R语言：关联DataFrame与向量以识别数据间隙及缺失行

现有如下DataFrame：

df <- structure(list(IDDATE = c(1669935600, 1669939200, 1669942800, 1669946400, 
1669950000, 1669953600, 1669957200, 1669960800, 1669964400, 1669968000, 
1669971600, 1669975200, 1669978800, 1669982400, 1669986000, 1669989600, 
1669993200, 1669996800, 1670000400, 1670004000, 1670007600, 1670011200, 
1670014800, 1670018400, 1670022000, 1670025600, 1670029200, 1670032800, 
1670036400, 1670040000, 1670043600, 1670047200, 1670050800, 1670054400, 
1670058000, 1670061600, 1670065200, 1670068800, 1670072400, 1670076000, 
1670079600, 1670083200, 1670086800, 1670090400, 1670094000, 1670097600, 
1670101200, 1670104800, 1670108400), Value = c(32, 18, 31, 29, 
34, 35, 21, 24, 35, 34, 31, 19, 29, 31, 29, 28, 19, 35, 22, 15, 
28, 18, 25, 17, 17, 24, 28, 35, 34, 35, 19, 29, 31, 33, 25, 21, 
28, 27, 22, 27, 15, 29, 27, 22, 17, 34, 17, 17, 31)), class = "data.frame", row.names = c(NA, 
-49L))

以及完整的时间戳向量：

IDDATE <- c(1669849200, 1669852800, 1669856400, 1669860000, 1669863600, 
1669867200, 1669870800, 1669874400, 1669878000, 1669881600, 1669885200, 
1669888800, 1669892400, 1669896000, 1669899600, 1669903200, 1669906800, 
1669910400, 1669914000, 1669917600, 1669921200, 1669924800, 1669928400, 
1669932000, 1669935600, 1669939200, 1669942800, 1669946400, 1669950000, 
1669953600, 1669957200, 1669960800, 1669964400, 1669968000, 1669971600, 
1669975200, 1669978800, 1669982400, 1669986000, 1669989600, 1669993200, 
1669996800, 1670000400, 1670004000, 1670007600, 1670011200, 1670014800, 
1670018400, 1670022000, 1670025600, 1670029200, 1670032800, 1670036400, 
1670040000, 1670043600, 1670047200, 1670050800, 1670054400, 1670058000, 
1670061600, 1670065200, 1670068800, 1670072400, 1670076000, 1670079600, 
1670083200, 1670086800, 1670090400, 1670094000, 1670097600, 1670101200, 
1670104800, 1670108400, 1670112000, 1670115600, 1670119200, 1670122800, 
1670126400, 1670130000, 1670133600, 1670137200, 1670140800, 1670144400, 
1670148000, 1670151600, 1670155200, 1670158800, 1670162400, 1670166000, 
1670169600, 1670173200, 1670176800, 1670180400, 1670184000, 1670187600, 
1670191200, 1670194800, 1670198400, 1670202000, 1670205600, 1670209200, 
1670212800, 1670216400, 1670220000, 1670223600, 1670227200, 1670230800, 
1670234400, 1670238000, 1670241600, 1670245200, 1670248800, 1670252400, 
1670256000, 1670259600, 1670263200, 1670266800, 1670270400, 1670274000, 
1670277600, 1670281200, 1670284800)

需要识别DataFrame中的数据间隙，尝试用dplyr的left_join关联时出现错误：

library(dplyr)
library(tidyverse)
Date <- df %>% left_join(IDDATE, by = "IDDATE")

错误信息：

Error in `auto_copy()`:
! `x` and `y` must share the same src.
ℹ set `copy` = TRUE (may be slow).
Run `rlang::last_error()` to see where the error occurred.

错误原因 #

left_join要求两个输入都是数据框（或tibble），但传入的第二个参数是普通数值向量，两者数据源类型不匹配，导致报错。

解决步骤 #

1. 将完整时间戳向量转为数据框
   先把IDDATE向量转换成包含同一列名的tibble：

   full_dates <- tibble(IDDATE = IDDATE)
   

2. 执行左连接
   用转换后的完整时间数据框和原数据框做左连接，保留所有完整时间戳，缺失数据的位置会填充NA：

   combined_df <- full_dates %>% 
     left_join(df, by = "IDDATE")
   

3. 识别数据间隙
   筛选出Value为NA的行就是数据间隙，也可以新增标记列明确区分：

   # 新增标记列，标记是否为数据间隙
   combined_df <- combined_df %>%
     mutate(is_gap = is.na(Value))
   
   # 提取所有数据间隙的时间戳
   gap_dates <- combined_df %>% filter(is_gap)
   

执行以上代码后，gap_dates就是所有缺失数据的时间戳集合，combined_df则包含了完整时间序列及对应的数据/间隙标记。

内容的提问来源于stack exchange，提问作者C. Guff