R for Data Science – 1 Getting started

Getting Started with R

When you type something into the console, R will give you a reply. For example:

2+4

#> [1] 6

As you probably expected, R returned 6.

Note:

You can ignore the [1] you see in the returned value. That’s just R saying that 6 is the 1st value (and only value here) of the output line.

Getting Started with R

R can be used as a calculator.

(59 + 73 + 2) / 3

#> [1] 44.66667

10^(3+1)

#> [1] 10000

Note:

Arithmetic operators are the same as they are in most other computer applications.

Arithmetic operators

Description	Operator
Addition	`+`
Subtraction	`-`
Multiplication	`*`
Division	`/`
Exponentiation	`^ or **`
integer division `10%/%3` is 3	`x %/% y`
modulus (x mod y) `10%%3` is 1	`x %% y`

Exercise 1.1

Use R to calculate the following:

Add 8 to 22 and then multiply the answer by 3
Divide 8 by 2.5 and then divide the answer by 3

Notice

The above calculations do not produce any kind of output that is remembered by R

Creating objects

To store our calculations in R we need to give it a name and tell R to store that as an object.
Assignment operators <- or = can be used to assign a value to an R object, and it is preferable to use <- as = has other uses.

my_obj <- 48

Now that we’ve created this object, R knows all about it and will keep track of it during this current R session
All of the objects you create will be stored in the current workspace and you can view all the objects in your workspace in RStudio by clicking on the Environment tab in the top right-top pane

Creating objects

If you click on the down arrow on the ‘List’ icon in the same pane and change to ‘Grid’ view, RStudio will show you a summary of the objects including
- the type (numeric - it’s a number)
- the length (only one value in this object)
- its ‘physical’ size, and
- its value (48 in this case)

Creating objects

There are many different types of values that you can assign to an object. For example

my_obj2 <- "R is cool"

Here we have created an object called my_obj2 and assigned it a value of R is cool which is a character string.

Note

We have enclosed the string in quotes.
If you forget to use the quotes you will receive an error message.

my_obj2 <- R is cool

#> Error in parse(text = input): <text>:1:14: unexpected symbol
#> 1: my_obj2 <- R is
#>                  ^

Creating objects

Our workspace now contains both objects we’ve created so far with my_obj2 listed as type character.

Creating objects

To change the value of an existing object we simply reassign a new value to it.
For example, to change the value of my_obj2 from "R is cool" to the number 1024

my_obj2 <- 1024

Creating objects

Once we have created a few objects, we can do stuff with our objects.
For example, the following code creates a new object my_obj3 and assigns it the value of my_obj added to my_obj2 which is

my_obj3 <- my_obj + my_obj2
my_obj3

#> [1] 1072

Creating objects

char_obj <- "hello"
char_obj2 <- "world!"
char_obj3 <- char_obj + char_obj2

#> Error in char_obj + char_obj2: non-numeric argument to binary operator

Reading the error message is important in R
This error message is essentially telling you that either one or both of the objects char_obj and char_obj2 is not a number and therefore cannot be added together

Creating objects

Another error message that you’ll get quite a lot when you first start using R is Error: object '**' not found. As an example, take a look at the code below.

my_obj <- 48
my_obj4 <- my_obj + no_obj

#> Error: object 'no_obj' not found

R returns an error message because we haven’t created (defined) the object no_obj yet.
If you check your environment, you’ll see that object my_obj4 has not been created

Naming objects

In R, object names are case sensitive, and a valid object name (syntactic name) consists of a combination of
- (a-z, A-Z), (0-9), (.), (-), and (_)
- An object name cannot start with a number or a hyphen or an underscore and can start with a dot, but it must be followed by a letter

A good programming practice is to use meaningful object names in the codes, and self-explanatory object names increase the readability of the codes
Existing R functions, names, or words (e.g., mean, log, exp, TRUE, c, etc.) should not be used as object names

Exercise 1.2

Create an object called x1 which is the number
Create another object called x2 which is the answer to the sum
Multiply x1 and x2 together and store the object as another object called x3
Subtract from x3 and calculate the 4th root.
The answer should be

Use of brackets

Parentheses ( & ) are used to define arithmetic expressions, and they must be matched; unmatched parentheses will result in errors

((3 + 12)/3 + 8)

#> [1] 13

Using curly brackets { & } do not result in any error but should not be used as they have some specific uses in R, e.g. defining a function

{10 + 2}+ 5

#> [1] 17

The square brackets [ & ] cannot be used in arithmetic expressions

[2 + 7]/3

#> Error in parse(text = input): <text>:1:1: unexpected '['
#> 1: [
#>     ^

R functions

Functions are ready-made pieces of codes.
Some of the mathematical functions in R:

Description	R symbol	Example
square root	sqrt	`sqrt(225)`
natural logarithm	log	`log(50)`
exponential	exp	`exp(3)`
absolute	abs	`abs(-10)`
factorial	factorial	`factorial(6)`
sine function	sin	`sin(25)`
inverse cosine	acos	`acos(-8.67)`

R functions

R has a large collection of built-in functions that are called like this:

function_name(arg1 = val1, arg2 = val2, ...)

Let’s try using sqrt()
- sqrt(25) or sqrt(x = 25) will return a value 5

Note

inputs (called arguments in R) should be within the parentheses ( ) even if there’s no input.
Multiple inputs, if needed, are separated by commas, e.g. fun_name(input1, input2, input3)

Some useful built-in R functions

round(3.567, digits=2)

#> [1] 3.57

floor(3.567)

#> [1] 3

ceiling(3.567)

#> [1] 4

pi   # Not a function, but useful

#> [1] 3.141593

R ignores excess spacing

(1+2)     ^     3

#> [1] 27

    ( 1+  2)    ^ 3

#> [1] 27

Basically, you can put spaces between different values, and you can put as many as you want and R won’t care.
However, if you insert a space within a single value, R will generate an error.

3   .14

#> Error in parse(text = input): <text>:1:5: unexpected numeric constant
#> 1: 3   .14
#>         ^

Commenting codes

R will ignore anything on the same line that follows the # symbol.

# Calculating BMI
weight <- 70 # This is in kg
height <- 1.7 # This is in meter
bmi <- weight / height ^ 2
bmi

#> [1] 24.22145

Exercise 1.3

Why does this code not work?

my_variable <- 10
my_varıable

#> Error: object 'my_varıable' not found

Exercise 1.4

Create an object called myObject and assign it a value between 1 and 100
Add 13 to myObject, making sure the object itself stores the updated value
Is myObject divisible by 2? by 3? by 13? by 21? Use the R code to get the answer.
How many times can 5 fit in myObject?