How to reach the column names in a huge .RData file without loading it

On 16/03/2016 1:40 PM, Jan Kim wrote:

Barry: that's an interesting hack.

I do feel compelled to make two comments, though, regarding the
general issue rather than the scraping idea:

(1) If your situation is that that image (.RData file) is the only
copy of the data, you'll need to rescue the data from that as soon as
possible anyway. Something like

    load(".RData");
    write.csv(mydataframe, file = "mydata.csv");

should do this trick. It will be slow, but you'll need to do it just
once, so you might as well enjoy your coffee while you wait. From that
point on, work with the mydata.csv file for getting at the colnames
(and anything else as well).

(2) If there's any chance / risk that scraping data off images is not
a one-off, the time to prevent that from catching on is now. If data is
of any value at all, it should be handled in a sane, portable, textual
format. For tabular data, csv is normally adequate or at least good
enough, but .RData images are never a good idea.

I agree with the sentiment, but not with the choice of .csv as a
"sane, portable, textual format".  CSV has no type information
included, so strings that contain only digits can turn into numbers
(and get rounded in the process), things that look like
dates can get converted to different formats, etc.

The .RData format has the disadvantages of being hard to use outside
R, but at least it is usable in R.

I don't know what I'd recommend if I wanted a portable textual
format.  JSON is close, but it can't handle the full
range of data that R can handle (e.g. no Inf).  dput() on a
dataframe is text, but nothing but R can read it.

Duncan Murdoch

Best regards, Jan

P.S.: I've seen .RData images containing many months worth of interactive
work, and multiple variants of data frames in variables with more or less
similar names, so the set of strings scraped off these will be rather more
bewildering than in Barry's clean example.


On Wed, Mar 16, 2016 at 05:17:25PM +0000, Barry Rowlingson wrote:

You *might* be able to get them from the raw file...

First, I don't quite know what "colnames" of an .RData file means.
"colnames" are the column names of a matrix (or data frame), so I'll
assume your .RData file contains exactly one data frame and you want
to column names of it.

So let's create one of those:


mydataframe = data.frame(mylongnamehere=runif(3),
anotherlongname=runif(3), z=runif(3), y=runif(3),
aasdkjhasdkjhaskdj=runif(3))
save(mydataframe, file="./test.RData")

Now I'm going to use some Unix utilities to see if there's any
identifiable strings in the file. .RData files are by default
compressed using `gzip`, so I'll `gunzip` them and pipe it into
`strings`:

$ gunzip -c test.RData | strings -t d
      0 RDX2
     35 mydataframe
    230 names
    251 mylongnamehere
    273 anotherlongname
    314 aasdkjhasdkjhaskdj
    347     row.names
    389 class
    410 data.frame


  - thats found the object name (mydataframe) and most of the column
names except the short ones, which are too short for `strings` to
recognise. But if your names are long enough (4 or more chars, I
think) they'll show up.

 Of course you'll have to filter them out from all the other string
output, but they should all appear shortly after the word "names",
since the colnames of a data frame are the "names" attribute of the
data.

 If you don't have a Unix or Mac machine handy you can get these
utilities on Windows via Cygwin but that's another story...

 Barry








On Wed, Mar 16, 2016 at 3:59 PM, Lida Zeighami <lid.zigh at gmail.com> wrote:

Hi,
I have a huge .RData file and I need just to get the colnames of it. so is
there any way to reach the column names without loading or reading the
whole file?
Since the file is so big and I need to repeat this process several times,
so it takes so long to load the file first and then take the colnames!

Thanks

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