R 在数据框的新列中打印匹配位置

我要做的是在一组列上搜索，然后返回一个包含 1.列中的字符串及其来源的列的名称

df <- structure(list(ID = c("A1.1234567_10", "A1.1234567_20"), 
                 var1 = c("NORMAL", "NORMAL"), 
                 var2 = c("NORMAL", "SUSPECTED"), 
                 var3 = c("NORMAL", "NORMAL"), 
                 var4 = c("NORMAL", "NORMAL"), 
                 var5 = c("NORMAL", "NORMAL"), 
                 var6 = c("NORMAL", "NORMAL"), 
                 var7 = c("NORMAL", "ABNORMAL"), 
                 var8 = c("NORMAL", "NORMAL")), 
            .Names = c("ID", "var1", "var2", "var3", "var4", "var5", "var6", "var7", "var8"), 
            class = "data.frame", row.names = c(NA, -2L))

           ID   var1   var2   var3   var4   var5   var6     var7   var8
A1.1234567_10  NORMAL NORMAL NORMAL NORMAL NORMAL NORMAL   NORMAL NORMAL
A1.1234567_20 NORMAL SUSPECTED NORMAL NORMAL NORMAL NORMAL ABNORMAL NORMAL

---

我知道我可以自己为它们编制索引，但最终查看它们的人需要在每一行中将其可视化。应用

函数将成为循环遍历每一行的主力。在每一行上使用自定义函数编译“坏”值的字符串向量及其对应的列名索引。在连接行上找到的所有坏值列组合之前，请将坏值和列名组合在一起。最后，该行应作为可添加到原始数据帧的向量返回

#This example uses the dataframe, `df` you defined in your question. 
#
# this function works on one row at a time and can accept one or more
# accepted values as a character vector.  
library(magrittr)

build_nonnorm_str <- function(row, col_names, norm_value) {
  # get the index of any bad values, excluding the column named "ID"
  bad_col_indx <- which(!row %in% norm_value &
                    !names(row) == "ID")

  # appropriately assign NA to rows with no bad values,
  # otherwise put together the string to be appended to
  # the new dataframe
  if (length(bad_col_indx > 0)) {
    abnorm_str <- paste0(row[bad_col_indx], 
                         "_",
                         col_names[bad_col_indx], 
                         sep = " ") %>%
      paste0(collapse = "") %>%
      trimws()
  } else {
    abnorm_str <- NA
  }

  return(abnorm_str)
}

# Use the apply function to send the function one rows worth of data
# and append it to the new column
df$abnormal_summary <- apply(df,
                             1,
                             build_nonnorm_str,
                             col_names = names(df),
                             norm_value = "NORMAL")

#此示例使用您在问题中定义的数据帧'df'。
#
#此函数一次只能处理一行，可以接受一行或多行
#接受值作为字符向量。
图书馆（magrittr）
构建\u非标准\u str%
trimws（）
}否则{
异常你是想返回所有非“正常”的列，还是只返回那些“可疑”或“异常”的列？这非常有效。我想我也可以通过更改
bad\u col\u index
和更改一些基于
bad\u col\u indx@Randy的参数来选择这些列，谢谢你的关注g函数调用中的输入错误
#This example uses the dataframe, `df` you defined in your question. 
#
# this function works on one row at a time and can accept one or more
# accepted values as a character vector.  
library(magrittr)

build_nonnorm_str <- function(row, col_names, norm_value) {
  # get the index of any bad values, excluding the column named "ID"
  bad_col_indx <- which(!row %in% norm_value &
                    !names(row) == "ID")

  # appropriately assign NA to rows with no bad values,
  # otherwise put together the string to be appended to
  # the new dataframe
  if (length(bad_col_indx > 0)) {
    abnorm_str <- paste0(row[bad_col_indx], 
                         "_",
                         col_names[bad_col_indx], 
                         sep = " ") %>%
      paste0(collapse = "") %>%
      trimws()
  } else {
    abnorm_str <- NA
  }

  return(abnorm_str)
}

# Use the apply function to send the function one rows worth of data
# and append it to the new column
df$abnormal_summary <- apply(df,
                             1,
                             build_nonnorm_str,
                             col_names = names(df),
                             norm_value = "NORMAL")