标签：r语言   数据分析   数据挖掘   机器学习   

1.      注意在pdf中绘图，每次plot都要调用dev.off()关闭设备

for(i in 1:10)

{

   pdf(paste(i,‘plots.pdf‘,sep=‘‘))

   plot(0)

   dev.off()

}

上述代码中，如果dev.off移到循环外面，则只有最后的图能正常生成出来。

2.       read.table函数跳过空白行

read.table的skip参数可以设置跳过前面的n行，blank.lines.skip参数可以设置跳过完全空白的行。

3.      对boxplot横坐标重新排序

InsectSprays1=data.frame(count=InsectSprays[,1],spray=ordered(InsectSprays[,2],levels=c("C","E","D","A","F","B")))

boxplot(count ~ spray, data =InsectSprays1, col = "lightgray")

4.      趣味实现:绘制时钟

A=seq(0,2*pi,length.out=1000)

x1=8*cos(A)

y1=8*sin(A)

x2=7*cos(A)

y2=7*sin(A)

plot(x1,y1,col="blue",lwd="0.01",xlim=c(-10,10),ylim=c(-10,10),asp=1)

points(x2,y2,col="blue",lwd="0.05")

for (k in 1:12)

{

xk=9*cos(-2*pi/12*k+pi/2)

yk=9*sin(-2*pi/12*k+pi/2)

lines(c(xk/9*8,xk/9*7),c(yk/9*8,yk/9*7),col="green")

text(xk,yk,k,col="red",lwd=0.1)

}

hour=as.integer(format(Sys.time(),"%H"))

min=as.integer(format(Sys.time(),"%M"))

sec=as.integer(format(Sys.time(),"%S"))

#计算时针的位置

th=-(hour+min/60+sec/3600)/12*2*pi+pi/2;

xh3=4.0*cos(th);

yh3=4.0*sin(th);

xh2=xh3/2+0.5*cos(th-pi/2);

yh2=yh3/2+0.5*sin(th-pi/2);

xh4=xh3/2-0.5*cos(th-pi/2);

yh4=yh3/2-0.5*sin(th-pi/2);

hh=polygon(c(0,xh2,xh3,xh4,0),c(0,yh2,yh3,yh4,0),col="red")

#hh=lines(c(0,xh2,xh3,xh4,0),c(0,yh2,yh3,yh4,0),col="red")

#计算分针的位置

tm=-(min+sec/60)/60*2*pi+pi/2;

xm3=6.0*cos(tm);

ym3=6.0*sin(tm);

xm2=xm3/2+0.5*cos(tm-pi/2);

ym2=ym3/2+0.5*sin(tm-pi/2);

xm4=xm3/2-0.5*cos(tm-pi/2);

ym4=ym3/2-0.5*sin(tm-pi/2);

hm=polygon(c(0,xm2,xm3,xm4,0),c(0,ym2,ym3,ym4,0),col="green")

#hm=lines(c(0,xm2,xm3,xm4,0),c(0,ym2,ym3,ym4,0),col="green")

#计算秒针的位置

ts=-sec/60*2*pi+pi/2;

hs=lines(c(0,6.5*cos(ts)),c(0,6.5*sin(ts)),col="black")

while(1)

{

hh=lines(c(0,xh2,xh3,xh4,0),c(0,yh2,yh3,yh4,0),col="white")

hm=lines(c(0,xm2,xm3,xm4,0),c(0,ym2,ym3,ym4,0),col="white")

hs=lines(c(0,6.5*cos(ts)),c(0,6.5*sin(ts)),col="white")

hour=as.integer(format(Sys.time(),"%H"))

min=as.integer(format(Sys.time(),"%M"))

sec=as.integer(format(Sys.time(),"%S"))

#计算时针的位置

th=-(hour+min/60+sec/3600)/12*2*pi+pi/2;

xh3=4.0*cos(th);

yh3=4.0*sin(th);

xh2=xh3/2+0.5*cos(th-pi/2);

yh2=yh3/2+0.5*sin(th-pi/2);

xh4=xh3/2-0.5*cos(th-pi/2);

yh4=yh3/2-0.5*sin(th-pi/2);

hh=polygon(c(0,xh2,xh3,xh4,0),c(0,yh2,yh3,yh4,0),col="red")

#hh=lines(c(0,xh2,xh3,xh4,0),c(0,yh2,yh3,yh4,0),col="red")

#计算分针的位置

tm=-(min+sec/60)/60*2*pi+pi/2;

xm3=6.0*cos(tm);

ym3=6.0*sin(tm);

xm2=xm3/2+0.5*cos(tm-pi/2);

ym2=ym3/2+0.5*sin(tm-pi/2);

xm4=xm3/2-0.5*cos(tm-pi/2);

ym4=ym3/2-0.5*sin(tm-pi/2);

hm=polygon(c(0,xm2,xm3,xm4,0),c(0,ym2,ym3,ym4,0),col="green")

#hm=lines(c(0,xm2,xm3,xm4,0),c(0,ym2,ym3,ym4,0),col="green")

#计算秒针的位置

ts=-sec/60*2*pi+pi/2;

hs=lines(c(0,6.5*cos(ts)),c(0,6.5*sin(ts)),col="black")

Sys.sleep(0.1)

}

5.      使用seq.Date函数生成日期序列

> date.range<-seq.Date(from =as.Date(‘2000-1-1‘),to = as.Date(‘2001-1-1‘),by = ‘month‘)

> date.range

 [1]"2000-01-01" "2000-02-01" "2000-03-01""2000-04-01" "2000-05-01" "2000-06-01""2000-07-01" "2000-08-01"

 [9]"2000-09-01" "2000-10-01" "2000-11-01""2000-12-01" "2001-01-01"

6.      打开文件，建立连接，并按行读取文件

把下面的文件名换成你自己的文本文件，即可按行读取。

con <-file(‘C:/mtcars.csv‘,open=‘rt‘,encoding = ‘latin1‘)#以只读方式建立连接

text <- readLines(con)

close(con) #注意关闭文件连接

7.       绘制三维圆锥图

library(lattice)

A<-matrix(ncol=2, nrow=64)

for(i in 0:63) {  A[i+1,1]<-sin(i/10) 

A[i+1,2]<-cos(i/10) }

Sigma<-matrix(c(0.5,0.1,0.1,0.25),byrow=TRUE,nrow=2)

G<-eigen(Sigma)

E1<-t(G$vector%*%t(A))

E2<-t(diag(sqrt(G$values))%*%t(E1))

mu<-c(0.1,0.2)

E3<-sweep(E2,2,-mu)

a<-sqrt(max(rowSums(sweep(E3,2,mu)**2)))

b<-sqrt(min(rowSums(sweep(E3,2,mu)**2)))

astar<-as.numeric(a+abs(mu[1]))

bstar<-as.numeric(b+abs(mu[2]))

xstar<-seq(-astar,astar,len=50)

ystar<-seq(-bstar,bstar,len=50)

g<-expand.grid(x=xstar,y=ystar)

p1<-2*g$x*mu[1]/a**2+2*g$y*mu[2]/b**2

p2<-(g$x**2/a**2+g$y**2/b**2)

p3<-mu[1]**2/a**2+mu[2]**2/b**2-1

q<-(p1+sqrt(p1**2-4*p2*p3))/(2*p2)

z<-sqrt(1-(q*g$x)**2-(q*g$y)**2)

zstar<-(z/q)

ind0<-!(q<1)

g$z<-zstar

sc<-matrix(c(rep(c(-1,-1,-1),sum(ind0))),nrow=sum(ind0),byrow=TRUE)

gstar<-rbind(g[ind0,],sc*g[ind0,])

group<-c(rep(1,nrow(gstar)/2),rep(2,nrow(gstar)/2))

gstar$group<-group

gstar <- g

gstar$z[!ind0] <- NA

gstar$z2 <- -gstar$z

wireframe(z + z2 ~ x * y, gstar,colorkey=TRUE,drape=TRUE, scales=list(arrows=FALSE))

8.      实现类似.NET LINQ功能的二元操作符

`%then%` = function(x, body) {

    x= substitute(x)

   fl = as.list(substitute(body))

   car = fl[[1L]]

   cdr = {

       if (length(fl) == 1)

           list()

       else

           fl[-1L]

    }

   combined = as.call(

       c(list(car, x), cdr)

    )

   eval(combined, parent.frame())

}

df = data.frame(x = 1:7)

df %then% subset(x > 2) %then% print

This prints

  x

3 3

4 4

5 5

6 6

7 7

(data.frame(

    x= c(1, 1, 1, 2, 2, 2),

    y= runif(6)

)

   %then% subset(y > 0.2)

   %then% ddply(.(x), summarize,

           ysum   = sum(y),

           ycount = length(y)

       )

   %then% print

)

9.      提取table函数中的频数

freq <- table(c(‘a‘,‘b‘,‘c‘,‘b‘,‘c‘,‘a‘,‘d‘))

Mat <- as.matrix(freq)

Mat[1:nrow(Mat)]

10. 创建使用ComboBox控件的界面

需要安装gWidgets2,gWidgets2RGtk2包

library(gWidgets2)

data(mtcars)

testdf <- data.frame(a=1:3, b= 1:3)

## list data frame names in envir

dfnms <- names(Filter(is.data.frame,mget(ls())) )

lsNms <- function(d,envir=.GlobalEnv)  names(get(d,envir=envir))

w <- gwindow("two combos")

g <- glayout(cont=w)

g[1,1] <- "Data frames:"

g[1,2] <- (dfs <- gcombobox(dfnms,cont=g))

g[2,1] <- "Variables:"

g[2,2] <- (vnames <- gcombobox(character(0),cont=g))

addHandlerChanged(dfs,handler=function(...)  vnames[] <-lsNms(svalue(dfs)))

11. ComboBox用户界面示例

library(gWidgets)

library(gWidgetsRGtk2)

options(guiToolkit="RGtk2")

w <- gwindow()

g <- ggroup(cont=w)

do_expand=TRUE

options <- glayout(cont=g, spacing=5,expand=do_expand)

items <- ""

options[1,1] = "vanilla"

options[1,2] <- gcombobox(items,cont=options)

options[2,1] = "expand"

options[2,2, expand=TRUE] <-gcombobox(items, cont=options)

options[3,1] = "expand, fill"

options[3,2, expand=TRUE,fill="y"] <- gcombobox(items, cont=options)

options[4,1] = "size"

options[4,2] <- (cb <-gcombobox(items, cont=options))

size(cb) <- c(250, -1)

## populate comboboxes

items <- state.name

sapply(options[,2], function(i) i[] <-items)

12. tcltk2包的ComboBox示例

library(tcltk2)

root<-tktoplevel()

v <- tclVar()

d <- tk2combobox(root, textvariable=v)

tkpack(d)

# works

tkconfigure(d, values=c("a string withspaces", "a second string"))

# inserts four items instead of one

spaceystr <- tclVar("a string withspaces")

tkconfigure(d, textvariable = spaceystr)

13.选择文件并将文件列入ComboBox的界面示例

library(gWidgets)

w <- gwindow("Testing",visible=FALSE)

g <- ggroup(cont=w, horizontal=FALSE)

fb <- gfilebrowse("Choose a CSVfile", quote=FALSE,

                  filter = list("CSVfiles"=list(patterns="*.csv")),

                  cont=g)

cb <- gcombobox("", cont=g)

addHandlerChanged(fb,handler=function(h,...) {

    x<- read.csv(svalue(fb))

   cb[] <- colnames(x)

})

visible(w) <- TRUE

14. 获取文件属性：大小、创建时间、修改时间等等

file.info("C:/Trace.txt")

            size isdir mode              mtime               ctime               atime exe

C:/Trace.txt    3 FALSE 666 2014-11-10 11:00:49 2013-12-24 17:51:18 2013-12-24 17:51:18  no

15. &和&&，|和||的区别

&和&&是“逻辑与”运算符，|和||是“逻辑或”运算符

对于两个向量来说，&和|会依次对两个向量中对应的数值进行逻辑运算，返回一个布尔值向量；而&&和||仅对第一个元素进行逻辑运算，仅返回一个布尔值。

> aa <-c(1,2,3,4,5,6)

> bb <-c(0,1,0,2,3,4)

> aa & bb

[1] FALSE  TRUE FALSE TRUE  TRUE  TRUE

> aa &&bb

[1] FALSE

> aa | bb

[1] TRUE TRUE TRUETRUE TRUE TRUE

> aa || bb

[1] TRUE

R语言基础编程技巧汇编 - 23

标签：r语言   数据分析   数据挖掘   机器学习   

原文地址：http://blog.csdn.net/liu7788414/article/details/44999031