R Data Analysis Cookbook - Second Edition

Kuntal Ganguly

• Publisher: Packt Publishing
• Year: 2017
• eBook ISBN: 9781787125315
• Edition: 2
• Topic: Computer Science
• Subtopic: Data Modelling & Design
• Index: Computer Science

Over 80 recipes to help you breeze through your data analysis projects using RAbout This Book• Analyse your data using the popular R packages like ggplot2 with ready-to-use and customizable recipes• Find meaningful insights from your data and generate dynamic reports• A practical guide to help you put your data analysis skills in R to practical useWho This Book Is ForThis book is for data scientists, analysts and even enthusiasts who want to learn and implement the various data analysis techniques using R in a practical way. Those looking for quick, handy solutions to common tasks and challenges in data analysis will find this book to be very useful. Basic knowledge of statistics and R programming is assumed.What You Will Learn• Acquire, format and visualize your data using R• Using R to perform an Exploratory data analysis• Introduction to machine learning algorithms such as classification and regression• Get started with social network analysis• Generate dynamic reporting with Shiny• Get started with geospatial analysis• Handling large data with R using Spark and MongoDB• Build Recommendation system- Collaborative Filtering, Content based and Hybrid• Learn real world dataset examples- Fraud Detection and Image RecognitionIn DetailData analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data.This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way.By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios.Style and Approach• Hands-on recipes to walk through data science challenges using R• Your one-stop solution for common and not-so-common pain points while performing real-world problems to execute a series of tasks.• Addressing your common and not-so-common pain points, this is a book that you must have on the shelf

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Table of Contents

1. Preface
   1. What this book covers
   2. What you need for this book
   3. Who this book is for
   4. Conventions
   5. Reader feedback
   6. Customer support
      1. Downloading the example code
      2. Downloading the color images of this book
      3. Errata
      4. Piracy
      5. Questions
1. Acquire and Prepare the Ingredients - Your Data
   1. Introduction
   2. Working with data
   3. Reading data from CSV files
      1. Getting ready
      2. How to do it...
      3. How it works...
      4. There's more...
         1. Handling different column delimiters
         2. Handling column headers/variable names
         3. Handling missing values
         4. Reading strings as characters and not as factors
         5. Reading data directly from a website
   4. Reading XML data
      1. Getting ready
      2. How to do it...
      3. How it works...
      4. There's more...
         1. Extracting HTML table data from a web page
         2. Extracting a single HTML table from a web page
   5. Reading JSON data
      1. Getting ready
      2. How to do it...
      3. How it works...
   6. Reading data from fixed-width formatted...

Table of contents

• Title Page
• Copyright
• Credits
• About the Author
• About the Reviewers
• www.PacktPub.com
• Customer Feedback
• Preface
• Acquire and Prepare the Ingredients - Your Data
• What's in There - Exploratory Data Analysis
• Where Does It Belong? Classification
• Give Me a Number - Regression
• Can you Simplify That? Data Reduction Techniques
• Lessons from History - Time Series Analysis
• How does it look? - Advanced data visualization
• This may also interest you - Building Recommendations
• It's All About Your Connections - Social Network Analysis
• Put Your Best Foot Forward - Document and Present Your Analysis
• Work Smarter, Not Harder - Efficient and Elegant R Code
• Where in the World? Geospatial Analysis
• Playing Nice - Connecting to Other Systems