In slides, a command (we’ll also call them code or a code chunk) will look like this

class(3)

[1] "numeric"

And then directly after it, will be the output of the code.
So class(3) is the code chunk and ‘[1] “numeric”’ is the output.

Send code to run in the console:

• Run the whole chunk with the green play button (top right of the chunk)
• Run single line with ⌘+return or ctrl+return

2 + 2

[1] 4

2 * 4

[1] 8

2^3

[1] 8

Note: when you enter your command in the Console, R inherently thinks you want to print the result.

• The R console is a full calculator
• Try to play around with it:
  • +, -, /, * are add, subtract, divide and multiply
  • ^ or ** is power
  • parentheses – ( and ) – work with order of operations
  • %% finds the remainder

2 + (2 * 3)^2

[1] 38

(1 + 3) / 2 + 45

[1] 47

6 / 2 * (1 + 2)

[1] 9

Try evaluating the following:

• 2 + 2 * 3 / 4 -3
• 2 * 3 / 4 * 2
• 2^4 - 1

# creates a comment in R code

# this is a comment

# nothing to its right is evaluated

# this # is still a comment
### you can use many #'s as you want

1 + 2 # Can be the right of code

[1] 3

In an .Rmd file, you can write notes outside the R chunks.

• You can create objects from within the R environment and from files on your computer
• R uses <- to assign values to an object name (you might also see = used, but this is not best practice)

x <- 2
x

[1] 2

x * 4

[1] 8

x + 2

[1] 4

• The most comfortable and familiar class/data type for many of you will be data.frame
• You can think of these as essentially spreadsheets with rows (usually subjects or observations) and columns (usually variables)
• data.frames are somewhat advanced objects in R; we will start with simpler objects

• Here we introduce “1 dimensional” classes; often referred to as ‘vectors’
• Vectors can have multiple sets of observations, but each observation has to be the same class.
• Use the class() function to check the class of an object.

class(x)

[1] "numeric"

y <- "hello world!"
class(y)

[1] "character"

We will talk in-depth about classes. For now:

numeric

• Numbers
• No quotation marks

2

character

• Text with quotation marks
• Green lettering (default)

"hello!"

Object names are case-sensitive, i.e., X and x are different

x

[1] 2

X

Error in eval(expr, envir, enclos): object 'X' not found

Commas separate objects in R, so they shouldn’t be used when entering big numbers.

z <- 3,000

Error: <text>:1:7: unexpected ','
1: z <- 3,
          ^

10 / 

Error: <text>:2:0: unexpected end of input
1: 10 / 
   ^

+ indicates an incomplete statement. Hit “esc” to clear and bring back the >.

Try assigning your full name to an R object called name

Try assigning your full name to an R object called name

name <- "Ava Hoffman"
name

[1] "Ava Hoffman"

The function c() collects/combines/joins single R objects into a vector of R objects. It is mostly used for creating vectors of numbers, character strings, and other data types.

x <- c(1, 4, 6, 8)
x

[1] 1 4 6 8

class(x)

[1] "numeric"

Try assigning your first and last name as 2 separate character strings into a single vector called name2

Try assigning your first and last name as 2 separate character strings into a length-2 vector called name2

name2 <- c("Ava", "Hoffman")
name2

[1] "Ava"     "Hoffman"

• The contents you give to an R function are called “arguments”
• Here, R assumes all arguments should be objects contained in the vector
• We will talk more about arguments as we use more complicated functions!

name2 <- c("Ava", "Hoffman")
# Arg 1    ^^^^^

name2 <- c("Ava", "Hoffman")
# Arg 2           ^^^^^^^^^

length(): Get or set the length of vectors (including lists) and factors, and of any other R object for which a method has been defined.

length(x)

[1] 4

y

[1] "hello world!"

length(y)

[1] 1

What do you expect for the length of the name object? What about the name2 object?

What are the lengths of each?

What do you expect for the length of the name object? What about the name2 object?

What are the lengths of each?

length(name)

[1] 1

length(name2)

[1] 2

You can perform functions to entire vectors of numbers very easily.

x + 2

[1]  3  6  8 10

x * 3

[1]  3 12 18 24

x + c(1, 2, 3, 4)

[1]  2  6  9 12

• Assign values to objects with <- (new name on left side)
• class() tells you the class (kind) of object
• Use the c() function to combine text/numbers/etc. into a vector
• Use the length() function to determine number of elements

💻 Lab

RStudio

• The Editor is for static code like scripts or R Markdown documents
  
• Send code to the Console to run it
  
• The Console can be used for quickly testing code on the fly
  
• R code goes within what is called a chunk (the gray box with a green play button)

📃RStudio Cheatsheet

Basic R

• Use c() to combine vectors
  
• Use <- to save (assign) values to objects
  
• if you don’t use <- to reassign objects that you want to modify, they will stay the same
  
• length() and class() tell you information about an object

You can perform functions to entire vectors of numbers very easily.

x + 2

[1]  3  6  8 10

x * 3

[1]  3 12 18 24

x + c(1, 2, 3, 4)

[1]  2  6  9 12

But things like algebra can only be performed on numbers.

name2 + 4

Error in name2 + 4: non-numeric argument to binary operator

Save these modified vectors as a new vector called y.

y <- x + c(1, 2, 3, 4)
y

[1]  2  6  9 12

Note that the R object y is no longer “hello world!” - It has been overwritten by assigning new data to the same name.

Reassigning allows you to make changes “in place”

# results not stored:
x + c(1, 2, 3, 4)

# x remains unchanged, results stored in `y`:
y <- x + c(1, 2, 3, 4)

# replace `x` in place
x <- x + c(1, 2, 3, 4)

You can get more attributes than just class. The function str() gives you the structure of the object.

str(x)

 num [1:4] 1 4 6 8

str(y)

 num [1:4] 2 6 9 12

This tells you that x is a numeric vector and tells you the length.

• Reassigning allows you to make changes “in place”
• str() tells you a lot of information about an object in your environment

💻 Lab

For numeric: seq() can be very useful- both integer and double.
The from argument says what number to start on.
The to argument says what number to not go above.
The by argument says how much to increment by.
The length.out argument says how long the vector should be overall.

seq(from = 0, to = 1, by = 0.2)

[1] 0.0 0.2 0.4 0.6 0.8 1.0

seq(from = 0, to = 10, by = 1)

 [1]  0  1  2  3  4  5  6  7  8  9 10

seq(from = -5, to = 5, length.out = 10)

 [1] -5.0000000 -3.8888889 -2.7777778 -1.6666667 -0.5555556  0.5555556
 [7]  1.6666667  2.7777778  3.8888889  5.0000000

For character: rep() can create very long vectors. Works for creating character and numeric vectors.

The each argument specifies how many of each item you want repeated. The times argument specifies how many times you want the vector repeated.

rep(WHAT_TO_REPEAT, arguments)

rep(c("black", "white"), each = 3)

[1] "black" "black" "black" "white" "white" "white"

rep(c("black", "white"), times = 3)

[1] "black" "white" "black" "white" "black" "white"

rep(c("black", "white"), each = 2, times = 2)

[1] "black" "black" "white" "white" "black" "black" "white" "white"

You can use the sample() function to make a random sequence. The x argument specifies what you are sampling from. The size argument specifies how many values there should be. The replace argument specifies if values should be replaced or not.

seq_hun <- seq(from = 0, to = 100, by = 1)
seq_hun

  [1]   0   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17
 [19]  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35
 [37]  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53
 [55]  54  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71
 [73]  72  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89
 [91]  90  91  92  93  94  95  96  97  98  99 100

y <- sample(x = seq_hun, size = 5, replace = TRUE)
y

[1] 60 96 39 14 86

• R functions as a calculator
• Use <- to save (assign) values to objects
• Use c() to combine vectors
• length(), class(), and str() tell you information about an object
• The sequence seq() function helps you create numeric vectors (from,to, by, and length.out arguments)
• The repeat rep() function helps you create vectors with the each and times arguments
• sample() makes random vectors

🏠 Class Website

💻 Basic R Lab

Image by Gerd Altmann from Pixabay