识别向量中的给定模式并添加缺少的元素以获得给定模式的重复

Question

这个问题与此Wide a dataframe and insert missing columns相关

假设我们有一个给定 5 个元素的模式，按以下顺序:“A”、“B”、“C”、“D”、“E”

这种模式会重复 10 次。但有时缺少一些元素(参见图片我的矢量(橙色)。

在R中是否可以识别重复的模式并填充缺少的元素(参见图片我想要的输出)。

我的向量:

my.vector <- c("A", "B", "C", "D", "E", "A", "B", "C", "D", "E", "B", "C", 
               "D", "E", "B", "C", "D", "E", "B", "C", "D", "E", "B", "C", "D", 
               "E", "B", "C", "D", "E", "B", "C", "D", "E", "A", "B", "C", "D", 
               "E", "B")

my.vector
 [1] "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "B" "C" "D" "E" "B" "C" "D" "E" "B" "C" "D" "E" "B" "C" "D" "E" "B" "C" "D" "E" "B" "C" "D" "E" "A" "B" "C" "D" "E" "B"

图形解释:

给定模式:

我的向量:

我想要的输出:要添加的红色标记元素

Answer 1

根据 diff 创建分组列的match ing 索引 LETTERS[1:5] , split (或使用任何分组函数，如tapply等)，并创建一个union与“字母[1:5] , 取消列表 the列表and取消名称`

unname( unlist(lapply(split(my.vector, cumsum(c(TRUE, 
     diff(match(my.vector, LETTERS[1:5])) != 1))),
       function(x) union(LETTERS[1:5], x))))

-输出

[1] "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A"
[37] "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E"

---

或者另一个选项是 complete

library(dplyr)
library(tidyr)
library(data.table)
tibble(col1 = my.vector) %>%
    group_by(rn = rowid(col1)) %>%
    complete(col1 = LETTERS[1:5]) %>%
    ungroup %>%
    pull(col1)

-输出

1] "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A"
[37] "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E"