Introduction: What is R?

The goal of our first meeting with R is to:

R is a language

  • … with a vocabulary and syntax:

    • verbs (functions)
    • objects (digital information boxes)
    • syntax (what you must say first and last, how you separate expressions)
    • synonyms

  • … with dialects

    • base-R (standard): the original and basic language. This comes with R.
    • tidyverse: particularly useful for preparing (cleaning) data. This comes in “packages”.
    • ggplot: for graphical representation

You don’t need to memorize words, and you can say things in many different ways. Soon you will find your own style!

R is an open-source statistical program

  • versatile and updated, but messy

  • facilitated for documentable analyses

    • for yourself
    • for sharing
    • to make things easy

Our first meeting

We start by clicking on the correct icon. We will open RStudio, not R.

Now we have three windows open: R console, the environment, and the window where we see our figures. We will initially ignore the last two windows.

Dialog in the console

We start with the “console”. This is a window for direct communication to R. In the future, you will only use this for minor things.

Now we can begin the dialog!

Imitation Game It takes place by me stating what I’m going to say in “quotation marks”. R repeats after me but performs no operations itself.

"Hi!"
## [1] "Hi!"

Dialog - calculator I can use R as a calculator. Then I ask, and R answers.

2+2
## [1] 4

R is familiar with most mathematical operations and practically resembles your pocket calculator (if you still remember it).

Don’t smile, don’t laugh We can ask R to ignore what we say with #.

# ignore this

It is useful when we document our codes.

Dialog via the notepad (script)

We have a better workflow when we use an R script. We open a new script through the “File” menu or by pressing “ctrl+shift+N”. We save through the file menu with the extension “.R”: script.R

We write on the notepad before we “send” the code down to R. We can do this by * highlighting the text and pressing “Run” (top right) * “ctrl+Enter”

Now we can continue our dialog.

Objects

We can save information in objects. These are digital storage boxes. If we don’t save information in objects, it is lost!

Here is the object two.

two <- 2

Synonyms We put information in the storage box (object) with an arrow into the object (<-) or with an equals sign (=).

two = 2; two <- 2

When we save information in an object, R does not give the answer in the console but places it directly in the object.

We can check what is in the object.

two
## [1] 2

Perform calculation operations on the object

two+2
## [1] 4

Overwrite the object (NB: you always overwrite; there is nothing called “updating” an object).

two <- 3
two
## [1] 3

Create a new object.

three <- 3

Perform operations on two objects.

two+three
## [1] 6

Save in a third object.

five <- two+three

Why objects?

R is an object-oriented language. We save all information in objects located in our workspace (in short-term memory when RStudio is open).

Examples of objects:

  • data matrices
  • model results
  • figures
  • variables/vectors

Guessing Game (more dialog)

Is it true? We can ask R if something is true

five == 5
## [1] FALSE

Negation Is the object not equal to 5?

five != 5
## [1] TRUE

Sizes Is five more than 6?

five > 6
## [1] FALSE

Equal to or more than?

five >= 6
## [1] TRUE

Multiple conditions Is five less than 6 and more than 0?

five < 6 & five > 0
## [1] FALSE

Is five more than 6 or less than 0?

five >= 6 | five > 0
## [1] TRUE

When you use “or,” it is wise to pack things in parentheses. Then you can combine both “and” and “or” in the same condition. It identifies several groups/subgroups.

Why is this useful?

This is golden when we check and recode data.

Conditional recoding Let’s correct our object by giving R a condition.

if(five != 5){
  five <- 5
}

#Check what happened
five
## [1] 5

Now it’s your turn!

Use the table below and play around!