Challenge Yourself
This lesson contains a series of challenges that require using tidyverse functions in R to process data.
last updated: 03 Sep 2019
Reproducible Science and Programming - Literate Expressive Programming
Automate Workflows Using Loops in R
When you are programming, it can be easy to copy and paste code that works. However this approach is not efficient. Learn how to create for-loops to process multiple files in R.
last updated: 03 Sep 2019
Handle Missing Data in R
Learn how to handle missing data in the R programming language.
last updated: 03 Sep 2019
Use tidyverse group_by and summarise to Manipulate Data in R
Learn how to write pseudocode to plan our your approach to working with data. Then use tidyverse functions including group_by and summarise to implement your plan.
last updated: 03 Sep 2019
Get Started with Clean Coding in R
Learn...
last updated: 03 Sep 2019
Use lapply in R Instead of For Loops to Process .csv files - Efficient Coding in R
Learn how to take code in a for loop and convert it to be used in an apply function. Make your R code more efficient and expressive programming.
last updated: 03 Sep 2019
If Statements, Functions, and For Loops
Learn how to combine if statements, functions and for loops to process sets of text files.
last updated: 03 Sep 2019
Create For Loops
Learn how to write a for loop to process a set of .csv format text files in R.
last updated: 03 Sep 2019
Working with Function Arguments
Learn how to work with function arguments in the R programming language..
last updated: 03 Sep 2019
Get to Know the Function Environment & Function Arguments in R
This lesson introduces the function environment and documenting functions in R. When you run a function intermediate variables are not stored in the global environment. This not only saves memory on your computer but also keeps our environment clean, reducing the risk of conflicting variables.
last updated: 03 Sep 2019
How to Write a Function in R - Automate Your Science
Learn how to write a function in the R programming language.
last updated: 03 Sep 2019
What Could be Improved In this R Code?
last updated: 03 Sep 2019
Write Efficient Scientific Code - the DRY (Don't Repeat Yourself) Principle
This lesson will cover the basic principles of using functions and why they are important.
last updated: 30 Mar 2020
How to Reuse Functions That You Create In Scripts - Source a Function in R
Learn how to source a function in R. Learn how to import functions that are stored in a separate file into a script or R Markdown file.
last updated: 30 Mar 2020
Write Clean Code - Expressive or Literate Programming in R - Data Science for Scientists 101
This lesson covers the basics of clean coding meaning that you ensure that the code that you write is easy for someone else to understand. The lesson will briefly cover style guides, consistent spacing, literate object naming best practices.
last updated: 30 Mar 2020