blocks|key|2023923|text|使用factor的levels参数|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2023924|df+<-+data.frame(f+=+1:4,+g+=+letters[1:4])
df
#+++f+g
#+1+1+a
#+2+2+b
#+3+3+c
#+4+4+d

levels(df$g)
#+[1]+"a"+"b"+"c"+"d"

df$g+<-+factor(df$g,+levels+=+letters[4:1])
#+levels(df$g)
#+[1]+"d"+"c"+"b"+"a"

df
#+++f+g
#+1+1+a
#+2+2+b
#+3+3+c
#+4+4+d|code-block|syntax|javascript|2023925|entityMap^0|2|6|9|6|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]|$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|S|8|@]|D|@]|E|$]]]|L|$]]

Use the <code>levels</code> argument of <code>factor</code>:

<pre><code>df &lt;- data.frame(f = 1:4, g = letters[1:4])
df
# f g
# 1 1 a
# 2 2 b
# 3 3 c
# 4 4 d

levels(df$g)
# [1] "a" "b" "c" "d"

df$g &lt;- factor(df$g, levels = letters[4:1])
# levels(df$g)
# [1] "d" "c" "b" "a"

df
# f g
# 1 1 a
# 2 2 b
# 3 3 c
# 4 4 d
</code></pre>

blocks|key|2023979|text|更多，只是为了记录|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2023980|##+reorder+is+a+base+function
df$letters+<-+reorder(df$letters,+new.order=letters[4:1])

library(gdata)
df$letters+<-+reorder.factor(df$letters,+letters[4:1])|code-block|syntax|javascript|2023981|您可能还会发现有用的Relevel和combine_factor。|offset|length|2023982|entityMap|0|LINK|mutability|MUTABLE|url|http://finzi.psych.upenn.edu/R/library/Epi/html/Relevel.html|1|http://finzi.psych.upenn.edu/R/library/reshape/html/combine-factor-9x.html^0|0|0|A|7|0|I|E|1|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]]|$1|G|3|H|5|6|7|W|8|@]|9|@$I|X|J|Y|1|Z]|$I|10|J|11|1|12]]|A|$]]|$1|K|3|-4|5|6|7|13|8|@]|9|@]|A|$]]]|L|$M|$5|N|O|P|A|$Q|R]]|S|$5|N|O|P|A|$Q|T]]]]

some more, just for the record

<pre><code>## reorder is a base function
df$letters &lt;- reorder(df$letters, new.order=letters[4:1])

library(gdata)
df$letters &lt;- reorder.factor(df$letters, letters[4:1])
</code></pre>

You may also find useful <a href="http://finzi.psych.upenn.edu/R/library/Epi/html/Relevel.html" rel="noreferrer">Relevel</a> and <a href="http://finzi.psych.upenn.edu/R/library/reshape/html/combine-factor-9x.html" rel="noreferrer">combine_factor</a>.

blocks|key|2024025|text|自从这个问题上一次活跃以来，哈德利已经发布了他的用于操纵因子的新forcats包，我发现它非常有用。OP数据框中的示例：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2024026|levels(df$letters)
#+[1]+"a"+"b"+"c"+"d"|code-block|syntax|javascript|2024027|要反转级别，请执行以下操作：|2024028|library(forcats)
fct_rev(df$letters)+%25>%25+levels
#+[1]+"d"+"c"+"b"+"a"|2024029|要添加更多级别，请执行以下操作：|2024030|fct_expand(df$letters,+"e")+%25>%25+levels
#+[1]+"a"+"b"+"c"+"d"+"e"|2024031|以及更多有用的fct_xxx()函数。|2024032|entityMap^0|W|7|0|0|0|0|0|0|7|9|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|Z|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|10|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|11|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|12|8|@]|D|@]|E|$]]|$1|Q|3|R|5|H|7|13|8|@]|D|@]|E|$I|J]]|$1|S|3|T|5|6|7|14|8|@$9|15|A|16|B|C]]|D|@]|E|$]]|$1|U|3|-4|5|6|7|17|8|@]|D|@]|E|$]]]|V|$]]

Since this question was last active Hadley has released his new <code>forcats</code> package for manipulating factors and I'm finding it outrageously useful. Examples from the OP's data frame:

<pre><code>levels(df$letters)
# [1] "a" "b" "c" "d"
</code></pre>

To reverse levels:

<pre><code>library(forcats)
fct_rev(df$letters) %&gt;% levels
# [1] "d" "c" "b" "a"
</code></pre>

To add more levels:

<pre><code>fct_expand(df$letters, "e") %&gt;% levels
# [1] "a" "b" "c" "d" "e"
</code></pre>

And many more useful <code>fct_xxx()</code> functions.

blocks|key|2024084|text|我希望添加另一种情况，其中级别可以是包含数字和一些特殊字符的字符串：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2024085|df+<-+data.frame(x+=+c("15-25",+"0-4",+"5-10",+"11-14",+"100%2B"))|code-block|syntax|javascript|2024086|x的默认级别为：|offset|length|style|CODE|2024087|df$x
#+[1]+15-25+0-4+++5-10++11-14+100%2B+
#+Levels:+0-4+100%2B+11-14+15-25+5-10|2024088|在这里，如果我们想要根据数值重新排序因子级别，而不显式地写出级别，我们可以做的是|2024089|library(gtools)
df$x+<-+factor(df$x,+levels+=+mixedsort(df$x))

df$x
#+[1]+15-25+0-4+++5-10++11-14+100%2B+
#+Levels:+0-4+5-10+11-14+15-25+100%2B
as.numeric(df$x)
#+[1]+4+1+2+3+5|2024090|我希望这能被认为是对未来读者有用的信息。|2024091|entityMap^0|0|0|0|1|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|X|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Y|8|@$I|Z|J|10|K|L]]|9|@]|A|$]]|$1|M|3|N|5|D|7|11|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|12|8|@]|9|@]|A|$]]|$1|Q|3|R|5|D|7|13|8|@]|9|@]|A|$E|F]]|$1|S|3|T|5|6|7|14|8|@]|9|@]|A|$]]|$1|U|3|-4|5|6|7|15|8|@]|9|@]|A|$]]]|V|$]]

I wish to add another case where the levels could be strings carrying numbers alongwith some special characters : like below example

<pre><code>df &lt;- data.frame(x = c("15-25", "0-4", "5-10", "11-14", "100+"))
</code></pre>

The default levels of <code>x</code> is :

<pre><code>df$x
# [1] 15-25 0-4 5-10 11-14 100+ 
# Levels: 0-4 100+ 11-14 15-25 5-10
</code></pre>

Here if we want to reorder the factor levels according to the numeric value, without explicitly writing out the levels, what we could do is 

<pre><code>library(gtools)
df$x &lt;- factor(df$x, levels = mixedsort(df$x))

df$x
# [1] 15-25 0-4 5-10 11-14 100+ 
# Levels: 0-4 5-10 11-14 15-25 100+
as.numeric(df$x)
# [1] 4 1 2 3 5
</code></pre>

I hope this can be considered as useful information for future readers.

blocks|key|1810852|text|下面是我的函数，用于对给定数据帧的因子进行重新排序：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1810853|reorderFactors+<-+function(df,+column+=+"my_column_name",+
+++++++++++++++++++++++++++desired_level_order+=+c("fac1",+"fac2",+"fac3"))+{

++x+=+df[[column]]
++lvls_src+=+levels(x)+

++idxs_target+<-+vector(mode="numeric",+length=0)
++for+(target+in+desired_level_order)+{
++++idxs_target+<-+c(idxs_target,+which(lvls_src+==+target))
++}

++x_new+<-+factor(x,levels(x)[idxs_target])

++df[[column]]+<-+x_new

++return+(df)
}|code-block|syntax|javascript|1810854|用法：reorderFactors(df,+"my_col",+desired_level_order+=+c("how","I","want"))|offset|length|style|CODE|1810855|entityMap^0|0|0|3|1Z|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Q|8|@$I|R|J|S|K|L]]|9|@]|A|$]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

Here's my function to reorder factors of a given dataframe:

<pre><code>reorderFactors &lt;- function(df, column = "my_column_name", 
 desired_level_order = c("fac1", "fac2", "fac3")) {

 x = df[[column]]
 lvls_src = levels(x) 

 idxs_target &lt;- vector(mode="numeric", length=0)
 for (target in desired_level_order) {
 idxs_target &lt;- c(idxs_target, which(lvls_src == target))
 }

 x_new &lt;- factor(x,levels(x)[idxs_target])

 df[[column]] &lt;- x_new

 return (df)
}
</code></pre>

Usage: <code>reorderFactors(df, "my_col", desired_level_order = c("how","I","want"))</code>

blocks|key|1810869|text|我将简单地使用级别参数：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1810870|levels(df$letters)+<-+levels(df$letters)[c(4:1)]|code-block|syntax|javascript|1810871|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

I would simply use the levels argument:
<pre><code>levels(df$letters) &lt;- levels(df$letters)[c(4:1)]
</code></pre>

blocks|key|2024464|text|添加另一种非常有用的方法，因为它将我们从记住不同包中的函数中解放出来。因子的级别只是属性，因此可以执行以下操作：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2024465|numbers+<-+1:4
letters+<-+factor(c("a",+"b",+"c",+"d"))
df+<-+data.frame(numbers,+letters)

#+Original+attributes
>+attributes(df$letters)
$levels
[1]+"a"+"b"+"c"+"d"

$class
[1]+"factor"

#+Modify+attributes
attr(df$letters,"levels")+<-+c("d",+"c",+"b",+"a")

>+df$letters
[1]+d+c+b+a
Levels:+d+c+b+a

#+New+attributes
>+attributes(df$letters)
$levels
[1]+"d"+"c"+"b"+"a"

$class
[1]+"factor"|code-block|syntax|javascript|2024466|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

To add yet another approach that is quite useful as it frees us from remembering functions from differents packages. The levels of a factor are just attributes, so one can do the following:
<pre><code>numbers &lt;- 1:4
letters &lt;- factor(c(&quot;a&quot;, &quot;b&quot;, &quot;c&quot;, &quot;d&quot;))
df &lt;- data.frame(numbers, letters)

# Original attributes
&gt; attributes(df$letters)
$levels
[1] &quot;a&quot; &quot;b&quot; &quot;c&quot; &quot;d&quot;

$class
[1] &quot;factor&quot;

# Modify attributes
attr(df$letters,&quot;levels&quot;) &lt;- c(&quot;d&quot;, &quot;c&quot;, &quot;b&quot;, &quot;a&quot;)

&gt; df$letters
[1] d c b a
Levels: d c b a

# New attributes
&gt; attributes(df$letters)
$levels
[1] &quot;d&quot; &quot;c&quot; &quot;b&quot; &quot;a&quot;

$class
[1] &quot;factor&quot;
</code></pre>

I have data frame with some numerical variables and some categorical <code>factor</code> variables. The order of levels for those factors is not the way I want them to be. 

<pre><code>numbers &lt;- 1:4
letters &lt;- factor(c("a", "b", "c", "d"))
df &lt;- data.frame(numbers, letters)
df
# numbers letters
# 1 1 a
# 2 2 b
# 3 3 c
# 4 4 d
</code></pre>

If I change the order of the levels, the letters no longer are with their corresponding numbers (my data is total nonsense from this point on).

<pre><code>levels(df$letters) &lt;- c("d", "c", "b", "a")
df
# numbers letters
# 1 1 d
# 2 2 c
# 3 3 b
# 4 4 a
</code></pre>

I simply want to change the level order, so when plotting, the bars are shown in the desired order - which may differ from default alphabetical order.

Reorder levels of a factor without changing order of values

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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我有一个包含一些数值变量和一些分类factor变量的数据框架。这些因素的级别顺序不是我想要的方式。numbers <- 1:4letters <- factor(c("a", "b", "c", "d"))df <- data.frame(numbers, letters)df# numbers letters# ...

问在不改变值顺序的情况下重新排序因子的级别
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问在不改变值顺序的情况下重新排序因子的级别
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