`name（df [1]）< - `和`names（df）[1]之间的区别< - [英] Difference between `names(df[1]) <- ` and `names(df)[1] <- `

问题描述

考虑以下内容：

  df<  -  data.frame（a = 1，b = 2，c = 3 ）
名称（df [1]）<  - d##第一种方法
 ## abc 
 ## 1 1 2 3 
 
名称（df ）[1]<  - d##第二种方法
 ## dbc 
 ## 1 1 2 3 
  

两个方法都没有返回错误，但是第一个没有更改列名称，而第二个方法没有。

我以为这与我仅在 df 的一个子集上进行操作有关，但为什么例如以下的工作呢？

  df [1]<  -  2 
 ## abc 
 ## 1 2 2 3 
  

解决方案

我认为发生的是将替换成数据帧忽略属性的数据框架。我不是100％肯定的，但以下实验似乎支持：

  df<  -  data.frame （a = 1：3，b = 5：7）
＃ab 
＃1 1 5 
＃2 2 6 
＃3 3 7 
 
 df2<  -  data.frame（c = 10:12）
＃c 
＃1 10 
＃2 11 
＃3 12 
 
 df [1]<  -  df2 [1]＃在这种情况下`df [1]<  -  df2`是等价的
  

哪些产生：

 ＃ab 
＃1 10 5 
＃2 11 6 
＃3 12 7 
  

请注意， df ，但不是名字。基本上，替换运算符`[< -` 仅替换值。这就是为什么这个名字没有更新。我相信这解释了所有的问题。

在这种情况下：

 名称（df [2]）<  - x
  

您可以将作业视为以下（这是一个简化，详见后篇）：

  tmp < -  df [2] 
＃b 
＃1 5 
＃2 6 
＃3 7 
 
名称（tmp）<  - x
＃x 
＃1 5 
＃2 6 
＃3 7 
 
 df [2]<  -  tmp＃`tmp'有x的名字，忽略了
＃ab 
＃1 10 5 
＃2 11 6 
＃3 12 7 
  

最后一步是使用`[< -` ，不遵守RHS的名称属性的作业。

但是在这种情况下：

  names（df）[2 ]<  - x
  

你可以将作业看作（再一次简化）：

  tmp<  - 名称（df）
＃[1]ab
 
 tmp [2]<  - x
＃[1]ax
 
名称（df）<  -  tmp 
＃ax 
＃1 10 5 
＃2 11 6 
＃3 12 7 
  

注意我们如何直接分配给名称，而不是分配给忽略属性的 df 。

  df [2]<  -  2 
  

因为我们直接分配给值而不是属性，所以这里没有问题。

---

$ b $编辑：根据一些评论om @ AriB.Friedman，这里是一个更精细的版本，我认为是这样（注意我省略了S3发送到`[.data.frame` 等等，为了清楚起见）：

版本1 名称（df [2]）< - x转换为：

  df<  - `[< -`（
 df，2，
 value =`names <-`（＃`names< -`这里返回一个重新命名的一列数据框
`[`（df，2），
 value =x
 ）
  

版本2 名称（df）[2]< - x转换为：

  df<  - `names< -`（
 df，
`[< -`（
 names（df），2，x
））
  

---

另外，在R Inferno Section 8.2.34（Thanks @Frank）中证明了这一点是记录的：

  right<  -  wrong<  -  c（a = 1，b = 2）
名称（错误[1]）< - '更改'
错误
＃ab 
＃1 2 
名称（右）[1]<  - '更改'
 right 
＃ d b 
＃1 2 
  

Consider the following:

df <- data.frame(a = 1, b = 2, c = 3)
names(df[1]) <- "d" ## First method
##  a b c
##1 1 2 3

names(df)[1] <- "d" ## Second method
##  d b c
##1 1 2 3

Both methods didn't return an error, but the first didn't change the column name, while the second did.

I thought it has something to do with the fact that I'm operating only on a subset of df, but why, for example, the following works fine then?

df[1] <- 2 
##  a b c
##1 2 2 3

解决方案

What I think is happening is that replacement into a data frame ignores the attributes of the data frame that is drawn from. I am not 100% sure of this, but the following experiments appear to back it up:

df <- data.frame(a = 1:3, b = 5:7)
#   a b
# 1 1 5
# 2 2 6
# 3 3 7

df2 <- data.frame(c = 10:12)
#    c
# 1 10
# 2 11
# 3 12

df[1] <- df2[1]   # in this case `df[1] <- df2` is equivalent

Which produces:

#    a b
# 1 10 5
# 2 11 6
# 3 12 7

Notice how the values changed for df, but not the names. Basically the replacement operator `[<-` only replaces the values. This is why the name was not updated. I believe this explains all the issues.

In the scenario:

names(df[2]) <- "x"

You can think of the assignment as follows (this is a simplification, see end of post for more detail):

tmp <- df[2]
#   b
# 1 5
# 2 6
# 3 7

names(tmp) <- "x"
#   x
# 1 5
# 2 6
# 3 7

df[2] <- tmp   # `tmp` has "x" for names, but it is ignored!
#    a b
# 1 10 5
# 2 11 6
# 3 12 7

The last step of which is an assignment with `[<-`, which doesn't respect the names attribute of the RHS.

But in the scenario:

names(df)[2] <- "x"

you can think of the assignment as (again, a simplification):

tmp <- names(df)
# [1] "a" "b"

tmp[2] <- "x"
# [1] "a" "x"

names(df) <- tmp
#    a x
# 1 10 5
# 2 11 6
# 3 12 7

Notice how we directly assign to names, instead of assigning to df which ignores attributes.

df[2] <- 2

works because we are assigning directly to the values, not the attributes, so there are no problems here.

---

EDIT: based on some commentary from @AriB.Friedman, here is a more elaborate version of what I think is going on (note I'm omitting the S3 dispatch to `[.data.frame`, etc., for clarity):

Version 1 names(df[2]) <- "x" translates to:

df <- `[<-`(
  df, 2, 
  value=`names<-`(   # `names<-` here returns a re-named one column data frame
    `[`(df, 2),       
    value="x"
) ) 

Version 2 names(df)[2] <- "x" translates to:

df <- `names<-`(
  df,
  `[<-`(
     names(df), 2, "x"
) )

---

Also, turns out this is "documented" in R Inferno Section 8.2.34 (Thanks @Frank):

right <- wrong <- c(a=1, b=2)
names(wrong[1]) <- 'changed'
wrong
# a b
# 1 2
names(right)[1] <- 'changed'
right
# changed b
# 1 2

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