读取并绑定多个 csv 文件

问题描述：

我有一系列具有相同列标题和不同行数的 csv 文件(每个文件一个).最初我正在阅读它们并像这样合并它们；

I have a series of csv files (one per anum) with the same column headers and different number of rows. Originally I was reading them in and merging them like so;

setwd <- ("N:/Ring data by cruise/Shetland")
LengthHeight2013 <- read.csv("N:/Ring data by      cruise/Shetland/R_0113A_S2013_WD.csv",sep=",",header=TRUE)
LengthHeight2012 <- read.csv("N:/Ring data by cruise/Shetland/R_0212A_S2012_WD.csv",sep=",",header=TRUE)
LengthHeight2011 <- read.csv("N:/Ring data by cruise/Shetland/R_0211A_S2011_WOD.csv",sep=",",header=TRUE)
LengthHeight2010 <- read.csv("N:/Ring data by cruise/Shetland/R_0310A_S2010_WOD.csv",sep=",",header=TRUE)
LengthHeight2009 <- read.csv("N:/Ring data by cruise/Shetland/R_0309A_S2009_WOD.csv",sep=",",header=TRUE)

LengthHeight <- merge(LengthHeight2013,LengthHeight2012,all=TRUE)
LengthHeight <- merge(LengthHeight,LengthHeight2011,all=TRUE)
LengthHeight <- merge(LengthHeight,LengthHeight2010,all=TRUE)
LengthHeight <- merge(LengthHeight,LengthHeight2009,all=TRUE)

我想知道是否有更短/更整洁的方法来做到这一点，同时考虑到每次运行脚本时我可能想要查看不同的年份范围.

I would like to know if there is a shorter/tidier way to do this, also considering that each time I run the script I might want to look at a different range of years.

我还发现了 Tony Cookson 的这段代码，它看起来像我想要的那样，但是它为我生成的数据帧只有正确的标题，但没有数据行.

I also found this bit of code by Tony Cookson which looks like it would do what I want, however the data frame it produces for me has only the correct headers but no data rows.

multmerge = function(mypath){
filenames=list.files(path=mypath, full.names=TRUE)
datalist = lapply(filenames, function(x){read.csv(file=x,header=T)})
Reduce(function(x,y) {merge(x,y)}, datalist)

mymergeddata = multmerge("C://R//mergeme")

答

查找文件(list.files)并循环读取文件(lapply)，然后调用 (do.call) 行绑定 (rbind) 将所有文件按行放在一起.

Find files (list.files) and read the files in a loop (lapply), then call (do.call) row bind (rbind) to put all files together by rows.

myMergedData <- 
  do.call(rbind,
          lapply(list.files(path = "N:/Ring data by cruise"), read.csv))

更新:有一个 vroom 包，根据对于手册，它比data.table::fread 和基础read.csv 快得多.语法看起来也很整洁:

Update: There is a vroom package, according to the manuals it is much faster than data.table::fread and base read.csv. The syntax looks neat, too:

library(vroom)
myMergedData <- vroom(files)

读取并绑定多个 csv 文件

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