R 学习笔记《九》 R语言初学者指南--循环和函数
1 循环
载入数据
setwd("E:/R/R-beginer-guide/data/RBook")
Owls <- read.table(file="Owls.txt",header=TRUE)
names(Owls)
str(Owls) 弄清鸟巢的名字
> unique(Owls$Nest) [1] AutavauxTV Bochet Champmartin ChEsard [5] Chevroux CorcellesFavres Etrabloz Forel [9] Franex GDLV Gletterens Henniez [13] Jeuss LesPlanches Lucens Lully [17] Marnand Moutet Murist Oleyes [21] Payerne Rueyes Seiry SEvaz [25] StAubin Trey Yvonnand 27 Levels: AutavauxTV Bochet Champmartin ChEsard ... Yvonnand >提取属于某个鸟巢的数据并画出ArrivalTime 和NegPerChick变量的plot图
Owls.ATV <- Owls[Owls$Nest=="AutavauxTV",]
plot(x=Owls.ATV$ArrivalTime,y=Owls.ATV$NegPerChick,
xlab="Arrival Time",main="AutauxTV",ylab="Negotiation behavaiour")
通用一点：
Nest.i <- "Bochet"
Owls.i <- Owls[Owls$Nest == Nest.i,]
plot(x=Owls.i$ArrivalTime,y=Owls.i$NegPerChick,
xlab="Arrival Time",main="AutauxTV",
ylab="Negotiation behavaiour") 将plot结果保存为jpeg文件
setwd("E:/R/R-beginer-guide/jpegs")
Nest.i <- "Bochet"
Owls.i <- Owls[Owls$Nest == Nest.i,]
YourFileName <- paste(Nest.i,".jpeg",sep="")
jpeg(file=YourFileName)
plot(x=Owls.i$ArrivalTime,y=Owls.i$NegPerChick,
xlab="Arrival Time",main="AutauxTV",
ylab="Negotiation behavaiour")
dev.off() 构造循环:
ALLNests <- unique(Owls$Nest)
for(i in 1:27){
Nest.i <- ALLNests[i]
Owls.i <- Owls[Owls$Nest == Nest.i,]
YourFileName <- paste(Nest.i,".jpeg",sep="")
jpeg(file=YourFileName)
plot(x=Owls.i$ArrivalTime,y=Owls.i$NegPerChick,
xlab="Arrival Time",main="AutauxTV",
ylab="Negotiation behavaiour")
dev.off()
} 2 函数
载入数据:
setwd("E:/R/R-beginer-guide/data/RBook")
Veg <- read.table(file="Vegetation2.txt",header=TRUE)
names(Veg) 定义函数:
NAPerVariable <- function(X1){
D1 <- is.na(X1)
colSums(D1)
}
执行函数:
>
> NAPerVariable(Veg[,5:24])
R ROCK LITTER ML BARESOIL FallPrec SprPrec SumPrec
0 0 0 0 0 0 0 0
WinPrec FallTmax SprTmax SumTmax WinTmax FallTmin SprTmin SumTmin
0 0 0 0 0 0 0 0
WinTmin PCTSAND PCTSILT PCTOrgC
0 0 0 0
> 函数解释:
函数的第一个参数X1列表是标量，行表是观察值.is.na(X1)生成了一个与X1维数相同的布尔矩阵,如果X1中某个值为确实值，那么得到的矩阵对应的元素的值就是TRUE，否则为FALSE。colSums是R自带的一个函数,其作用是计算每一列中元素的和.一般colSums作用与数值矩阵，但是当其作用与布尔矩阵时,将TRUE转化为1将FALSE转化为0.
使用函数:
载入数据:
Parasite <- read.table(file="CodParasite.txt",header=TRUE) names(Parasite)
> NAPerVariable(Parasite)
Sample Intensity Prevalence Year Depth Weight Length
0 57 0 0 0 6 6
Sex Stage Age Area
0 0 0 0
> 变量Intensity中有57个缺失值,weight和Length有6个缺失值
定义另外一函数，统计每个变量中到底有多少个0
ZeroPerVaviable <- function(X1){
D1=(X1==0)
colSums(D1)
} 运用这个函数:
> ZeroPerVaviable <- function(X1){
+ D1=(X1==0)
+ colSums(D1)
+ }
>
> ZeroPerVaviable(Parasite)
Sample Intensity Prevalence Year Depth Weight Length
0 NA 654 0 0 NA NA
Sex Stage Age Area
82 82 84 0
> 有NA值，从新定义函数:
ZeroPerVaviable <- function(X1){
D1=(X1==0)
colSums(D1,na.rm=TRUE)
}
> ZeroPerVaviable <- function(X1){
+ D1=(X1==0)
+ colSums(D1,na.rm=TRUE)
+ }
>
> ZeroPerVaviable(Parasite)
Sample Intensity Prevalence Year Depth Weight Length
0 654 654 0 0 0 0
Sex Stage Age Area
82 82 84 0
> 多参数函数
VariableInfo <- function(X1,Choice1){
if(Choice1 == "Zeros"){
D1=(X1==0)
}
if(Choice1 == "NAs"){
D1 <- is.na(X1)
}
colSums(D1,na.rm=TRUE)
} 使用:
> VariableInfo <- function(X1,Choice1){
+ if(Choice1 == "Zeros"){
+ D1=(X1==0)
+ }
+ if(Choice1 == "NAs"){
+ D1 <- is.na(X1)
+ }
+ colSums(D1,na.rm=TRUE)
+ }
>
> VariableInfo(Parasite,"Zeros")
Sample Intensity Prevalence Year Depth Weight Length
0 654 654 0 0 0 0
Sex Stage Age Area
82 82 84 0
>
> VariableInfo(Parasite,"NAs")
Sample Intensity Prevalence Year Depth Weight Length
0 57 0 0 0 6 6
Sex Stage Age Area
0 0 0 0
> 设计稳健的函数，默认值，拼写容错，ifelse使用
VariableInfo <- function(X1,Choice1="Zeros"){
if(Choice1 == "Zeros"){
D1=(X1==0)
}
if(Choice1 == "NAs"){
D1 <- is.na(X1)
}
if(Choice1 !="Zeros" & Choice1 != "NAs"){
print("you made a typo")
} else{
colSums(D1,na.rm=TRUE)
}
}
> VariableInfo <- function(X1,Choice1="Zeros"){
+ if(Choice1 == "Zeros"){
+ D1=(X1==0)
+ }
+ if(Choice1 == "NAs"){
+ D1 <- is.na(X1)
+ }
+ if(Choice1 !="Zeros" & Choice1 != "NAs"){
+ print("you made a typo")
+ } else{
+ colSums(D1,na.rm=TRUE)
+ }
+
+ }
> VariableInfo(Parasite,"dsa")
[1] "you made a typo"
>