Question

我有一个大文件，必须在R中导入。为此，我使用了fread。 fread正在将数字字段中的空格识别为NA，但无法将字符和integer64字段中的空格识别为NA。

fread将空格识别为字符字段的空单元格，并将空格识别为整数64字段的0。

当我使用read.table导入相同的数据时，它会将所有空格识别为NA。

请找到可复制的示例，

library(data.table)
x1 <- c("","","")
x2 <- c("1006678566","","1011160152")
x3 <- c("","ac","")
x4 <- c("","2","3")
df <- cbind.data.frame(x1,x2,x3,x4)
write.csv(df,"tr.csv")

tr1 <- fread("tr.csv", header=T, fill = T,
             sep= ",", na.strings = c("",NA), data.table = F,
             stringsAsFactors = FALSE)

tr2 <- read.table("tr.csv", fill = TRUE, header=T, 
                  sep= ",", na.strings = c(""," ", NA), 
                  stringsAsFactors = FALSE)

详细输出：

Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 4 threads (omp_get_max_threads()=4, nth=4)
  NAstrings = [<<>>, <<NA>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as integer
[02] Opening the file
  Opening file tr.csv
  File opened, size = 409 bytes.
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the input and different lines can end with different line endings (e.g. mixed \n and \r\n in one file). This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<"","x1","x2","x3","x4","x5","x>>
[06] Detect separator, quoting rule, and ncolumns
  Using supplied sep ','
  sep=','  with 7 fields using quote rule 0
  Detected 7 columns on line 1. This line is either column names or first data row. Line starts as: <<"","x1","x2","x3","x4","x5","x>>
  Quote rule picked = 0
  fill=true and the most number of columns found is 7
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to true
  Number of sampling jump points = 1 because (407 bytes from row 1 to eof) / (2 * 407 jump0size) == 0
  Type codes (jump 000)    : 56A255A  Quote rule 0
  All rows were sampled since file is small so we know nrow=16 exactly
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 56A255A
[10] Allocate memory for the datatable
  Allocating 7 column slots (7 - 0 dropped) with 16 rows
[11] Read the data
  jumps=[0..1), chunk_size=1048576, total_size=373
Read 16 rows x 7 columns from 409 bytes file in 00:00.042 wall clock time
[12] Finalizing the datatable
  Type counts:
         1 : bool8     '2'
         3 : int32     '5'
         1 : int64     '6'
         2 : string    'A'
=============================
   0.009s ( 22%) Memory map 0.000GB file
   0.029s ( 68%) sep=',' ncol=7 and header detection
   0.002s (  5%) Column type detection using 16 sample rows
   0.001s (  2%) Allocation of 16 rows x 7 cols (0.000GB) of which 16 (100%) rows used
   0.001s (  2%) Reading 1 chunks (0 swept) of 1.000MB (each chunk 16 rows) using 1 threads
   +    0.000s (  0%) Parse to row-major thread buffers (grown 0 times)
   +    0.000s (  0%) Transpose
   +    0.001s (  2%) Waiting
   0.000s (  0%) Rereading 0 columns due to out-of-sample type exceptions
   0.042s        Total

请帮助我解决此问题。

谢谢！

Answer 1

如果要避免在读取文件后进行其他操作，可以尝试使用

quote = FALSE

在写入csv时。这样可以防止在值周围使用引号" "，现在所有缺少的值都应读为NA。它应该看起来像这样-

# also turned off row names to prevent an additional column when reading the file.
write.csv(df, "tr.csv", quote = FALSE, row.names = FALSE)

输出-

tr1 <- fread("tr.csv", header=T, fill = T,
             sep= ",", na.strings = c("",NA), data.table = F,
             stringsAsFactors = FALSE)
tr1

 x1         x2   x3 x4
1 NA 1006678566 <NA> NA
2 NA         NA   ac  2
3 NA 1011160152 <NA>  3

tr2 <- read.table("tr.csv", fill = TRUE, header=T, 
                  sep= ",", na.strings = c(""," ", NA), 
                  stringsAsFactors = FALSE)
tr2

  x1         x2   x3 x4
1 NA 1006678566 <NA> NA
2 NA         NA   ac  2
3 NA 1011160152 <NA>  3

Answer 2

遇到了同样的问题，不得不求助于：

as.data.frame(
lapply(tr1,  function(x) {ifelse(x == "", NA, x)})
)

Answer 3

我发现的一件事是执行write.csv（）时数据的保存方式。

打开csv文件，对X4中的空白单元格单击Delete并保存。如果立即导入，则NA将显示在R中。

要检查：

apply(tr1, 2, function(x) length(which(is.na(x))))

V1 x1 x2 x3 x4

0 3 1 2 1

如果csv文件中包含空格，并且我们确实使用

na.strings（“”，NA）

字符数据类型也以空白显示为“ NA”。

Answer 4

在 fread() 被修复之前，使用 vroom::vroom() 代替。它与 data.table::fread() 的速度相当。在我的机器上，从 SD 卡驱动器读取 3.25 10^6 行 csv 文件需要 0.89 秒。

fread中的空白未被识别为NA

4 个答案:

输出-