Thanks David! I do get confused sometimes when sth can be easily and
directly done in Excel which is what I am familiar with, but I find it
takes more time for me to operate that in R.


On Thu, Apr 18, 2013 at 4:27 PM, David Winsemius <dwinsemius@comcast.net>wrote:

>
> On Apr 18, 2013, at 3:46 PM, Ye Lin wrote:
>
> > Hey,
> >
> > Is it possible that R can calculate each options under each column and
> > return a summary table?
> >
> > Suppose I have a table like this:
> >
> > Gender   Age   Rate
> > Female    0-10   Good
> > Male        0-10   Good
> > Female     11-20  Bad
> > Male         11-20  Bad
> > Male         >20     N/A
> >
> > I want to have a summary table including the information that how many
> > answers in each category, sth like this:
>
> Some of the tables simple did not have N/A so it's not appropriate to
> append an N/A row for them:
>
>  dat1<-read.table(text="
>  Gender  Age  Rate
>  Female    0-10  Good
>  Male        0-10  Good
>  Female    11-20  Bad
>  Male        11-20  Bad
>  Male        >20    N/A
>  ",sep="",header=TRUE)
>
>  sapply(lapply(dat1, table), as.matrix)
>
> $Gender
>        [,1]
> Female    2
> Male      3
>
> $Age
>       [,1]
> >20      1
> 0-10     2
> 11-20    2
>
> $Rate
>      [,1]
> Bad     2
> Good    2
> N/A     1
>
>
> >
> >  X         Gender
> > Male       3
> > Female    2
> > N/A        0
> >
> >  X          Age
> > 0-10         2
> > 11-20         2
> >> 20           1
> > N/A         0
> >
> > X          Rate
> > Good       2
> > Bad          2
> > N/A         1
> >
> > So basically I want to calculate, in each column, how many people choose
> > each answer, including N/A. I know I can do it in Excel in a very
> > visualized way, but is there anyway to do it in R in a robust way if I
> have
> > a fairly large dataset.
>
> You appear confused about the relative robustness of R and Excel.
>
> --
>
> David Winsemius
> Alameda, CA, USA
>
>

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