The single csv file like list output.
aa(cm)
1, 2 , 3,
bb(mm)
1, 2, 3,
4, 5, 6,
7, 8, 9,
cc(mm)
3, 4, 5,
7, 5, 9,
6, 5, 8,
---- 在 星期日, 06 十月 2019 05:08:41 -0700 Duncan Murdoch
<murdoch.dun...@gmail.com> 撰写 ----
> On 06/10/2019 7:29 a.m., vod vos via R-help wrote:
> > I got hundreds of csv files. The real formats in each csv file are as
follows:
> >
> > aa(cm)
> > 1, 2 , 3,
> >
> > bb(mm)
> > 1, 2, 3,
> > 4, 5, 6,
> > 7, 8, 9,
> >
> > cc(mm)
> > 3, 4, 5,
> > 7, 5, 9,
> > 6, 5, 8,
> >
> > How can I use read.table or read.csv to convert the csv files
> > to a tidy data frame format as follow:
> >
> > aa, bb, cc
> > 1, 1, 3
> > 1, 2, 4
> > 1, 3, 5
> > 2, 4, 7
> > 2, 5, 5
> > 2, 6, 9
> > 3, 7, 6
> > 3, 8, 5
> > 3, 9, 8
> >
> > many thanks.
>
> You'll need more than those two functions to do the transformation you
> want. To work out what you need, write out the process in detail in
> English (or another natural language), not in code. For example:
>
> 1. Read aa from file 1.
> 2. Read bb from file 2.
> 3. Read cc from file 3.
> 4. Expand all vectors to the same length.
> 5. Combine them into a single dataframe.
>
> Then work out each step separately. I think you'll want to use
> something like scan("filename", skip = 1, sep = ",") in steps 1, 2, and
> 3, but this will add NA values at the end of each line because of the
> final comma, so you could do this:
>
> aa <- scan("file1", skip = 1, sep = ",")
> aa <- aa[!is.na(aa)]
>
> and similarly for the others.
>
> I don't know the rules for expanding that you'll need in your real data,
> but for your example step 4 could be
>
> aa <- rep(aa, each = 3)
>
> Then step 5 could be
>
> result <- data.frame(aa, bb, cc)
>
> Duncan Murdoch
>
