Part II: R Fundamentals

Before starting, here are some Official manuals and books we will be learning from :

R as a calculator

The best way to get used to R is to use it as a calculator.

You can start by using the R console and doing simple operations.

Basic arithmetic operations

Addition

3+5
#> [1] 8

Subtraction

143-12
#> [1] 131

Multiplication

4*5
#> [1] 20

Division

180/23
#> [1] 7.826087

Exponientiation

4^2
#> [1] 16

Arithmetic Functions

this functions may be useful to replace your calculator

Absolute value

abs(-23)
#> [1] 23

Square root

sqrt(16)
#> [1] 4

Remainder/modulo

7 %% 3
#> [1] 1

Logarithms and exponentials i.e,

\[\log_a b = c,\quad ln_e b=a , \quad e^{a}=b\]

log2(4)
#> [1] 2
log10(1000)
#> [1] 3
log(4)
#> [1] 1.386294
exp(8)
#> [1] 2980.958
2.71828^8
#> [1] 2980.942

Variables and data types (numeric,character)

Assigment Operators

in R, to create a variable , you can use the assigment symbol <-, or = however, the later is not commonly used in R.

To assign the value of 7 to x , we will do

x <- 7
print(x)
#> [1] 7

We can now perform operations on these variables

3*x+3 # 3*7+3 = 21+3 =24
#> [1] 24

Remark: R is case sensitive so, x is different from X

calling print(X) will output error

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

Data types

R has five basic or “atomic” classes of objects:

character
numeric (real numbers)
integer
complex
logical (True/False)

Exercise 1

Run the following code, then use typeof(), class() functions to find out the data type and/or class object.

my_numeric <- 42.5
John_jay <- "university"
my_logical <- TRUE
my_date <- as.Date("05/29/2018", "%m/%d/%Y")

Use typeof() or class()function to find out what the data type of a variable is .

What is the difference between typeof() and class()?

Here we can see that typeof(my_date) is a double, and class(my_date) is Date. This is because typeof output the lowest level data type of the object. While class outputs the class of the object.

If you are writing code that involves checking whether an element is of an specific data type , then you need to be careful on how you check that. Depending on the function , it may give you a true value when in reality you want a false value to be returned.

For example, Imagine you are asked to check if all dates in a dateframe have the correct data type.

In some cases it might be "05/29/2018" but in a rare case (maybe due to a data entry error), there is a "42.5"

typeof(my_date) == typeof(my_numeric)
#> [1] TRUE

In the previous comparison , it returns true, meaning that the two data types are the same, maybe youu thought you are comparing if both are date type, but in reality , you are comparing the lowest level data types which are indeed equal (double)

Instead, you should do.

class(my_date) == class(my_numeric)
#> [1] FALSE

Character Data type A character stores character values or strings

char <- "This is a character data type"
char
#> [1] "This is a character data type"
typeof(char)
#> [1] "character"

Numeric Data type

This is for numerical values .

num <- 3
print(num)
#> [1] 3
num_2 <- -2.35
num_2
#> [1] -2.35
typeof(num_2)
#> [1] "double"
class(num_2)
#> [1] "numeric"

Integer Data type

For integers, we must specify it as so, and to do it , we must convert the data type. Remark: if it is a decimal, it will remove all decimal, acting as a floor function .

int <- as.integer(3.6332)
int
#> [1] 3
typeof(int)
#> [1] "integer"
int2 <- as.integer(7)
int2
#> [1] 7
typeof(int2)
#> [1] "integer"
class(int2)
#> [1] "integer"

We can also create a integer by adding an L after it

int3 <- 8L
int3
#> [1] 8

Remark: It does not work with decimals

int4 <- 3.4546L
int4
#> [1] 3.4546

Complex Data type Complex data types are stored as x+yi , i.e, with the imaginary component

compl <- 13+7i
compl
#> [1] 13+7i
typeof(compl)
#> [1] "complex"
complex(real = 23, imaginary = 7)
#> [1] 23+7i

Boolean Data type This stores boolean values of TRUE and FALSE

my_bool <- TRUE
my_bool
#> [1] TRUE

typeof(my_bool)
#> [1] "logical"

my_boolean <- F
my_boolean
#> [1] FALSE
typeof(my_boolean)
#> [1] "logical"

Converting Data types

Convert into Numeric

We can convert values as numeric. Using as.numeric() to change the type but keeping the values as they are. When converting

complex: removes the imaginary part
logical: TRUE becomes 1 , FALSE becomes 0
character: to its numerical values, but if it has letters then to NA

We can use is.numeric() to check if a variable is numeric

# Complex
is.numeric(compl)
#> [1] FALSE
number <- as.numeric(compl)
#> Warning: imaginary parts discarded in coercion
number
#> [1] 13
is.numeric(number)
#> [1] TRUE

#Logical 
is.numeric(my_bool)
#> [1] FALSE
number2 <- as.numeric(my_bool)
number2
#> [1] 1
is.numeric(number2)
#> [1] TRUE

# Character
char
#> [1] "This is a character data type"
is.numeric(char)
#> [1] FALSE
number3 <- as.numeric(char)
#> Warning: NAs introduced by coercion
number3
#> [1] NA
is.numeric(number3)
#> [1] TRUE

my_char <- "2023"
is.numeric(my_char)
#> [1] FALSE
number4 <- as.numeric(my_char)
number4
#> [1] 2023
is.numeric(number4)
#> [1] TRUE

Convert into integer

inte1<-as.integer("234")
inte1
#> [1] 234
typeof(inte1)
#> [1] "integer"

inte2<-as.integer(23+6i)
#> Warning: imaginary parts discarded in coercion
inte2
#> [1] 23
typeof(inte2)
#> [1] "integer"

inte3<-as.integer(F)
inte3
#> [1] 0
typeof(inte3)
#> [1] "integer"

Converting into Logical

Return FALSE for 0 , TRUE otherwise

print(as.logical(0))
#> [1] FALSE
typeof(as.logical(0))
#> [1] "logical"

print(as.logical(-324))
#> [1] TRUE
typeof(as.logical(-324))
#> [1] "logical"

Exercise 2

Create 1 datatype of each: Character, numeric, integer, complex, Boolean

Getting help

You can use the Plots and files pane (bottom left pane) to click on Help and then search for whichever function you need help with.

You can also use the ? before each function.

?mean

This will open the information about the function on the plots and files pane.

Part I: Introduction to R

Part III: Data Structures