跨数据框的特定列按行连接 [英] Concatenate row-wise across specific columns of dataframe

问题描述

我有一个带有列的数据框，当将这些列连接(按行)作为字符串时，我可以将数据框划分为所需的形式.

I have a data frame with columns that, when concatenated (row-wise) as a string, would allow me to partition the data frame into a desired form.

> str(data)
'data.frame':   680420 obs. of  10 variables:
 $ A              : chr  "2011-01-26" "2011-01-26" "2011-02-09" "2011-02-09" ...
 $ B              : chr  "2011-01-26" "2011-01-27" "2011-02-09" "2011-02-10" ...
 $ C              : chr  "2011-01-26" "2011-01-26" "2011-02-09" "2011-02-09" ...
 $ D              : chr  "AAA" "AAA" "BCB" "CCC" ...
 $ E              : chr  "A00001" "A00002" "B00002" "B00001" ...
 $ F              : int  9 9 37 37 37 37 191 191 191 191 ...
 $ G              : int  NA NA NA NA NA NA NA NA NA NA ...
 $ H              : int  4 4 4 4 4 4 4 4 4 4 ...

对于每一行，我想将 F、E、D 和 C 列中的数据连接成一个字符串(下划线字符作为分隔符).以下是我在这方面的失败尝试:

For each row, I would like to concatenate the data in columns F, E, D, and C into a string (with the underscore character as separator). Below is my unsuccessful attempt at this:

data$id <- sapply(as.data.frame(cbind(data$F,data$E,data$D,data$C)), paste, sep="_")

下面是不想要的结果:

  > str(data)
    'data.frame':   680420 obs. of  10 variables:
     $ A              : chr  "2011-01-26" "2011-01-26" "2011-02-09" "2011-02-09" ...
     $ B              : chr  "2011-01-26" "2011-01-27" "2011-02-09" "2011-02-10" ...
     $ C              : chr  "2011-01-26" "2011-01-26" "2011-02-09" "2011-02-09" ...
     $ D              : chr  "AAA" "AAA" "BCB" "CCC" ...
     $ E              : chr  "A00001" "A00002" "B00002" "B00001" ...
     $ F              : int  9 9 37 37 37 37 191 191 191 191 ...
     $ G              : int  NA NA NA NA NA NA NA NA NA NA ...
     $ H              : int  4 4 4 4 4 4 4 4 4 4 ...
     $ id             : chr [1:680420, 1:4] "9" "9" "37" "37" ...
      ..- attr(*, "dimnames")=List of 2
      .. ..$ : NULL
      .. ..$ : chr  "V1" "V2" "V3" "V4"

任何帮助将不胜感激.

推荐答案

尝试

 data$id <- paste(data$F, data$E, data$D, data$C, sep="_")

相反.向量化代码的美妙之处在于您不需要逐行循环或循环等效的 *apply 函数.

instead. The beauty of vectorized code is that you do not need row-by-row loops, or loop-equivalent *apply functions.

编辑更好的是

 data <- within(data,  id <- paste(F, E, D, C, sep=""))

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