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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