[] 和 $ 运算符之间用于子集化的区别 [英] Difference between [] and $ operators for subsetting
问题描述
我正在尝试使用变量名称对数据框进行子集化.我有它的工作，但有一部分我不太明白.
I am trying to subset a data frame by using a variable name. I have it working but there is a part which I don't quite understand.
最初我有这个:rownames (mtcars[mtcars$hp >150,]).
然后，我想将hp"分配给一个变量，而不是硬编码hp":foo <-hp" 和它的子集.我使用这个:rownames (mtcars[mtcars[foo] >150,]).(感谢 链接这阻止了我使用 $ 运算符.)
Then, rather than hard-coding "hp", I wanted to assign "hp" to a variable: foo <- "hp" and subset with that. I got it working using this: rownames (mtcars[mtcars[foo] >150,]). (Thanks to link which stopped me from playing with the $ operator.)
但是，在我构建此声明时，我注意到两者之间存在差异.对于 mtcars$hp >150，我得到这个输出:
But, as I was building up this statement, I noticed there was a difference between the two. For mtcars$hp > 150, I get this output:
[1] FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE
[13] TRUE TRUE TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE
[25] TRUE FALSE FALSE FALSE TRUE TRUE TRUE FALSE
对于 mtcars[foo] >150，我明白了:
hp
Mazda RX4 FALSE
Mazda RX4 Wag FALSE
Datsun 710 FALSE
Hornet 4 Drive FALSE
Hornet Sportabout TRUE
...
这两个是同一个类型"吗?R 显示第一个没有行名而第二个有行名的原因是什么?
Are these two of the same "type"? Is there any reason why R displays the first one without rownames and the second one with rownames?
也许我天真地认为 $ 和 [] 或多或少是等价的.我可以得到相同的最终结果，但我很好奇并担心我的假设是否有误.还好"，我忽略了这个差异，继续进行，得到了相同的最终结果.
Perhaps I've naively thought that $ and [] were more or less equivalent. I can get the same final result, but I am curious and worried if my assumptions had been wrong. "Fortunately", I ignored this difference and carried on and got the same final result.
谢谢！
推荐答案
下面我们将使用一行数据框以提供更简洁的输出:
Below we will use the one-row data frame in order to provide briefer output:
mtcars1 <- mtcars[1, ]
注意这些之间的差异.我们可以像class(mtcars["hp"])一样使用class来调查返回值的类.
Note the differences among these. We can use class as in class(mtcars["hp"]) to investigate the class of the return value.
前两个对应问题中的代码，分别返回一个数据框和一个普通向量.[ 和 $ 之间的主要区别在于 [ (1) 可以指定多列，(2) 允许传递变量作为索引和 (3) 返回一个数据框(尽管稍后参见示例)而 $ (1) 只能指定一个列，(2) 索引必须是硬编码的，并且 (3) 它返回一个矢量.
The first two correspond to the code in the question and return a data frame and plain vector respectively. The key differences between [ and $ are that [ (1) can specify multiple columns, (2) allows passing of a variable as the index and (3) returns a data frame (although see examples later on) whereas $ (1) can only specify a single column, (2) the index must be hard coded and (3) it returns a vector.
mtcars1["hp"] # returns data frame
## hp
## Mazda RX4 110
mtcars1$hp # returns plain vector
## [1] 110
索引是单个元素的其他示例.请注意，下面的第一个和第二个示例实际上与 drop = TRUE 是默认值相同.
Other examples where index is a single element. Note that the first and second examples below are actually the same as drop = TRUE is the default.
mtcars1[, "hp"] # returns plain vector
## [1] 110
mtcars1[, "hp", drop = TRUE] # returns plain vector
## [1] 110
mtcars1[, "hp", drop = FALSE] # returns data frame
## hp
## Mazda RX4 110
还有 [[ 运算符，它类似于 $ 运算符，除了它可以接受变量作为索引，而 $ 需要要硬编码的索引:
Also there is the [[ operator which is like the $ operator except it can accept a variable as the index whereas $ requires the index to be hard coded:
mtcars1[["hp"]] # returns plain vector
## [1] 110
其他索引指定多个元素的情况.$ 和 [[ 不能与多个元素一起使用，因此这些示例仅使用 [:
Others where index specifies multiple elements. $ and [[ cannot be used with multiple elements so these examples only use [:
mtcars1[c("mpg", "hp")] # returns data frame
## mpg hp
## Mazda RX4 21 110
mtcars1[, c("mpg", "hp")] # returns data frame
## mpg hp
## Mazda RX4 21 110
mtcars1[, c("mpg", "hp"), drop = FALSE] # returns data frame
## mpg hp
## Mazda RX4 21 110
mtcars1[, c("mpg", "hp"), drop = TRUE] # returns list
## $mpg
## [1] 21
##
## $hp
## [1] 110
[
mtcars[foo] 如果 foo 是具有多个元素的向量，则可以返回多于一列，例如mtcars[c("hp", "mpg")]，并且在所有情况下，返回值都是一个 data.frame，即使 foo 只有一个元素(因为它在问题中确实如此).
mtcars[foo] can return more than one column if foo is a vector with more than one element, e.g. mtcars[c("hp", "mpg")], and in all cases the return value is a data.frame even if foo has only one element (as it does in the question).
还有 mtcars[, foo, drop = FALSE] 返回与 mtcars[foo] 相同的值，所以它总是返回一个数据帧.drop = TRUE 在 foo 指定多列的情况下，它将返回一个列表而不是一个 data.frame，如果它指定一个单列，则返回列本身.
There is also mtcars[, foo, drop = FALSE] which returns the same value as mtcars[foo] so it always returns a data frame. With drop = TRUE it will return a list rather than a data.frame in the case that foo specifies multiple columns and returns the column itself if it specifies a single column.
[[
另一方面 mtcars[[foo]] 仅在 foo 有一个元素并且返回该列而不是数据框时才有效.
On the other hand mtcars[[foo]] only works if foo has one element and it returns that column, not a data frame.
$
mtcars$hp 也仅适用于单个列，例如 [[，并返回该列，而不是包含该列的数据框.
mtcars$hp also only works for a single column, like [[, and returns the column, not a data frame containing that column.
mtcars$hp 就像 mtcars[["hp"]];但是，不可能通过 $ 传递变量索引.只能使用 $ 对索引进行硬编码.
mtcars$hp is like mtcars[["hp"]]; however, there is no possibility to pass a variable index with $. One can only hard-code the index with $.
子集
请注意，这是有效的:
subset(mtcars, hp > 150)
返回包含那些 hp 列超过 150 的行的数据框:
returning a data frame containing those rows where the hp column exceeds 150:
mpg cyl disp hp drat wt qsec vs am gear carb
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
其他对象
以上属于数据帧，但其他可以使用 $、[ 和 [[ 的对象将有自己的规则.特别是如果 m 是一个矩阵，例如m <- as.matrix(BOD)，那么m[, 1]是一个向量，不是一列矩阵，而是m[, 1,drop = FALSE] 是一列矩阵.m[[1]] 和 m[1] 都是 m 的第一个元素，而不是第一列.m$a 根本不起作用.
The above pertain to data frames but other objects that can use $, [ and [[ will have their own rules. In particular if m is a matrix, e.g. m <- as.matrix(BOD), then m[, 1] is a vector, not a one column matrix, but m[, 1, drop = FALSE] is a one column matrix. m[[1]] and m[1] are both the first element of m, not the first column. m$a does not work at all.
帮助
有关详细信息，请参阅 ?Extract.此外，?"$"、?"[" 和 ?"[[" 也都到达同一页面.
See ?Extract for more information. Also ?"$", ?"[" and ?"[[" all get to the same page, as well.
这篇关于[] 和 $ 运算符之间用于子集化的区别的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
