ifelse to speed up loop?

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

 test:
   V1
1   1
2   1
3   1
4   2
5   2
6   2
7   1
8   1
9   1
10  2
11  2
12  2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

 test
   V1 group
1   1  1
2   1  1
3   1  1
4   2  2
5   2  2
6   2  2
7   1 3
8   1  3
9   1  3
10  2  4
11  2  4
12  2  4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
 I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
 Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

        [[alternative HTML version deleted]]

Your query is a little unclear to me, but I suspect
?rle
is what you want.

-- Bert

On Thu, Jan 24, 2013 at 1:20 PM, Jeffrey Fuerte <fuertejn at vcu.edu> wrote:

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

 test:
   V1
1   1
2   1
3   1
4   2
5   2
6   2
7   1
8   1
9   1
10  2
11  2
12  2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

 test
   V1 group
1   1  1
2   1  1
3   1  1
4   2  2
5   2  2
6   2  2
7   1 3
8   1  3
9   1  3
10  2  4
11  2  4
12  2  4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
 I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
 Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

        [[alternative HTML version deleted]]

--

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
Of arun
Sent: Thursday, January 24, 2013 3:37 PM
To: Jeffrey Fuerte
Cc: R help
Subject: Re: [R] ifelse to speed up loop?

HI,

This might be better.
test$group<-cumsum(abs(c(1,diff(test[,1]))))
A.K.




----- Original Message -----
From: Jeffrey Fuerte <fuertejn at vcu.edu>
To: r-help at r-project.org
Cc:
Sent: Thursday, January 24, 2013 4:20 PM
Subject: [R] ifelse to speed up loop?

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

test:
?  V1
1?  1
2?  1
3?  1
4?  2
5?  2
6?  2
7?  1
8?  1
9?  1
10? 2
11? 2
12? 2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

test
?  V1 group
1?  1? 1
2?  1? 1
3?  1? 1
4?  2? 2
5?  2? 2
6?  2? 2
7?  1 3
8?  1? 3
9?  1? 3
10? 2? 4
11? 2? 4
12? 2? 4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

??? [[alternative HTML version deleted]]

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
Of arun
Sent: Thursday, January 24, 2013 3:37 PM
To: Jeffrey Fuerte
Cc: R help
Subject: Re: [R] ifelse to speed up loop?

HI,

This might be better.
test$group<-cumsum(abs(c(1,diff(test[,1]))))
A.K.




----- Original Message -----
From: Jeffrey Fuerte <fuertejn at vcu.edu>
To: r-help at r-project.org
Cc:
Sent: Thursday, January 24, 2013 4:20 PM
Subject: [R] ifelse to speed up loop?

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

test:
?? V1
1?? 1
2?? 1
3?? 1
4?? 2
5?? 2
6?? 2
7?? 1
8?? 1
9?? 1
10? 2
11? 2
12? 2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

test
?? V1 group
1?? 1? 1
2?? 1? 1
3?? 1? 1
4?? 2? 2
5?? 2? 2
6?? 2? 2
7?? 1 3
8?? 1? 3
9?? 1? 3
10? 2? 4
11? 2? 4
12? 2? 4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

??? [[alternative HTML version deleted]]

-----Original Message-----
From: arun [mailto:smartpink111 at yahoo.com]
Sent: Thursday, January 24, 2013 3:53 PM
To: William Dunlap
Cc: R help
Subject: Re: [R] ifelse to speed up loop?

Hi,

I guess you meant:
c(TRUE, cumsum( v[-length(v)] != v[-1] ))
?[1] 1 0 0 1 1 1 2 2 2 3 3 3
this:
?cumsum(c(TRUE, v[-length(v)] != v[-1] ))
# [1] 1 1 1 2 2 2 3 3 3 4 4 4
A.K.




----- Original Message -----
From: William Dunlap <wdunlap at tibco.com>
To: arun <smartpink111 at yahoo.com>; Jeffrey Fuerte <fuertejn at vcu.edu>
Cc: R help <r-help at r-project.org>
Sent: Thursday, January 24, 2013 6:48 PM
Subject: RE: [R] ifelse to speed up loop?

I like
?  v <- test[,1]
?  c(TRUE, cumsum( v[-length(v)] != v[-1] ))
(R's arithmetic on logicals treats TRUE as 1 and FALSE as 0.)

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
Of arun
Sent: Thursday, January 24, 2013 3:37 PM
To: Jeffrey Fuerte
Cc: R help
Subject: Re: [R] ifelse to speed up loop?

HI,

This might be better.
test$group<-cumsum(abs(c(1,diff(test[,1]))))
A.K.




----- Original Message -----
From: Jeffrey Fuerte <fuertejn at vcu.edu>
To: r-help at r-project.org
Cc:
Sent: Thursday, January 24, 2013 4:20 PM
Subject: [R] ifelse to speed up loop?

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

test:
?? V1
1?? 1
2?? 1
3?? 1
4?? 2
5?? 2
6?? 2
7?? 1
8?? 1
9?? 1
10? 2
11? 2
12? 2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

test
?? V1 group
1?? 1? 1
2?? 1? 1
3?? 1? 1
4?? 2? 2
5?? 2? 2
6?? 2? 2
7?? 1 3
8?? 1? 3
9?? 1? 3
10? 2? 4
11? 2? 4
12? 2? 4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

??? [[alternative HTML version deleted]]

Hi,
You could do this:
test<-read.table(text="
  V1
1  1
2  1
3  1
4  2
5  2
6  2
7  1
8  1
9  1
10  2
11  2
12  2
",sep="",header=T)

 test$Group<-cumsum(abs(c(0,diff(test[,1]))))+1
test
#   V1 Group
#1   1     1
#2   1     1
#3   1     1
#4   2     2
#5   2     2
#6   2     2
#7   1     3
#   1     3
#9   1     3
#10  2     4
#11  2     4
#12  2     4
A.K.



----- Original Message -----
From: Jeffrey Fuerte <fuertejn at vcu.edu>
To: r-help at r-project.org
Cc: 
Sent: Thursday, January 24, 2013 4:20 PM
Subject: [R] ifelse to speed up loop?

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

test:
   V1
1   1
2   1
3   1
4   2
5   2
6   2
7   1
8   1
9   1
10  2
11  2
12  2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

test
   V1 group
1   1  1
2   1  1
3   1  1
4   2  2
5   2  2
6   2  2
7   1 3
8   1  3
9   1  3
10  2  4
11  2  4
12  2  4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

    [[alternative HTML version deleted]]

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
Of Jeff
Sent: Thursday, January 24, 2013 4:08 PM
To: arun
Cc: R help; Jeffrey Fuerte
Subject: Re: [R] ifelse to speed up loop?

Thank you for the tips. I should mention that the V1 is numeric in this case but I am trying
to automate the overall procedure so it may not be numeric always. Would that matter
with these functions?

Sent from my iPhone

On Jan 24, 2013, at 6:34 PM, arun <smartpink111 at yahoo.com> wrote:

Hi,
You could do this:
test<-read.table(text="
  V1
1  1
2  1
3  1
4  2
5  2
6  2
7  1
8  1
9  1
10  2
11  2
12  2
",sep="",header=T)

 test$Group<-cumsum(abs(c(0,diff(test[,1]))))+1
test
#   V1 Group
#1   1     1
#2   1     1
#3   1     1
#4   2     2
#5   2     2
#6   2     2
#7   1     3
#   1     3
#9   1     3
#10  2     4
#11  2     4
#12  2     4
A.K.



----- Original Message -----
From: Jeffrey Fuerte <fuertejn at vcu.edu>
To: r-help at r-project.org
Cc:
Sent: Thursday, January 24, 2013 4:20 PM
Subject: [R] ifelse to speed up loop?

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

test:
   V1
1   1
2   1
3   1
4   2
5   2
6   2
7   1
8   1
9   1
10  2
11  2
12  2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

test
   V1 group
1   1  1
2   1  1
3   1  1
4   2  2
5   2  2
6   2  2
7   1 3
8   1  3
9   1  3
10  2  4
11  2  4
12  2  4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

    [[alternative HTML version deleted]]

Hi,
You could do this:
test<-read.table(text="
?  V1
1? 1
2? 1
3? 1
4? 2
5? 2
6? 2
7? 1
8? 1
9? 1
10? 2
11? 2
12? 2
",sep="",header=T)

? test$Group<-cumsum(abs(c(0,diff(test[,1]))))+1
test
#?  V1 Group
#1?  1? ?  1
#2?  1? ?  1
#3?  1? ?  1
#4?  2? ?  2
#5?  2? ?  2
#6?  2? ?  2
#7?  1? ?  3
#?  1? ?  3
#9?  1? ?  3
#10? 2? ?  4
#11? 2? ?  4
#12? 2? ?  4
A.K.



----- Original Message -----
From: Jeffrey Fuerte <fuertejn at vcu.edu>
To: r-help at r-project.org
Cc: 
Sent: Thursday, January 24, 2013 4:20 PM
Subject: [R] ifelse to speed up loop?

Hello,

I'm not sure how to explain what I'm looking for but essentially I have a
test dataset that looks like this:

test:
? ? V1
1?  1
2?  1
3?  1
4?  2
5?  2
6?  2
7?  1
8?  1
9?  1
10? 2
11? 2
12? 2

And what I want to be able to do is create another column that captures a
"grouping" variable that looks like this:

test
? ? V1 group
1?  1? 1
2?  1? 1
3?  1? 1
4?  2? 2
5?  2? 2
6?  2? 2
7?  1 3
8?  1? 3
9?  1? 3
10? 2? 4
11? 2? 4
12? 2? 4

So, it's keeping track of the changes in V1, but even though V1 could be
the same in different instances, the group is treating it as a new group.
I have written a loop that does what I want, but this takes too long to
run, so I was hoping for either a faster approach or an ifelse statement.
Any ideas?

By the loop I was using looks like this:

groupings <- 1
test$group[1] <- groupings
for (i in 2:length(test$V1))
{
if (test$V1[i]==test$V1[i-1])
{
test$group[i] <- groupings
} else {
groupings <- groupings+1
test$group[i] <- groupings
}
}

Thanks for the help.

? ?  [[alternative HTML version deleted]]