R in Action
最新书摘：
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黑涩布朗尼2013-04-28Warning message:describe.by is deprecated. Please use the describeBy function
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黑涩布朗尼2013-04-273 Variables 32 Observations-----------------------------------------------------------------------------------------------------------mpg n missing uniqueMean .05 .10 .25 .50 .75 .90 .95 32 0 25 20.09 12.00 14.34 15.43 19.20 22.80 30.09 31.30 lowest : 10.4 13.3 14.3 14.7 15.0, highest: 26.0 27.3 30.4 32.4 33.9
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黑涩布朗尼2013-04-27> summary(mtcars[vars]) mpg hpwt Min. :10 Min. : 52 Min. :1.5 1st Qu.:15 1st Qu.: 96 1st Qu.:2.6 Median :19 Median :123 Median :3.3 Mean :20 Mean :147 Mean :3.2 3rd Qu.:23 3rd Qu.:180 3rd Qu.:3.6 Max. :34 Max. :335 Max. :5.4
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黑涩布朗尼2013-04-27在描述性统计量的计算方面，R中的选择多得让人尴尬。
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黑涩布朗尼2013-04-26ID <- c(1,1,2,2)Time <- c(1,2,1,2)X1 <- c(5,3,6,2)X2 <- c(6,5,1,4)library(reshape)mydata <- data.frame(ID,Time,X1,X2)md <- melt(mydata, id=(c("ID","Time")))# ID Time variable value#1 11 X1 5# 貌似melt一下 元素的名称都变了# 关于整合Castcast(md,ID~variable,mean)# 任何时间内 ID1和2 X1和X2的均值#ID X1 X2#1 1 4 5.5#2 2 4 2.5#> md[which(md$ID==1 & md$variable=="X1"),]#ID Time variable value#1 11 X1 5#2 12 X1 3#> mean(c(5,3))#[1] 4> md[which(md$ID==1 & md$variable=="X2"),]#ID Time variable value#5 11 X2 6#6 12 X2 5#> mean(c(6,5))#[1] 5.5cast(md,Time~variable,mean)# 在time1和time2上的variable各自的value均值#Time X1 X2#11 5.5 3.5#22 2.5 4.5#> md[which(md$Time==1 & md$variable=="X2"),]#ID Time variable ...
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黑涩布朗尼2013-04-26「把数据折叠起来」
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黑涩布朗尼2013-04-26options(digits=2)#import dataStudent <- c("John Davis","Angela Williams","Bullwinkle Moose","David Jones","Janice Markhammer", "Cheryl Cushing","Reuven Ytzrhak","Greg Knox","Joel England","Mary Rayburn")Math <- c(502,600,412,358,495,512,410,625,573,522)Science <- c(95,99,80,82,75,85,80,95,89,86)English <- c(25,22,18,15,20,28,15,30,27,18)roster <- data.frame(Student,Math,Science,English,stringAsFactors=FALSE)#Step.1 计算综合得分#--scale#attr(,"scaled:center")#Math Science English #501 87 22 #-- 单位标准差 因为各项分值差别过大 标准差和均值没有价值z <- scale(roster[,2:4])#> apply(z,1,mean)#[1] 0.56 0.92 -0.86 -1.16 -0.63 0.35 -1.05 1.34 0.70 -0.18#> z[1,]#Math Science English #0.013 1.078 0.587 #> mean(z[1,])#[1] 0.56#> mean(z[2,])#[1] 0.92score <- apply(z,1,mean)...
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黑涩布朗尼2013-04-24> strDates <- c("2007-06-22","2004-02-13")> as.Date(strDates,"%Y/%m/%d")[1] NA NA> as.Date(strDates,"%Y-%m-%d")[1] "2007-06-22" "2004-02-13"
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黑涩布朗尼2013-04-24par(pin=c(3,3))
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黑涩布朗尼2013-04-24opar <- par(no.readonly=TRUE)
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黑涩布朗尼2013-04-23par(lwd=2,cex=1.5,font.lab=2)plot(dose,drugA,type="b",pch=15,lty=1,col="red",ylim=c(0,60),main="Drug A vs. Drug B",xlab="Drug Dosage",ylab="Drug Response")lines(dose,drugB,type="b",pch=17,lty=2,col="blue")abline(h=c(30),lwd=1.5,lty=2,col="gray")legend("topleft",inset=.05,title="Drug Type",c("A","B"),lty=c(1,2),pch=c(15,17),col=c("red","blue"))
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黑涩布朗尼2013-04-23mylist[["ages"]][1:2]
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黑涩布朗尼2013-04-23mylist <- list(title=g,ages=age,j)
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黑涩布朗尼2013-04-23status_factor_order <- factor(status, order=TRUE, levels=c("Poor","Improved","Excellent"))
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黑涩布朗尼2013-04-23名义型变量和有序型变量在R中成为因子(Factor)。因子在R中非常重要，因为他决定了数据的分析方式以及如何进行视觉呈现。
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黑涩布朗尼2013-04-23dim1 <- c("A1","A2")dim2 <- c("B1","B2","B3")dim3 <- c("C1","C2","C3","C4")z <- array(1:24,c(2,3,4), dimnames=list(dim1,dim2,dim3))z[1,2,3]
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黑涩布朗尼2013-04-23pdf()png()jpeg()bmp()
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黑涩布朗尼2013-04-23setwd("D:/r") 设置当前工作目录getwd() 显示当前工作目录ls()显示当前加载的数据对象有哪些rm() 删除一部分对象 硬盘小或对象太复杂的话。。。history()savehistory()loadhistory()save.image("MyFile") 你每次q()退出的时候都会问你 默认是 .RData文件这两个是最实用的save(cars,file="RCars")load("RCars")可以单独保存一些比较重要的对象文件# 全部保存save(list =ls(all=TRUE), file=".RData")
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黑涩布朗尼2013-05-02> states <- state.x77[,1:6]> cor(states) Population Income Illiteracy Life Exp Murder HS GradPopulation 1.0000 0.208 0.108 -0.0681 0.344 -0.0985Income 0.2082 1.000 -0.437 0.3403 -0.230 0.6199Illiteracy 0.1076 -0.437 1.000 -0.5885 0.703 -0.6572Life Exp -0.0681 0.340 -0.588 1.0000 -0.781 0.5822Murder 0.3436 -0.230 0.703 -0.7808 1.000 -0.4880HS Grad -0.0985 0.620 -0.657 0.5822 -0.488 1.0000