• 1 Introduction
  • 2 Acknowledgments
  • 3 Resources
  • 4 Getting Started
    • 4.1 Prerequisites
    • 4.2 Software Requirements
      • 4.2.1 R and RStudio
    • 4.3 Required Packages
      • 4.3.1 Option 1: Use tidyverse
      • 4.3.2 Option 2: Install Individual Packages
  • 5 Basic Operations
    • 5.1 Data pipelines
    • 5.2 Dataset
    • 5.3 Select
    • 5.4 Filter
      • 5.4.1 Exercise
    • 5.5 Arrange
      • 5.5.1 Exercise
    • 5.6 Mutate
      • 5.6.1 Exercise
    • 5.7 Summarise
      • 5.7.1 Exercise
    • 5.8 Unite
    • 5.9 Separate
      • 5.9.1 Exercise
  • 6 Merging Datasets
    • 6.1 Left Join
    • 6.2 Right Join
    • 6.3 Inner Join
    • 6.4 Full Join
    • 6.5 Different Column Names
    • 6.6 Exercise
  • 7 Reshaping

Data Manipulation in R

3 Resources

  • Google

  • Tidy Data

  • Tidyverse

  • Data Wrangling with dplyr and tidyr Cheat Sheet

  • R for Data Science

  • Advanced R

  • Data manipulation with dplyr, 2014
  • Introduction to dplyr

  • Hands-on dplyr tutorial for faster data manipulation in R