R Workshop-NCU_Finance

Set up Work Directory

setwd('/Users/Sam/Desktop/R_file/Workshop')

Install packages

install.packages('quantmod')

Load in packages

library(quantmod)
require(quantmod)
#both can use, but the latter is more commonly used

Detach packages(not recommand to use it)

detach('package:quantmod')

Read in files

da <- read.table("WTI.csv",sep=",")
da <- read.csv("WTI.csv")

Output data

write.table(da,file="/Users/Sam/Desktop/R_file/Workshop/FX.csv",sep=",")
write.csv(da,file="/Users/Sam/Desktop/R_file/Workshop/FX.csv")
#use write.table can output data in various type, like .txt, .csv etc

Arithmetics

1 + 2 + 3   # add / plus
6 - 3       # subtract / minus
3 * 7 * 2   # multiple / times
120 / 3     # divide
120 / 7
4 * 6 + 5
(4 * 6) + 5
4 * (6 + 5)

Advanced Arithmetics

6 ^ 2       # second power

## [1] 36

6 ** 2      # second power

## [1] 36

6 ^ 5       # six to the fifth power

## [1] 7776

sqrt(36)    # square root

## [1] 6

27 ^ (1/3)  # cube root / third root of 27

## [1] 3

16 %/% 3    # quotient

## [1] 5

16 %% 3     # remainder

## [1] 1

Sign of a number

sign(10)    # print out +1 if positive

## [1] 1

sign(0)     # print out  0 if zero

## [1] 0

sign(-10)   # print out -1 if negative

## [1] -1

absolute value

abs(-10)

## [1] 10

logarithm

log(10)     # based on e

## [1] 2.302585

log1p(9)    # log(x) = log1p(x - 1), log(10) = log1p(9)

## [1] 2.302585

log(10, 2)  # based on 2

## [1] 3.321928

log2(10)    # based on 2

## [1] 3.321928

log10(10)   # based on 10

## [1] 1

exponential

exp(3)

## [1] 20.08554

expm1(3)    # expm1(x) = exp(x) - 1

## [1] 19.08554

Type of Data - Vector_Numeric、character、logic

a <- seq(from=1, to=20 ,by=2)  # numeric
b <- letters[1:10]             # character 
c <- rep(c(TRUE,FALSE),5)      # logic
a ; b ; c 

##  [1]  1  3  5  7  9 11 13 15 17 19

##  [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j"

##  [1]  TRUE FALSE  TRUE FALSE  TRUE FALSE  TRUE FALSE  TRUE FALSE

class(a) ; class(b) ; class(c) 

## [1] "numeric"

## [1] "character"

## [1] "logical"

# use class() to detect the data type

Type of Data - dataframe、matrix、list

d <- matrix(1:15,ncol = 3,nrow = 5,byrow = T)
e <- as.data.frame(d)   # transfer matrix into dataframe
f <- list(d,e)          # make it as a list 
d ; e ; f 

##      [,1] [,2] [,3]
## [1,]    1    2    3
## [2,]    4    5    6
## [3,]    7    8    9
## [4,]   10   11   12
## [5,]   13   14   15

##   V1 V2 V3
## 1  1  2  3
## 2  4  5  6
## 3  7  8  9
## 4 10 11 12
## 5 13 14 15

## [[1]]
##      [,1] [,2] [,3]
## [1,]    1    2    3
## [2,]    4    5    6
## [3,]    7    8    9
## [4,]   10   11   12
## [5,]   13   14   15
## 
## [[2]]
##   V1 V2 V3
## 1  1  2  3
## 2  4  5  6
## 3  7  8  9
## 4 10 11 12
## 5 13 14 15

#func starts with as.~ : transfer complex into simple 
#func starts with no as.~ : transfer simple into complex 

class(d) ; class(e) ; class(f)

## [1] "matrix"

## [1] "data.frame"

## [1] "list"

Common orders to use

t(d)       # transition matrix

##      [,1] [,2] [,3] [,4] [,5]
## [1,]    1    4    7   10   13
## [2,]    2    5    8   11   14
## [3,]    3    6    9   12   15

dim(d)     # report the dim of matrix

## [1] 5 3

table(c)   # compute the data frequency 

## c
## FALSE  TRUE 
##     5     5

summary(d) # summary statistic of the data 

##        V1           V2           V3    
##  Min.   : 1   Min.   : 2   Min.   : 3  
##  1st Qu.: 4   1st Qu.: 5   1st Qu.: 6  
##  Median : 7   Median : 8   Median : 9  
##  Mean   : 7   Mean   : 8   Mean   : 9  
##  3rd Qu.:10   3rd Qu.:11   3rd Qu.:12  
##  Max.   :13   Max.   :14   Max.   :15

head(d)    # report head 6 data 

##      [,1] [,2] [,3]
## [1,]    1    2    3
## [2,]    4    5    6
## [3,]    7    8    9
## [4,]   10   11   12
## [5,]   13   14   15

tail(d)    # report tail 6 data 

##      [,1] [,2] [,3]
## [1,]    1    2    3
## [2,]    4    5    6
## [3,]    7    8    9
## [4,]   10   11   12
## [5,]   13   14   15

cbind(a,b,c) # bind data together via columes

##       a    b   c      
##  [1,] "1"  "a" "TRUE" 
##  [2,] "3"  "b" "FALSE"
##  [3,] "5"  "c" "TRUE" 
##  [4,] "7"  "d" "FALSE"
##  [5,] "9"  "e" "TRUE" 
##  [6,] "11" "f" "FALSE"
##  [7,] "13" "g" "TRUE" 
##  [8,] "15" "h" "FALSE"
##  [9,] "17" "i" "TRUE" 
## [10,] "19" "j" "FALSE"

rbind(a,b,c) # bind data together via rows 

##   [,1]   [,2]    [,3]   [,4]    [,5]   [,6]    [,7]   [,8]    [,9]  
## a "1"    "3"     "5"    "7"     "9"    "11"    "13"   "15"    "17"  
## b "a"    "b"     "c"    "d"     "e"    "f"     "g"    "h"     "i"   
## c "TRUE" "FALSE" "TRUE" "FALSE" "TRUE" "FALSE" "TRUE" "FALSE" "TRUE"
##   [,10]  
## a "19"   
## b "j"    
## c "FALSE"

merge(d,e,by="V1") # merge two data set, "by"" means via which colume

##   V1 V2.x V3.x V2.y V3.y
## 1  1    2    3    2    3
## 2  4    5    6    5    6
## 3  7    8    9    8    9
## 4 10   11   12   11   12
## 5 13   14   15   14   15

Data Manipulation

d[1,2]      #report the data set in first row, second colume 

## [1] 2

d[,-2]      #delete the data in second colume 

##      [,1] [,2]
## [1,]    1    3
## [2,]    4    6
## [3,]    7    9
## [4,]   10   12
## [5,]   13   15

colnames(e) ; rownames(e)  #return the colnames and rownames of data

## [1] "V1" "V2" "V3"

## [1] "1" "2" "3" "4" "5"

as.character(d[,2]) #point specific data set to do the data transformation 

## [1] "2"  "5"  "8"  "11" "14"

head(paste(d[,1],"%",sep=","))  #dealing with character binding 

## [1] "1,%"  "4,%"  "7,%"  "10,%" "13,%"

head(round(d[,1],2))  #extract the numbers below the points

## [1]  1  4  7 10 13

Simple loops

x <- 0 
for( i in -10:10){
x <- (i+i^2-i^3)
print(x)
}

## [1] 1090
## [1] 801
## [1] 568
## [1] 385
## [1] 246
## [1] 145
## [1] 76
## [1] 33
## [1] 10
## [1] 1
## [1] 0
## [1] 1
## [1] -2
## [1] -15
## [1] -44
## [1] -95
## [1] -174
## [1] -287
## [1] -440
## [1] -639
## [1] -890

x <- 1
while(x < 5) {
   x= x+1; 
print(x)
}

## [1] 2
## [1] 3
## [1] 4
## [1] 5