如何在R中读取和命名不同的CSV文件 [英] How to read and name different CSV files in R

问题描述

我想在多个csv文件上进行比较，所以我编写了这段代码来读取我拥有的不同csv文件：

I would like to work on several csv files to make some comparisons, so I wrote this code to read the different csv files I have:

path <- "C:\\data\\"
files <- list.files(path=path, pattern="*.csv")
for(file in files)
{
  perpos <- which(strsplit(file, "")[[1]]==".")
  assign(
    gsub(" ","",substr(file, 1, perpos-1)), 
    read.csv(paste(path,file,sep="")))
}

我的csv文件是这样的：

My csv files are something like this:

Start Time,End Time,Total,Diffuse,Direct,Reflected
04/09/14 00:01:00,04/09/14 00:01:00,2.221220E-003,5.797364E-004,0.000000E+000,1.641484E-003,
04/09/14 00:02:00,04/09/14 00:02:00,2.221220E-003,5.797364E-004,0.000000E+000,1.641484E-003,
04/09/14 00:03:00,04/09/14 00:03:00,2.221220E-003,5.797364E-004,0.000000E+000,1.641484E-003,
(...)

使用我的代码，R正确分离所有文件，但要分别em会在表的开头添加一个额外的空间：

Using my code, R separate correctly all files, but for each of them it creates a table adding a more extra space at the beginning:

                 |Start Time       |End Time     |Total        |Diffuse      |Direct       |Reflected
04/09/14 00:01:00|04/09/14 00:01:00|2.221220E-003|5.797364E-004|0.000000E+000|1.641484E-003|NA
...

我该如何解决？

此外，考虑到每个文件的原始名称确实很长，是否可以使用文件的最后一个字母来命名每个data.frame？还是只是基数？

Moreover, considering that the original name of each file is really long, is it possible to name each data.frame using the last letters of the file? Or just a cardinal number?

推荐答案

我建议使用data.table包-速度更快，并且用于非空白列最后，它将这些转换为 NA （以我的经验）。这是我为类似任务编写的一些代码：

I would suggest using the data.table package - it's faster and for non-blank columns in the end, it converts those to NA (in my experience). Here's some code I wrote for a simialr task:

read_func <- function(z) {
  dat <- fread(z, stringsAsFactors = FALSE)
  names(dat) <- c("start_time", "end_time", "Total", "Diffuse", "Direct", "Reflect")
  dat$start_tme <- as.POSIXct(strptime(dat$start_tme,
                    format = "%d/%m/%y %H:%M:%S"), tz = "Pacific/Easter")
  patrn <- "([0-9][0-9][0-9])\\.csv"
  dat$type <- paste("Dataset",gsub(".csv", "", regmatches(z,regexpr(patrn, z))),sep="")
  return(as.data.table(dat))
}

path <- ".//Data/" 
file_list <- dir(path, pattern = "csv")
file_names <- unname(sapply(file_list, function(x) paste(path, x, sep = "")))
data_list <- lapply(file_names, read_func)

dat <- rbindlist(data_list, use.names = TRUE) 

rm(path, file_list, file_names)

带有每个项目的列表作为cor中的data.table响应文件名。我假设所有文件名在扩展名前都有一个三位数，我曾用它为每个data.table分配一个变量 type 。您可以更改 patrn 以匹配您的特定用例。这样，当您将它们全部合并到单个data.table dat 中时，始终可以根据类型进行排序/过滤。例如，如果您想绘制 Dataset158 diffuse vs direct >和 datase222 ，您可以执行以下操作：

This will give you a list with each item as the data.table from the corresponding file name. I assumed that all file names have a three digit number before the extension which I used to assign a variable type to each data.table. You can change patrn to match your specific use case. This way, when you combine all of them into a single data.table dat, you can always sort/filter based on type. For example, if youwanted to plot diffuse vs direct for Dataset158 and datase222, you could do the following:

ggplot(data = dat[type == 'Dataset158' | type == 'Dataset222'], 
       aes(x = Diffuse, y = Direct)) + geom_point()

希望这会有所帮助！

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