R help - Aug 2010 - Using apply for logical conditions

Hi,

I've got some boolean data in a data.frame in the form:
      X    Y    Z    A   B   C
[1]  T     T    F    T   F   F
[2]  F     T    T    F   F   F
.
.
.


What I want to do is create a new column which is the logical disjunction of
several of the columns.
Just like:

new.column <- data$X | data$Y | data$Z

However I don't want to hard code the particular columns into the expression
like that. I've tried using apply row wise with `|` as the function:

columns <- c(X,Y,Z)
apply(data[,columns], 1,`|`)

This doesn't seem to do what I would have expected, does anyone have any
advice how to use the the apply or similar function to perform a boolean
operation on each row (and a specific subset of the columns) in a data
frame? 

Thanks,
Alastair


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`|` is a binary operator which is why the apply will not work.  See

help("Reduce")

For example,

set.seed(1)
data <- data.frame(A = runif(10) > 0.5, B = runif(10) > 0.5, C = 
runif(10) > 0.5)
Reduce(`|`, data)
#  [1]  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE

Hope this helps.

Allan

On 02/08/10 21:35, Alastair wrote:
> Hi,
>
> I've got some boolean data in a data.frame in the form:
>        X    Y    Z    A   B   C
> [1]  T     T    F    T   F   F
> [2]  F     T    T    F   F   F
> .
> .
> .
>
>
> What I want to do is create a new column which is the logical disjunction
of
> several of the columns.
> Just like:
>
> new.column<- data$X | data$Y | data$Z
>
> However I don't want to hard code the particular columns into the
expression
> like that. I've tried using apply row wise with `|` as the function:
>
> columns<- c(X,Y,Z)
> apply(data[,columns], 1,`|`)
>
> This doesn't seem to do what I would have expected, does anyone have
any
> advice how to use the the apply or similar function to perform a boolean
> operation on each row (and a specific subset of the columns) in a data
> frame?
>
> Thanks,
> Alastair
>
>
>

Alastair wrote:
> Hi,
> 
> I've got some boolean data in a data.frame in the form:
>       X    Y    Z    A   B   C
> [1]  T     T    F    T   F   F
> [2]  F     T    T    F   F   F
> .
> .
> .
> 
> 
> What I want to do is create a new column which is the logical disjunction
of
> several of the columns.
> Just like:
> 
> new.column <- data$X | data$Y | data$Z
> 
> However I don't want to hard code the particular columns into the
expression
> like that. I've tried using apply row wise with `|` as the function:
> 
> columns <- c(X,Y,Z)
> apply(data[,columns], 1,`|`)
> 
Please provide *reproducible* examples.  I cannot run any of your code 
since you don't give us the objects X, Y, or Z.  An easy way to do this 
is to use ?dput on the objects we need to run your code, e.g., your 
data.frame.

Does this do what you want?

df1 <- data.frame(x = sample(c(TRUE, FALSE), 10, replace = TRUE),
                   y = sample(c(TRUE, FALSE), 10, replace = TRUE),
                   z = sample(c(TRUE, FALSE), 10, replace = TRUE))

columns <- c("x", "y", "z")

apply(df1[columns], 1, any)

Reduce() is much nicer, but I usually use

rowSums(A) > 0 for 'or', and
rowSums(A) == ncols for 'and'.

Which works slightly faster.

I noticed, though, that Reduce() doesn't work on matrices. Is there an
alternative for matrices, or do you have to convert the matrix first to a
data.frame, and then use Reduce?


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