20151203Demo.Rmd

---
title: '20151203'
author: "David Chiu"
date: "2015年12月3日"
output: html_document
---


## RBasic
```
a = 3
b <-2 
a + b
a - b
a * b
a/ b

a = 3
a = c(3)
a = c(1,2,3,4)
b = c(4,3,2,1)

matrix(1:9 , nrow =3, byrow=TRUE)

data.frame(a=c(1,2,3), b= c(2,3,4))
data(iris)
class(iris)

employee = list(age=30, profession="it")

a = c('sunny', 'sunny', 'rainy')
factor(a)

```
## Flow Control
```
x=5;
if(x>3){
  print
  ("x > 3");
}else{
  print
  ("x <= 3");
}


x=5;
if(x>3){
  print ("x > 3");
} else if (x ==3){
  print ("x == 3");
}else{
  print
  ("x <= 3");
}

for(i in 1:10){
  print(i);
}

sum=0
for(i in 1:100){
  sum= sum+ i;
}
sum

sum(1:100)


ary = rep(NA, 100)
for(i in 1:100){
  ary[i]= i;
}
ary

ary2 =c()
for(i in 1:100){
  ary2 = c(ary2, i);
}
ary2

seq_len(5)

mat = matrix(1:9, byrow=TRUE, nrow=3)
for(i in seq_len(nrow(mat))) {
  for(j in seq_len(ncol(mat))) {
    cat(mat[i, j], " ")
  }
  cat('\n');
}

sum = 0;
cnt = 0;
while(cnt <= 100){
  sum = sum + cnt;
  cnt = cnt + 1;
}
sum
```


```
for (i in 1:9){
  for (j in 1:9){  
      cat(i * j, " " );
  }
  cat(" \n" );
}


for (i in 1:9){
  for (j in 1:9){  
      cat(sprintf("%d * %d = %d", i, j, i * j), " ");
  }
  cat(" \n" );
}

matrix(1:9, nrow =9) %*% matrix(1:9, nrow= 1)

```


```
a = c(1,2,3,4)
b = c()
for(i in 1:4){
    if(a[i] != 3){
       b = c(b, a[i]);
    }
}
b    

a = c(1,2,3,4)
b = c(TRUE, TRUE, FALSE, TRUE)
a[b]

f = function(a = 3) {
    b = 2
    b
}

f()

b = 3
f = function(a = 3) {
    b = 2
    b
}
f()
b

b = 3
f = function(a = 3) {
    b
}
f()
b


f = function(a, b = 2, c = NULL) {
   a + b
}
f(a = 3)

f(3)


f = function(a, b = 2, c = NULL) {
   return(a + b)
}
f(3)


f= function(a, b){
    a*2
}
f(3)

f= function(a, b){
     print(a+b)
}
f(3)

f = function(a,b){
    if(a > 3){
       a = 100;
    }
    a + b;
}

f(5,8)
f(5,"Hello World")
debug(f)
f(5,"Hello World")
undebug(f)


mat = matrix(-1, nrow=5, ncol = 5)
mat
rownames(mat) = c("A","B","C","D","E")
colnames(mat) = c("A","B","C","D","E")

mat['A','C'] = 3


```

```
mat = matrix(-1, nrow=5, ncol = 5)
mat
rownames(mat) = c("A","B","C","D","E")
colnames(mat) = c("A","B","C","D","E")

mat['A','C'] = 3
match = read.table('match.txt', sep= "|")
for (i in 1:nrow(match)){
    mat[match[i,1], match[i,2]] = match[i,3];
}
mat

match_func = function(filename= "match.txt"){
  mat = matrix(-1, nrow=5, ncol = 5)
  rownames(mat) = c("A","B","C","D","E")
  colnames(mat) = c("A","B","C","D","E")
  
  match = read.table(filename, sep= "|")
  for (i in 1:nrow(match)){
      mat[match[i,1], match[i,2]] = match[i,3];
  }
  mat
}

match_func('match.txt')
match_func()
```


```
grades =list(kevin = c(80,60,92), marry = c(56,75,64,84,56), QOO = c(10,20,3,4,10))

unlist(grades[1])
for (i in 1:length(grades)){
      print(sum(unlist(grades[i])));
}

lapply(grades, sum)
lapply(grades, mean)
lapply(grades, function(e){list(sum = sum(e), min = min(e))})

lapply(c(1,2,3,4,5),  function(e){paste(as.character(e), "hello")})
m1 = matrix(1:4, byrow=TRUE, nrow=2)
m2 = matrix(5:8, byrow=TRUE, nrow=2)

li = list(m1, m2)
lapply(li, mean)


class(lapply(grades, sum))
sapply(grades, sum)

m1 = matrix(1:4, byrow=TRUE, nrow=2)
m2 = matrix(5:8, byrow=TRUE, nrow=2)
li = list(m1, m2)
sapply(li, mean)
sapply(li,function(e) e[1,])

m = matrix(1:4, byrow=TRUE, nrow=2)
apply(m, 1, sum) # rowsums
apply(m, 2, sum) # colsums

rowmeans = apply(m, 1, mean)
colmeans = apply(m, 2, mean)

x = c(80,70,59,88,72,57)
t = c(1,1,2,1,1,2)
tapply(x,t, mean)

data(iris)

tapply(iris$Sepal.Length, iris$Species,mean)

```
## Find Center
```
names(cdc)
str(cdc)
?hist
hist(cdc$weight)

a = c(1,2,2,3,1,2,4,5,6,5,6,7,8,9,9,8)
hist(a)


salary = c(22,23,25,27,32,35,22,23,25,27,32,35,50,55,60,220,230,250,300,220,230,250,300)
hist(salary)

low = rnorm(40, mean= 28, sd = 3)
med = rnorm(20, mean= 50, sd = 10)
high = rnorm(40, mean= 200, sd = 20)
hist(c(low, med, high))
hist(cdc$weight, breaks=50)
hist(cdc$weight, breaks=500)

```

```
table(cdc$weight %% 10)

a = c(1,2,2,3,1,2,4,5,6,5,6,7,8,9,9,8)
hist(a)
stem(a)

salary = c(22,23,25,27,32,35,22,23,25,27,32,35,50,55,60,220,230,250,300,220,230,250,300)
stem(salary)

a = c(100,120,130,110,100,90,80,90,100,110)
sum(a) / 10
mean(a)

b = c(a, 10000)
mean(b)

a 
sort(a)
median(a)

sort(b)
median(b)

mean(cdc$weight)
median(cdc$weight)
names(which.max(table(a)))
str(cdc)
table(cdc$smoke100)mosaicplot(gender_smokers)


table(cdc$smoke100) / length(cdc$smoke100)
barplot(table(cdc$smoke100))
gender_smokers = table(cdc$gender,cdc$smoke100)
mosaicplot(gender_smokers)


```

```
a = c(150, 155, 160, 162, 168, 171, 173, 175, 178, 182, 185)
stem(a)
quantile(a,0.5)
quantile(a,0.25)
quantile(a,0.75)
quantile(a,0.75) - quantile(a,0.25)
IQR(a)
boxplot(a)

low_adjacent = max(median(a) - 1.5 * IQR(a), 150)
high_adjacent = min(median(a) + 1.5 * IQR(a), 180)
low_adjacent
b = c(150, 155, 160, 162, 168, 171, 173, 175, 178, 182, 185, 220)
boxplot(b)

boxplot(cdc$weight)


par(mfrow=c(2,1))
hist(cdc$weight)
boxplot(cdc$weight, horizontal=TRUE)

# par(mfrow=c(2,2))
boxplot(cdc$weight ~ cdc$gender)
boxplot(cdc$height ~ cdc$gender)

temp = c(20,30,22,21,35,23,24,27,28)
temp = rnorm(10000, mean = 25, sd = 5)

temp2 = c(temp, 9999,9999,9999,9999,9999,9999,-1,-1,-1,-1)
mean(temp)
mean(temp2)

boxplot(temp2)
boxplot(temp2[temp2 < 50 & temp2 > 0])

bmi = (cdc$weight/cdc$height^2) * 703
boxplot(bmi ~ cdc$genhlth)

plot(cdc$weight, cdc$wtdesire)

```

```
sd(cdc$weight)
sd(cdc$weight) ^ 2

var(cdc$weight)

rnorm(10)
?rnorm

rnorm(10, mean =70, sd = 10)
hist(rnorm(10, mean =70, sd = 10))
hist(rnorm(100, mean =70, sd = 10))
hist(rnorm(1000, mean =70, sd = 10))

h1 = rnorm(1000, mean =70, sd = 10)
dh1 = density(h1)
plot(dh1)
dnorm(70, mean = 70, sd = 10)
dnorm(100, mean = 70, sd = 10)

curve(dnorm, -3,3)
dnorm(0)

dice = sample.int(6, 10000, replace=TRUE)
hist(dice)

set.seed(123)
sample.int(42, 6)

set.seed(50)
y = runif(10000,0,5)
hist(y)

hist(rpois(5000,3))
hist(rpois(5000,300))

pnorm(0)
pnorm(1)
pnorm(2)

curve(dnorm, -3,3)
pnorm(1) - pnorm(-1)
x = c(-1,seq(-1,1,0.1),1)
y = c(0,dnorm(seq(-1,1,0.1)),0)
polygon(x,y, col = "blue")

pnorm(2) - pnorm(-2)
pnorm(1.96) - pnorm(-1.96)

curve(dnorm, -3,3)
pnorm(1) - pnorm(-1)
x = c(-1.96,seq(-1.96,1.96,0.1),1.96)
y = c(0,dnorm(seq(-1.96,1.96,0.1)),0)
polygon(x,y, col = "red")
```