Decompress gz file using R

Question

I have used ?unzip in the past to get at contents of a zipped file using R. This time around, I am having a hard time extracting the files from a .gz file which can be found here.

I have tried ?gzfile and ?gzcon but have not been able to get it to work. Any help you can provide will be greatly appreciated.

score 70 · Answer 1 · edited May 14 '18 at 17:41

70

Here is a worked example that may help illustrate what gzfile() and gzcon() are for

foo <- data.frame(a=LETTERS[1:3], b=rnorm(3))
foo
#  a        b
#1 A 0.586882
#2 B 0.218608
#3 C 1.290776
write.table(foo, file="/tmp/foo.csv")
system("gzip /tmp/foo.csv")             # being very explicit

Now that the file is written, instead of implicit use of file(), use gzfile():

read.table(gzfile("/tmp/foo.csv.gz"))   
#  a        b
#1 A 0.586882
#2 B 0.218608
#3 C 1.290776

The file you point is a compressed tar archive, and as far as I know, R itself has no interface to tar archives. These are commonly used to distribute source code--as for example for R packages and R sources.

edited May 14 '18 at 17:41

stas g

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answered Apr 23 '11 at 13:51

Dirk Eddelbuettel

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is it possible to do this with `fread{data.table}` ? I have tried without success so far – rafa.pereira Apr 25 '16 at 22:38
That is obvious yet not useful as data.table cannot consume that stream. – Dirk Eddelbuettel Jun 10 '16 at 15:59
That's useful. Its standard heuristic tries reading in three different locations which requires forward/backward positioning you cannot do on a stream. I looked for freak support once and think I saw 'nope' but maybe that has changed. – Dirk Eddelbuettel Jun 10 '16 at 16:11
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Current version of `data.table` in fact supports `csv.gz` natively (no need for `zcat`) – MichaelChirico Jul 05 '19 at 08:45
`gzfile` also worked for me on `txt.gz` where `untar` failed (I didn't finagle with `untar` too much) – MichaelChirico Jul 05 '19 at 08:48
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This should work now (+9 years after)library(data.table) library(R.utils) d – GabrielMontenegro May 12 '20 at 08:10

Robert Hijmans · Answer 2 · 2019-08-04T03:09:31.220

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To un-gz a file in R you can do

library(R.utils)
gunzip("file.gz", remove=FALSE)

or

gunzip("file.gz")

But then you get the default (remove=TRUE) behavior in which the input file is removed after that the output file is fully created and closed.

edited Aug 04 '19 at 03:09

answered May 09 '15 at 19:25

Robert Hijmans

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Thats what i was looking for. Be aware: `NOTE: The default (remove=TRUE) behavior is that the input file is removed after that the output file is fully created and closed.` - see `?gunzip` – Rentrop Dec 27 '16 at 10:33

score 40 · Accepted Answer · answered Apr 24 '11 at 11:57

40

If you really want to uncompress the file, just use the untar function which does support gzip. E.g.:

untar('chadwick-0.5.3.tar.gz')

answered Apr 24 '11 at 11:57

daroczig

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WCC · Answer 4 · 2014-01-10T20:35:06.980

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http://blog.revolutionanalytics.com/2009/12/r-tip-save-time-and-space-by-compressing-data-files.html

R added transparent decompression for certain kinds of compressed files in the latest version (2.10). If you have your files compressed with bzip2, xvz, or gzip they can be read into R as if they are plain text files. You should have the proper filename extensions.

The command...

myData <- read.table('myFile.gz')

#gzip compressed files have a "gz" extension

Will work just as if 'myFile.gz' were the raw text file.

edited Jan 10 '14 at 20:35

answered Sep 24 '13 at 17:36

WCC

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It does work unless you specify colClasses argument. If you add myData – Met Jun 12 '15 at 16:58

score 2 · Answer 5 · answered Aug 05 '20 at 01:57

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library(vroom)
columns3 = c('A', 'B',...) ## define column names
Data1<- vroom(".../XXX.tsv",col_names = columns3)

works fine with tsv.gz

answered Aug 05 '20 at 01:57

iHermes

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score 0 · Answer 6 · answered Feb 11 '22 at 15:14

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If it's a comma/tab-separated file, you can use data.table's fread(). It can handle zipped (.zip, .gz) files:

fread('myFile.csv.gz')

answered Feb 11 '22 at 15:14

andschar

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Decompress gz file using R

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