R Programming Intermediate: Control Flow and Conditional Statements

Name: R Programming Intermediate: Control Flow and Conditional Statements
Author: Tom Rosenwinkel

Use conditional statements to write R functions with control flow and subset data structures

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Course: On-Demand

Hello, my name is Tom Rosenwinkle. In this series of lessons, we are going to learn conditional statements and control flow in R. We are going to review the basic data structures and data types in R as well as functional programming concepts, and we will see how conditional statements and control flow can relate with functional programming concepts, including subsetting data structures. I'm working in RStudio. Remember that one of the first things that is important to do when working in R is to set the working directory to be where you expect, in case you are going to source any of the files from your directory. In these lessons, I'm mostly going to be sourcing one line at a time using RStudio. Remember also that if you need a package in R, you need to run an install.packages command in order to find and install the package. RStudio has some functionality that will find the package and run that install.packages command. And then to source the package, you need to run the library command. RStudio also has functionality to help with that. For this lesson, on names in R, I'm using the object address function from this LOBSTER package or LOBSTER. So when I assign the name X to the vector 1, 2, 3, I can check the address for where the name X is pointing or referring. This is the address for the vector 1, 2, 3. Notice I say that with this assignment operator, I assigned the name X to the vector rather than the other way around, which is also common when people speak about R. But I do it that way because if I change one component of the vector X and look at the address of X, I see actually that now there's a different address here and that's because that is the address of the vector 3, 2, 3, not the vector 1, 2, 3, anymore. These vectors have the same place on my machine and the name has changed to point to the new vector. I can assign a second name to this vector and now X and Y have the same address. And if I modify one component of X, then the address of X has changed and the address of Y is still the same vector 3, 2, 3. When I remove the name Y, I can see that X has the same address and that Y does not have an address anymore. And I can change one component of X another time to see that the name has now a new address for the vector 11, 2, 3. This behavior in R is called copy on modify and it's important to know as we start to look at scalable R code because we should remember that when we modify a component within a vector, usually the copy on modify behavior is happening behind the scenes on the machine, which could take up some extra memory. I can remove the name X and I can also run a function called the garbage collector that frees up that space. Now the garbage collector is actually run at many times during our workflows behind the scenes and we don't even often have to know when that garbage collector is run, but if we ever have doubt and need to run the garbage collector, we can run it as the function GC. In the next lesson, we will look more at the basic data types and vectors in R. Thank you for watching.

Intermediate Provider : Tom Rosenwinkel 7 Lessons · 41m in English

Course Description

How can you explore the data types and structures in R, or change them as needed? How can you control the flow of your R code, or the structure of your data subsets? Data types, object attributes, and conditional statements are foundational in R. Learning how to create the right conditional statements for control flow and data subsetting is an essential skill for any R programmer. The topics discussed in these lessons will build on your understanding of the R language and form a foundation for vectorization, scaling functional programming, and class concepts.

In these lessons, you will learn how to write R functions with conditional control flow. We will explore the base data structures in R including class properties and attributes, along with functional programming concepts. By the end of these lessons, you will be able to write conditional statements and apply them to control flow and to subset data structures.

What You'll Learn

Understand the base data types, class attributes, and structures in R
Write R functions with conditional control flow
Apply functional programming concepts to organize and control R code flow
Use logical conditions and operators to build conditional statements
Apply conditional statements to subset R data structures
Explore base data structures in R including class properties and attributes

Key Takeaways

Data types, object attributes, and conditional statements are foundational concepts in R.
Creating the right conditional statements for control flow and data subsetting is an essential skill for any R programmer.
These topics build a foundation for vectorization, scaling functional programming, and class concepts.
By the end of the lessons, learners can write conditional statements and apply them to control flow and to subset data structures.
The course reviews names, vectors, attributes, and subsetting alongside logical conditions and functions.

Frequently Asked Questions

Who is this course for?

It is intended for R programmers looking to build on their understanding of the R language, covering foundational concepts like data types, object attributes, and conditional statements.

What topics does this course cover?

It covers base data types, class attributes and structures in R, logical conditions and operators, conditional control flow, functions, functional programming concepts, and subsetting. Lessons include Review of Names, Review of Vectors, Review of Attributes for Common Structures, Logical Conditions and Operators, Conditional Control Flow, Functions, and Review of Subsetting.

What skills will I gain?

You will gain skills in writing conditional statements and data infrastructure, applying conditional statements to control flow and to subset data structures.

What will I be able to do by the end?

By the end of these lessons, you will be able to write conditional statements and apply them to control flow and to subset data structures.

How does this course fit into a broader R learning path?

The topics build on your understanding of the R language and form a foundation for vectorization, scaling functional programming, and class concepts.