Blank space not recognised as NA in fread

Question

I have a large file which has to be imported in R. I used fread for this purpose. fread is recognizing blank spaces from numeric fields as NA but it is not recognizing blank spaces from character and integer64 fields as NA.

fread recognises blank space as an empty cell for character fields and it recognises blank space as 0 for integer64 fields.

When I imported the same data using read.table, it recognizes all blank spaces as NA.

Please find a reproducible example,

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) 

Verbose output :

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 

Please help me solve this issue.

Thanks!

Answer 1

In case you want to avoid the additional manipulation after reading the file, you could try using

quote = FALSE

when writing to csv. This prevents the use of quotations " " around the values and all missing values should now be read as NAs. It should look like this -

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

Output -

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