R help - Jul 2015 - dplyr help

Hello,
    I've recently discovered the helpful dplyr package.  I'm using the
'aggregate' function as such:


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?  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

I would be thankful for any suggestion!

Thanks,
Jonathan

	[[alternative HTML version deleted]]

?dplyr solution:

bevs %>% group_by(name, sex, drink) %>% summarise(?cost = sum(cost))
%>%
select(name, drink, cost, sex)

The last select statement puts the output in the column order you wanted in
your result.

I hope this helps.

Brian



On Wed, Jul 29, 2015 at 9:37 PM, Jon BR <jonsleepy at gmail.com> wrote:
> Hello,
>     I've recently discovered the helpful dplyr package.  I'm using
the
> 'aggregate' function as such:
>
>
> 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?  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
>
> I would be thankful for any suggestion!
>
> Thanks,
> Jonathan
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
	[[alternative HTML version deleted]]

Hi Brian,
    Thanks for the suggestion, although the command is throwing an error as
such:
> bevs %>% group_by(name, sex, drink) %>% summarise( cost = sum(cost))
%>%
select(name, drink, cost, sex)
Error: unexpected input in "bevs %>% group_by(name, sex, drink) %>%
summarise( "

Your syntax is new to me so I'm not immediately clear on how to fix it; any
idea how?

Thanks again,
Jonathan


On Wed, Jul 29, 2015 at 11:07 PM, Brian Kreeger <brian.kreeger at
gmail.com>
wrote:
> ?dplyr solution:
>
> bevs %>% group_by(name, sex, drink) %>% summarise(?cost = sum(cost))
%>%
> select(name, drink, cost, sex)
>
> The last select statement puts the output in the column order you wanted
> in your result.
>
> I hope this helps.
>
> Brian
>
>
>
> On Wed, Jul 29, 2015 at 9:37 PM, Jon BR <jonsleepy at gmail.com>
wrote:
>
>> Hello,
>>     I've recently discovered the helpful dplyr package.  I'm
using the
>> 'aggregate' function as such:
>>
>>
>> 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? 
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
>>
>> I would be thankful for any suggestion!
>>
>> Thanks,
>> Jonathan
>>
>>         [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
	[[alternative HTML version deleted]]

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

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 <dwinsemius at
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]]