Question

我有一个df，其中value表示drug的状态：

g1 = data.frame ( 
    drug = c('a','a','a','d','d'),
    value = c('fda','trial','case','case','pre')
)

drug value
1    a   fda
2    a trial
3    a  case
4    d  case
5    d   pre

对于药物，我想根据drug的以下优先顺序替换任何重复的value：

fda > trial > case > pre

因此，例如，如果药物d既是“ case”又是“ pre”，则d的所有发生率都将重新分类为“ case”。决赛桌应如下所示。

  drug value
1    a   fda
2    a   fda
3    a   fda
4    d  case
5    d  case

如何做到这一点而又不必遍历每种药物并先弄清优先顺序，然后替换呢？

Answer 1

使用映射MenuItem进行更新，因为我不想更改列类型，所以我曾经这样做。

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Answer 2

类似于@ Wen-Ben的答案，使用base函数，您还可以执行以下操作：

g1$value <- factor(g1$value, levels = c("fda", "trial", "case", "pre"))
g1 <- g1[order(g1$value),]
g1$value <- g1[match(g1$drug, g1$drug), "value"]

Answer 3

由于这是一个序数变量，因此可以将g1$value设为ordered因子，作为对应的class。然后，您可以像使用数字一样使用min和max之类的函数：

g1$value <- ordered(g1$value, levels = c("fda", "trial", "case", "pre"))
g1$value
#[1] fda   trial case  case  pre  
#Levels: fda < trial < case < pre
g1$value <- ave(g1$value, g1$drug, FUN=min)
g1
#  drug value
#1    a   fda
#2    a   fda
#3    a   fda
#4    d  case
#5    d  case

或在 dplyr 中说：

g1 %>%
  mutate(value = ordered(value, levels = c("fda", "trial", "case", "pre"))) %>%
  group_by(drug) %>%
  mutate(value = min(value))

数据集中的顺序和任何drug组中存在的值的范围都不会影响此结果：

g2 = data.frame ( 
    drug = c( "a","a","a","d","d","e","e","e"),
    value = c("fda","trial","case","case","pre","pre","fda","case")
)

#  drug value
#1    a   fda
#2    a trial
#3    a  case
#4    d  case
#5    d   pre
#6    e   pre
#7    e   fda
#8    e  case

g2 %>%
  mutate(value = ordered(value, levels = c("fda", "trial", "case", "pre"))) %>%
  group_by(drug) %>%
  mutate(value = min(value))

## A tibble: 8 x 2
## Groups:   drug [3]
#  drug  value
#  <fct> <ord>
#1 a     fda  
#2 a     fda  
#3 a     fda  
#4 d     case 
#5 d     case 
#6 e     fda  
#7 e     fda  
#8 e     fda

重复时如何基于优先级重新分类/替换值

3 个答案: