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177

answers:

2

@EZGraphs on Twitter writes: "Lots of online csvs are zipped. Is there a way to download, unzip the archive, and load the data to a data.frame using R? #Rstats"

I was also trying to do this today, but ended up just downloading the zip file manually.

I tried something like:

fileName <- "http://www.newcl.org/data/zipfiles/a1.zip"
con1 <- unz(fileName, filename="a1.dat", open = "r")

but I feel as if I'm a long way off. Any thoughts?

+7  A: 

Zip archives are actually more a 'filesystem' with content metadata etc. See help(unzip) for details. So to do what you sketch out above you need to

  1. Create a temp. file name (eg tempfile())
  2. Use download.file() to fetch the file into the temp. file
  3. Use unz() to extract the target file from temp. file
  4. Remove the temp file via unlink()

which in code (thanks for basic example, but this is simpler) looks like

temp <- tempfile()
download.file("http://www.newcl.org/data/zipfiles/a1.zip",temp)
data <- read.table(unz(temp, "a1.dat"))
unlink(temp)

Compressed (.z) or gzipped (.gz) or bzip2ed (.bz2) files are just the file and those you can read directly from a connection. So get the data provider to use that instead :)

Dirk Eddelbuettel
Awesome! That's great.
Jeromy Anglim
+7  A: 

Just for the record, I tried translating Dirk's answer into code :-P

temp <- tempfile()
download.file("http://www.newcl.org/data/zipfiles/a1.zip",temp)
con <- unz(temp, "a1.dat")
data <- matrix(scan(con),ncol=4,byrow=TRUE)
unlink(temp)
gd047
Thanks - does help.
Tal Galili
Don't use `scan()`; you can use `read.table()` et al directly on a connection. See my edited answer,
Dirk Eddelbuettel
Thanks for showing how to implement it.
Jeromy Anglim