blocks|key|2325751|text|这是人们想要做的一种常见的事情，特别是当他们来自其他编程语言时。然而，有更好的方法来完成同样的事情，并且您不应该遵循使用assign的建议；这是一个糟糕的建议，以后您可能会后悔。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2325752|我们在R中这样做的方法是使用列表，特别是命名列表：|2325753|x+<-+replicate(1000,rnorm(200,0,1),simplify+=+FALSE)
x+<-+setNames(x,paste0("A",seq_along(x)))|code-block|syntax|javascript|2325754|现在，x是长度为1000的命名列表，每个元素都是正常(0，1)分布中长度为200的向量。|2325755|您可以根据需要通过x[[1]]或x[["A1"]]引用每一个。此外，由于它们都在同一个对象中，所以可以使用像lapply这样的工具轻松地作为一个组对它们进行操作。|2325756|当您发现自己想要创建一个具有相似名称的对象序列时，这应该是一个信号，表明您应该使用一个列表。|2325757|entityMap^0|1O|6|0|0|0|3|1|0|9|6|G|9|1I|6|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@$9|V|A|W|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|X|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|Y|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|Z|8|@$9|10|A|11|B|C]]|D|@]|E|$]]|$1|O|3|P|5|6|7|12|8|@$9|13|A|14|B|C]|$9|15|A|16|B|C]|$9|17|A|18|B|C]]|D|@]|E|$]]|$1|Q|3|R|5|6|7|19|8|@]|D|@]|E|$]]|$1|S|3|-4|5|6|7|1A|8|@]|D|@]|E|$]]]|T|$]]

This is a common sort of thing that people want to do, especially when they are coming from other programming languages. However, there are better ways to accomplish the same thing, and you should not follow recommendations to use <code>assign</code>; that is bad advice that you will likely regret later on.

The way we do this sort of thing in R is to use lists, specifically named lists:

<pre><code>x &lt;- replicate(1000,rnorm(200,0,1),simplify = FALSE)
x &lt;- setNames(x,paste0("A",seq_along(x)))
</code></pre>

Now <code>x</code> is a named list of length 1000, each element is a vector of length 200 from a normal(0,1) distribution.

You can refer to each one via <code>x[[1]]</code> or <code>x[["A1"]]</code> as needed. Additionally, since they are all in the same object, you can operate on the easily as a group using tools like <code>lapply</code>.

Pretty much any time you find yourself wanting to create a sequence of objects with similar names, that should be a signal to you that you should be using a list instead.

blocks|key|41286|text|没有必要用这么多变量来凌乱您的环境，请尝试将它们存储在一个命名列表中。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|41287|l1+<-+setNames(lapply(1:5,+function(x)+rnorm(5)),+paste0("A",+1:5))
l1

#$A1
#[1]++0.4951453+-1.4278665++0.5680115++0.3537730+-0.7757363

#$A2
#[1]+-0.11096037++0.05958700++0.02578168++1.00591996++0.54852030

#$A3
#[1]++0.1058318++0.6988443+-0.8213525+-0.1072289++0.8757669

#$A4
#[1]+-0.6629634++0.8321713+-0.3073465+-0.2645550+-1.0064132

#$A5
#[1]++2.2191246++0.2054360+-0.1768357++1.6875302+-1.1495807|code-block|syntax|javascript|41288|现在，您可以访问单个列表元素，如|41289|l1[["A1"]]
#[1]+0.4951453+-1.4278665++0.5680115++0.3537730+-0.7757363|41290|此外，另一种方法是将所有数字一起生成，然后将它们split为list。|offset|length|style|CODE|41291|groups+=+5
each+=+5

setNames(split(rnorm(groups+*+each),+rep(seq_len(groups),+each+=+each)),+
+++++++++paste0("A",+seq_len(groups)))|41292|entityMap^0|0|0|0|0|O|5|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|V|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|W|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|X|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|Y|8|@$M|Z|N|10|O|P]]|9|@]|A|$]]|$1|Q|3|R|5|D|7|11|8|@]|9|@]|A|$E|F]]|$1|S|3|-4|5|6|7|12|8|@]|9|@]|A|$]]]|T|$]]

There is no point in cluttering your environment with so many variables, try to store them in a named list instead

<pre><code>l1 &lt;- setNames(lapply(1:5, function(x) rnorm(5)), paste0("A", 1:5))
l1

#$A1
#[1] 0.4951453 -1.4278665 0.5680115 0.3537730 -0.7757363

#$A2
#[1] -0.11096037 0.05958700 0.02578168 1.00591996 0.54852030

#$A3
#[1] 0.1058318 0.6988443 -0.8213525 -0.1072289 0.8757669

#$A4
#[1] -0.6629634 0.8321713 -0.3073465 -0.2645550 -1.0064132

#$A5
#[1] 2.2191246 0.2054360 -0.1768357 1.6875302 -1.1495807
</code></pre>

Now you can access individual list element as

<pre><code>l1[["A1"]]
#[1] 0.4951453 -1.4278665 0.5680115 0.3537730 -0.7757363
</code></pre>

<hr>

Moreover, other method is to generate all the numbers together and then <code>split</code> them into list. 

<pre><code>groups = 5
each = 5

setNames(split(rnorm(groups * each), rep(seq_len(groups), each = each)), 
 paste0("A", seq_len(groups)))
</code></pre>

blocks|key|2325809|text|我同意其他人的意见，这不是一个好主意。不管怎样，要回答你的问题，你应该怎么做|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2325810|k+<-+1000+#+number+of+variables
n+<-+200+#+sample+size+of+each+variable
for(i+in+1:k){
assign(paste0("variable",+i),+rnorm(n,+0,+1))}
variable1
-0.012947062++0.728284959+-1.627796366++0.003471491+...|code-block|syntax|javascript|2325811|不过，就我个人而言，我更倾向于另一种解决办法。到目前为止，这两个答案都建议使用列表。我发现lsts非常麻烦，特别是如果您对R还不熟悉的话，所以我建议创建一个矩阵，其中每一列都包含一个变量。|offset|length|style|BOLD|2325812|#+creates+a+matrix
m+<-+matrix(rep(NA,+n*k),+ncol=+k)
#+generates+rnorm()+in+each+column
for(i+in+1:k){
m[+,+i]+<-+rnorm(n,+0,+1)
}

#+now+you+can+name+the+columns
colnames(m)+<-+paste0("variable",+1:k)
m
++++++++variable1+++variable2++++...
+[1,]++0.30950749+-2.07388046
+[2,]+-1.13232330+-0.55511476
++...+++|2325813|entityMap^0|0|0|22|J|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|R|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|S|8|@$I|T|J|U|K|L]]|9|@]|A|$]]|$1|M|3|N|5|D|7|V|8|@]|9|@]|A|$E|F]]|$1|O|3|-4|5|6|7|W|8|@]|9|@]|A|$]]]|P|$]]

I agree with the others that this is not a good idea. Anyway, to answer your question how you wolud do that is

<pre><code>k &lt;- 1000 # number of variables
n &lt;- 200 # sample size of each variable
for(i in 1:k){
assign(paste0("variable", i), rnorm(n, 0, 1))}
variable1
-0.012947062 0.728284959 -1.627796366 0.003471491 ...
</code></pre>

However, personally I would prefer another solution. The both answers so far suggest using lists. I find lsts quite cumbersome, especially if you are new to R. So I would suggest creating a matrix where every column contains one variable.

<pre><code># creates a matrix
m &lt;- matrix(rep(NA, n*k), ncol= k)
# generates rnorm() in each column
for(i in 1:k){
m[ , i] &lt;- rnorm(n, 0, 1)
}

# now you can name the columns
colnames(m) &lt;- paste0("variable", 1:k)
m
 variable1 variable2 ...
 [1,] 0.30950749 -2.07388046
 [2,] -1.13232330 -0.55511476
 ... 
</code></pre>

I am trying to create 1000 variables, which I want to name with the index number. I don't know how to create these new variables. 

<pre><code>for(i in 1:1000) {
 Ui &lt;- rnorm(200,0,1)
}
</code></pre>

How can I create Variables A1,A2,...,A100 using a loop in R?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我正在尝试创建1000个变量，我想用索引号命名这些变量。我不知道如何创建这些新变量。for(i in 1:1000) { Ui <- rnorm(200,0,1)}

问如何使用R中的循环创建变量A1、A2、.、A100？
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问如何使用R中的循环创建变量A1、A2、.、A100？EN