Created by Silvie Cinková
powerful data analysis and in addition functionalities of general-purpose programming languages such as Python
A few data sets are "stored" in R's packages and used over and over when explaining functions or concepts
Some examples:
To see more of them and learn what they describe, type into the RStudio console datasets:: and pres tab. A roll-up menu appears with the individual datasets. Some more data sets can be part of other packages.
... and some others, not important here
https://campus.datacamp.com/courses/free-introduction-to-r/chapter-1-intro-to-basics-1?ex=1
https://campus.datacamp.com/courses/intermediate-r/chapter-3-functions?ex=1
https://campus.datacamp.com/courses/free-introduction-to-r/chapter-2-vectors-2?ex=1
https://campus.datacamp.com/courses/free-introduction-to-r/chapter-6-lists?ex=1
https://campus.datacamp.com/courses/free-introduction-to-r/chapter-4-factors-4?ex=1
https://campus.datacamp.com/courses/free-introduction-to-r/chapter-4-factors-4?ex=1
https://campus.datacamp.com/courses/free-introduction-to-r/chapter-3-matrices-3?ex=1
if statementhttps://campus.datacamp.com/courses/intermediate-r/chapter-1-conditionals-and-control-flow?ex=1
https://campus.datacamp.com/courses/intermediate-r/chapter-2-loops?ex=1
Much faster and r-borne option to loops. All elements are handled simultaneously.
Very good, but can be somewhat difficult. Also they very often change the data type (e.g. data frame to matrix) and one has to "repair" the processed object afterwards.
https://campus.datacamp.com/courses/intermediate-r/chapter-4-the-apply-family?ex=1
Extremely fast and does not change data structures of the elements, like apply functions sometimes do.
Only learn when you already know very well how to use lists!!!!
tidy data: each variable in one column, each observation in one row
These libraries usually use functions from other R libraries.
Some are written in other programming languages like C++, so you won't understand their code. but they work in R.