R help - Jan 2015 - How to split a data table into multiple tables based on column (unique value) and save them separately

How to split a data table into multiple tables based on column (unique value)
and save them separately ?

 For example: 
dat<-structure(list(name = structure(c(1L, 1L, 1L, 2L, 2L, 3L, 3L, 
4L), .Label = c("A", "B", "C", "D"),
class = "factor"), date = structure(c(6L,
7L, 8L, 1L, 2L, 3L, 4L, 5L), .Label = c("5/10/2011",
"5/11/2011",
"5/12/2011", "5/13/2011", "5/14/2011",
"5/7/2011", "5/8/2011",
"5/9/2011"), class = "factor"), index = c(0.880538463,
0.256183209,
0.447239913, 0.942572251, 0.756441284, 0.098201146, 0.730044176, 
0.177744529)), .Names = c("name", "date",
"index"), class = "data.frame", row.names = c(NA,
-8L))
to make seperate table based on unique value, I did following way
siteA<-subset(dat, dat$name=="A")
write.csv(siteA, "siteA.csv")
Similarly for site B, 
siteB<-subset(dat, dat$name=="B")
write.csv(siteB, "siteB.csv")
and so on 

But I have more than 800 unique numbers in the column "name".
Therefore, I have to repeat it more than 800 times,
I am wondering there is a quickest way to split the data and save automatically
in csv format.
Thanks for your help. 
KG

  		 	   		  
	[[alternative HTML version deleted]]

The answer is right there in your question: see ?split

Best,
Ista
On Jan 22, 2015 12:55 PM, "Kristi Glover" <kristi.glover at
hotmail.com> wrote:
> How to split a data table into multiple tables based on column (unique
> value) and save them separately ?
>
>  For example:
> dat<-structure(list(name = structure(c(1L, 1L, 1L, 2L, 2L, 3L, 3L,
> 4L), .Label = c("A", "B", "C",
"D"), class = "factor"), date > structure(c(6L,
> 7L, 8L, 1L, 2L, 3L, 4L, 5L), .Label = c("5/10/2011",
"5/11/2011",
> "5/12/2011", "5/13/2011", "5/14/2011",
"5/7/2011", "5/8/2011",
> "5/9/2011"), class = "factor"), index = c(0.880538463,
0.256183209,
> 0.447239913, 0.942572251, 0.756441284, 0.098201146, 0.730044176,
> 0.177744529)), .Names = c("name", "date",
"index"), class = "data.frame",
> row.names = c(NA,
> -8L))
> to make seperate table based on unique value, I did following way
> siteA<-subset(dat, dat$name=="A")
> write.csv(siteA, "siteA.csv")
> Similarly for site B,
> siteB<-subset(dat, dat$name=="B")
> write.csv(siteB, "siteB.csv")
> and so on
>
> But I have more than 800 unique numbers in the column "name".
Therefore, I
> have to repeat it more than 800 times,
> I am wondering there is a quickest way to split the data and save
> automatically in csv format.
> Thanks for your help.
> KG
>
>
>         [[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]]

Kristi:

You post here frequently.

1. Have you gone through any R tutorials (e.g. "An Intro to R", which
ships with R) where you would find out about how to handle such basic
operations? If not, why not??

2. Why do you persist in posting in HTML, even though you have been
asked not to? Not an issue here, particularly, but ...

2.5 But kudos on posting a small reproducible example that can be cut
and pasted.

3. To answer your question, either the base R idiom
lapply(split(...),FUN=..) or ?tapply handles this. ?by, ?aggregate,
and ?ave are wrappers that might be more convenient, so you might
start there. Hadley Wickham's widely used plyr package provides what
many consider to be much more usable interfaces and flexibility for
this sort of thing, so you may wish to learn and use this instead.

Cheers,
Bert

Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374

"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll




On Thu, Jan 22, 2015 at 9:52 AM, Kristi Glover
<kristi.glover at hotmail.com> wrote:
> How to split a data table into multiple tables based on column (unique
value) and save them separately ?
>
>  For example:
> dat<-structure(list(name = structure(c(1L, 1L, 1L, 2L, 2L, 3L, 3L,
> 4L), .Label = c("A", "B", "C",
"D"), class = "factor"), date = structure(c(6L,
> 7L, 8L, 1L, 2L, 3L, 4L, 5L), .Label = c("5/10/2011",
"5/11/2011",
> "5/12/2011", "5/13/2011", "5/14/2011",
"5/7/2011", "5/8/2011",
> "5/9/2011"), class = "factor"), index = c(0.880538463,
0.256183209,
> 0.447239913, 0.942572251, 0.756441284, 0.098201146, 0.730044176,
> 0.177744529)), .Names = c("name", "date",
"index"), class = "data.frame", row.names = c(NA,
> -8L))
> to make seperate table based on unique value, I did following way
> siteA<-subset(dat, dat$name=="A")
> write.csv(siteA, "siteA.csv")
> Similarly for site B,
> siteB<-subset(dat, dat$name=="B")
> write.csv(siteB, "siteB.csv")
> and so on
>
> But I have more than 800 unique numbers in the column "name".
Therefore, I have to repeat it more than 800 times,
> I am wondering there is a quickest way to split the data and save
automatically in csv format.
> Thanks for your help.
> KG
>
>
>         [[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.