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Creating a Custom Function in R

Justin Flett

R is a widely used programming language for statistical computing and graphics. This course will teach you the fundamentals of understanding, using and creating your very own custom functions within R.

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R is a widely used programming language for statistical computing and graphics. This course will teach you the fundamentals of understanding, using and creating your very own custom functions within R.

R is a widely used programming language for statistical computing and graphics. In this course, you will learn foundational knowledge of creating your very own custom functions within R. First, you will learn the basics of using and creating simple functions. Next, you will learn how to handle function arguments and how to pass various data structures as arguments to a function. Finally, you will explore lazy evaluation and scoping within R. When you’re finished with this course, you will have the skills and knowledge of R functions needed to create your very own custom functions.

This course is no longer available. Find something similar by browsing:
R Functions Custom Functions Function Arguments Passing Data Structures Lazy Evaluation Scoping

What's inside

Syllabus

Course Overview
Introduction to Functions
Implementing Function Calls
Function Arguments
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Teaches the basics and fundamentals of creating custom functions within R, which is valuable to learners who are new to R
Builds a strong foundation for learners who are new to creating custom functions within R
Strengthens an existing foundation for intermediate learners of R
Develops skills and knowledge in creating custom functions within R, which are core skills for data scientists, statisticians, and analysts
Taught by Justin Flett, an instructor recognized for their work in the R programming language

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Reviews summary

Foundational course on r custom functions

According to students, this course provides a solid foundation in creating custom functions in R. Learners frequently highlight the clear explanations and practical examples, which make complex concepts like scoping digestible. Many agree it is an excellent starting point for beginners, with some noting it demystified R functions for them. However, a few learners with prior R experience found the content too basic, wishing for more advanced techniques or deeper coverage of topics like lazy evaluation. Some also suggested a need for more interactive coding exercises or real-world projects to solidify learning.
Ideal for those new to R functions, less so for experienced users.
"Excellent course! ...Highly recommend for R novices."
"Fantastic for beginners! I had zero experience with R functions and now I feel confident."
"Disappointed. I already know basic R and was looking for more advanced techniques. This course covered only the very basics..."
"For an intermediate user, it might be too basic, but for a true beginner, some concepts might be overwhelming without extra resources."
Offers helpful hands-on examples and practical scenarios.
"The hands-on examples were very helpful for understanding how to implement functions. I particularly enjoyed the practical application scenarios."
"I liked the course's focus on practical function creation. The content on scoping was well-explained."
"The practical exercises really helped. This course is a game-changer for anyone wanting to write cleaner, more efficient R code."
Provides easily understandable concepts for beginners.
"As a beginner to R, I appreciated how the instructor broke down complex concepts into digestible parts."
"Absolutely brilliant! The instructor's teaching style is engaging, making even dry topics like scoping interesting."
"This course effectively teaches the core concepts of creating functions in R. I found the explanations of function arguments and parameter passing very clear."
Could benefit from more real-world projects and coding exercises.
"My only critique is that I wished for more real-world case studies or a project to apply all the concepts learned."
"I think the course could benefit from more interactive coding exercises. Sometimes it felt like just watching videos without enough practice."
"The quizzes were too simple."
Covers foundational topics well but lacks advanced exploration.
"I found the section on lazy evaluation particularly insightful, though it could use a bit more depth for advanced users."
"I agree with others that some of the advanced topics like lazy evaluation felt a bit light. It's a good starting point but don't expect to become an expert solely from this course."
"The course is okay, but I felt some parts were rushed, especially when dealing with different data structures as arguments."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Creating a Custom Function in R with these activities:
Seek Guidance from an Experienced R Programmer
Connecting with an experienced R programmer can provide you with valuable insights, personalized guidance, and support throughout your learning journey.
Show steps
  • Identify potential mentors through professional networks, online forums, or research.
  • Reach out to your chosen mentor and express your interest in seeking guidance.
R Programming Concepts Review
Reviewing R programming concepts will help you refresh your memory and strengthen your understanding of the fundamentals, making it easier to follow along in the course and apply the concepts effectively.
Browse courses on R Programming
Show steps
  • Go through your notes or textbooks from previous courses or online resources covering R programming basics.
  • Work through practice problems or exercises to test your understanding of the concepts.
Follow a Tutorial on Custom Functions in R
Following a tutorial specifically focused on creating custom functions in R will provide you with step-by-step guidance and practical examples, helping you grasp the concepts more efficiently.
Show steps
  • Find a reputable tutorial or online course that covers custom functions in R.
  • Follow the tutorial instructions and complete the exercises provided.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Study Group for R Functions
Joining a study group will provide you with opportunities to collaborate with peers, discuss concepts, and reinforce your understanding through shared learning.
Show steps
  • Find a study group or create one with classmates or fellow learners.
  • Attend regular study sessions and actively participate in discussions.
  • Collaborate on projects or assignments related to custom functions.
Create and Test Custom Functions
Creating and testing custom functions yourself will provide you with hands-on experience and help you solidify your understanding of the concepts covered in the course.
Browse courses on Custom Functions
Show steps
  • Design a simple custom function based on the concepts you have learned.
  • Write the R code for your function.
  • Test your function with different inputs and scenarios.
Write a Blog Post on Custom Functions
Writing a blog post on custom functions will encourage you to synthesize your knowledge, explain the concepts in your own words, and potentially benefit others by sharing your insights.
Show steps
  • Choose a specific aspect of custom functions to focus on.
  • Research and gather information on the topic.
  • Write a well-structured blog post explaining the concepts.
  • Consider sharing your blog post on relevant platforms.
Contribute to Open-Source R Projects
Contributing to open-source R projects will expose you to real-world applications, enhance your problem-solving skills, and provide opportunities to learn from experienced developers.
Show steps
  • Identify open-source R projects that align with your interests and skill level.
  • Review the project's documentation and contribution guidelines.
  • Find an issue or feature to work on and submit a pull request.

Career center

Learners who complete Creating a Custom Function in R will develop knowledge and skills that may be useful to these careers:
Statistician
Statisticians collect, analyze, interpret, and present data. They use statistical methods to develop models that can be used to make predictions about future events. R is a preferred programming language for statistical computing and graphics, and a course on creating custom functions in R can help Statisticians develop the skills they need to succeed in this field.
See salaries and explore the career path for Statistician
Biostatistician
Biostatisticians use statistical methods to analyze data in the field of biology. They use statistical methods to design experiments, analyze data, and to make inferences about biological processes. R is a popular programming language for biostatistics, and a course on creating custom functions in R would provide Biostatisticians with the skills they need to succeed in this field.
See salaries and explore the career path for Biostatistician
Data Scientist
Data Scientists utilize programming languages and software to analyze large data sets. They use statistical methods to identify trends and patterns in data and to make predictions about future events. R is a powerful programming language for data analysis and visualization, making it a valuable tool for Data Scientists. A course that delves into the creation of custom functions in R would be an excellent resource for someone looking to enter this field.
See salaries and explore the career path for Data Scientist
Data Analyst
Data Analysts use data to solve business problems. They use statistical methods to analyze data and to identify trends and patterns. R is a powerful tool for data analysis, and a course on creating custom functions in R would provide Data Analysts with the skills they need to succeed in this field.
See salaries and explore the career path for Data Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They use these models to make investment decisions and to develop trading strategies. R is a widely used programming language in quantitative finance, and a course on creating custom functions in R would provide Quantitative Analysts with the skills they need to succeed in this field.
See salaries and explore the career path for Quantitative Analyst
Research Scientist
Research Scientists conduct scientific research and development. They use statistical methods to analyze data and to develop new theories and models. R is a programming language that is often used in scientific research, and a course on creating custom functions in R would provide Research Scientists with the skills they need to succeed in this field.
See salaries and explore the career path for Research Scientist
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. They use programming languages, such as R, to write code that implements machine learning algorithms. A course on creating custom functions in R would provide Machine Learning Engineers with a deeper understanding of programming fundamentals and best practices, which they can apply to their work.
See salaries and explore the career path for Machine Learning Engineer
Business Analyst
Business Analysts use data to solve business problems. They use statistical methods to analyze data and to identify trends and patterns. R is a powerful tool for business analysis, and a course on creating custom functions in R would provide Business Analysts with the skills they need to succeed in this field.
See salaries and explore the career path for Business Analyst
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. They use these models to develop insurance policies and to set premiums. R is a programming language that is often used in actuarial science, and a course on creating custom functions in R would provide Actuaries with the skills they need to succeed in this field.
See salaries and explore the career path for Actuary
Data Science Manager
Data Science Managers lead teams of data scientists and data analysts. They are responsible for planning and executing data science projects and for ensuring that data science projects are aligned with business goals. A course on creating custom functions in R would provide Data Science Managers with the skills they need to understand the technical aspects of data science projects and to make informed decisions about data science investments.
See salaries and explore the career path for Data Science Manager
Risk Analyst
Risk Analysts use statistical methods to assess risk and uncertainty. They use these models to develop risk management strategies and to make decisions about risk mitigation. R is a programming language that is often used in risk analysis, and a course on creating custom functions in R would provide Risk Analysts with the skills they need to succeed in this field.
See salaries and explore the career path for Risk Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They use these models to develop and improve business processes. R is a widely used programming language in operations research, and a course on creating custom functions in R would provide Operations Research Analysts with the skills they need to succeed in this field.
See salaries and explore the career path for Operations Research Analyst
Financial Analyst
Financial Analysts use financial data to make recommendations about investments and business decisions. They use statistical methods to analyze data and to build models that can be used to predict future financial performance. R is a powerful tool for financial analysis, and a course on creating custom functions in R would provide Financial Analysts with the skills they need to succeed in this field.
See salaries and explore the career path for Financial Analyst
Software Engineer
Software Engineers design, develop, and maintain computer software. They use programming languages, such as R, to write code that implements algorithms and data structures to solve business problems. A course on creating custom functions in R will provide Software Engineers with a deeper understanding of programming fundamentals and best practices, which they can apply to their work.
See salaries and explore the career path for Software Engineer
Data Architect
Data Architects design and implement data management solutions. They use programming languages, such as R, to write code that automates data processing tasks. A course on creating custom functions in R would provide Data Architects with a deeper understanding of programming fundamentals and best practices, which they can apply to their work.
See salaries and explore the career path for Data Architect

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Creating a Custom Function in R.
Cover image
R for Data Science
Save
Provides a comprehensive overview of R, including how to use functions, write your own functions, and handle data structures. It valuable resource for both beginners and experienced R users.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$
Cover image
The R Book
Save
Comprehensive reference for R, covering everything from basic syntax to advanced statistical techniques. It valuable resource for both beginners and experienced R users.
The R Book
Hardcover
$$$
The R Book
Kindle Edition
$$$
Cover image
Modern Data Visualization with R
Save
Provides a practical introduction to R, covering topics such as data manipulation, visualization, and statistical modeling. It valuable resource for both beginners and experienced R users who want to learn more about the language.
Modern Data Visualization with R (Chapman &...
Kindle Edition
$$$
Cover image
Business Analytics
Save
Provides a comprehensive overview of statistical methods using R. It valuable resource for both beginners and experienced statisticians who want to learn more about statistical methods.
Business Analytics
Paperback
$$
Business Analytics
Hardcover
$$$$
Essentials of Business Analytics
Hardcover
$$$
Essentials of Business Analytics
Hardcover
$$$$
Bundle: Business Analytics, Loose-leaf Version, 3rd...
Product Bundle
$$$$
Bundle: Business Analytics, Loose-leaf Version, 3rd...
Product Bundle
$$$$
Business Analytics
Kindle Edition
$$$
Cover image
R Graphics Cookbook
Save
Provides a collection of recipes for creating various types of graphs in R. It valuable resource for both beginners and experienced R users who want to learn more about data visualization.
R Graphics Cookbook: Practical Recipes for...
Paperback
$$$
R Graphics Cookbook: Practical Recipes for...
Paperback
$$
(中文) R Graphics Cookbook: Practical Recipes for...
Paperback
$$
R Graphics Cookbook: Practical Recipes for...
Kindle Edition
$$$
R Graphics Cookbook: Practical Recipes for...
Kindle Edition
$$
Cover image
The Art of Machine Learning
Save
Provides a comprehensive overview of R programming, covering topics such as data manipulation, visualization, and statistical modeling. It valuable resource for both beginners and experienced R users who want to learn more about the language.
The Art of Machine Learning: A Hands-On Guide to...
Paperback
$$
The Art of Machine Learning: A Hands-On Guide to...
Kindle Edition
$$
Cover image
R for Everyone
Save
Provides a gentle introduction to R, covering topics such as data manipulation, visualization, and statistical modeling. It valuable resource for beginners who want to learn more about R.
R for Everyone: Advanced Analytics and Graphics...
Paperback
$$
R for Everyone: Advanced Analytics and Graphics...
Kindle Edition
$$
R for Everyone: Advanced Analytics and Graphics...
Unknown Binding
$$$
Cover image
Money, Language, and Thought
Save
Provides a gentle introduction to R, covering topics such as data manipulation, visualization, and statistical modeling. It valuable resource for beginners who want to learn more about R.
Money, Language, and Thought: Literary and...
Paperback
$$
Money, Language, and Thought: Literary and...
Kindle Edition
$$

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Time
92 hours
Level
Introductory
Via
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Instructor
Justin Flett
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Teaches the basics and fundamentals of creating custom functions within R, which is valuable to learners who are new to R
Builds a strong foundation for learners who are new to creating custom functions within R
Strengthens an existing foundation for intermediate learners of R
Develops skills and knowledge in creating custom functions within R, which are core skills for data scientists, statisticians, and analysts
Taught by Justin Flett, an instructor recognized for their work in the R programming language
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