虽然这是一个相当老的问题，但我必须说，它正好触及了我在R的第一步中所缺失的知识——即如何将我手中的数据表示为R中的对象，或者如何从现有的对象中进行选择。对于一个R新手来说，从一开始就“在R盒子里”思考并不容易。

所以我自己开始使用下面的拐杖，这帮助我找到什么对象使用什么数据，基本上想象现实世界的用法。

虽然我没有给出问题的确切答案，但下面的简短文本可能会帮助那些刚刚以R开头并提出类似问题的读者。

Atomic vector ... I called that "sequence" for myself, no direction, just sequence of same types. [ subsets. Vector ... the sequence with one direction from 2D, [ subsets. Matrix ... bunch of vectors with the same length forming rows or columns, [ subsets by rows and columns, or by sequence. Arrays ... layered matrices forming 3D Dataframe ... a 2D table like in excel, where I can sort, add or remove rows or columns or make arit. operations with them, only after some time I truly recognized that data frame is a clever implementation of list where I can subset using [ by rows and columns, but even using [[. List ... to help myself I thought about the list as of tree structure where [i] selects and returns whole branches and [[i]] returns item from the branch. And because it is tree like structure, you can even use an index sequence to address every single leaf on a very complex list using its [[index_vector]]. Lists can be simple or very complex and can mix together various types of objects into one.

所以对于列表，你可以根据情况选择更多的方法，就像下面的例子。

l <- list("aaa",5,list(1:3),LETTERS[1:4],matrix(1:9,3,3))
l[[c(5,4)]] # selects 4 from matrix using [[index_vector]] in list
l[[5]][4] # selects 4 from matrix using sequential index in matrix
l[[5]][1,2] # selects 4 from matrix using row and column in matrix

这种思维方式对我帮助很大。

为什么这两个不同的操作符[]和[[]]返回相同的结果?

x = list(1, 2, 3, 4)

[ ] provides sub setting operation. In general sub set of any object will have the same type as the original object. Therefore, x[1] provides a list. Similarly x[1:2] is a subset of original list, therefore it is a list. Ex. x[1:2] [[1]] [1] 1 [[2]] [1] 2 [[ ]] is for extracting an element from the list. x[[1]] is valid and extract the first element from the list. x[[1:2]] is not valid as [[ ]] does not provide sub setting like [ ]. x[[2]] [1] 2 > x[[2:3]] Error in x[[2:3]] : subscript out of bounds

关于大家提出的问题，我愿按顺序回答并举例说明:

1)如果return语句添加了一个列表，则返回一个列表。考虑

 R> retList <- function() return(list(1,2,3,4)); class(retList())
 [1] "list"
 R> notList <- function() return(c(1,2,3,4)); class(notList())
 [1] "numeric"
 R> 

2)没有设置名称:

R> retList <- function() return(list(1,2,3,4)); names(retList())
NULL
R> 

3)它们不会返回相同的东西。你的例子给出了

R> x <- list(1,2,3,4)
R> x[1]
[[1]]
[1] 1
R> x[[1]]
[1] 1

其中x[1]返回x的第一个元素——这和x是一样的。每个标量都是长度为1的向量。另一方面，x[[1]]返回列表的第一个元素。

4)最后，两者的不同之处在于，它们分别创建一个包含四个标量的列表和一个包含单个元素的列表(恰好是一个包含四个元素的向量)。

虽然这是一个相当老的问题，但我必须说，它正好触及了我在R的第一步中所缺失的知识——即如何将我手中的数据表示为R中的对象，或者如何从现有的对象中进行选择。对于一个R新手来说，从一开始就“在R盒子里”思考并不容易。

所以我自己开始使用下面的拐杖，这帮助我找到什么对象使用什么数据，基本上想象现实世界的用法。

虽然我没有给出问题的确切答案，但下面的简短文本可能会帮助那些刚刚以R开头并提出类似问题的读者。

Atomic vector ... I called that "sequence" for myself, no direction, just sequence of same types. [ subsets. Vector ... the sequence with one direction from 2D, [ subsets. Matrix ... bunch of vectors with the same length forming rows or columns, [ subsets by rows and columns, or by sequence. Arrays ... layered matrices forming 3D Dataframe ... a 2D table like in excel, where I can sort, add or remove rows or columns or make arit. operations with them, only after some time I truly recognized that data frame is a clever implementation of list where I can subset using [ by rows and columns, but even using [[. List ... to help myself I thought about the list as of tree structure where [i] selects and returns whole branches and [[i]] returns item from the branch. And because it is tree like structure, you can even use an index sequence to address every single leaf on a very complex list using its [[index_vector]]. Lists can be simple or very complex and can mix together various types of objects into one.

所以对于列表，你可以根据情况选择更多的方法，就像下面的例子。

l <- list("aaa",5,list(1:3),LETTERS[1:4],matrix(1:9,3,3))
l[[c(5,4)]] # selects 4 from matrix using [[index_vector]] in list
l[[5]][4] # selects 4 from matrix using sequential index in matrix
l[[5]][1,2] # selects 4 from matrix using row and column in matrix

这种思维方式对我帮助很大。

x = list(1, 2, 3, 4)
x2 = list(1:4)
all.equal(x,x2)

不一样，因为1:4等于c(1,2,3,4) 如果你想让它们相同，那么:

x = list(c(1,2,3,4))
x2 = list(1:4)
all.equal(x,x2)

关于其他语言中的向量和哈希/数组概念:

Vectors are the atoms of R. Eg, rpois(1e4,5) (5 random numbers), numeric(55) (length-55 zero vector over doubles), and character(12) (12 empty strings), are all "basic". Either lists or vectors can have names. > n = numeric(10) > n [1] 0 0 0 0 0 0 0 0 0 0 > names(n) NULL > names(n) = LETTERS[1:10] > n A B C D E F G H I J 0 0 0 0 0 0 0 0 0 0 Vectors require everything to be the same data type. Watch this: > i = integer(5) > v = c(n,i) > v A B C D E F G H I J 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > class(v) [1] "numeric" > i = complex(5) > v = c(n,i) > class(v) [1] "complex" > v A B C D E F G H I J 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i 0+0i Lists can contain varying data types, as seen in other answers and the OP's question itself.

我见过一些语言(ruby, javascript)，其中的“数组”可能包含变量数据类型，但例如在c++中，“数组”必须是相同的数据类型。我相信这是一个速度/效率的问题:如果你有一个数字(1e6)，你可以先验地知道它的大小和每个元素的位置;如果某个未知片段中可能包含“紫飞食人”，那么你就必须真正分析这些内容来了解它的基本事实。

当类型得到保证时，某些标准R操作也更有意义。例如cumsum(1:9)是有意义的，而cumsum(list(1,2,3,4,5，'a'，6,7,8,9)则没有意义，因为不能保证类型为double。

关于你的第二个问题:

即使在调用函数时从未传入List，也可以从函数返回List

函数返回的数据类型总是与输入的数据类型不同。Plot返回一个Plot，即使它不接受一个Plot作为输入。Arg返回一个数字，即使它接受了复数。等。

(至于strsplit:源代码在这里。)