R中的子集()与$

subset() in R with $

我试图理解 R 中 subset() 函数的怪癖以及 $ 运算符的使用。我将使用 R 中的 CO2 数据集作为示例:

我可以运行

sub <- subset(CO2, CO2$Type=="Quebec")

没有错误地到达与我运行

相同的数据集
sub <- subset(CO2, Type=="Quebec")

但是,我观察到情况并非总是如此。

有时在 subset() 函数中包含 $ 会产生以下错误

$ operator is invalid for atomic vectors

是什么触发了“$ operator is invalid for atomic vectors”错误? 为什么在某些情况下允许 $(如上面的 CO2 示例)但在其他情况下不允许?(当我通过 read.csv() 和有时我在尝试使用 $ 进行子集化时出现错误,有时我没有任何可辨别的模式)

谢谢!

根据下面的评论,我正在尝试 post 可重现的示例。

这里是触发错误的情况:

    Moose<-structure(list(Moose = 1:25, Tagging_Loc = structure(c(1L, 1L, 
2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 
2L, 1L, 1L, 2L, 1L, 2L, 2L), .Label = c("A", "B"), class = "factor"), 
    Gender = structure(c(2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 
    2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 
    2L), .Label = c("F", "M"), class = "factor"), Age = c(20L, 
    23L, 14L, 15L, 10L, 9L, 5L, 10L, 19L, 22L, 21L, 21L, 7L, 
    16L, 19L, 9L, 23L, 5L, 9L, 10L, 16L, 8L, 13L, 14L, 6L), Weight = c(1366L, 
    1006L, 888L, 1359L, 899L, 635L, 400L, 1000L, 1012L, 1480L, 
    1001L, 1100L, 482L, 1414L, 971L, 725L, 1400L, 416L, 790L, 
    970L, 921L, 560L, 1103L, 904L, 669L), Distance = c(250.5, 
    410.239, 457.6402591, 245.8523, 430.9975, 308.8673107, 212.5212497, 
    414.2093545, 439.6581, 215.6491489, 464.2384, 425.4256828, 
    233.5635555, 207.98, 453.7098751, 390.0506365, 235.5212497, 
    207.368, 427.5084899, 443.0452824, 459.8999274, 274.6856592, 
    350.5661674, 456.9600032, 330.146)), .Names = c("Moose", 
"Tagging_Loc", "Gender", "Age", "Weight", "Distance"), class = "data.frame", row.names = c(NA, 
-25L))

sub_Moose<-subset(Moose, Moose$Tagging_Loc=="A")

sub_Moose<-subset(Moose, Tagging_Loc=="A")'

但是如果我只更改数据集的名称,subset() 运行 的两个版本都很好 - 没有错误:

    mOose<-structure(list(Moose = 1:25, Tagging_Loc = structure(c(1L, 1L, 
2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 
2L, 1L, 1L, 2L, 1L, 2L, 2L), .Label = c("A", "B"), class = "factor"), 
    Gender = structure(c(2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 
    2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 
    2L), .Label = c("F", "M"), class = "factor"), Age = c(20L, 
    23L, 14L, 15L, 10L, 9L, 5L, 10L, 19L, 22L, 21L, 21L, 7L, 
    16L, 19L, 9L, 23L, 5L, 9L, 10L, 16L, 8L, 13L, 14L, 6L), Weight = c(1366L, 
    1006L, 888L, 1359L, 899L, 635L, 400L, 1000L, 1012L, 1480L, 
    1001L, 1100L, 482L, 1414L, 971L, 725L, 1400L, 416L, 790L, 
    970L, 921L, 560L, 1103L, 904L, 669L), Distance = c(250.5, 
    410.239, 457.6402591, 245.8523, 430.9975, 308.8673107, 212.5212497, 
    414.2093545, 439.6581, 215.6491489, 464.2384, 425.4256828, 
    233.5635555, 207.98, 453.7098751, 390.0506365, 235.5212497, 
    207.368, 427.5084899, 443.0452824, 459.8999274, 274.6856592, 
    350.5661674, 456.9600032, 330.146)), .Names = c("Moose", 
"Tagging_Loc", "Gender", "Age", "Weight", "Distance"), class = "data.frame", row.names = c(NA, 
-25L))

sub_Moose<-subset(mOose, mOose$Tagging_Loc=="A")

sub_Moose<-subset(mOose, Tagging_Loc=="A")

不要对子集使用 $!要么使用

sub <- subset(CO2, Type=="Quebec")

或使用

sub <- CO2[CO2$Type=="Quebec", ]

subset() 函数通过评估 data.frame 环境中的所有符号来工作。在您的 Moose 示例中,您的 data.frame Moose 有一个列名称 Moose。所以当你 运行

sub_Moose <- subset(Moose, Moose$Tagging_Loc=="A")

表达式 Moose$Tagging_Loc=="A" 在 data.frame 的环境中计算。在那个 data.frame 中,有一个名为 Moose 的列,因此在找到同名的 data.frame 之前计算列向量。请注意,with()subset() 非常相似,因为它在环境或 data.frame 的上下文中计算表达式。观察

class(Moose)
# [1] "data.frame"
with(Moose, class(Moose))
# [1] "integer"
class(Moose$Moose)
# [1] "integer"

所以 Moose$Tagging_Loc=="A" 仅在 Moose 是 data.frame 时有效,但是当您使用 subset() 时,Moose 是整数向量,因为它正在寻找专栏第一。