R recipes : a problem-solution approach

Table of Contents: 1. Migrating to R: As Easy As 1, 2, 3 2. Input and Output 3. Data Structures 4. Merging and Reshaping Datasets 5. Working with Dates and Strings 6. Working with Tables 7. Summarizing and Describing Data 8. Graphics and Data Visualization 9. Probability Distributions 10. Hypothesis Tests for Means, Ranks, or Proportions 11. Relationships Between and Among Variables 12. Contemporary Statistical Methods 13. Writing Reusable Functions 14. Working with Financial Data 15. Dealing with Big Data 16. Mining the Gold in Data and Text

This book is handy problem-solution reference for learning and using the popular R programming language for statistics and other numerical analysis. Packed with hundreds of code and visual recipes, this book helps you to quickly learn the fundamentals and explore the frontiers of programming, analyzing and using R. This book provides textual and visual recipes for easy and productive templates for use and re-use in your day-to-day R programming and data analysis practice. Whether you're in finance, cloud computing, big or small data analytics, or other applied computational and data science - should be a staple for your code reference library.