Reproduced, thanks. Can't think why that is, but will fix. Please file
as a bug so it's not forgotten.
In the meantime, setting the class manually for that column (colClasses
argument) works in this example :
fread( paste0( strData, collapse="\n" ), integer64="character",
colClasses=list(numeric="b"))
Is that workable for the full example? I've used that syntax for
colClasses so you can pass a vector of column names to be read as
numeric more easily, if need be.
Matt
On 03/05/14 02:08, Harish wrote:
I was trying to use fread() to read data when I got the following
error which made no sense:
In fread(paste0(strData, collapse = "\n"), integer64 = "character") :
Bumped column 2 to type character on data row 13, field contains '2464.77'.
Coercing previously read values in this column from integer or numeric back to
character which may not be lossless; e.g., if '00' and '000' occurred before
they will now be just '0', and there may be inconsistencies with treatment of
',,' and ',NA,' too (if they occurred in this column before the bump). If this
matters please rerun and set 'colClasses' to 'character' for this column.
Please note that column type detection uses the first 5 rows, the middle 5 rows
and the last 5 rows, so hopefully this message should be very rare. If
reporting to datatable-help, please rerun and include the output from
verbose=TRUE.
because "2464.77" is a perfectly legitimate number and there is no
reason to coerce the column to character for that.
Here is how to reproduce it:
dtT <- data.table( a = 1:72, b=0 )
dtT[ 13, b := 2464.77 ]
strData <- capture.output( write.table( dtT, row.names=FALSE,
quote=FALSE, sep="\t" ) )
fread( paste0( strData, collapse="\n" ), integer64="character" )
Note that the following works okay without the integer64="character"
argument:
dtT <- data.table( a = 1:72, b=0 )
dtT[ 13, b := 2464.77 ]
strData <- capture.output( write.table( dtT, row.names=FALSE,
quote=FALSE, sep="\t" ) )
fread( paste0( strData, collapse="\n" ) )
I would appreciate if you could provide some sort of a workaround for
this. The reason I am using the integer64="character" argument is
that I have large numbers at times which seems to be having issues
once it is read as integer64 -- and that might have nothing to do with
data.table but I have not had time to look into it. My work-around
for that issue was to read it as character, but I run into the above
issue.
Thanks for your help.
Regards,
Harish
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