R help - Nov 2012 - Using cbind to combine data frames and preserve header/names

I have a dataframe that has a header like so:

class	value1	value2	value3

class is a factor

the actual values in the columns value1, value2 and value3 are 0-255, I wish to
binarize these using biclust.
I can do this like so:

binarize(dataframe[,-1])

this will return a dataframe, but then I lose my first column class, so I
thought I could combine it like so:

dataframe <- cbind(dataframe$label, binarize(dataframe[,-1]))

but then I lose my header (names).............how can I do the above operation
and keep my header in tact?

Basically i just want to binarize everything but the first column (since its a
factor column and not numeric).

Thank you for any help you can give me, I am relatively new to R.

Brian

Not sure where the problem is?

Since you did not provide sample data, I took the iris data set and converted it
to your structure:

x <- cbind( iris[5], iris[1:3] )

head( x )
  Species Sepal.Length Sepal.Width Petal.Length
1  setosa          5.1         3.5          1.4
2  setosa          4.9         3.0          1.4
3  setosa          4.7         3.2          1.3
4  setosa          4.6         3.1          1.5
5  setosa          5.0         3.6          1.4
6  setosa          5.4         3.9          1.7

Does that look like your data?

If so, 

xbin <- cbind( x[1], binarize( x[2:4] ) )

gives a result that should look just like what you want:

head( xbin )
  Species Sepal.Length Sepal.Width Petal.Length
1  setosa            1           0            0
2  setosa            1           0            0
3  setosa            1           0            0
4  setosa            1           0            0
5  setosa            1           0            0
6  setosa            1           0            0

Using
xbin <- cbind( x$Species, binarize( x[-1] ) )
doesn't make a difference.

Or did I not understand your problem well?

Rgds,
Rainer



On Saturday 17 November 2012 00:39:02 Brian Feeny wrote:
> I have a dataframe that has a header like so:
> 
> class	value1	value2	value3
> 
> class is a factor
> 
> the actual values in the columns value1, value2 and value3 are 0-255, I
wish to binarize these using biclust.
> I can do this like so:
> 
> binarize(dataframe[,-1])
> 
> this will return a dataframe, but then I lose my first column class, so I
thought I could combine it like so:
> 
> dataframe <- cbind(dataframe$label, binarize(dataframe[,-1]))
> 
> but then I lose my header (names).............how can I do the above
operation and keep my header in tact?
> 
> Basically i just want to binarize everything but the first column (since
its a factor column and not numeric).
> 
> Thank you for any help you can give me, I am relatively new to R.
> 
> Brian
> 
> ______________________________________________
> R-help at r-project.org mailing list
> 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.

On Nov 16, 2012, at 9:39 PM, Brian Feeny wrote:
> I have a dataframe that has a header like so:
>
> class	value1	value2	value3
>
> class is a factor
>
> the actual values in the columns value1, value2 and value3 are  
> 0-255, I wish to binarize these using biclust.
> I can do this like so:
>
> binarize(dataframe[,-1])
>
> this will return a dataframe, but then I lose my first column class,  
> so I thought I could combine it like so:
>
> dataframe <- cbind(dataframe$label, binarize(dataframe[,-1]))
There is no column with the name "label". There is also no function  
named "label" in base R although I cannot speak about biclust. Even if
there were, you cannot apply functions to data.frames with the "$"  
function.
>
> but then I lose my header (names).............how can I do the above  
> operation and keep my header in tact?
>
> Basically i just want to binarize everything but the first column  
> (since its a factor column and not numeric).
I have no idea how 'binarize' works but if you wanted to
'defactorize'
a factor then you should learn to use 'as.character' to turn factors  
into character vectors. Perhaps:

dfrm <- cbind( as.character(dataframe[1]), binarize(dataframe[,-1]))

You should make sure this is still a dataframe since cbind.default   
returns a matrix and this would be a character matrix. I'm taking your  
word that the second argument is a dataframe, and that would mean the  
cbind.data.frame method would be dispatched.

It is a rather unfortunate practice to call your dataframes  
"dataframe" and also bad to name your columns "class" since
the first
is a fundamental term and the second a basic function. If you persist,  
people will start talking to you about dogs named "Dog".



David Winsemius, MD
Alameda, CA, USA