## Basic calculations

# Addition: `+`
# Subtraction: `-`
# Multiplication: `*`
# Division: `/`
# Exponentiation: `^`
# Modulo: `%%`


# An addition
2 + 5 
# A subtraction
10 - 5 
# A multiplication
2 * 6
# A division
(6 + 2) / 2 
# Exponentiation
10^2
# Modulo
11%%3

## Variable assignment 

# Assign the value 50 to `x`
x <- 50


# Print out the value of the variable `x`
x

# Assign the value 2 to `y` and sum `x + y`
y <- 2
x + y

## Data type/classes
# Numeric, integer, logic, character, factor, etc.

# Numeric class
class(x)
is.numeric(x)
is.integer(x)
x_int <- as.integer(x)
is.integer(x_int)

### String class
# Stores all kinds of text data.

my_name <- "Juan"
my_name
class(my_name)
is.character(my_name)
is.character(x)
is.numeric(my_name)
x + my_name


### Logical class
# Stores boolean truth values, i.e. TRUE and FALSE. 
# Numeric values can be converted to logical (0 = false, all others = true).
3 > 2
2 > 3
3 == 3
4 == 3
4 >= 3
my_T <- 3 > 2
my_F <- 2 > 3
my_T
my_F
class(my_T)
is.logical(my_F)
as.logical(0)
as.logical(1)

#Example of logical operations:

my_T | my_F
my_T & my_F
!my_T


### Factors
# Not discussed here

## Basic data structures
# Vectors, matrices, data frames.

### Vectors
# One-Dimensional arrays. All elements must have the same type. 
# They are declared with `c(...)`.
v <- c("Juan", 2, TRUE)
v
class(v)
w <- c(1, 2, 3)
w
class(w)


### Matrix.
# Two dimensional version of a vector. 
# Also requires all data to be of the same type.

# Produce a matrix
A <- matrix( c(2, 4, 3, 1, 5, 7), # the data elements 
             nrow = 3,              # number of rows 
             ncol = 2,              # number of columns 
             byrow = FALSE)        # fill matrix by rows 
A


# Access elements of the matrix
A[1,] # first row
A[,1] # first column
A[c(1,3),] # row 1 and 3
A[2,2] #element in second row, second column


### Data frame
# Used to store data with columns of different data-types.
students <- c("Juan","Johan","Joan","John","Giovanni")
country <- c("Mexico","Sweden","Sweden","England","Italy")
age <- c(20,21,24,19,30)
is_exchange <- c(TRUE,FALSE,FALSE,TRUE,TRUE)
my_class <- data.frame(Name = students, Country = country, Age = age, 
                       Exchange = is_exchange, stringsAsFactors = FALSE)
my_class


# Access data from a data frame. 
# It can be done in the same way as with matrices, e.g. with the `[r,c]` notation. 
# It can also be done using the `$` notation to access specific columns.
my_class$Age
my_class$Country
my_class$Exchange