Working With Vectorized Functions

Build your understanding of the importance of writing vectorized code for making the most of R's functionality.


  • Use vectorized functions for if-else statements.
  • Solve split-apply-combine-problems.
  • Learn best practices for chaining multiple functions together.

Mission Outline

1. R Functions as Alternatives to Loops
2. How Does Vectorization Make Code Faster?
3. A Vectorized Function for If-Else Statements
4. Multiple Cases: Nesting Functions to Chain If-Else Statements
5. Functions for Solving "Split-Apply-Combine" Problems
6. Grouping and Summarizing Data Frames
7. Summarizing a Data Frame by Multiple Variables
8. Chaining Functions Together Using the Pipe Operator
9. Next Steps
10. Takeaways

Course Info:

Intermediate R Programming


The average completion time for this course is 10-hours.

This course is free. This course includes 4 missions and 1 guided project. This course is the 2nd course in the Data Analyst in R path.


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