我们可以使用dplyr和tidyr中的函数将所有列的内容合并在一起，然后过滤掉与合并列名相同的内容，dt2就是最终的输出。

# Create example data
dt <- read.table(text = "Name Age MonthBorn
Bob 23 September
Steve 45 June 
Bob 23 September
Name Age MonthBorn
Sue 74 January
Name Age MonthBorn
Tracy 31 February",
                 header = TRUE, stringsAsFactors = FALSE)

# Load package
library(dplyr)
library(tidyr)

# Process the data
dt2 <- dt %>%
  unite(ColName, everything(), sep = ", ", remove = FALSE) %>%
  filter(ColName != toString(colnames(dt))) %>%
  select(-ColName)

dt2
   Name Age MonthBorn
1   Bob  23 September
2 Steve  45      June
3   Bob  23 September
4   Sue  74   January
5 Tracy  31  February

您的数据

df <- structure(list(Name_ = c("Bob", "Steve", "Bob", "Name", "Sue", 
"Name", "Tracy"), `_Age_` = c("23", "45", "23", "Age", "74", 
"Age", "31"), `_MonthBorn` = c("September", "June", "September", 
"MonthBorn", "January", "MonthBorn", "February")), .Names = c("Name_", 
"_Age_", "_MonthBorn"), row.names = c(NA, -7L), class = c("data.table", 
"data.frame"))

溶液

library(stringr)
df[!sapply(1:nrow(df), function(x) all(mapply(function(x,y) str_detect(x,y), colnames(df), df[x,]))),]

输出

Name_ _Age_ _MonthBorn
1:   Bob    23  September
2: Steve    45       June
3:   Bob    23  September
4:   Sue    74    January
5: Tracy    31   February

如果您的数据框大致如下所示：

Df <- Data.frame(Name, Age, MonthBorn)

然后，您可以使用ifelse语句来测试“MonthBorn”是否出现在一行中。

Df$MonthBornTest <- ifelse(Df$MonthBorn == “MonthBorn”, “True”, “False”}

然后，您应该能够执行此操作以删除包含True的行，从而有效地删除不再需要的行。

Df <- Df[!(Df$MonthBornTest == “True”), ]