使用循环将多个 data.frames 合并为一个 data.frame [英] Merge several data.frames into one data.frame with a loop

问题描述

我正在尝试merge几个data.frames到一个data.frame.因为我有一个完整的文件列表，所以我试图用循环结构来做.

I am trying to merge several data.frames into one data.frame. Since I have a whole list of files I am trying to do it with a loop structure.

到目前为止循环方法工作正常.但是，它看起来效率很低，我想知道是否有更快更简单的方法.

So far the loop approach works fine. However, it looks pretty inefficient and I am wondering if there is a faster and easier approach.

场景如下:我有一个包含多个 .csv 文件的目录.每个文件都包含可用作合并变量的相同标识符.由于文件相当大，我想一次将每个文件一个读取到 R 中，而不是一次读取所有文件.所以我用 list.files 获取目录的所有文件并读入前两个文件.之后我使用 merge 得到一个 data.frame.

Here is the scenario: I have a directory with several .csv files. Each file contains the same identifier which can be used as the merger variable. Since the files are rather large in size I thought to read each file one at a time into R instead of reading all files at once. So I get all the files of the directory with list.files and read in the first two files. Afterwards I use merge to get one data.frame.

FileNames <- list.files(path=".../tempDataFolder/")
FirstFile <- read.csv(file=paste(".../tempDataFolder/", FileNames[1], sep=""),
             header=T, na.strings="NULL")
SecondFile <- read.csv(file=paste(".../tempDataFolder/", FileNames[2], sep=""),
              header=T, na.strings="NULL")
dataMerge <- merge(FirstFile, SecondFile, by=c("COUNTRYNAME", "COUNTRYCODE", "Year"),
             all=T)

现在我使用 for 循环来获取所有剩余的 .csv 文件并将它们merge 到已经存在的 数据中.框架:

Now I use a for loop to get all the remaining .csv files and merge them into the already existing data.frame:

for(i in 3:length(FileNames)){ 
ReadInMerge <- read.csv(file=paste(".../tempDataFolder/", FileNames[i], sep=""),
               header=T, na.strings="NULL")
dataMerge <- merge(dataMerge, ReadInMerge, by=c("COUNTRYNAME", "COUNTRYCODE", "Year"),
             all=T)
}

尽管它工作得很好，但我想知道是否有更优雅的方式来完成工作?

Even though it works just fine I was wondering if there is a more elegant way to get the job done?

推荐答案

您可能想仔细查看 stackoverflow 上的相关问题.

我会分两步来解决这个问题:导入所有数据(使用 plyr)，然后将它们合并在一起:

I would approach this in two steps: import all the data (with plyr), then merge it together:

filenames <- list.files(path=".../tempDataFolder/", full.names=TRUE)
library(plyr)
import.list <- llply(filenames, read.csv)

这将为您提供您现在需要合并在一起的所有文件的列表.有很多方法可以做到这一点，但这里有一种方法(使用 Reduce):

That will give you a list of all the files that you now need to merge together. There are many ways to do this, but here's one approach (with Reduce):

data <- Reduce(function(x, y) merge(x, y, all=T, 
    by=c("COUNTRYNAME", "COUNTRYCODE", "Year")), import.list, accumulate=F)

或者，如果您对 Reduce 不满意，您可以使用 reshape 包执行此操作:

Alternatively, you can do this with the reshape package if you aren't comfortable with Reduce:

library(reshape)
data <- merge_recurse(import.list)

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