根据列 r 上的两个条件删除重复行

Question

我正在尝试删除重复项并保留具有最大值的行。我可以根据策略单独执行此操作。

但是，当基于策略基于两个单独的条件尝试执行此操作时，数据框在尝试应用这些条件时往往会相互覆盖。

这是必需的，因为一种策略包含一种策略具有而另一种策略不具有的值；不过请注意，它们确实共享一个公共列。

当前数据

  ID strategy Common DNA_Col RNA_Col
1 ABA      DNA   0.65    0.66      NA
2 ABB      RNA   0.65      NA    0.15
3 ABB      RNA   0.65      NA    0.12
4 ABC      DNA   0.55    0.88      NA
5 ABC      DNA   0.14    0.14      NA
6 ABC      DNA   0.15    0.50      NA
7 ABD      RNA   0.25      NA    0.12

所需的数据帧

   ID strategy Common DNA_Col RNA_Col
1 ABA      DNA   0.65    0.66      NA
2 ABB      RNA   0.65      NA    0.15
3 ABC      DNA   0.55    0.88      NA
4 ABD      RNA   0.25      NA    0.12

代码

生成数据框：

> df <- data.frame(
+   stringsAsFactors = FALSE,
+   ID = c("ABA", "ABB", "ABB", "ABC", "ABC", "ABC", "ABD"),
+   strategy =c("DNA", "RNA", "RNA", "DNA", "DNA", "DNA", "RNA"),
+   Common = c(0.65, 0.65, 0.65, 0.55, 0.14, 0.15, 0.25),
+   DNA_Col= c(0.66, NA, NA, 0.88, 0.14, 0.5, NA),
+   RNA_Col = c(NA, 0.15, 0.12, NA, NA, NA, 0.12)
+ )

应用条件

if (df$strategy == "RNA") {
  df = df %>% group_by(id) %>% slice_max(RNA_Col, n=1) %>% ungroup
} else if (df$strategy == "DNA") {
  df = df %>% group_by(df) %>% slice_max(DNA_Col, n=1) %>% ungroup
}

Answer 1

这可以通过使用 pivot_longer() 函数将 RNA_Col 和 DNA_Col 变量的值放入一个单独的列中同时处理来完成，然后可以用于使用 ifelse().

重新填充列


library(tidyverse)

df <- data.frame(
     stringsAsFactors = FALSE,
     ID = c("ABA", "ABB", "ABB", "ABC", "ABC", "ABC", "ABD"),
     strategy =c("DNA", "RNA", "RNA", "DNA", "DNA", "DNA", "RNA"),
     Common = c(0.65, 0.65, 0.65, 0.55, 0.14, 0.15, 0.25),
     DNA_Col= c(0.66, NA, NA, 0.88, 0.14, 0.5, NA),
     RNA_Col = c(NA, 0.15, 0.12, NA, NA, NA, 0.12)
   )

df %>% 
  pivot_longer(cols = c(DNA_Col, RNA_Col),
               names_to = "Original_Col",
               values_to = "Value") %>% 
  group_by(ID) %>% 
  slice_max(Value, n = 1) %>% 
  ungroup() %>% 
  mutate(DNA_Col = ifelse(
    Original_Col == "DNA_Col", Value, NA
  ),
  RNA_Col = ifelse(
    Original_Col == "RNA_Col", Value, NA
  )) %>% 
  select(ID, strategy, Common, DNA_Col, RNA_Col)

# A tibble: 4 × 5
  ID    strategy Common DNA_Col RNA_Col
  <chr> <chr>     <dbl>   <dbl>   <dbl>
1 ABA   DNA        0.65    0.66   NA   
2 ABB   RNA        0.65   NA       0.15
3 ABC   DNA        0.55    0.88   NA   
4 ABD   RNA        0.25   NA       0.12

Answer 2

可能的解决方案：

library(tidyverse)

df <- data.frame(
  stringsAsFactors = FALSE,
  ID = c("ABA", "ABB", "ABB", "ABC", "ABC", "ABC", "ABD"),
  strategy = c("DNA", "RNA", "RNA", "DNA", "DNA", "DNA", "RNA"),
  Common = c(0.65, 0.65, 0.65, 0.55, 0.14, 0.15, 0.25),
  DNA_Col = c(0.66, NA, NA, 0.88, 0.14, 0.5, NA),
  RNA_Col = c(NA, 0.15, 0.12, NA, NA, NA, 0.12)
)

df %>% 
  group_by(ID) %>% 
  slice_max(DNA_Col, n = 1) %>% 
  ungroup %>% 
  bind_rows(
    df %>% 
      group_by(ID) %>% 
      slice_max(RNA_Col, n = 1) %>% 
      ungroup)

#> # A tibble: 4 × 5
#>   ID    strategy Common DNA_Col RNA_Col
#>   <chr> <chr>     <dbl>   <dbl>   <dbl>
#> 1 ABA   DNA        0.65    0.66   NA   
#> 2 ABC   DNA        0.55    0.88   NA   
#> 3 ABB   RNA        0.65   NA       0.15
#> 4 ABD   RNA        0.25   NA       0.12

根据列 r 上的两个条件删除重复行

removing duplicate rows based on two conditionals on columns r

r

duplicates

dplyr

当前数据

所需的数据帧

代码