R Introduction II

This document provides an introduction and overview of R and RStudio. It begins with the objectives of understanding R as a programming language, installing R and RStudio, and an overview of RStudio. It then demonstrates basic R functions for arithmetic, trigonometry, vectors, matrices, and data frames. Examples are provided for various data types and operations in R including addition, division, logarithms, and assigning objects. The document concludes with a brief discussion of importing data into R and creating R projects.

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R Introduction II

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cristina

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Introduction to R

and Rstudio
PhD: HUAMAN DE LA CRUZ, Alex Ruben
Email contact: alebut2@hotmail.com
OBJECTIVES

1. Understand R as a programming language

2. Install R and R Studio
3. Overview of R Studio
4. Introduction of R as an object oriented
language
Software Environment

1. Statistics
2. Graphics
3. Programming
4. Calculator
5. GIS
6. Etc……….
R Basic examples - Arithmetic
# Addition
1 + 1
[1] 2
# Multiplication
10 * 10
[1] 100
# Compute Logarithm
log10(100)
[1] 2
# 7 to the 8th power
7^8
[1] 5764801
# square root of 2
sqrt(2)
[1] 1.414214
Notice the comment character #.
R Basic examples - Trigonometry

#Sine(π/2):
sin(pi/2) [1] 1
#Cosine(π):
cos(pi) [1] -1
#Tangent(π/4):
tan(pi/3) [1] 1.732051
#Cotangent(π/3):
1/tan(pi/3) [1] 0.5773503
#cosine inverse = -1
acos(-1) [1] 3.141593
#tangent inverse = 0.5
atan(0.5) [1] 0.4636476
R Basic examples
# Division
10/3
[1] 3.333333
# Square root
Square(2)
[1] 2.718281

Options (digits=3)

# Division
10/3
[1] 3.33
# Square root
Sqrt(2)
[1] 1.41
R Basic examples

# Print Text
"Hello World"
[1] “Hello World”
R Assignment, Object names, and
Data types
# Assignment
test <- 1
#or
test = 1
# dont see the calculated value
test #take a look
[1] 1

10 -> x # Rightwards assignment

x
[1] 10
AS VARIABLES and Object names

x <- 7*41/pi
x numeric
[1] 91.35494

a = "The dog ate my homework"

sub("dog","cat",a)
character
[1] "The cat ate my homework“ string
b<-c("the", "dog","ate", "my","homework")
b
[1] “the” “dog” “ate”
[4] “my” “homework”
AS VARIABLES and object names

s = (1+1==3)
s
[1] FALSE

p = (1+1+1==3)
s
[1] TRUE

logical
AS VARIABLES and object names

x <- 5
y <- 16
x<y
[1] TRUE
x>y
[1] FALSE
x<=5
[1] TRUE
y>=20
[1] FALSE
y == 16
[1] TRUE
x != 5
[1] FALSE
Grouped Expressions in R

You can issue many commands on a

single line by separating each command
with a semicolon (;). When doing so,
evaluation of commands is in order from
left to right:

A <- 1; B <- 2; C <- A + B

C
[1] 3
Data Types
VECTORS

In R, Vector is a basic structure that

contains element of similar type
(logical, integer, double, character,
complex or raw
R <- c(2, 3, 5)
R
[1] 2 3 5
lenght (R)
[1] 3
T<- length(c("aa", "bb", "cc", "dd", "ee")
T
[1] 5
VECTORS - Exercises
a<-c(8.5:4.5)#sequence of numbers from 8.5 down to 4.5
b<-c(20:1)
c<-c(1:20)
d<-c(1, 1:3, c(5, 8), 13)#values concatenated into single value
length(a)
e<- c(8:20, step=2)
seq(0,1, length=11)
str(seq(rnorm(20)))
seq(1,9, by = 2) # match
seq(1,9, by = pi)# stay below
seq(1,6, by = 3)
seq(1.575, 5.125, by=0.05)
f <-seq(2,20, by=2)
VECTORS
Exercises # MINIMUM AND MAXIMUM VALUE
i <- c(1,-2,3,-4)
j <- c(-1,2,-3,4)
min(i)
min(j)
min(i,j)
max(i)
max(j)
max(i,j)
pmin(i,j) # show all minor values
pmax(i,j)
## lenght
length(i)
length(j)
mean(i)
mean(j)
var(i)
var(j)
sd(i)
sd(j)
VECTORS - Exercises
TEMPERATURE<-c(1,5,6,9)
TEMPERATURE<-c(2:5)
TEMPERATURE
TEMPERATURE[2] # show the 2 element
[1] 5
TEMPERATURE[c(1,3,4)] #Select specific set
of elements
TEMPERATURE[3:4]
TEMPERATURE[-2]
#This will give a vector of all elements except 2 nd element.

[1] 2 4 5
LISTS IN R

A list is a generic vector containing

other objects
n<-c(2,3,5)
s<-c("a","b","c","d","e")
b<-c(TRUE,FALSE,TRUE,FALSE,FALSE)
x<-list(n,s,b,3) # x contains copies of n,s,b
x[2] # slice containing the second member of x
x[1]
x[c(2,4)] #retrieve a slice containing multiple
members
LISTS IN R

A list is a generic vector containing

other objects

# COPY}
x[[2]]
# we can modify its content directly
x[[2]][1]="ta"
x[[2]]
s # is not affected
MATRICES IN R

Matrix is a collection of data elements

arranged in a two-dimensional
rectangular layout. The following is an
example of a matrix with 2 rows and 3
columns. matrix () function
MATRICES IN R

A<-matrix(c(2,4,3,1,5,7), nrow = 2,
ncol = 3)

A<-matrix(c(2,4,3,1,5,7), nrow = 2,
ncol = 3, byrow = TRUE)
MATRICES IN R
MATRICES IN R
Matrices can represent the binding of two or more vectors of equal
length. If we have the X and Y coordinates for five quadrats within a grid,
we can use cbind() (combine by columns) or rbind() (combine by rows)
functions to combine them into a single matrix, as follows:
X <- c(16.92, 24.03, 7.61, 15.49, 11.77)
Y <- c(8.37, 12.93, 16.65, 12.2, 13.12) A<-c(16.92, 8.37)
XY <- cbind(X, Y) B<-c(24.03, 12.93)
XY <- rbind(X,Y) C<-c(7.61, 16.65)
#Exercises D<-c(15.42, 12.20)
E<-c(11.77, 13.12)
XY<-cbind(A,B,C,D,E)
XY
XY[2,3] # [row, column]
XY[2,] #It displays entire second row
XY[,2] #It displays entire second column
XY[,-2] #It displays all columns except second column
XY[1:2, "A"] #It displays rows 1 trough 2 for column A
XY[,"C"] #It displays column named C
DATAFRAME IN R