我在三个单独的文件夹中有许多csv文件,如下所示:
folder1
a1_0023.csv
a2_0034.csv
a3_6163.csv
...
(100 files)
folder2
b1_0023.csv
b2_0034.csv
b3_6163.csv
...
(100 files)
folder3
c1_0023.csv
c2_0034.csv
c3_6163.csv
...
(100 files)
我有一个文本文件列出了最后四位数字:
theLastFourDigits.txt
0023
0034
6163
...
(100 lines)
对于0023
文件,我在R中做了一个简单的工作:
a <- read.table("D:/folder1/a1_0023.csv", header=FALSE, sep=",")
a <- as.matrix(a)
b <- read.table("D:/folder2/b1_0023.csv", header=FALSE, sep=",")
b <- as.matrix(b)
c <- read.table("D:/folder3/c1_0023.csv", header=FALSE, sep=",")
c <- as.matrix(c)
# Initiate the column vector that contains the results
myanswer <- matrix(0, nrow=100, ncol=1)
# Do a simple job, and store the result in myanswer column
myanswer[1] = nrow(a)*nrow(b)/nrow(c)
我在这里有两个问题:(1)我们如何为整个100位数字迭代这个过程? (2)如果我没有theLastFourDigits.txt
列表文件,我们如何才能完成多个工作?
修改
我尝试过以下内容:
setwd("D:/folder1/")
filelist1 <- Sys.glob("*.csv")
setwd("D:/folder2/")
filelist2 <- Sys.glob("*.csv")
setwd("D:/folder3/")
filelist3 <- Sys.glob("*.csv")
for (i in 1:100) {
setwd("D:/folder1/")
a <- read.csv(filelist1[i], header=FALSE, sep=",")
a <- as.matrix(a)
setwd("D:/folder2/")
b <- read.csv(filelist2[i], header=FALSE, sep=",")
b <- as.matrix(b)
setwd("D:/folder3/")
c <- read.csv(filelist3[i], header=FALSE, sep=",")
c <- as.matrix(c)
nrow(a)*nrow(b)/nrow(c)
}
错误信息如下:
Error in read.table(file = file, header = header, sep = sep, quote = quote, :
no lines available in input
3 stop("no lines available in input")
2 read.table(file = file, header = header, sep = sep, quote = quote,
dec = dec, fill = fill, comment.char = comment.char, ...)
1 read.csv(filelist1[i], header = FALSE, sep = ",")
我在这里缺少什么?
答案 0 :(得分:2)
对于问题(2),您可能会发现此功能很有用。我过去曾用它来读取给定文件夹中的所有csv文件(Windows 7)。您需要根据应用程序的需要修改read.csv()参数。读入文件夹中的所有数据后,您可以使用lapply()将所有数据帧转换为矩阵。
list.csv <- function(mydir, add.source=TRUE) {
# combine all csv files in a given directory into a single list
filenames <- list.files(mydir)[grep(".csv$", list.files(mydir))]
nfiles <- length(filenames)
# create an empty list where all the files will be stored
files.list <- vector(mode="list", length=nfiles)
for(i in 1:nfiles) {
# read the data into a temporary file
temp <- read.csv(paste(mydir, filenames[i], sep=""), as.is=TRUE)
# add a new column identifying the source file
if(add.source) temp$source <- filenames[i]
# put the data into the list
files.list[[i]] <- temp
}
files.list
}
mylist <- list.csv("C:/temp/")
# look at headers from all the data frames
lapply(mylist, head)
# convert all the data frames to matrices
mylistm <- lapply(mylist, as.matrix)