# ######################################################################
# CHAPTER - INTRODUCTION
# ----------------------------------------------------------------------

# ======================================================================
# Section 'R objects'

y <- 39
y
43 -> y
y

z <- 5
w <- z^2
w
i <- (z*2 + 45)/2
i

(w <- z^2)

(34 + 90)/12.5

ls()
rm(y)
rm(z,w,i)


# ======================================================================
# Section 'Vectors'

v <- c(4,7,23.5,76.2,80)
v
length(v)
mode(v)

v <- c(4,7,23.5,76.2,80,"rrt")
v

v <- c(NA,"rrr")
v
u <- c(4,6,NA,2)
u
k <- c(T,F,NA,TRUE)
k

v[2]

v[1] <- 'hello'
v

v <- vector()

v[3] <- 45
v

v <- c(45,243,78,343,445,645,2,44,56,77)
v
v <- c(v[5],v[7])
v


# ======================================================================
# Section 'Vectorizarion'

v <- c(4,7,23.5,76.2,80)
x <- sqrt(v)
x

v1 <- c(4,6,87)
v2 <- c(34,32.4,12)
v1+v2

v1 <- c(4,6,8,24)
v2 <- c(10,2)
v1+v2

v1 <- c(4,6,8,24)
v2 <- c(10,2,4)
v1+v2

v1 <- c(4,6,8,24)
2*v1


# ======================================================================
# Section 'Factors'

g <- c('f','m','m','m','f','m','f','m','f','f')
g

g <- factor(g)
g

other.g <- factor(c('m','m','m','m','m'),levels=c('f','m'))
other.g

table(g)
table(other.g)

a <- factor(c('adult','adult','juvenile','juvenile','adult','adult',
       'adult','juvenile','adult','juvenile'))
table(a,g)

t <- table(a,g)
margin.table(t,1)
margin.table(t,2)

prop.table(t,1)
prop.table(t,2)
prop.table(t)


# ======================================================================
# Section 'Generating sequences'
x <- 1:1000

10:15-1
10:(15-1)

5:0

seq(-4,1,0.5)

seq(from=1,to=5,length=4)
seq(from=1,to=5,length=2)
seq(length=10,from=-2,by=.2)

rep(5,10)
rep('hi',3)
rep(1:3,2)

gl(3,5)
gl(2,5,labels=c('female','male'))

rnorm(10)

rnorm(10,mean=10,sd=3)

rt(5,df=10)


# ======================================================================
# Section 'Indexing'

x <- c(0,-3,4,-1,45,90,-5)
x
x > 0
y <- x>0

x[y]

x[x>0]

x[x <= -2 | x > 5]
x[x > 40 & x < 100]

x[c(4,6)]
x[1:3]

x[-1]
x[-c(4,6)]
x[-(1:3)]

pH <- c(4.5,7,7.3,8.2,6.3)
names(pH) <- c('area1','area2','mud','dam','middle')
pH

pH['mud']
pH[c('area1','dam')]


# ======================================================================
# Section 'Arrays and matrices'

m <- c(45,23,66,77,33,44,56,12,78,23)
m
dim(m) <- c(2,5)
m

m <- matrix(c(45,23,66,77,33,44,56,12,78,23),2,5)

m <- matrix(c(45,23,66,77,33,44,56,12,78,23),2,5,byrow=T)
m

m[-2,2]
m[1,-c(3,5)]

m[1,]
m[,4]

m1 <- matrix(c(45,23,66,77,33,44,56,12,78,23),2,5)
m1
cbind(c(4,76),m1[,4])
m2 <- matrix(rep(10,50),10,5)
m2
m3 <- rbind(m1[1,],m2[5,])
m3

a <- array(1:50,dim=c(2,5,5))
a

a[1,5,2]
a[1,,4]
a[1,3,]
a[,c(3,4),-4]
a[1,c(1,5),-c(4,5)]

m <- matrix(c(45,23,66,77,33,44,56,12,78,23),2,5)
m
m*3
m1 <- matrix(c(45,23,66,77,33,44),2,3)
m1
m2 <- matrix(c(12,65,32,7,4,78),2,3)
m2
m1+m2

# ======================================================================
# Section 'Lists'

my.lst <- list(stud.id=34453, stud.name="John", stud.marks=c(14.3,12,15,19)) 

my.lst

my.lst[[1]]
my.lst[[3]]

my.lst[1]

my.lst$stud.id

names(my.lst)
names(my.lst) <- c('id','name','marks')
my.lst

my.lst$parents.names <- c("Ana","Mike")
my.lst

length(my.lst)

other <- list(age=19,sex='male')
lst <- c(my.lst,other)
lst

unlist(my.lst)




# ======================================================================
# Section 'Data frames'

my.dataset <- data.frame(site=c('A','B','A','A','B'),season=c('Winter','Summer','Summer','Spring','Fall'),pH = c(7.4,6.3,8.6,7.2,8.9))
my.dataset

my.dataset[3,2]

my.dataset$pH

my.dataset[my.dataset$pH > 7,]
my.dataset[my.dataset$site == 'A','pH']
my.dataset[my.dataset$season == 'Summer',c('site','pH')]


attach(my.dataset)
my.dataset[pH > 8,]
season

detach(my.dataset)
season

my.dataset$NO3 <- c(234.5,256.6,654.1,356.7,776.4)
my.dataset

nrow(my.dataset)
ncol(my.dataset)

my.dataset <- edit(my.dataset)

new.data <- edit(data.frame())

names(my.dataset)
names(my.dataset) <- c("area","season","pH","NO3" )
my.dataset

names(my.dataset)[4] <- "PO4"
my.dataset

data()
data(USArrests)


# ======================================================================
# Section 'Creating new functions'

se

se <- function(x) {
  v <- var(x)
  n <- length(x)
  return(sqrt(v/n))
}

se(c(45,2,3,5,76,2,4))

basic.stats <- function(x,more=F) {
  stats <- list()

  clean.x <- x[!is.na(x)]

  stats$n <- length(x)
  stats$nNAs <- stats$n-length(clean.x)

  stats$mean <- mean(clean.x)
  stats$std <- sd(clean.x)
  stats$med <- median(clean.x)
  if (more) {
    stats$skew <- sum(((clean.x-stats$mean)/stats$std)^3)/length(clean.x)
    stats$kurt <- sum(((clean.x-stats$mean)/stats$std)^4)/length(clean.x) - 3
  }
  stats
}
  
  
basic.stats(c(45,2,4,46,43,65,NA,6,-213,-3,-45))
basic.stats(c(45,2,4,46,43,65,NA,6,-213,-3,-45),more=T)

f <- function(x) {
  for(i in 1:10) {
    res <- x*i
    cat(x,'*',i,'=',res,'\n')
  }
}

# ======================================================================
# Section 'Managing your session'

source('mycode.R')

save(f,my.dataset,file='mysession.R')

load('mysession.R')

save.image()

# ======================================================================
# Section 'A short introduction to MySQL'

mysql -u myuser -p

mysql -h myserver.xpto.pt -u myuser -p

create database contacts;
use contacts;

create table people(id INT primary key,name CHAR(30),address CHAR(60));

insert into people  values(1,'John Smith','Strange Street, 34, Unknown City');

select * from people;
select name, address from people;
select name from people where id >= 1 and id < 10;