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Applying Functions in R

Chase DeHan

The functional approach to programming is something that makes R unique. In this course you will learn how to leverage the tools in this programming paradigm, such as the apply family of functions, and know how to apply them in the real world

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The functional approach to programming is something that makes R unique. In this course you will learn how to leverage the tools in this programming paradigm, such as the apply family of functions, and know how to apply them in the real world

The functional approach to programming is something that makes R unique and powerful. In this course, Applying Functions in R, you will learn foundational knowledge of functional programming in R. First, you will understand how the apply functions work. Next, you will discover why the functional approach is far superior to for loops in R. Finally, you will explore a multitude of functions that apply in different use cases. When you are finished with this course, you will have the skills and knowledge of using the apply family of functions needed to write clear and concise code without a for loop.

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What's inside

Syllabus

Course Overview
Understanding Functional Programming and Apply
Adding Anonymous Functions to Apply
Using Common Apply Functions
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Using and Understanding Which Function to Use

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Focuses on the functional programming paradigm, specifically the use and application of the apply family of functions in R, Empowering learners to write concise and clear code
Provides a practical understanding of the functional approach, demonstrating its superiority to for loops in R programming
Instructed by Chase DeHan, an expert in R programming, ensuring relevance and industry-aligned insights
Suitable for learners who seek to strengthen their R programming skills and explore functional programming techniques
Assumes a basic understanding of R programming, making it suitable for intermediate learners
May require additional resources for beginners who need a more comprehensive introduction to R programming

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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 Applying Functions in R with these activities:
Review your notes from a previous course on programming in R
Reviewing your notes from a previous course on programming in R will help you refresh your memory and prepare for this course.
Browse courses on R Programming
Show steps
  • Gather your notes from the previous course.
  • Review the notes.
Join a study group for this course
Joining a study group for this course will provide you with an opportunity to discuss the material with other students and get help with any difficult concepts.
Browse courses on Functional Programming
Show steps
  • Find a study group for this course.
  • Attend the study group meetings.
Practice R functions on your own dataset
Practice using R functions on your own dataset will help you solidify your understanding of the functional approach to programming in R.
Browse courses on Functional Programming
Show steps
  • Find a dataset that interests you.
  • Load the dataset into R.
  • Apply various R functions to the dataset.
  • Explore the results of the functions.
Five other activities
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Show all eight activities
Attend a workshop on the functional approach to programming in R
Attending a workshop on the functional approach to programming in R will provide you with an opportunity to learn from experts and get hands-on experience with the concept.
Browse courses on Functional Programming
Show steps
  • Find a workshop on the functional approach to programming in R.
  • Attend the workshop.
Complete the R for Data Science Specialization on Coursera
Completing the R for Data Science Specialization on Coursera will provide you with a comprehensive understanding of the functional approach to programming in R.
Browse courses on Functional Programming
Show steps
  • Enroll in the R for Data Science Specialization on Coursera.
  • Complete the courses in the specialization.
  • Apply what you learn in the specialization to your own projects.
Write a blog post about the functional approach to programming in R
Writing a blog post about the functional approach to programming in R will help you solidify your understanding of the concept and share your knowledge with others.
Browse courses on Functional Programming
Show steps
  • Choose a topic for your blog post.
  • Research the topic.
  • Write the blog post.
  • Publish the blog post.
Create a data visualization using the functional approach to programming in R
Creating a data visualization using the functional approach to programming in R will help you apply your knowledge of the concept to a real-world problem.
Browse courses on Functional Programming
Show steps
  • Choose a dataset for your visualization.
  • Load the dataset into R.
  • Apply the functional approach to programming to create your visualization.
  • Interpret your visualization.
Build a small R package that implements the functional approach to programming
Building a small R package that implements the functional approach to programming will allow you to demonstrate your understanding of the concept and contribute to the R community.
Browse courses on Functional Programming
Show steps
  • Choose a topic for your package.
  • Design the package.
  • Implement the package.
  • Test the package.
  • Publish the package to CRAN.

Career center

Learners who complete Applying Functions in R will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. Functional programming in R can be an extremely valuable skill for those in this role, as it allows for efficient and concise data analysis. This course can help data analysts develop the skills necessary to leverage R's apply functions and other functional programming tools to streamline their work.
See salaries and explore the career path for Data Analyst
Statistician
Statisticians use mathematical and statistical methods to collect, analyze, interpret, and present data. The functional programming approach in R is highly valuable in statistics, as it allows for the efficient manipulation and analysis of large datasets. This course can help statisticians build a strong foundation in functional programming in R, enabling them to develop more efficient and effective statistical models.
See salaries and explore the career path for Statistician
Research Scientist
Research scientists conduct scientific research to advance knowledge in various fields. Functional programming in R is increasingly used in scientific research, as it provides a powerful and flexible framework for data analysis and modeling. This course can help research scientists develop the skills needed to leverage R's functional programming capabilities to enhance their research.
See salaries and explore the career path for Research Scientist
Software Engineer
Software engineers design, develop, and maintain software systems. Functional programming is a fundamental concept in software engineering, and R is a popular language for developing statistical and data analysis software. This course can help software engineers build a solid understanding of functional programming in R, enabling them to create more efficient and maintainable software.
See salaries and explore the career path for Software Engineer
Data Engineer
Data engineers design, build, and maintain data pipelines and infrastructure. Functional programming is becoming increasingly important in data engineering, as it allows for the efficient and scalable processing of large datasets. This course can help data engineers develop the skills needed to apply functional programming in R to build robust and efficient data pipelines.
See salaries and explore the career path for Data Engineer
Quantitative Analyst
Quantitative analysts use mathematical and statistical models to analyze financial data and make investment decisions. Functional programming in R is widely used in quantitative finance, as it provides a powerful and flexible framework for developing and backtesting financial models. This course can help quantitative analysts build a strong foundation in functional programming in R, enabling them to develop more sophisticated and effective financial models.
See salaries and explore the career path for Quantitative Analyst
Machine Learning Engineer
Machine learning engineers design, develop, and deploy machine learning models. Functional programming is gaining popularity in machine learning, as it provides a natural and concise way to express complex machine learning algorithms. This course can help machine learning engineers build a solid understanding of functional programming in R, enabling them to develop more efficient and maintainable machine learning models.
See salaries and explore the career path for Machine Learning Engineer
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. Functional programming in R can be a valuable skill for actuaries, as it allows for the efficient and accurate calculation of risk metrics. This course can help actuaries develop the skills needed to leverage R's functional programming capabilities to enhance their risk assessment and modeling work.
See salaries and explore the career path for Actuary
Biostatistician
Biostatisticians apply statistical methods to analyze biological and medical data. Functional programming in R is becoming increasingly popular in biostatistics, as it provides a powerful and flexible framework for analyzing complex biological and medical datasets. This course can help biostatisticians build a strong foundation in functional programming in R, enabling them to develop more efficient and effective statistical models for biomedical research.
See salaries and explore the career path for Biostatistician
Financial Analyst
Financial analysts use financial data to make investment recommendations. Functional programming in R can be a valuable skill for financial analysts, as it allows for the efficient and accurate analysis of financial data. This course can help financial analysts develop the skills needed to leverage R's functional programming capabilities to enhance their financial analysis and modeling work.
See salaries and explore the career path for Financial Analyst
Market Researcher
Market researchers conduct research to understand consumer behavior and market trends. Functional programming in R can be a valuable skill for market researchers, as it allows for the efficient and accurate analysis of market research data. This course can help market researchers develop the skills needed to leverage R's functional programming capabilities to gain valuable insights from market research data.
See salaries and explore the career path for Market Researcher
Operations Research Analyst
Operations research analysts use mathematical and statistical methods to improve the efficiency of business operations. Functional programming in R can be a valuable skill for operations research analysts, as it allows for the efficient and accurate modeling of business processes. This course can help operations research analysts develop the skills needed to leverage R's functional programming capabilities to develop more effective and efficient business models.
See salaries and explore the career path for Operations Research Analyst
Risk Manager
Risk managers identify, assess, and manage risks. Functional programming in R can be a valuable skill for risk managers, as it allows for the efficient and accurate analysis of risk data. This course can help risk managers develop the skills needed to leverage R's functional programming capabilities to enhance their risk management practices.
See salaries and explore the career path for Risk Manager
Data Scientist
Data scientists use scientific methods to extract knowledge from data. Functional programming is a fundamental concept in data science, and R is a popular language for data analysis and modeling. This course can help data scientists build a strong foundation in functional programming in R, enabling them to develop more efficient and effective data science solutions.
See salaries and explore the career path for Data Scientist
Economist
Economists study the production, distribution, and consumption of goods and services. Functional programming in R can be a valuable skill for economists, as it allows for the efficient and accurate analysis of economic data. This course can help economists develop the skills needed to leverage R's functional programming capabilities to enhance their economic analysis and modeling work.
See salaries and explore the career path for Economist

Reading list

We've selected ten 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 Applying Functions in R.
Cover image
R for Data Science
Save
Provides a comprehensive introduction to the R programming language, with a focus on data science applications. It covers a wide range of topics, including data manipulation, visualization, and statistical modeling.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$
Cover image
The Art of Machine Learning
Save
Provides a comprehensive introduction to the R programming language, with a focus on programming principles and best practices.
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 Packages
Save
Provides an in-depth look at the advanced features of the R programming language, including topics such as functional programming, object-oriented programming, and high-performance computing.
R Packages
Paperback
Check
R Packages
Kindle Edition
Check
Cover image
R Programming for Data Science
Save
Provides a comprehensive introduction to the R programming language, with a focus on data science applications. It covers a wide range of topics, including data manipulation, visualization, and statistical modeling.
R Programming for Data Science
Paperback
$$
Cover image
The R Book
Save
Comprehensive reference guide to the R programming language, covering a wide range of topics, including data manipulation, visualization, and statistical modeling.
The R Book
Hardcover
$$$
The R Book
Kindle Edition
$$$
Cover image
Modern Data Visualization with R
Save
Provides a practical introduction to the R programming language, with a focus on data analysis and visualization.
Modern Data Visualization with R
Paperback
Check
Modern Data Visualization with R
Kindle Edition
Check
Cover image
Data Manipulation with R
Save
Provides a comprehensive guide to data manipulation in R, covering a wide range of topics, including data cleaning, transformation, and reshaping.
Data Manipulation with R (Use R!)
Paperback
$$$
Data Manipulation with R (Use R!)
Kindle Edition
$$$
Cover image
R Cookbook
Save
Provides a collection of recipes for solving common problems in R, covering a wide range of topics, including data manipulation, visualization, and statistical modeling.
R Cookbook: Proven Recipes for Data Analysis,...
Paperback
$$$
R Cookbook: Proven Recipes for Data Analysis,...
Kindle Edition
$$$
Cover image
R Graphics Cookbook
Save
Provides a collection of recipes for creating visualizations in R, covering a wide range of topics, including data visualization, statistical graphics, and interactive graphics.
R Graphics Cookbook
Paperback
Check
R Graphics Cookbook
Kindle Edition
Check
Cover image
R for Everyone
Save
Provides a gentle introduction to the R programming language, with a focus on data analysis and visualization.
R for Everyone: Advanced Analytics and Graphics...
Paperback
$$
R for Everyone: Advanced Analytics and Graphics...
Kindle Edition
$$
R for Everyone: Advanced Analytics and Graphics...
Unknown Binding
$$$

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Course image
Time
72 hours
Level
Advanced
Via
Pluralsight
Instructor
Chase DeHan
Language
English
Good to know
Focuses on the functional programming paradigm, specifically the use and application of the apply family of functions in R, Empowering learners to write concise and clear code
Provides a practical understanding of the functional approach, demonstrating its superiority to for loops in R programming
Instructed by Chase DeHan, an expert in R programming, ensuring relevance and industry-aligned insights
Suitable for learners who seek to strengthen their R programming skills and explore functional programming techniques
Assumes a basic understanding of R programming, making it suitable for intermediate learners
May require additional resources for beginners who need a more comprehensive introduction to R programming
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