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remove missing values from matrix or data frame

5 messages · William Briggs, Spencer Graves, Brian Ripley +2 more

#
Is there any way besides looping to remove complete rows from a matrix 
or data frame where there is at least one NA in any of the columns?

For example
 > a
        [,1]     [,2]
   [1,] 0        2.6875
   [2,] 8.366667 6.625
   [3,] 15.6     4.375
   [4,] 23.4     6.25
   [5,] 29       5.09375
   [6,] 18       NA
   [7,] 0        4.15625
   [8,] 9.366667 6.25
   [9,] 14.73333 5.875
  [10,] 31.26667 6.15625
  [11,] NA       2.357
  [12,] NA       5.4234
  [13,] 0        3.34375
  [14,] 7.666667 2.78125
  [15,] NA       NA

In a, rows 6, 11, 12, and 15 should be removed.

na.omit(a) does nothing, nor does na.omit(as.data.frame(a)).  I can get 
a matrix of which are NA and not by "i<-!is.na(a)", but this doesn't 
seem to help ("a[i]" isn't the thing I'm after).

I know I am missing something simple and standard, but I haven't been 
able to see it yet (nor on Google).

Thanks.
#
How about the following: 

 > (A <- array(c(1, NA, 3, NA, 4, 5), dim=c(3,2)))
     [,1] [,2]
[1,]    1   NA
[2,]   NA    4
[3,]    3    5
 > A[apply(A, 1, function(x)!any(is.na(x))), , drop=F]
     [,1] [,2]
[1,]    3    5

      hope this helps.  spencer graves
William Briggs wrote:

            

  
    
#
Something is not as it seems:
1:  0        2.6875
3:  8.366667 6.625
5:  15.6     4.375
7:  23.4     6.25
9:  29       5.09375
11:  18       NA
13:  0        4.15625
15:  9.366667 6.25
17:  14.73333 5.875
19:  31.26667 6.15625
21:  NA       2.357
23:  NA       5.4234
25:  0        3.34375
27:  7.666667 2.78125
29:  NA       NA
31:
Read 30 items

and a looks like yours and
[,1]    [,2]
 [1,]  0.000000 2.68750
 [2,]  8.366667 6.62500
 [3,] 15.600000 4.37500
 [4,] 23.400000 6.25000
 [5,] 29.000000 5.09375
 [6,]  0.000000 4.15625
 [7,]  9.366667 6.25000
 [8,] 14.733330 5.87500
 [9,] 31.266670 6.15625
[10,]  0.000000 3.34375
[11,]  7.666667 2.78125
attr(,"na.action")
[1] 11 12 15  6
attr(,"class")
[1] "omit"

does something, in fact what you asked for.

So what is a?  What does str(a) say about it?
On Tue, 9 Nov 2004, William Briggs wrote:

            

  
    
#
?na.omit  

as in A<-na.omit(A)

-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA
 
"The business of the statistician is to catalyze the scientific learning
process."  - George E. P. Box
#
You might be interested in complete.cases(), as in:

use <- complete.cases(a)
a[use, ]

-roger
William Briggs wrote: