交叉检查跨数据框的重复值

2 回答

• 0

  我相信，到目前为止，我已经修复了原始问题中的循环，它们返回了预期的结果：

  # create lists
  dflist <- list(df1, df2, df3)
  criterialist <- list(c(1,2), c(1,3), c(2,3))
  
  # add index columns
  dflist <- lapply(dflist, function(x) {x[["index"]] <- seq_len(nrow(x)); x})
  
  # find combinations of dataframes to check
  combi <- combn(seq_along(dflist), 2)
  combi
  

  [，1] [，2] [，3]
  [1，] 1 1 2
  [2，] 2 3 3

  # check for matching rows
  for (k in seq_len(ncol(combi))) {
    i <- combi[1, k]
    j <- combi[2, k]
    tmp <- merge(dflist[[i]], dflist[[j]], 
                 by.x=criterialist[[i]], by.y=criterialist[[j]], all.x=TRUE)
    dflist[[i]][[paste0("row_df", j)]] <- tmp[order(tmp$index.x), "index.y"]
  }
  dflist
  

  [[1]]
  name1 zip1 data1 index row_df2 row_df3
  1 George 123 abc 1 2 NA
  2 Marge 456 def 2 3 NA
  3 Mike 789 foo 3 1 2

  [[2]]
  name2 data2 zip2 index row_df3
  1 Mike klm 789 1 2
  2 George xxx 123 2 NA
  3 Marge yyy 456 3 NA
  4 Bob zzz 678 4 1

  [[3]]
  data3 name3 zip3索引
  1 zzz Bob 678 1
  2 ggg Mike 789 2

  请注意，这是检查3个数据帧的预期结果（在问题的Edit2之前） .

  有几个缺陷导致原始代码中断：

  • 第二个 for 循环中的循环限制定义不正确： for (i in 1:length(dflist)-1){ . 这里， : 运算符优先，因此索引从 0 开始，这会导致错误 . 这可以通过另外一对parantheses for (i in 1:(length(dflist)-1)){ 来修复，甚至可以通过使用 seq_len() 函数更好地修复 for (i in seq_len(length(dflist)-1)) {

  • merge() 返回两列 index.x 和 index.y . 它只返回单个 index 列，以便与 df1 合并，其中OP不遗余力地添加索引列 .

  • merge() 的结果需要在追加之前按 index.x 排序 .

  • 双 for 循环导致数据帧与其自身的比较 . 相反， combn() 函数用于查找所有唯一组合 .

  回复于 2024-05-03T02:00:33+08:00
• 0

  谢谢你的反馈！

  道歉，我想当我编辑我的原始帖子时，它删除了我收到的一些输入 . 我不知道会那样做 .

  但是，我为此设置了一个解决方案，其中一个最重要的是合并，因为我没有意识到它会改变列和行的顺序 .

  无论如何，这有效：

  cross_checker4 <- function(dflist,criterialist) {
    # Initialize the output list
  
    returnlist <- list()
  
  
    # Initialize the outer loop length, 
    # this can be omitted in the for-loop below but let's 
    # keep it for historical reasons
  
    looplen1 <- length(dflist) - 1
  
    # Loop through all dataframes in dflist, 
    # this could just as well be for (i in 1:length(dflist)-1){}
  
    for (i in 1:looplen1) {
      # Initialize a temporary dataframe 
      # since we can't copy the data within dflist
      # Rearrange the columns for the output. 
      # Merge will mix them up otherwise
  
      temp_df1_drop <- dflist[[i]][-c(critlist[[i]])]
      temp_df1_keep <- dflist[[i]][c(critlist[[i]])]
      temp_df1 <- cbind(temp_df1_keep,temp_df1_drop)
  
      # Initialize the temporary criteria from criterialist
  
      temp_crit1 <- c(1:length(critlist[[i]]))
  
      # Loop through all remaining dataframes in dflist 
      # --> This is where we compare
  
      for (j in (i + 1):length(dflist)) {
        temp_df2 <- dflist[[j]]
  
  
        temp_df2_drop <- temp_df2[-c(critlist[[j]])]
        temp_df2_keep <- temp_df2[c(critlist[[j]])]
        temp_df2 <- cbind(temp_df2_keep,temp_df2_drop)
  
        # Add index column into dataframe to indicate 
        # which row the duplicate entry is on
  
        temp_df2$index <- 1:nrow(temp_df2)
  
        # Rename the index column
  
        indexer <- paste(c("index", j),collapse = " ")
        colnames(temp_df2)[colnames(temp_df2) == 'index'] <- indexer
  
        temp_crit2 <- c(1:length(critlist[[j]]))
  
        # Do the merge
  
        temp_df1 <-
          merge(
            temp_df1,temp_df2,by.x = temp_crit1,by.y = temp_crit2,all.x = TRUE
          )
      }
  
      # Insert merged dataframe into the returnlist
  
      returnlist[[length(returnlist) + 1]] <- temp_df1
  
    }
    # Since merge shoves in all columns in the comparison dataframe, 
    # we remove those columns and only leave index x
  
    for (k in 1:length(returnlist)) {
      for (o in (ncol(dflist[[k]]) + 1):(ncol(returnlist[[k]]))) {
        if (!grepl("index",names(returnlist[[k]])[o])) {
          returnlist[[k]] <- returnlist[[k]][,-o]
        }
  
      }
    }
  
    # Exit the loops and return the output list
    return(returnlist)
  }
  

  回复于 2024-05-03T02:00:33+08:00