条件赋值 frame$col <- val with magrittr

Question

基于 Iris$Petal.Length 分配 Iris$column 的 Magrittr 语法是什么？没有 Magrittr 的示例：

df      <- iris[47:56,]
df$val1 <- NA                                           ## create column
df$val1[which(df$Petal.Length < 1.52)]                         <- "cake"
df$val1[which(df$Petal.Length > 1.55 & df$Petal.Length <=4.55)] <- "pie"
df$val1[which(df$Petal.Length > 4.55)]                        <- "apple"

head(df)

这导致：

Petal.Length Petal.Width  Species    val1

1.6                0.2     setosa     pie

1.4                0.2     setosa     cake

1.5                0.2     setosa     cake

1.4                0.2     setosa     cake

1.4                1.4.  versicolor   apple

Answer 1

我们可以用case_when

res <- df %>% 
          mutate(val1 = case_when(Petal.Length < 1.52 ~ 'cake',
                  Petal.Length > 1.55 & Petal.Length <= 4.55 ~ 'pie',
                   Petal.Length > 4.55 ~'apple'))
head(res, 5)
#  Sepal.Length Sepal.Width Petal.Length Petal.Width    Species  val1
#1          5.1         3.8          1.6         0.2     setosa   pie
#2          4.6         3.2          1.4         0.2     setosa  cake
#3          5.3         3.7          1.5         0.2     setosa  cake
#4          5.0         3.3          1.4         0.2     setosa  cake
#5          7.0         3.2          4.7         1.4 versicolor apple

Answer 2

与您所写内容完全等效的 magrittr 语法是：

df %>% transform(val1 = NA) %$%
  inset(.,Petal.Length < 1.52,"val1","cake") %$%
  inset(.,Petal.Length > 1.55 & Petal.Length <= 4.55,"val1","pie") %$%
  inset(.,Petal.Length > 4.55,"val1","apple")

或者对magrittr的别名非常热心：

df %>% transform(val1 = NA) %$%
  inset(.,Petal.Length %>% is_less_than(1.52),"val1","cake") %$%
  inset(.,Petal.Length %>% is_greater_than(1.55) & Petal.Length %>% 
  is_weakly_less_than(4.55),"val1","pie") %$%
  inset(.,Petal.Length %>% is_greater_than(4.55),"val1","apple")

还有一个变体：

df %>% transform(val1 = NA) %$%
  inset(.,Petal.Length %>% is_less_than(1.52),"val1","cake") %$%
  inset(.,Petal.Length %>% {is_greater_than(.,1.55) & is_weakly_less_than(.,4.55)},"val1","pie") %$%
  inset(.,Petal.Length %>% is_greater_than(4.55),"val1","apple")

前两个在 base 中严格等同于此（管道除外！）：

df %>% transform(val1 = NA) %$%
  `[<-`(.,Petal.Length < 1.52,"val1","cake") %$%
  `[<-`(.,Petal.Length > 1.55 & Petal.Length <= 4.55,"val1","pie") %$%
  `[<-`(.,Petal.Length > 4.55,"val1","apple")

变体等同于：

df %>% transform(val1 = NA) %$%
  `[<-`(.,Petal.Length < 1.52,"val1","cake") %$%
  `[<-`(.,Petal.Length %>% {`>`(.,1.55) & `<=`(.,4.55)},"val1","pie") %$%
  `[<-`(.,Petal.Length > 4.55,"val1","apple")

我使用 transform 因为它是一个 base 函数，而 mutate 是一个 dplyr 函数，但它们在这里的工作方式相同。

有关所有别名的定义，请参阅：?extract

条件赋值 frame$col <- val with magrittr

Conditional Assignment frame$col <- val with magrittr

r

variable-assignment

magrittr