Basic R

Author
Affiliation
Jubayer Hossain

Founder & Instructor, CHIRAL Bangladesh

Published

May 7, 2023

Agenda

  • Introduction to R
  • Getting Started
  • Variables and Reserved Keywords
  • Data Types in R
  • Operators

Common new users frustrations

  1. Different versions of software
  2. Data type problems (is that a character or a number?)
  3. Working directory problems: trying to read files that R “can’t find”
    • RStudio can help, and so do RStudio Projects
    • discuss in Data Input/Output lecture
  4. Typos (R is case sensitive, x and X are different)
    • RStudio helps with “tab completion”
    • discussed throughout

Explaining output

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

print("Hello World!")
[1] "Hello World!"

And then directly after it, will be the output of the code.
So print("I'm code") is the code chunk and [1] “I’m code” is the output.

R as a calculator

2 + 2
[1] 4
2 * 4
[1] 8
2^3
[1] 8

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

R as a calculator

  • 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

R as a calculator

2 + (2 * 3)^2
[1] 38
(1 + 3) / 2 + 45
[1] 47
6 / 2 * (1 + 2)
[1] 9

Problem gives answer of 1 or 9 depending on calculator.

Problem gives answer of 1 or 9 depending on calculator.

R as a calculator

Try evaluating the following:

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

Commenting in Scripts

# 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.

Assigning values to objects

  • 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)
  • Object names are case-sensitive, i.e. X and x are different
x <- 2
x
[1] 2
x * 4
[1] 8
x + 2
[1] 4

Variables(Identifiers) in R

  • Variables are used to store data, whose value can be changed according to our need.
  • A variable is a name given to a memory location, which is used to store values in a computer program.
  • Variables in R programming can be used to store numbers (real and complex), words, matrices, and even tables.
  • R is a dynamically programmed language which means that unlike other programming languages, we do not have to declare the data type of a variable before we can use it in our program.
  • Unique name given to variable (function and objects as well) is identifier.

Rules for writing Identifiers in R

  • Identifiers can be a combination of letters, digits, period (.) and underscore (_).
  • It must start with a letter or a period. If it starts with a period, it cannot be followed by a digit.
  • It should not start with a number (e.g: 2x)
  • It should not start with a dot followed by a number (e.g: .2x)
  • It should not start with an underscore (e.g: _x)
  • Reserved words in R cannot be used as identifiers(e.g: TRUE, FALSE)

Basically, there are 5 naming conventions - alllowercase: e.g. myname - period.separated: e.g. new.name - underscore_separated: e.g. my_name - lowerCamelCase: e.g. myName - UpperCamelCase: e.g. MyName

Creating Variables

Using equal(=) operator

x = 10

Using leftward(<-) operator

y <- 15

Reserved Keaywords in R

  • Don’t use any reserved keyword as variable name. List all of reserved words in R by using (?Reserved).
?Reserved
starting httpd help server ... done

Entering Input

At the R prompt/console we type expressions.

num <- 10

The <- symbol is the assignment operator. The grammar of the language determines whether an expression is complete or not.

Evaluation

When a complete expression is entered at the R console, it is evaluated and the result of evaluated expression is returned. The result may be auto-printed.

x <- 10
x
[1] 10
x <- 10
print(x)
[1] 10
x <- 10
cat(x)
10

Assigning values to objects

  • 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

Assigning values to 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.
class(x)
[1] "numeric"
y <- "hello world!"
print(y)
[1] "hello world!"
class(y)
[1] "character"

Simple object practice

Try assigning your full name to an R object called name

Simple object practice

Try assigning your full name to an R object called name

name <- "Ava Hoffman"
name
[1] "Ava Hoffman"

The ‘combine’ function

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"

The ‘combine’ function

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

The ‘combine’ function

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"

Arguments inside R functions

  • 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 of R objects

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

length of R objects

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

What are the lengths of each?

length of R objects

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

Math + vector objects

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

Lab Part 1

💻 Lab

Math + vector objects

But things like algebra can only be performed on numbers.

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

Reassigning to a new object

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 to a new object

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)

R objects

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.

R objects

This is handy when we start dealing with bigger / more complex objects.

str(z)
 num [1:100] 2 6 6 12 2 9 9 6 12 6 ...

Comments in R

The # character indicates a comment.

x <- 10 # This is a comment

Anything to the right of the # (inlcuding the # itself) is ignored.
This is only comment character in R.
R does not support multi-line comments or comment block.

Data Types in R

R has five basic data types - character(e.g: ‘abul’, “abul”) - numeric(e.g: 2, 3) - integer(e.g: 5L) - complex(e.g: 5i) - logical(True/False)

Numbers

  • Numbers in R generally treated as numeric objects(i.e. double precision real numbers)
  • If you explicitly want an integer, you need to specify the L suffix.
  • There is also a special number Inf which is represents infinity; e.g. 1 / 0
  • Inf can be used in ordinary calculations; e.g. 1/Inf is 0
  • The value NaN represents an undefined value(“not a number”); e.g. 0/0
  • NaN can also be thought of as a missing value.

The numeric constants are

  • integer(L)
  • double
  • complex(i)

Creating Numeric Objects

# Create numeric object
n <- 5  
# Check type of object
typeof(n)
[1] "double"
# Create an integer type object 
i = 5L 
# Check type of object
typeof(i)
[1] "integer"

Creating Numeric Objects

# Create a double type object 
d = 22
# Check type of object
typeof(d)
[1] "double"
# Create a complex type object 
c = 4i 
# Check type of object
typeof(c)
[1] "complex"

Characters

Character constants can be represented using either single quotes (’’) or double quotes (““) as delimiters.

# Create a character type object 
char = "Hello"
# Check type of object 
typeof(char)
[1] "character"

Atributes

R objects can have attributes

  • names, dimnames
  • dimensions(e.g. matrices, arrays)
  • class
  • length
  • other user-defined attributes/metadata

Attributes of an object can be accessed using the attributes() function.

Built-in Constants in R

pi # value of pi 
[1] 3.141593
LETTERS
 [1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S"
[20] "T" "U" "V" "W" "X" "Y" "Z"
month.name 
 [1] "January"   "February"  "March"     "April"     "May"       "June"     
 [7] "July"      "August"    "September" "October"   "November"  "December"

Operators in R

  • R has many operators to carry out different mathematical and logical operations.
  • Operators in R can mainly be classified into the following categories.
    1. Arithmetic Operators
    2. Relational Operators
    3. Logical Operators
    4. Assignment Operators

Arithmetic Operators

x <- 10 
y <- 2 
# Addition
x+y
[1] 12
# Subtraction
2-5
[1] -3

Arithmetic Operators

# Multiplication
2 * 5 
[1] 10
# Division
2 / 5 
[1] 0.4
# Exponent 
2 ^ 5
[1] 32

Arithmetic Operators

# Modulus(Remainder from division)
2 %% 5
[1] 2
# Integer Division 
2 %/% 5
[1] 0

Logical Operators

# Logical NOT(!)
! TRUE
[1] FALSE
! FALSE   
[1] TRUE

Logical Operators

# Logical AND(&&)
TRUE && TRUE
[1] TRUE
TRUE && FALSE 
[1] FALSE
FALSE && FALSE 
[1] FALSE

Logical Operators

# Logical OR(|)
TRUE | TRUE 
[1] TRUE
TRUE | FALSE 
[1] TRUE
FALSE | FALSE    
[1] FALSE

Relational Operators

x <- 10
y <- 5 
# Equality 
x == y 
[1] FALSE
# Inequality
x != y 
[1] TRUE
# Less Than 
x < y 
[1] FALSE

Relational Operators

# Greater Than 
x > y 
[1] TRUE
# Less or Equal 
x <= y 
[1] FALSE
# Greater or Equal
x >= y 
[1] TRUE

Summary

  • 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

🏠 Class Website

💻 Basic R Lab