I would like to be able to skip a column that is read into R via data.table
's fread
function in v1.8.9. But the csv I am reading in, has no column headers…which appears to be a problem for fread... is there a way to just specify that I don't want specific columns?
Would it be better to just pre-allocate a column name and then let it read it in so that it can be skipped?
To give an example, I downloaded the data from the following URL
http://www.truefx.com/dev/data/2013/MAY-2013/AUDUSD-2013-05.zip
unzipped it…
and read the csv into R using fread and it has pretty much the same file name just with the csv extension.
system.time(pp <- fread("AUDUSD-2013-05.csv",sep=","))
user system elapsed
16.427 0.257 16.682
head(pp)
V1 V2 V3 V4
1: AUD/USD 20130501 00:00:04.728 1.03693 1.03721
2: AUD/USD 20130501 00:00:21.540 1.03695 1.03721
3: AUD/USD 20130501 00:00:33.789 1.03694 1.03721
4: AUD/USD 20130501 00:00:37.499 1.03692 1.03724
5: AUD/USD 20130501 00:00:37.524 1.03697 1.03719
6: AUD/USD 20130501 00:00:39.789 1.03697 1.03717
str(pp)
Classes ‘data.table’ and 'data.frame': 4060762 obs. of 4 variables:
$ V1: chr "AUD/USD" "AUD/USD" "AUD/USD" "AUD/USD" ...
$ V2: chr "20130501 00:00:04.728" "20130501 00:00:21.540" "20130501 00:00:33.789" "20130501 00:00:37.499" ...
$ V3: num 1.04 1.04 1.04 1.04 1.04 ...
$ V4: num 1.04 1.04 1.04 1.04 1.04 ...
- attr(*, ".internal.selfref")=<externalptr>
I tried using the new(ish) colClasses or skip arguments to ignore the fact that the first column is all the same…and is unnecessary.
but doing:
pp1 <- fread("AUDUSD-2013-05.csv",sep=",",skip=1)
doesn't omit the reading in of the first column
and using colClasses leads to the following error
pp1 <- fread("AUDUSD-2013-05.csv",sep=",",colClasses=list(NULL,"character","numeric","numeric"))
Error in fread("AUDUSD-2013-05.csv", sep = ",", colClasses = list(NULL, :
colClasses is type list but has no names
other attempts incude
pp1 <- fread("AUDUSD-2013-06.csv",sep=",", colClasses=c(V1=NULL,V2="character",V3="numeric",V4="numeric"))
str(pp1)
Classes ‘data.table’ and 'data.frame': 5524877 obs. of 4 variables:
$ V1: chr "AUD/USD" "AUD/USD" "AUD/USD" "AUD/USD" ...
$ V2: chr "20130603 00:00:00.290" "20130603 00:00:00.291" "20130603 00:00:00.292" "20130603 00:00:03.014" ...
$ V3: num 0.962 0.962 0.962 0.962 0.962 ...
$ V4: num 0.962 0.962 0.962 0.962 0.962 ...
- attr(*, ".internal.selfref")=<externalptr>
i.e pretty much exactly the same as if I had not used colClasses...
Are there any suggestions to be able to speed up the reading in of data by omitting the first column?
Also perhaps a bit much to ask, but is it possible to directly read a zip file rather than unzipping it first and then reading in the csv?
Oh and if it wasn't clear I'm using data.table v1.8.9
I think the argument you're looking for is drop
. Try:
require(data.table) # 1.9.2+
pp <- fread("AUDUSD-2013-05.csv", drop = 1)
Note that you can drop
by name or position.
fread("AUDUSD-2013-05.csv", drop = c("columThree","anotherColumnName"))
fread("AUDUSD-2013-05.csv", drop = 10:15) # read all columns other than 10:15
And you can select
by name or position, too.
fread("AUDUSD-2013-05.csv", select = 10:15) # read only columns 10:15
fread("AUDUSD-2013-05.csv", select = c("columnA","columnName2"))
These arguments were added to v1.9.2 (released to CRAN in Feb 2014) and are documented in ?fread
. You'll need to upgrade to use them.