R plyr data.table，应用data.frame的某些列

问题描述

我正在寻找加速代码的方法.我正在研究apply/ply方法以及data.table.不幸的是，我遇到了问题.

I am looking for ways to speed up my code. I am looking into the apply/ply methods as well as data.table. Unfortunately, I am running into problems.

这是一个小样本数据:

ids1   <- c(1, 1, 1, 1, 2, 2, 2, 2)
ids2   <- c(1, 2, 3, 4, 1, 2, 3, 4)
chars1 <- c("aa", " bb ", "__cc__", "dd  ", "__ee", NA,NA, "n/a")
chars2 <- c("vv", "_ ww_", "  xx  ", "yy__", "  zz", NA, "n/a", "n/a")
data   <- data.frame(col1 = ids1, col2 = ids2,
                 col3 = chars1, col4 = chars2,
          stringsAsFactors = FALSE)

这是使用循环的解决方案:

Here is a solution using loops:

library("plyr")
cols_to_fix <- c("col3","col4")
for (i in 1:length(cols_to_fix)) {
  data[,cols_to_fix[i]] <- gsub("_", "", data[,cols_to_fix[i]])
  data[,cols_to_fix[i]] <- gsub(" ", "", data[,cols_to_fix[i]])
  data[,cols_to_fix[i]] <- ifelse(data[,cols_to_fix[i]]=="n/a", NA, data[,cols_to_fix[i]])
}

我最初看过ddply，但是我想使用的某些方法仅采用矢量.因此，我无法弄清楚如何仅对某些列进行ddply

I initially looked at ddply, but some methods I want to use only take vectors. Hence, I cannot figure out how to do ddply across just certain columns one-by-one.

此外，我一直在查看laply，但是我想返回更改后的原始data.frame.谁能帮我?谢谢.

Also, I have been looking at laply, but I want to return the original data.frame with the changes. Can anyone help me? Thank you.

根据先前的建议，这是我尝试从plyr软件包中使用的内容.

Based on the suggestions from earlier, here is what I tried to use from the plyr package.

选项1:

data[,cols_to_fix] <- aaply(data[,cols_to_fix],2, function(x){
   x <- gsub("_", "", x,perl=TRUE)
   x <- gsub(" ", "", x,perl=TRUE)
   x <- ifelse(x=="n/a", NA, x)
},.progress = "text",.drop = FALSE)

选项2:

data[,cols_to_fix] <- alply(data[,cols_to_fix],2, function(x){
   x <- gsub("_", "", x,perl=TRUE)
   x <- gsub(" ", "", x,perl=TRUE)
   x <- ifelse(x=="n/a", NA, x)
},.progress = "text")

选项3:

data[,cols_to_fix] <- adply(data[,cols_to_fix],2, function(x){
   x <- gsub("_", "", x,perl=TRUE)
   x <- gsub(" ", "", x,perl=TRUE)
   x <- ifelse(x=="n/a", NA, x)
},.progress = "text")

这些都不给我正确的答案.

None of these are giving me the correct answer.

apply效果很好，但是我的数据非常大，并且plyr包中的进度条非常好.再次感谢.

apply works great, but my data is very large and the progress bars from plyr package would be a very nice. Thanks again.

推荐答案

这是使用set的data.table解决方案.

Here's a data.table solution using set.

require(data.table)
DT <- data.table(data)
for (j in cols_to_fix) {
    set(DT, i=NULL, j=j, value=gsub("[ _]", "", DT[[j]], perl=TRUE))
    set(DT, i=which(DT[[j]] == "n/a"), j=j, value=NA_character_)
}

DT
#    col1 col2 col3 col4
# 1:    1    1   aa   vv
# 2:    1    2   bb   ww
# 3:    1    3   cc   xx
# 4:    1    4   dd   yy
# 5:    2    1   ee   zz
# 6:    2    2   NA   NA
# 7:    2    3   NA   NA
# 8:    2    4   NA   NA

注意:使用PCRE(perl=TRUE)可以提高速度，特别是在较大的向量上.

Note: Using PCRE (perl=TRUE) has nice speed-up, especially on bigger vectors.

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