David,
I do appreciate your help, if not the dose of contempt. I hope you
feel OK.
Thanks for the tips,
-Jonathan
On Wed, Jul 29, 2015 at 11:14 PM, David Winsemius <dwinsem...@comcast.net>
wrote:
>
> On Jul 29, 2015, at 7:37 PM, Jon BR wrote:
>
> > Hello,
> > I've recently discovered the helpful dplyr package. I'm using the
> > 'aggregate' function as such:
>
> The `aggregate` function is part of base-R:
>
> > bevs <- data.frame(cbind(name = c("Bill", "Mary"), drink = c("coffee",
> > "tea", "cocoa", "water"), cost = seq(1:8), sex = c("male","female")));
> > bevs$cost <- seq(1:8)
> >
> >> bevs
> > name drink cost sex
> > 1 Bill coffee 1 male
> > 2 Mary tea 2 female
> > 3 Bill cocoa 3 male
> > 4 Mary water 4 female
> > 5 Bill coffee 5 male
> > 6 Mary tea 6 female
> > 7 Bill cocoa 7 male
> > 8 Mary water 8 female
> >>
> >
> >> aggregate(cost ~ name + drink, data = bevs, sum)
> > name drink cost
> > 1 Bill cocoa 10
> > 2 Bill coffee 6
> > 3 Mary tea 8
> > 4 Mary water 12
> >
> > My issue is that I would like to keep a column for 'sex', for which there
> > is a 1:1 mapping with 'name', such that every time 'Bill' appears, it is
> > always 'male'.
> >
> > Does anyone know of a way to accomplish this, with or without dplyr?
>
> As pointed out you have not yet demonstrated any dplyr functions.
>
> > The
> > ideal command(s) would produce this:
> >
> > name drink cost sex
> > 1 Bill cocoa 10 male
> > 2 Bill coffee 6 male
> > 3 Mary tea 8 female
> > 4 Mary water 12 female
>
> Doesn't this (glaringly obvious?) approach succeed?
>
> > aggregate(cost ~ name + drink+sex, data = bevs, sum)
> name drink sex cost
> 1 Mary tea female 8
> 2 Mary water female 12
> 3 Bill cocoa male 10
> 4 Bill coffee male 6
> >
>
>
> >
> > I would be thankful for any suggestion!
> >
> > Thanks,
> > Jonathan
> >
> > [[alternative HTML version deleted]]
> >
> >
>
> Please learn to post in plain text.
>
> --
>
> David Winsemius
> Alameda, CA, USA
>
>
[[alternative HTML version deleted]]
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