[R language] [3] apply, tapply, lapply, sapply, mapply and par function related parameters

前言

RThe language drawing looks terse though,But there are too many function parameters——虽然学了4天,But it's like a week of study,In fact, my current goal is to draw nice pictures,Then it would be nice to have a drawing template.Because the function calls in the book I bought are too concise,df$SODetc. Variable data comes from nowhere,So you have to accumulate templates yourself.

这里存在一些问题,Even if you have learned knowledge, you will have an impression even if you forget it,But if you forget too much, you have to learn it again！Like picking it up in months or years,used several timesmatlab,Every time I have to retype the syntax code and drawing code for a day or two,才能找到感觉……

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apply

m <- array(
  c(1:10),
  dim=c(2,5)
  # byrow=TRUE #按行填充 array没有这个参数
)
m
a=apply(m,1,sum)   #按行求和
a
a=apply(m,2,sum)   #按列求和
a

> m
     [,1] [,2] [,3] [,4] [,5]
[1,]    1    3    5    7    9
[2,]    2    4    6    8   10
> a
[1] 25 30
> a
[1]  3  7 11 15 19

a <- array(
  c(1:8),
  dim=c(2,2,2)
)
a
res=apply(a,1,sum)    #第1层2x2,第2层2x2
res
res=apply(a,2,sum)    #第1片2x2,第2片2x2
res
res=apply(a,c(1,2),sum)   #6根1x2
res

> a
, , 1

     [,1] [,2]
[1,]    1    3
[2,]    2    4

, , 2

     [,1] [,2]
[1,]    5    7
[2,]    6    8
> res
[1] 16 20
> res
[1] 14 22
> res
     [,1] [,2]
[1,]    6   10
[2,]    8   12

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tapply 分组计算

v <- c(1:5)
v
group <- c(rep('a',3),rep('b',2))
group

#a b
#6 9
tapply(v,group,sum)  #按group分组,将对应的vadd up the elements in 



mat <- matrix(c(1:10),nrow=2)
mat
group <- matrix(c(rep(1,5),rep(2,5)),nrow=2)
group

# 1 2
#15 40
# tapply(mat,group,sum) #按group分组,将对应的matadd up the elements in 

#1 2
#3 8
tapply(mat,group,mean) #按group分组,将对应的matThe elements in are added together to find the mean

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lapply Multi-element computations are grouped by row

需要转成data.frame

l <- list(
  a=c(1:5),
  b=c(6:10)
)
#返回一个list
res <- lapply(l,mean )   # 3 8
#转成data.frame
res <- as.data.frame(res)
res

> res
  a b
1 3 8

rownames <- paste('a',LETTERS,sep='#')
rownames

#去掉前缀a#
names <- unlist(lapply(
  strsplit(rownames,'#'),
  function(x) x[2]   #取第二个元素
))
names

> rownames
 [1] "a#A" "a#B" "a#C" "a#D" "a#E" "a#F" "a#G" "a#H" "a#I"
[10] "a#J" "a#K" "a#L" "a#M" "a#N" "a#O" "a#P" "a#Q" "a#R"
[19] "a#S" "a#T" "a#U" "a#V" "a#W" "a#X" "a#Y" "a#Z"
> names
 [1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N"
[15] "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"

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sapply 简化版lapply

l <- list(
  a=c(1:5),
  b=c(6:10)
)
sapply(l,mean,simplify=T) #T表示不用unlist了

a b 
3 8 

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mapply 多data计算

#可以传入多个data
mapply(
  sum,
  list(a=1,b=2,c=3),
  list(a=10,b=20,d=30)
)

mapply(
  sum,
  list(a=1,b=2,c=3),
  list(a=10,b=20,c=30),
  list(a=15,b=25,d=35)
)

mapply(
  function(x,y) x%%y,
  c(1:50),
  c(1:10)
)

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par

bty The border of the figure

par(mfrow=c(3,2))
bty <- c('o','l','7','c',']','u')    #btyis the border of the graph
for(i in 1:6){
    
  par(bty=bty[i])
  plot(1:5,main=paste('bty=',bty[i],sep=':'))
}

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fg/bg 前景/背景

The foreground is the border of the graph

par(
  fg='red',          #前景(边框)
  bg='white'         #背景
)
par(mfrow=c(1,1),
    font=3,          #1普通,2粗体,3斜体,4粗斜体
    family='serif')  #字体serif就是Times New Roman


#气泡图
plot(1:5,
     main="Times New Roman",
     cex=1:5,        #cex是点的大小
     col=1:5         #col是颜色
)

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las Coordinate axis horizontal and vertical numbers

#lasIndicates the horizontal and vertical axis numbers
par(mfrow=c(2,2))
for( i in 0:3){
    
  par(las=i)
  plot(1:5,main=paste('las=',i))
}

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lty 线的类型

par(mfrow=c(2,3))
for( i in 1:6){
    
  par(lty=i,lwd=i/2)   #lwd默认是1,线段粗细
  plot(1:5,type='l',main=paste('lty=',i),sub='subtitle')
}

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