Software Development
Applying and Using R Programming Structures
Final Exam: Applying and Using R Programming Structures
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Using R Programming Structures: Functions & Environments
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Using R Programming Structures: Leveraging R with Control Flow & Looping
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Using R Programming Structures: Object Systems
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Final Exam: Applying and Using R Programming Structures
Lesson Objectives
Final Exam: Applying and Using R Programming Structures
- create a reference class that inherits or derives from another reference class
- create custom classes using the class() and attr() functions
- create custom classes using the class() and structure() functions
- create inner nested functions within outer functions
- implement if statements and nested for loops within outer for loops
- implement inner nested functions within outer functions
- implement OOP using reference classes
- implement the use of named arguments to pass in data to functions
- introduce the return function and recall ways of returning data without invoking it
- make use of the ifelse() function to execute conditional operations
- make use of the switch statement to execute conditional operations
- recall how built-in functions can be viewed and new functions created
- recall the functions print() invokes on the type of input argument
- recall the use of R environments as bindings of variable names to values
- recognize how the print() function works based on the S3 object system
- specify default arguments for functions
- specify functions as input arguments to other functions
- use if statements to execute a set of operations only if a condition is satisfied
- use repeat loops to repeat an operation until a break statement is reached
- use while loops to operate while a condition is true
Overview/Description
Final Exam: Applying and Using R Programming Structures will test your knowledge and application of the topics presented throughout the Applying and Using R Programming Structures track of the Skillsoft Aspire Data Analysis with R Journey.
Target
Prerequisites: none
Using R Programming Structures: Functions & Environments
Lesson Objectives
Using R Programming Structures: Functions & Environments
- discover the key concepts covered in this course
- recall how built-in functions can be viewed and new functions created
- introduce the return function and recall ways of returning data without invoking it
- implement the use of named arguments to pass in data to functions
- specify default arguments for functions
- specify functions as input arguments to other functions
- use functions with switch statements and store functions in other data structures
- recall the use of R environments as bindings of variable names to values
- create inner nested functions within outer functions
- recognize the nested environments created by default within a function
- implement closures, which include the environment, body, and input arguments to a function
- create and use replacement functions to specify functions that can be l-values
- summarize the key concepts covered in this course
Overview/Description
R supports several powerful features, such as first-class functions, functions on the left-hand side of an assignment, and explicit environment objects that bind variables to values. Taken together, these make R a powerful language for functional programming. This course will show you how to work effectively with functions in R. Specifically, you'll learn how to create and invoke functions in R and leverage R support for functional programming and first-class functions. You'll recognize how an R environment is a virtual binding between variable names and values. You'll create nested environments and leverage the fact that individual functions have their own local environments. You'll also create and invoke closures as well as replacement functions. By the end of the course, you'll have the confidence to work with functions in your R programming projects.
R supports several powerful features, such as first-class functions, functions on the left-hand side of an assignment, and explicit environment objects that bind variables to values. Taken together, these make R a powerful language for functional programming. This course will show you how to work effectively with functions in R. Specifically, you'll learn how to create and invoke functions in R and leverage R support for functional programming and first-class functions. You'll recognize how an R environment is a virtual binding between variable names and values. You'll create nested environments and leverage the fact that individual functions have their own local environments. You'll also create and invoke closures as well as replacement functions. By the end of the course, you'll have the confidence to work with functions in your R programming projects.
Target
Prerequisites: none
Using R Programming Structures: Leveraging R with Control Flow & Looping
Lesson Objectives
Using R Programming Structures: Leveraging R with Control Flow & Looping
- discover the key concepts covered in this course
- use if statements to execute a set of operations only if a condition is satisfied
- make use of the ifelse() function and the switch statement to execute conditional operations
- recall how for loops can be used to iterate over a vector of values
- iterate over recursive lists and two-dimensional matrices using for loops
- implement if statements and nested for loops within outer for loops
- use while loops to perform an operation while a condition is true
- use repeat loops to repeat an operation until a break statement is reached
- use the sapply(), vapply(), and tapply() functions to apply functions to elements in vectors
- summarize the key concepts covered in this course
Overview/Description
Becoming adept at using R will form a valuable part of your statistical data analysis programming language toolkit. Achieving this involves learning how to utilize the functional programming structures of R. This course shows how to use conditional constructs, statements, looping, and functions effectively in R. You'll practice using if, else, and the ifelse functions and the switch construct. You'll work with for and while loops. Recognize the next and break statements in R. And examine the repeat loop, which does not have a condition at all and must be used with a break statement. You'll then move on to advanced looping using the vapply(), lapply(), and sapply() functions in R. By the end of this course, you'll be able to use f R for control flow and looping.
Becoming adept at using R will form a valuable part of your statistical data analysis programming language toolkit. Achieving this involves learning how to utilize the functional programming structures of R. This course shows how to use conditional constructs, statements, looping, and functions effectively in R. You'll practice using if, else, and the ifelse functions and the switch construct. You'll work with for and while loops. Recognize the next and break statements in R. And examine the repeat loop, which does not have a condition at all and must be used with a break statement. You'll then move on to advanced looping using the vapply(), lapply(), and sapply() functions in R. By the end of this course, you'll be able to use f R for control flow and looping.
Target
Prerequisites: none
Using R Programming Structures: Object Systems
Lesson Objectives
Using R Programming Structures: Object Systems
- discover the key concepts covered in this course
- recognize how the print() function works based on the S3 object system
- recall the functions print() invokes based on the type of input argument
- create custom classes using the class(), attr(), and structure() functions
- extend the print functionality to work with custom classes
- implement OOP using reference classes
- create an R5 reference class with various member variables and member functions
- create a reference class that inherits or derives from another reference class
- summarize the key concepts covered in this course
Overview/Description
R supports not one but multiple alternative object-oriented programming paradigms. These are known as object systems and constitute a relatively underutilized but incredibly powerful feature of the R language. This course will show you how to work effectively with object systems in R. You'll begin by identifying different object systems. You'll then examine how the S3 object system allows some features of object-oriented programming, albeit in a very different form from other OOP languages. You'll move to leverage the R5 object system, also known as the system of reference classes, to create classes and instantiate objects, specify member variables and methods, and initialize values of member functions. You'll also implement inheritance using the system of reference classes. When you're done with this course, you'll be able to utilize different object systems in your R programming projects.
R supports not one but multiple alternative object-oriented programming paradigms. These are known as object systems and constitute a relatively underutilized but incredibly powerful feature of the R language. This course will show you how to work effectively with object systems in R. You'll begin by identifying different object systems. You'll then examine how the S3 object system allows some features of object-oriented programming, albeit in a very different form from other OOP languages. You'll move to leverage the R5 object system, also known as the system of reference classes, to create classes and instantiate objects, specify member variables and methods, and initialize values of member functions. You'll also implement inheritance using the system of reference classes. When you're done with this course, you'll be able to utilize different object systems in your R programming projects.
Target
Prerequisites: none
