使用R中的mutate和case_when（）语句将unite（）填充为整列

debugcn 发表于 Dev

shu251

我有一个名称列表，并为这些名称分配了阈值，以确定我是否适当分配了该名称。

您可以使用以下方法重新创建测试数据集：

df <- data.frame(level1 = c("Eukaryota","Eukaryota","Eukaryota","Eukaryota","Eukaryota"), 
             level2=c("Opisthokonta","Alveolata","Opisthokonta","Alveolata","Alveolata"), 
             level3=c("Fungi","Ciliophora","Fungi","Ciliophora","Dinoflagellata"),
             level4=c("Basidiomycota","Spirotrichea","Basidiomycota","Spirotrichea","Dinophyceae"), 
             value = c("100;5;4;2", "100;100;100;100", "100;80;60;50", "90;50;40;40","100;80;20;0"))

我想使用整洁的诗歌，mutate()并case_when()找到通过适当阈值的分类标准。因此，下面整洁的经文声明将阈值分解，然后尝试执行此操作。我的瓶颈

使用case_when()vsifelse()语句-使用ifelse（）可能更合适？
我不知道如何用连接的level1-levelX填充名为Name_updated的新列。目前，unite（）不适合，因为这与整个数据集有关。实际上，我有更多的专栏文章，因此如果没有整洁的诗句level1:level3语法，这样做会很痛苦！

df_updated <- df %>% 
  separate(value, c("threshold1","threshold2", "threshold3", "threshold4"), sep =";") %>% 
  mutate(Name_updated = case_when(
    threshold4 >= 50 ~ unite(level1:level4, sep = ";"), #Fill with all taxonomic names to level4
    threshold4 < 50 & threshold3 >= 60 ~ unite(level1:level3, sep = ";"), #If last threshold is <50, only fill with taxonomic names to level3
    threshold4 < 50 & threshold3 < 60 & threshold2 >= 50 ~ unite(level1:level2, sep = ";"), #If thresholds for level 3 and 4 are below, fill only level1;level2
    TRUE ~ level1)) %>% #Otherwise fill with only level 1
  data.frame

所需的输出

> df_updated$Name_updated
# Output of this new list:
Eukaryota
Eukaryota;Alveolata;Ciliophora;Spirotrichea
Eukaryota;Opisthokonta;Fungi;Basidiomycota
Eukaryota;Alveolata
Eukaryota;Alveolata

理想的下一步是编写一个函数，该函数允许用户指定脚本中使用的阈值。因此，我确实需要进行探测/确定什么阈值可以通过。

阿克伦

问题是unite，也是type在中separate编列。默认情况下，convert = FALSE它将是一个character类列

library(dplyr)
library(tidyr)
library(purrr)
library(stringr)
df %>% 
  type.convert(as.is = TRUE) %>%
  separate(value, c("threshold1","threshold2", 
          "threshold3", "threshold4"), sep =";", convert = TRUE) %>% 
  mutate(Name_updated = 
     case_when(
      threshold4 >= 50 ~
         select(., starts_with('level')) %>% 
            reduce(str_c, sep=";"),
       threshold4 < 50 & threshold3 >= 60 ~ 
          select(., level1:level3) %>%
            reduce(str_c, sep=";"), 
       threshold4 < 50 & threshold3 < 60 & threshold2 >= 50 ~ 
          select(., level1:level2) %>% 
            reduce(str_c, sep=";"), 
      TRUE ~ level1))
#  level1       level2         level3        level4 threshold1 threshold2 threshold3 threshold4
#1 Eukaryota Opisthokonta          Fungi Basidiomycota        100          5          4          2
#2 Eukaryota    Alveolata     Ciliophora  Spirotrichea        100        100        100        100
#3 Eukaryota Opisthokonta          Fungi Basidiomycota        100         80         60         50
#4 Eukaryota    Alveolata     Ciliophora  Spirotrichea         90         50         40         40
#5 Eukaryota    Alveolata Dinoflagellata   Dinophyceae        100         80         20          0
#                                 Name_updated
#1                                   Eukaryota
#2 Eukaryota;Alveolata;Ciliophora;Spirotrichea
#3  Eukaryota;Opisthokonta;Fungi;Basidiomycota
#4                         Eukaryota;Alveolata
#5                         Eukaryota;Alveolata

本文收集自互联网，转载请注明来源。

如有侵权，请联系[email protected] 删除。