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R Recipes: A Problem-Solution Approach

Book Description

R Recipes is your 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.

R Recipes 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 - R Recipes should be a staple for your code reference library.

Table of Contents

  1. Cover
  2. Title
  3. Copyright
  4. Contents at a glance
  5. Contents
  6. About the Author
  7. About the Technical Reviewer
  8. Acknowledgments
  9. Introduction
  10. Chapter 1: Migrating to R: As Easy As 1, 2, 3
    1. Getting R Up and Running on Your System
    2. Okay, So I Have R. What’s Next?
    3. Understanding the Data Types in R
      1. Handling Missing Data in R
      2. Working with Vectors in R
      3. Working with Matrices in R
    4. Looking Backward and Forward
  11. Chapter 2: Input and Output
    1. Recipe 2-1. Inputting and Outputting Data
      1. Problem
      2. Solution
    2. Recipe 2-2. Cleaning Up Data
      1. Problem
      2. Solution
    3. Recipe 2-3. Dealing with Text Data
      1. Problem
      2. Solution
    4. Recipe 2-4. Getting Data from the Internet
      1. Problem
      2. Solution
  12. Chapter 3: Data Structures
    1. Recipe 3-1. How to Work with Vectors
      1. Problem
      2. Solution
    2. Recipe 3-2. How to Work with Matrices
      1. Problem
      2. Solution
    3. Recipe 3-3. How to Work with Lists
      1. Problem
      2. Solution
    4. Recipe 3-4. Working with Data Frames
      1. Problem
      2. Solution
  13. Chapter 4: Merging and Reshaping Datasets
    1. Recipe 4-1. Merging Datasets by a Common Variable
      1. Problem
      2. Solution
    2. Recipe 4-2. Adding Rows and Columns
      1. Problem
      2. Solution
    3. Recipe 4-3. Reshaping a Dataset
      1. Problem
      2. Solution
    4. Recipe 4-4. Stacking and Unstacking Data
      1. Problem
      2. Solution
  14. Chapter 5: Working with Dates and Strings
    1. Recipe 5-1. Working with Dates and Times
      1. Problem
      2. Solution
    2. Recipe 5-2. Working with Character Strings
      1. Problem
      2. Solution
  15. Chapter 6: Working with Tables
    1. Recipe 6-1. Working with One-Way Tables
      1. Problem
      2. Solution
    2. Recipe 6-2. Working with Two-Way Tables
      1. Problem
      2. Solution
    3. Recipe 6-3. Analyzing One- and Two-Way Tables
      1. Problem
      2. Solution
    4. Recipe 6-4. Working with Higher-Order Tables
      1. Problem
      2. Solution
  16. Chapter 7: Summarizing and Describing Data
    1. Recipe 7-1. Creating Simple Frequency Distributions
      1. Problem
      2. Solution
    2. Recipe 7-2. Creating Grouped Frequency Distributions
      1. Problem
      2. Solution
    3. Recipe 7-3. Calculating Summary Statistics
      1. Problem
      2. Solution
    4. Recipe 7-4. Working with Quantiles
      1. Problem
      2. Solution
  17. Chapter 8: Graphics and Data Visualization
    1. Recipe 8-1. Getting the Colors You Want
      1. Problem
      2. Solution
    2. Recipe 8-2. Using the Standard Graphs
      1. Problem
      2. Solution
    3. Recipe 8-3. Using Graphics for Exploratory Data Analysis
      1. Problem
      2. Solution
    4. Recipe 8-4. Using Graphics for Data Visualization
      1. Problem
      2. Solution
  18. Chapter 9: Probability Distributions
    1. Recipe 9-1. Finding Areas Under the Standard Normal Curve
      1. Problem
      2. Solution
    2. Recipe 9-2. Working with Binomial Probabilities
      1. Problem
      2. Solution
    3. Recipe 9-3. Working with Poisson Probabilities
      1. Problem
      2. Solution
    4. Recipe 9-4. Finding p Values and Critical Values of t, F, and Chi-Square
      1. Problem
      2. Solution
  19. Chapter 10: Hypothesis Tests for Means, Ranks, or Proportions
    1. Recipe 10-1. One-Sample Tests
      1. Problem
      2. Solution
    2. Recipe 10-2. Two-Sample Tests for Related Means, Ranks, and Proportions
      1. Problem
      2. Solution
    3. Recipe 10-3. Two-Sample Tests for Independent Means, Ranks, and Proportions
      1. Problem
      2. Solution
    4. Recipe 10-4. Tests for Three or More Means
      1. Problem
      2. Solution
    5. Recipe 10-5. Repeated-Measures Designs
      1. Problem
      2. Solution
  20. Chapter 11: Relationships Between and Among Variables
    1. Recipe 11-1. Determining Whether Two Scale Variables Are Correlated
      1. Problem
      2. Solution
    2. Recipe 11-2. Special Cases of the Correlation Coefficient
      1. Problem
      2. Solution
    3. Recipe 11-3. A Brief Introduction to Multiple Regression
      1. Problem
      2. Solution
  21. Chapter 12: Contemporary Statistical Methods
    1. Recipe 12-1. Resampling Techniques
      1. Problem
      2. Solution
    2. Recipe 12-2. Making Inferences About Means from Real Data
      1. Problem
      2. Solution
    3. Recipe 12-3. Permutation Tests
      1. Problem
      2. Solution
  22. Chapter 13: Writing Reusable Functions
    1. Recipe 13-1. Understanding R Functions
      1. Problem
      2. Solution
    2. Recipe 13-2. Writing Functions That Produce Other Functions
      1. Problem
      2. Solution
    3. Recipe 13-3. Writing Functions That Request User Input
      1. Problem
      2. Solution
    4. Recipe 13-4. Taking R to the Web
      1. Problem
      2. Solution
  23. Chapter 14: Working with Financial Data
    1. Recipe 14-1. Getting and Visualizing Financial Data
      1. Problem
      2. Solution
    2. Recipe 14-2. Analyzing Stock Returns
      1. Problem
      2. Solution
    3. Recipe 14-3. Comparing Stocks
      1. Problem
      2. Solution
    4. Recipe 14-4. A Brief Introduction to Portfolios
      1. Problem
      2. Solution
  24. Chapter 15: Dealing with Big Data
    1. Recipe 15-1. Parallel R
      1. Problem
      2. Solution
    2. Recipe 15-2. Using Data Tables
      1. Problem
      2. Solution
    3. Recipe 15-3. Compiled Code and Preallocation
      1. Problem
      2. Solution
  25. Chapter 16: Mining the Gold in Data and Text
    1. Recipe 16-1. Reducing the Dimensionality of Data
      1. Problem
      2. Solution
    2. Recipe 16-2. Finding Clusters of Individuals or Objects
      1. Problem
      2. Solution
    3. Recipe 16-3. Looking for Associations
      1. Problem
      2. Solution
    4. Recipe 16-4. Mining Text: A Brief Introduction
      1. Problem
      2. Solution
  26. Index