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您好，我是这个论坛的新手，并且在 R 中编码相对较新。我在构建频率表时遇到问题，当我的一些变量被链接时，该表填充零计数。我的测试数据包括 3 个植被属的植被计数，在 10 个地块中，有 2 种处理类型和两种子站点类型。我的每个地块只能是湿的或干的，治疗或控制不能两者兼而有之。

以下是我的数据的结构：

structure(list(SITE = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "NAKVAK", class = "factor"), 
PLOT = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("1A", 
"1B", "2A", "2B", "3A", "3B", "4A", "4B", "5A", "5B"), class = "factor"), 
PLOT2 = c(1L, 1L, 1L, 1L, 1L, 1L), SUBSITE = structure(c(1L, 
1L, 1L, 1L, 1L, 1L), .Label = c("DRY", "WET"), class = "factor"), 
TRTMT = structure(c(2L, 2L, 2L, 2L, 2L, 2L), .Label = c("CTL", 
"OTC"), class = "factor"), YEAR = c(2010L, 2010L, 2010L, 
2010L, 2010L, 2021L), GENUS = structure(c(3L, 1L, 2L, 2L, 
3L, 1L), .Label = c("Betula", "Carex", "Cladonia"), class = "factor"), 
LIFEFORM = structure(c(2L, 3L, 1L, 1L, 2L, 3L), .Label = c("FORB", 
"LICHEN", "SDECI"), class = "factor"), ABUND = c(1L, 1L, 
1L, 1L, 1L, 1L)), row.names = c(NA, -6L), class = c("tbl_df",

“tbl”，“data.frame”））

我正在尝试构建一个表格，其中包含 Plot ID、子站点（湿或干）、处理（OTC 或对照）、年份（2010 或 2021）、属和丰度计数。我也想包括零，所以我需要知道什么时候没有找到特定的属。我已经能够构建一个填充零计数的频率表，但问题是它还创建了我的数据集中不存在的变量组合。例如，地块 1A 始终位于经过 OTC 处理的干燥子站点中。然而，代码为地块 1A、湿子站点、OTC 和地块 1A、干子站点、控制等创建了一行...我正在寻找一种方法来链接我的地块、子站点和处理变量，以便丰度计数为零填写我的数据集中实际存在的绘图、子站点和处理的组合。

看起来它们应该是我最好的选择的功能是 tidyverse 的扩展和嵌套功能，但我愿意接受任何和所有建议！

**** 编辑以包含解决方案

vegdat <- as_tibble(read.csv("DummyDat100.csv"))
   
 spec.sum <- vegdat %>%
      group_by(PLOT, SUBSITE, TRTMT, GENUS, YEAR) %>% 
      summarise(count = sum(ABUND))

     Spec.sum <- as.data.table(spec.sum)
    
    #Create a new column that contains all site data 
    Spec.sum[, 'sampling' := paste(YEAR, PLOT, SUBSITE, TRTMT, sep = '_')]
    
    #Now get rid of columns that were combined into sampling col
    Spec.sum <- Spec.sum[, c('sampling', 'GENUS', 'count')]
    
    #Now expand this smaller data.table to include zeroes for absent genera
    Spec.sum <- as.data.table(complete(Spec.sum, sampling, GENUS,  fill = list(count = 0)))
    
    #Split that sampling col back into original columns
    Spec.sum <- Spec.sum[, c('YEAR', 'PLOT', 'SUBSITE', 'TRTMT') := tstrsplit(sampling, '_', keep = c(1,2,3,4))]
    
    #Remove the sampling column (if you want)
    Spec.sum[, sampling := NULL]

#Reorder the data.table
Spec.sum.tidy <- Spec.sum[, c('PLOT', 'SUBSITE', 'TRTMT', 'GENUS', 'YEAR', 'count')]
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