MISSION 339

Working With Vectorized Functions

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

Objectives

  • 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

intermediate-r-programming

Course Info:

Intermediate R Programming

Intermediate

The median completion time for this course is 6.4 hours.

This course is free. This course includes five missions. This course is the second course in the Data Analyst in R path.

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