1. R Language
note

2. Data analysis and graphics with R
• R is a language and environment for statistical
computing and graphics, similar to the S
language originally developed at Bell Labs

3. Common commands
• getwd() 读工作目录.
• setwd(“c:/”) 改变工作目录
• ls() 显示当前workspace的变量
• rm(objectlist) Remove (delete) one or more objects.
• options() View or set current options.
• savehistory("myfile") Save the commands history to myfile ( default =
• .Rhistory).
• loadhistory("myfile") Reload a command's history (default = .Rhistory).
• save.image("myfile") Save the workspace to myfile (default = .RData).
• save(objectlist,file="myfile") Save specific objects to a file.
• load("myfile") Load a workspace into the current session (default =
• .RData).

4. R Data Structures
•

5. Vector
• Vector
– c (2,3,1,6,5,2)
– X = c (1:9)
– X*2 向量乘
• 2,4,6,8,10,12,14,16,18

6. Array
• array(c(1:9), dim=c(3,3))
– [,1] [,2] [,3]
– [1,] 1 4 7
– [2,] 2 5 8
– [3,] 3 6 9

7. Matrix
myymatrix <- matrix(
vector,
nrow=number_of_rows,
ncol=number_of_columns,
byrow=logical_value,
dimnames=list(
char_vector_rownames,
char_vector_colnames
)
)
M = matrix(c(1:10), nrow=2, ncol=5, byrow=T)
byrow=T横向填充 byrow=F竖向填充
[,1] [,2] [,3] [,4] [,5] [,1] [,2] [,3] [,4] [,5]
[1,] 1 2 3 4 5 [1,] 1 3 5 7 9
[2,] 6 7 8 9 10 [2,] 2 4 6 8 10

8. Matrix
a=matrix(c(1:10), nrow=2, ncol=5, byrow=T,
dimnames=list(c('R1','R2'),c('a','b','c','d','e')))
abcd e
R1 1 2 3 4 5
R2 6 7 8 9 10
• 选择数据：
– a[1,2] 结果：2
– a[2,c(3:5)] 结果：8,9,10

9. Array
• n1=c('r1','r2')
• n2=c('col1','col2','col3')
• n3=c('p1','p2','p3','p4')
•array(c(1:24),c(2,3,4),dimnames=list(n1,n2,n3)
)
三维 数组

10. data frame
• name=c('jack','tom','joe','linda')
• age=c('21','23','20','19')
• city=c('bj','sh','sh','bj')
• d = data.frame(name,age,city)
• Query:
– d['age']
– d[c('age','city')]
– d[1:2]
– d$age
• Edit:
– d = edit(d)

11. data frame
• table(d$city,d$name)
– jack joe linda tom
– bj 1 0 1 0
– sh 0 1 0 1
attach(d) with(d,{
summary(name) summary(name)
… …
detach(d) })

12. Lists
• Lists are the most complex of the R data types
• g <- "My First List"
• h <- c(25, 26, 18, 39)
• j <- matrix(1:10, nrow=5)
• k <- c("one", "two", "three")
• mylist <- list(title=g, ages=h, j, k)

13. data input
•

14. data input
• mydata <-
data.frame(age=numeric(0), gender=char
acter(0), weight=numeric(0))
mydata <- edit(mydata)
• mydataframe =
read.table("c:/a.txt", header=FALSE, sep="t",
row.names="name")
– header:是否把第一行作为column name
– row.names:标识

15. data input
• read excel:
– library(RODBC)
– channel <- odbcConnectExcel("c:/t.xlsx")
– mydataframe <- sqlFetch(channel, "Sheet1")
– odbcClose(channel)
• excel2007:
– library(xlsx)
– workbook <- "c:/myworkbook.xlsx"
– mydataframe <- read.xlsx(workbook, 1)

16. data input
• library(RODBC)
• myconn <-odbcConnect("mydsn", uid="Rob",
pwd="aardvark")
• crimedat <- sqlFetch(myconn, Crime)
• pundat <- sqlQuery(myconn, "select * from
Punishment")
• close(myconn)

17. data export
• png(), jpeg(),
• bmp(), tiff(), xfig()
• pdf("mygraph.pdf")
• …….
• dev.off()