Dataframes in R

Learning to work with data structures is critical for programming in R. Data structures are essential concepts in programming because efficient data storage and operartions rely on them.

In this fourth lesson of our interactive Data Structures in R course, you will continue adding to your R programming skills as you learn about dataframes and they're used for data analysis in R

Throughout this course, we've learned about different data structures available to us in R. Matrices and their use for storing numbers in an organized structure, and how lists are useful for keeping data of different types together in the same data structure. As we approach the end of this course, we'll explore an essential data structure for analysis. In this mission, we'll learn how to deal with tabular data, and the tidyverse's special data structure for tabular data: the tibble.

After you finish this lesson, you will be comfortable working with dataframes and it will be very clear how tibbles will be a criticial component of your data analysis work in R.


  • Learn about tabular data, tibbles, and dataframes.
  • Learn about piping with the %>% operator.
  • Learn to use tibble columns as vectors.

Mission Outline

  1. Introduction
  2. Getting Familiar with the Data
  3. Selecting Columns
  4. Filtering Rows
  5. Piping with the %>% Operator
  6. Creating New Columns
  7. Sorting Data
  8. Summarizing Data
  9. Using Tibble Columns as Vectors
  10. Next Steps

Course Info:


This course requires a Basic subscription and includes four missions and one guided project.  It is the second course in the Data Analyst in R learning path.


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