专题3 条件和循环

i = -1
if (i<0) print('up')

## [1] "up"

if (i>0) print('up')

#理解下面代码
if(!require(tidyr)) install.packages('tidyr')

i =1
if (i>0){
  print('+')
} else {
  print("-")
}

## [1] "+"

i = 1
ifelse(i>0,"+","-")

## [1] "+"

x = rnorm(3) # 可以是逻辑值或逻辑值向量
x

## [1] -0.7623049  0.9558385  2.0604772

ifelse(x>0,"+","-")

## [1] "-" "+" "+"

library(stringr)

samples = c("tumor1","tumor2","tumor3","normal1","normal2","normal3")
k1 = str_detect(samples,"tumor");k1

## [1]  TRUE  TRUE  TRUE FALSE FALSE FALSE

ifelse(k1,"tumor","normal")

## [1] "tumor"  "tumor"  "tumor"  "normal" "normal" "normal"

k2 = str_detect(samples,"normal");k2

## [1] FALSE FALSE FALSE  TRUE  TRUE  TRUE

ifelse(k2,"normal","tumor")

## [1] "tumor"  "tumor"  "tumor"  "normal" "normal" "normal"

i = 0
if (i>0){
  print('+')
} else if (i==0) {
  print('0')
} else if (i< 0){
  print('-')
}

## [1] "0"

ifelse(i>0,"+",ifelse(i<0,"-","0"))

## [1] "0"

for( i in 1:4){
  print(i)
}

## [1] 1
## [1] 2
## [1] 3
## [1] 4

par(mfrow = c(2,2))
for(i in 1:4){
  plot(iris[,i],col = iris[,5])
}

pks = c("tidyr","dplyr","stringr")
for(g in pks){
  if(!require(g,character.only = T))
    install.packages(g,ask = F,update = F)
}

library(dplyr)
# case_when() # 可用于将数据转换为分类因子

df <- data.frame(player = c('AJ', 'Bob', 'Chad', 'Dan', 'Eric', 'Frank'),
                 position = c('G', 'F', 'F', 'G', 'C', NA),
                 points = c(12, 15, 19, 22, 32, NA),
                 assists = c(5, 7, 7, 12, 11, NA))
df

##   player position points assists
## 1     AJ        G     12       5
## 2    Bob        F     15       7
## 3   Chad        F     19       7
## 4    Dan        G     22      12
## 5   Eric        C     32      11
## 6  Frank     <NA>     NA      NA

df %>%
  mutate(quality = case_when(points > 20 ~ 'high',
                             points > 15 ~ 'med',
                             TRUE ~ 'low' ))

##   player position points assists quality
## 1     AJ        G     12       5     low
## 2    Bob        F     15       7     low
## 3   Chad        F     19       7     med
## 4    Dan        G     22      12    high
## 5   Eric        C     32      11    high
## 6  Frank     <NA>     NA      NA     low