Programming Skills for Data Science · Start Writing Code to Wrangle, Analyze, and Visualize Data with R, First Edition by Freeman, Michael -- Read -- Imperial Library of Trantor

Index

Cover Page About This E-Book Title Page Copyright Page Dedication Page Contents Foreword Preface

Focus of the Book Who Should Read This Book Book Structure Book Conventions How to Read This Book Accompanying Code

Acknowledgments About the Authors I Getting Started

1 Setting Up Your Computer

1.1 Setting up Command Line Tools 1.2 Installing git 1.3 Creating a GitHub Account 1.4 Selecting a Text Editor 1.5 Downloading the R Language 1.6 Downloading RStudio

2 Using the Command Line

2.1 Accessing the Command Line 2.2 Navigating the File System 2.3 Managing Files 2.4 Dealing with Errors 2.5 Directing Output 2.6 Networking Commands

II Managing Projects

3 Version Control with git and GitHub

3.1 What Is git? 3.2 Configuration and Project Setup 3.3 Tracking Project Changes 3.4 Storing Projects on GitHub 3.5 Accessing Project History 3.6 Ignoring Files from a Project

4 Using Markdown for Documentation

4.1 Writing Markdown 4.2 Rendering Markdown

III Foundational R Skills

5 Introduction to R

5.1 Programming with R 5.2 Running R Code 5.3 Including Comments 5.4 Defining Variables 5.5 Getting Help

6 Functions

6.1 What Is a Function? 6.2 Built-in R Functions 6.3 Loading Functions 6.4 Writing Functions 6.5 Using Conditional Statements

7 Vectors

7.1 What Is a Vector? 7.2 Vectorized Operations 7.3 Vector Indices 7.4 Vector Filtering 7.5 Modifying Vectors

8 Lists

8.1 What Is a List? 8.2 Creating Lists 8.3 Accessing List Elements 8.4 Modifying Lists 8.5 Applying Functions to Lists with lapply()

IV Data Wrangling

9 Understanding Data

9.1 The Data Generation Process 9.2 Finding Data 9.3 Types of Data 9.4 Interpreting Data 9.5 Using Data to Answer Questions

10 Data Frames

10.1 What Is a Data Frame? 10.2 Working with Data Frames 10.3 Working with CSV Data

11 Manipulating Data with dplyr

11.1 A Grammar of Data Manipulation 11.2 Core dplyr Functions 11.3 Performing Sequential Operations 11.4 Analyzing Data Frames by Group 11.5 Joining Data Frames Together 11.6 dplyr in Action: Analyzing Flight Data

12 Reshaping Data with tidyr

12.1 What Is “Tidy” Data? 12.2 From Columns to Rows: gather() 12.3 From Rows to Columns: spread() 12.4 tidyr in Action: Exploring Educational Statistics

13 Accessing Databases

13.1 An Overview of Relational Databases 13.2 A Taste of SQL 13.3 Accessing a Database from R

14 Accessing Web APIs

14.1 What Is a Web API? 14.2 RESTful Requests 14.3 Accessing Web APIs from R 14.4 Processing JSON Data 14.5 APIs in Action: Finding Cuban Food in Seattle

V Data Visualization

15 Designing Data Visualizations

15.1 The Purpose of Visualization 15.2 Selecting Visual Layouts 15.3 Choosing Effective Graphical Encodings 15.4 Expressive Data Displays 15.5 Enhancing Aesthetics

16 Creating Visualizations with ggplot2

16.1 A Grammar of Graphics 16.2 Basic Plotting with ggplot2 16.3 Complex Layouts and Customization 16.4 Building Maps 16.5 ggplot2 in Action: Mapping Evictions in San Francisco

17 Interactive Visualization in R

17.1 The plotly Package 17.2 The rbokeh Package 17.3 The leaflet Package 17.4 Interactive Visualization in Action: Exploring Changes to the City of Seattle

VI Building and Sharing Applications

18 Dynamic Reports with R Markdown

18.1 Setting Up a Report 18.2 Integrating Markdown and R Code 18.3 Rendering Data and Visualizations in Reports 18.4 Sharing Reports as Websites 18.5 R Markdown in Action: Reporting on Life Expectancy

19 Building Interactive Web Applications with Shiny

19.1 The Shiny Framework 19.2 Designing User Interfaces 19.3 Developing Application Servers 19.4 Publishing Shiny Apps 19.5 Shiny in Action: Visualizing Fatal Police Shootings

20 Working Collaboratively

20.1 Tracking Different Versions of Code with Branches 20.2 Developing Projects Using Feature Branches 20.3 Collaboration Using the Centralized Workflow 20.4 Collaboration Using the Forking Workflow

21 Moving Forward

21.1 Statistical Learning 21.2 Other Programming Languages 21.3 Ethical Responsibilities

Index Credits Code Snippets

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