R Data Analysis Cookbook Front Cover

R Data Analysis Cookbook

  • Length: 328 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2015-05-29
  • ISBN-10: 1783989068
  • ISBN-13: 9781783989065
  • Sales Rank: #2898244 (See Top 100 Books)
Description

Over 80 recipes to help you breeze through your data analysis projects using R

About This Book

  • Analyse data with ready-to-use and customizable recipes
  • Discover convenient functions to speed-up your work and data files
  • Demystifies several R packages that seasoned data analysts regularly use

Who This Book Is For

This book is ideal for those who are already exposed to R, but have not yet used it extensively for data analytics and are seeking to get up and running quickly for analytics tasks. This book will help people who aspire to enhance their skills in any of the following ways:

  • perform advanced analyses and create informative and professional charts
  • become proficient in acquiring data from many sources
  • apply supervised and unsupervised data mining techniques
  • use R’s features to present analyses professionally

In Detail

Data 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 empowers you by showing you ways to use R to generate professional analysis reports. It provides examples for various important analysis and machine-learning tasks that you can try out with associated and readily available data. The book also teaches you to quickly adapt the example code for your own needs and save yourself the time needed to construct code from scratch.

Table of Contents

Chapter 1. Acquire and Prepare the Ingredients – Your Data
Chapter 2. What’s in There? – Exploratory Data Analysis
Chapter 3. Where Does It Belong? – Classification
Chapter 4. Give Me a Number – Regression
Chapter 5. Can You Simplify That? – Data Reduction Techniques
Chapter 6. Lessons from History – Time Series Analysis
Chapter 7. It’s All About Your Connections – Social Network Analysis
Chapter 8. Put Your Best Foot Forward – Document and Present Your Analysis
Chapter 9. Work Smarter, Not Harder – Efficient and Elegant R Code
Chapter 10. Where in the World? – Geospatial Analysis
Chapter 11. Playing Nice – Connecting to Other Systems

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