join four indie authors in a journey from the basics of Python to the structure of production-ready systems, going through the core features of the language, some intermediate projects and a... - #6
All the Books of The Medical Futurist
6 Books
We put together the most popular books from The Medical Futurist to provide a clear picture about the major trends shaping the future of medicine and healthcare. Digital health technologies, artificial intelligence, the future of 20 medical specialties, big pharma, data privacy, digital health investments and how technology giants such as Amazon... - #7
Abandon Your Job - Leaving the Rat Race with Python
8 Books
Now, get all the great Python and Freelancing books from finxter.com in one single bundle!Coffee Break Python - All Python BasicsCoffee Break Python Workbook - Practice the basics of PythonCoffee Break Python Mastery Workouts - Practice advanced Python conceptsCoffee Break Python Slicing - All about SlicingCoffee Break Python NumPy - Get started... - #9
Pattern-Oriented Memory Forensics and Malware Detection
2 Books
This training bundle for security engineers and researchers, malware and memory forensics analysts includes two accelerated training courses for Windows memory dump analysis using WinDbg. It is also useful for technical support and escalation engineers who analyze memory dumps from complex software environments and need to check for possible...
