For now, we will be working in the Console (Pane 1 )

• 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

Try evaluating the following. Type these in the Console and press return to evaluate:

• 2 + 2
• 2 * 3 / 4
• 2^4 - 1

Object - an object is something that can be worked with or on in R - can be lots of different things!

You can think of objects as nouns in R.

• a variable
• a dataset
• a plot

… many more

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

x <- 2
x

[1] 2

x * 4

[1] 8

x + 2

[1] 4

A. Something I can touch

B. Something that can be worked with in R

C. A software version

Create objects with text using quotation marks:

y <- "hello world!"
y

[1] "hello world!"

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"

Use c() to collect/combine single R objects into a vector of R objects. It is mostly used for creating vectors of numbers and character strings.

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

[1] 1 4 6 8

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

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

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

[1] "Ava"     "Hoffman"

Function - a function is a piece of code that allows you to do something in R. You can write your own, use functions that come directly from installing R, or use functions from additional packages.

You can think of a function as verb in R.

A function might help you add numbers together, create a plot, or organize your data.

• class() tells us what kind of values the object contains (numeric, character, etc)
• length() tells us how many elements.

name

[1] "Ava Hoffman"

class(name)

[1] "character"

x

[1] 1 4 6 8

length(x)

[1] 4

A. a number or text

B. a button inside RStudio

C. code that does something

It’s fine to combine vectors, but all values will end up with the same class!

vect <- c(name, x)
vect

[1] "Ava Hoffman" "1"           "4"           "6"           "8"          

class(vect)

[1] "character"

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

What is the class?

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

What is the class?

length(name2)

[1] 2

class(name2)

[1] "character"

# creates a comment in R code

# 1 + 2 <- this does not get run

1 + 2 # <- this does

[1] 3

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

Just open up the file to see the questions for lab. More about the file type soon!

💻 Lab

You can perform math with vectors.

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 math 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.

Argument - what you pass to a function

• can be data like the number 1 or 20234
• can be options about how you want the function to work
• separated by commas

Like an adverb.

For numeric: seq()

• 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] 66 99 94 92  4

Some functions and data come with R right out of the box (“base R”). We will add more functionality with packages. Think of these like “expansion packs” for R.

Must be done once for each installation of R (e.g., version 4.2 >> 4.3).

An important package we will use is tidyverse. It is a mega-package great for data import, wrangling, and visualization.

install.packages("tidyverse")

After installing packages, you will need to “load” them into memory so that you can use them.

This must be done every time you start R.

We use a function called library to load packages.

library(tidyverse)

• R functions as a calculator
• Use <- to save (assign) values to objects. Reassigning allows you to make changes “in place”.
• Use c() to combine into 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
• install.packages() and library() install and load packages, respectively.

🏠 Class Website

💻 Basic R Lab

📃 Day 1 Cheatsheet

Image by Gerd Altmann from Pixabay