On Apr 25, 2010, at 10:15 PM, robert lee wrote:
> I have two data frames ( x and y -- sample values below). The rows
> have HH:MM:SS and columns have names of devices.
>
> I am trying to find a list of 5 least used devices during recorded
> time period. When apply function is used to sum on the column, I
> get the correct answer on data frame called x, but not for y. The
> data type of return answer is different and I cannot figure out
> why. Any insight into what is happening of possibly different
> simpler ways to do this would be appreciated.
>
>> colnames(t(sort(apply(x,2,sum))[1:5]))
> [1] "5x" "6x" "7x" "4x"
"103x"
Why are you getting colnames on the transpose of x?>
> # the above returns the answer I am trying to get
>
>> colnames(t(sort(apply(y,2,sum))[1:5]))
> NULL
Again. Why get colnames on transpose?
>
> # the above does not
>
> below is sample data and output of the apply for each
>
>> x
> 0x 1x 2x 3x 4x 5x 6x 7x 32x 33x 34x 35x 36x 37x 38x 39x 64x
> 65x 66x 67x 68x
> 13:55:24 21 18 18 18 17 16 16 17 29 29 25 23 19 18 18 21
> 24 22 22 21 20
> 13:55:54 16 3 3 4 4 1 1 6 40 29 16 9 6 23 19 21
> 27 19 29 15 19
> 13:56:24 3 2 6 2 1 1 4 1 33 40 28 13 10 2 4 15
> 25 17 8 14 11
> [ truncated .... ]
You have not told us how you constructed "x" and it is undoubtedly
important. We probably need at the very least the results of str(x)
and str(y). This looks like a zoo object which is not a data.frame.
>
>> apply(x,2,sum)
> 0x 1x 2x 3x 4x 5x 6x 7x 32x 33x 34x
> 35x 36x 37x
> 12042 11411 11343 11237 10937 10811 10909 10911 18341 16055 14406
> 13770 12252 12003
> 38x 39x 64x 65x 66x 67x 68x
> 12266 13450 15426 14163 13913 13615 12972
So where did these extra columns come from>
> 69x 70x 71x 96x 97x 98x 99x
> 12656 13089 13329 12671 12562 12336 12045
> 100x 101x 102x 103x
> 11476 11212 11066 10997
>
>> y
> nfs6 sd0 sd1 sd30 sd31 sd36 sd6 ssd100 ssd101 ssd102 ssd103
> ssd104 ssd105
> 13:55:54 0 2 0 0 0 0 0 0 0 0
> 0 0 0
> 13:56:54 0 3 0 0 0 0 0 0 0 0
> 0 0 0
> 13:57:54 0 1 0 0 0 0 0 0 0 0
> 0 0 0
> 13:58:54 0 1 0 0 0 0 0 0 0 0
> 0 0 0
> [ truncated .... ]
This might or might not be a data.frame. Doing a transpose on a
data.frame might have the side-effect of NULLing out the resulting
colnames.>
>> apply(y,2,sum)
> [1] 0 515 0 0 0 0 0 96 0 0 0 90
> 0 0 0 0
> [17] 0 1 13 96 0 31 0 0 0 0 0 0
> 0 0 11 0
> [33] 0 0 12 0 0 0 0 0 0 0 16 0
> 0 0 0 0
> [49] 31 0 0 0 0 0 0 0 0 10 0 0
> 0 0 0 0
> [65] 0 0 7 0 0 84 337 642 1005 0 605 518
> 0 0 5 0
> [81] 0 86 335 646 1014 0 606 513 0 737 418 306
> 277 607 301 410
> [97] 1690 445 432 0 738 424 315 283 608 302 411 1688
> 446 431 0 0
> [113] 0 0 0 93 0 0 0 0 0 1 12 0 0
>>
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David Winsemius, MD
West Hartford, CT