r - 如何在r中从类别转换为数字

Question

这是我的问题:

我有一个包含类别的表格，我想对它们进行排名:

category
dog
cat
fish
dog
dog

我想要的是添加一列并对它们进行排名:

category       rank    
dog             1  
cat             2
fish            3
dog             1
dog             1

很抱歉这个糟糕的表(帮助在堆栈溢出中编写普通表也很棒)

关于如何添加排名列的任何想法？

谢谢!

Answer 1

只是为了完整起见，并且因为我在评论中发布的解决方案效率低下(而且非常丑陋)，我也会发布一个答案。

原来，OP的起始设置是这样的:

x = c("cat", "dog", "fish", "dog", "dog", "cat", "fish", "catfish")
x = factor(x)

最后，手动指定的数字分类 x被通缉。例如，假设需要以下匹配:

cat -> 1, dog -> 2, fish -> 3, catfish -> 4

所以，一些替代方案:

sapply(as.character(x), switch, "cat" = 1, "dog" = 2, "fish" = 3, "catfish" = 4, 
                                                                USE.NAMES = F)
#[1] 1 2 3 2 2 1 3 4

match(x, c("cat", "dog", "fish", "catfish")) #note that match's internal 'do_match' 
                                             #calls 'match_transform' that coerces
                                             #`factor` to `character`, so no need
                                             #for 'as.character(x)'
                                  #(http://svn.r-project.org/R/trunk/src/main/unique.c)
#[1] 1 2 3 2 2 1 3 4

local({    #just to not change 'x'
levels(x) = list("cat" = 1, "dog" = 2, "fish" = 3, "catfish" = 4)
as.numeric(x)
})
#[1] 1 2 3 2 2 1 3 4

library(fastmatch)
fmatch(x, c("cat", "dog", "fish", "catfish"))  #a faster alternative to 'match'
#[1] 1 2 3 2 2 1 3 4

并在更大的向量上进行基准测试:

X = rep(as.character(x), 1e5)
X = factor(X)
f1 = function() sapply(as.character(X), switch, 
            "cat" = 1, "dog" = 2, "fish" = 3, "catfish" = 4, USE.NAMES = F)
f2 = function() match(X, c("cat", "dog", "fish", "catfish")) 
f3 = function() {levels(X) = list("cat" = 1, "dog" = 2, "fish" = 3, "catfish" = 4) ;
                                                       as.numeric(X)}
library(fastmatch)
f4 = function() fmatch(X, c("cat", "dog", "fish", "catfish"))

library(microbenchmark)
microbenchmark(f1(), f2(), f3(), f4(), times = 10)
#Unit: milliseconds
# expr         min          lq      median         uq       max neval
# f1() 1745.111666 1816.675337 1961.809102 2107.98236 2896.0291    10
# f2()   22.043657   22.786647   23.987263   31.45057  111.9600    10
# f3()   32.704779   32.919150   38.865853   47.67281  134.2988    10
# f4()    8.814958    8.823309    9.856188   19.66435  104.2827    10
sum(f1() != f2())
#[1] 0
sum(f2() != f3())
#[1] 0
sum(f3() != f4())
#[1] 0