Cannot rescale a constant/zero column error.

On 10/31/2012 11:47 PM, fillay89 wrote:

I am trying to run the R Script below, I have actually simplified it to just
this part that is causing issues.  When I run this script I continue to get
an error that says "cannot rescale a constant/zero column to a unit
variance".  I cannot figure out what is going on here.  I have stripped down
my data file so it is more manageable so I can try to figure this out.

The data.txt file that is being read looks like this:


I have made this file very basic on purpose to see if I could get this to
work, but it is not working.  Of course once I get this to actually work I
will expand the data file to match the data I am actually using.



If I change the attribute in the prcomp function to scale=FALSE of course I
can run my script.  But if it is scaling...which is causing the issues, it
errors.

Any help would be GREATLY appreciated.

Hi fillay89,
You seem to be trying to run a principal component analysis on two numbers, which won't produce anything useful. If I make up some data that is more realistic:

pcmatrix<-data.frame(Q1=sample(1:5,10,TRUE),Q2=sample(1:5,10,TRUE))
pcmatrix[,1] <- pcmatrix[,1] + 96
pcmatrix[,2] <- pcmatrix[,2] + 96
x.pca <- prcomp(pcmatrix,retx=TRUE,center=TRUE,scale=TRUE,cor=TRUE)
x.pca
Standard deviations:
[1] 1.263267 0.635733

Rotation:
        PC1        PC2
Q1 0.7071068 -0.7071068
Q2 0.7071068  0.7071068

it runs and I get a slightly more useful result. Running your code does bomb in exactly the way you describe, as does:

x.pca <- prcomp(data.frame(Q1=99,Q2=98), retx=TRUE, center=TRUE, scale=TRUE, cor=TRUE)
Error in prcomp.default(data.frame(Q1 = 99, Q2 = 98), retx = TRUE, center = TRUE,  :
 cannot rescale a constant/zero column to unit variance

Your problem is that you have a data frame with only one value (i.e. a constant) in each column.

Jim

Jim,

Thank you for your reply.  I guess I am just not understanding what the
difference is.  If I run your example using the pcmatrix<-
data.frame(Q1=sample(1:5,10,TRUE),Q2=sample(1:5,10,TRUE)) and print out
pcmatrix I get:

	Q1	Q2
1	98	99

pcmatrix<-data.frame(Q1=sample(1:5,10,TRUE),Q2=sample(1:5,10,TRUE))
pcmatrix

Then if I mirror my input file to be, would would be what the samples
from above would have created, it would look like this:

ID,Q1,Q2
1,2,3

And I run the script printing out pcmatrix I get the exact same thing.

	Q1	Q2
1	98	99

So I would think they are basically the same representations, however
one works when passed into the prcomp function and the other does not.
I am just trying to tweak a script that we had created for us (cannot
find the guy now) so I can pass more columns of data.  I clearly really
do not know what I am doing, but again thanks for you time and any
direction you can point me in would be awesome.

Thanks

Jason

On Nov 1, 2012, at 3:57 AM, Jim Lemon wrote:

On 10/31/2012 11:47 PM, fillay89 wrote:

I am trying to run the R Script below, I have actually simplified it
to just this part that is causing issues.  When I run this script I
continue to get an error that says "cannot rescale a constant/zero
column to a unit variance".  I cannot figure out what is going on
here.  I have stripped down my data file so it is more manageable so

I can try to figure this out.

The data.txt file that is being read looks like this:


I have made this file very basic on purpose to see if I could get
this to work, but it is not working.  Of course once I get this to
actually work I will expand the data file to match the data I am

actually using.

If I change the attribute in the prcomp function to scale=FALSE of
course I can run my script.  But if it is scaling...which is causing
the issues, it errors.

Any help would be GREATLY appreciated.

Hi fillay89,
You seem to be trying to run a principal component analysis on two

numbers, which won't produce anything useful. If I make up some data
that is more realistic:

pcmatrix<-data.frame(Q1=sample(1:5,10,TRUE),Q2=sample(1:5,10,TRUE))
pcmatrix[,1] <- pcmatrix[,1] + 96
pcmatrix[,2] <- pcmatrix[,2] + 96
x.pca <- prcomp(pcmatrix,retx=TRUE,center=TRUE,scale=TRUE,cor=TRUE)
x.pca
Standard deviations:
[1] 1.263267 0.635733

Rotation:
        PC1        PC2
Q1 0.7071068 -0.7071068
Q2 0.7071068  0.7071068

it runs and I get a slightly more useful result. Running your code

does bomb in exactly the way you describe, as does:

x.pca <- prcomp(data.frame(Q1=99,Q2=98), retx=TRUE, center=TRUE,
scale=TRUE, cor=TRUE) Error in prcomp.default(data.frame(Q1 = 99, Q2

= 98), retx = TRUE, center = TRUE,  :

 cannot rescale a constant/zero column to unit variance

Your problem is that you have a data frame with only one value (i.e.

a constant) in each column.

Jim

Hi

Jim,

Thank you for your reply.  I guess I am just not understanding what the
difference is.  If I run your example using the pcmatrix<-
data.frame(Q1=sample(1:5,10,TRUE),Q2=sample(1:5,10,TRUE)) and print out
pcmatrix I get:

	Q1	Q2
1	98	99

Thats rather surprising. I get

pcmatrix<-data.frame(Q1=sample(1:5,10,TRUE),Q2=sample(1:5,10,TRUE))
pcmatrix

  Q1 Q2
1   4  4
2   3  3
3   4  1
4   4  4
5   4  2
6....

this what I get

Then if I mirror my input file to be, would would be what the samples
from above would have created, it would look like this:

ID,Q1,Q2
1,2,3

what about include 

dput(head(yourfile)) 
to your post to let us see how it looks like. Or at least 

str(yourfile)

Regards
Petr

And I run the script printing out pcmatrix I get the exact same thing.

	Q1	Q2
1	98	99

So I would think they are basically the same representations, however
one works when passed into the prcomp function and the other does not.
I am just trying to tweak a script that we had created for us (cannot
find the guy now) so I can pass more columns of data.  I clearly really
do not know what I am doing, but again thanks for you time and any
direction you can point me in would be awesome.

Thanks

Jason

On Nov 1, 2012, at 3:57 AM, Jim Lemon wrote:

On 10/31/2012 11:47 PM, fillay89 wrote:

I am trying to run the R Script below, I have actually simplified it
to just this part that is causing issues.  When I run this script I
continue to get an error that says "cannot rescale a constant/zero
column to a unit variance".  I cannot figure out what is going on
here.  I have stripped down my data file so it is more manageable so

I can try to figure this out.

The data.txt file that is being read looks like this:


I have made this file very basic on purpose to see if I could get
this to work, but it is not working.  Of course once I get this to
actually work I will expand the data file to match the data I am

actually using.

If I change the attribute in the prcomp function to scale=FALSE of
course I can run my script.  But if it is scaling...which is causing
the issues, it errors.

Any help would be GREATLY appreciated.

Hi fillay89,
You seem to be trying to run a principal component analysis on two

numbers, which won't produce anything useful. If I make up some data
that is more realistic:

pcmatrix<-data.frame(Q1=sample(1:5,10,TRUE),Q2=sample(1:5,10,TRUE))
pcmatrix[,1] <- pcmatrix[,1] + 96
pcmatrix[,2] <- pcmatrix[,2] + 96
x.pca <- prcomp(pcmatrix,retx=TRUE,center=TRUE,scale=TRUE,cor=TRUE)
x.pca
Standard deviations:
[1] 1.263267 0.635733

Rotation:
       PC1        PC2
Q1 0.7071068 -0.7071068
Q2 0.7071068  0.7071068

it runs and I get a slightly more useful result. Running your code

does bomb in exactly the way you describe, as does:

x.pca <- prcomp(data.frame(Q1=99,Q2=98), retx=TRUE, center=TRUE,
scale=TRUE, cor=TRUE) Error in prcomp.default(data.frame(Q1 = 99, Q2

= 98), retx = TRUE, center = TRUE,  :

cannot rescale a constant/zero column to unit variance

Your problem is that you have a data frame with only one value (i.e.

a constant) in each column.

Jim