Question

美好的一天，我有几个文本文件具有相同的布局，我想用fread（）函数读入。（请参阅此处的两个示例文件：https://www.dropbox.com/sh/grpai6ppc6oq3ka/AADyECZHz5KW7wtv5xjF5-ena?dl=0）文件分为两部分，第一部分包含16列，第二部分包含第7列。我只想要第一部分的数据，而只需要第1列和第2列。

 dat10 <- fread("CalcV10.txt", select = c(1,2), verbose=TRUE, col.names = c("Net", "Nrp"))

> head(dat10)
Net Nrp
1: 225   1
2: 247   1
3: 268   1
4: 287   1
5: 301  12
6: 302   4

这适用于我的部分数据（例如CalcV10），其中不仅有一行数据。

对于另一个文件，它只包含一行数据，但是第一部分被跳过，而文档的第二部分则被读取：

> head(dat3)
Net  Nrp
1: 1000      9.9   
2: 1000     14.8   
3: 1000     12.7    
4: 1000     14.8    
5: 1000     11.7    
6: 1000     14.8

我试图改变行数（colClasses = list（character = 1:16）），但这没有帮助。我很感激每一个小小的提示！

最好，yakuelin

我正在使用1.10.4版本的data.table，R版本3.3.2，版本1.0.136的R Studio（所有这些都在两周前更新）

修改

我有40个相同名称和布局的文件（Calc.txt）。它们位于20个文件夹中，名为V1 - V20，每个文件夹都有两个以两个sim_types命名的子文件夹。为了读入这些文本文件，我创建了以下函数：

   read.res <- function(NrV, sim_type, FT) {
   dat <- data.frame()
   V <- paste("V", 1:NrV, sep="")

   for (i in 1:NrV) {
   Dir <- file.path(dataDir, V[i], sim_type)
   setwd(Dir)
   dat0 <- fread("Calc.txt", select = c(1,2), col.names = c("Net", "Nrp"))
   dat0$type <- FT
    dat<-rbind(dat, dat0)
   }
  dat<-as.data.frame(dat)
  return(dat) }

  Forest <- read.res(NrV=20, sim_type=sim_F,  FT="F") 
  nonForest <- read.res(NrV=20, sim_type=sim_nF, FT="nF") 
  data <- rbind(Forest, nonForest)

@ Sathish可以一次读取一个文件，但是对所有文件自动执行此步骤会很棒。我很难将Sathish的建议纳入我的职能。有什么想法吗？

Answer 1

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修改

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如果您想要使用文件和目录，请尝试使用此可重现的示例，该示例将创建目录和文件。将library('data.table') fn1 <- "CalcV3.txt" fn2 <- "CalcV10.txt" n1 <- grep('Sim_data', readLines(fn1)) - 5 # get the line number matching Sim_data and subtract 5 to it x1 <- fread(fn1, nrows = n1, header = F, skip = 1, sep = '\t', strip.white = F, stringsAsFactors = F) # get file contents for the n1 rows n2 <- grep('Sim_data', readLines(fn2)) - 5 x2 <- fread(fn2, nrows = n2, header = F, skip = 1, sep = '\t', strip.white = F, stringsAsFactors = F) # split the file contents and convert it to data table my_func <- function(x, from, to) { y <- strsplit(x, '\ ') # split string by space y <- lapply(y, function(z) as.numeric(z[ z != '' ] )[from:to]) # remove blank characters t(rbindlist(l = list( y ))) # combine list elements into data table } my_func(x1$V1, 1, 16) # all columns # [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] # V1 1000 2100 7 10 11 12 0.9 1.9 2 2.2 12.3 14.8 17.1 42.1 -52.1 -40.1 my_func(x1$V1, 2, 4) # columns from 2 to 4 # [,1] [,2] [,3] # V1 2100 7 10 my_func(x2$V1, 1, 16) # all columns # [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] # V1 225 1 773.1 773.1 773.1 773.1 0.5 0.5 0.5 0.5 21.5 21.5 34.7 34.7 -42.5 -42.5 # V2 247 1 833.5 833.5 833.5 833.5 0.6 0.6 0.6 0.6 20.2 20.2 40.9 40.9 -15.4 -15.4 # V3 268 1 704.4 704.4 704.4 704.4 1.8 1.8 1.8 1.8 20.6 20.6 32.8 32.8 -42.9 -42.9 # V4 287 1 325.1 325.1 325.1 325.1 0.9 0.9 0.9 0.9 14.0 14.0 25.0 25.0 -42.1 -42.1 # V5 301 12 170.8 325.8 437.8 437.8 0.5 0.8 5.9 5.9 9.8 16.3 17.2 27.2 -32.2 -20.2 # V6 302 4 85.0 218.0 218.0 218.0 0.5 0.5 0.5 0.5 6.8 14.9 8.1 15.1 -38.4 -34.4 # V7 303 3 70.5 85.5 85.5 85.5 0.5 0.5 0.5 0.5 6.2 6.4 11.4 12.4 -26.9 -17.9 # V8 316 56 499.1 689.1 728.1 772.1 0.6 1.3 1.8 1.9 15.9 20.9 28.9 36.9 -38.6 -31.6 # V9 317 772 367.5 569.5 618.5 705.5 0.5 0.7 0.9 1.0 13.7 17.9 27.3 35.3 -26.6 -14.6 # V10 318 52 304.2 445.2 511.2 615.2 0.6 1.3 1.8 2.0 12.5 17.8 23.5 34.5 -21.6 0.4 # V11 319 4 412.3 527.3 527.3 527.3 0.6 0.7 0.7 0.7 15.1 20.9 21.9 33.9 -25.8 -4.8 # V12 330 14 107.7 264.7 421.7 421.7 0.5 0.8 1.3 1.3 8.2 14.4 14.7 27.7 -45.7 -27.7 # V13 331 872 229.3 406.3 468.3 531.3 0.5 1.0 1.5 2.3 11.7 17.1 19.2 28.2 -47.5 -37.5 # V14 332 35 428.1 690.1 728.1 774.1 1.1 3.2 4.1 4.8 17.0 22.6 22.6 35.6 -51.3 -35.3 # V15 333 4 452.0 523.0 523.0 523.0 0.7 1.0 1.0 1.0 15.8 17.1 28.5 29.5 -45.9 -38.9 # V16 1000 2100 143.6 200.6 215.6 232.6 1.2 2.1 2.3 2.4 12.4 14.8 8.1 17.1 -52.1 -41.1变量设置为所需位置。

# split the file contents and convert it to data table my_func <- function(x, from, to) { y <- strsplit(x, '\ ') # split string by space y <- lapply(y, function(z) as.numeric(z[ z != '' ] )[from:to]) # remove blank characters t(rbindlist(l = list( y ))) # combine list elements into data table } root_path <- "temp" # Set `root_path` variable to a desired location fdirs <- unlist(lapply(file.path(root_path, c(paste('V', 1:20, sep = ''))), function(x) file.path(x, c(paste('sim_types', 1:2, sep = ''))))) all_dfs <- list() # this list contains data frames of all files for ( i in fdirs) { require('data.table') fn <- file.path(i, 'Calc.txt') if ( file.exists( fn ) ){ n1 <- grep('Sim_data', readLines(fn)) - 5 # get the line number matching Sim_data and subtract 5 to it x1 <- fread(fn, nrows = n1, header = F, skip = 1, sep = '\t', strip.white = F, stringsAsFactors = F) # get file contents for the n1 rows df <- my_func(x1$V1, 1, 2) colnames(df) <- c('Net', 'Nrp') all_dfs[[fn]] <- df } else { warning(paste('The file ', fn, ' does not exist!', sep = '')) } } warnings() # 38: The file temp/V20/sim_types2/Calc.txt does not exist! all_dfs # $`temp/V1/sim_types1/Calc.txt` # Net Nrp # V1 1000 2100 # # $`temp/V1/sim_types2/Calc.txt` # Net Nrp # V1 1000 2100 # # $`temp/V2/sim_types1/Calc.txt` # Net Nrp # V1 1000 2100 # # $`temp/V2/sim_types2/Calc.txt` # Net Nrp # V1 1000 2100

data.table fread（） - 跳过文档的第一部分

1 个答案: