阅读并rbind多个csv文件 [英] Read and rbind multiple csv files

问题描述

我有一系列csv文件（每一个一个）具有相同的列标题和不同的行数。原来我正在读他们，并合并他们像这样;

  setwd<  - （N：/通过巡航/设得兰格数据）
 LengthHeight2013<  - .csv（N：/通过巡航/ Shetland / R_0113A_S2013_WD.csv振铃数据，sep =，，header = TRUE）
 LengthHeight2012<  -  read.csv（N： Shetland / R_0212A_S2012_WD.csv，sep =，，header = TRUE）
 LengthHeight2011<  -  read.csv（N：/通过巡航/ Shetland / R_0211A_S2011_WOD.csv振铃数据，sep =， ，header = TRUE）
 LengthHeight2010<  -  read.csv（N：/通过巡航环境数据/ Shetland / R_0310A_S2010_WOD.csv，sep =，，header = TRUE）
 LengthHeight2009& -  read.csv（N：/通过巡航/ Shetland / R_0309A_S2009_WOD.csv振铃数据，sep =，，header = TRUE）
 
 LengthHeight<  -  merge（LengthHeight2013，LengthHeight2012，all = TRUE）
 LengthHeight<  -  merge（LengthHeight，LengthHeight2011，all = TRUE）
 LengthHeight<  -  merge（LengthHeight，LengthHeight2010，all = TRUE）
 LengthHeight<  -  merge ，LengthHeight2009，all = TRUE）
  

我想知道re是一个更短或更简单的方法来做到这一点，也考虑到每次我运行脚本，我可能想看看不同的几年。

我也发现托尼·库克森（Tony Cookson）的这段代码看起来像我想要的，但是它为我生成的数据帧只有正确的头，但没有数据行。

  multmerge = function（mypath）{
 filenames = list.files（path = mypath，full.names = TRUE ）
 datalist = lapply（filenames，function（x）{read.csv（file = x，header = T）}）
减少（function（x，y）{merge（x，y）} ，datalist）
 
 mymergeddata = multmerge（C：// R // mergeme）
  

解决方案

查找文件（ list.files ），并循环读取文件（ lapply ），然后调用（ do.call ）行绑定（ rbind ）将所有文件一起排列。

  myMergedData<  -  
 do.call（rbind，
 lapply .files（path =N：/通过巡航记录数据），read.csv）
  

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)

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.

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")

解决方案

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))

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