Thanks for that. It works as expected now. A case of GIGO (garbage in-
garbage out) on my part, with some head-banging. :-)
Regards
Viju Moses
Yihui Xie wrote:
just put na.omit() inside length() if you intend to omit the NA
elements of the vector (otherwise you are trying to omit the NA's of
the returned value of length() which is a scalar 2):
length(na.omit(sno[a==1 & b==0]))
Regards,
Yihui
--
Yihui Xie <xieyi...@gmail.com>
Phone: 515-294-6609 Web: http://yihui.name
Department of Statistics, Iowa State University
3211 Snedecor Hall, Ames, IA
On Mon, Oct 5, 2009 at 11:51 PM, Viju Moses <vijumo...@gmail.com> wrote:
I'm seeing what looks to me like odd behaviour when I use na.omit on a
simple "length" function, as follows.
sno
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
25 26 27 28 29 30 31 32 33 34
a
[1] 0 1 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
b
[1] 1 1 0 1 1 1 0 0 NA 0 0 0 NA 0 1 NA 0 1 0 0 0 0 NA 0
0 0 0 NA 0 NA 0 1 0 0
#NA refers to no data available.
df=data.frame(sno,a,b)
# I'm pasting the sorted data frame below:
sortdf=df[order(a,b),]
sortdf
sno a b
3 3 0 0
7 7 0 0
8 8 0 0
10 10 0 0
11 11 0 0
12 12 0 0
14 14 0 0
17 17 0 0
20 20 0 0
21 21 0 0
22 22 0 0
24 24 0 0
25 25 0 0
26 26 0 0
27 27 0 0
29 29 0 0
31 31 0 0
33 33 0 0
34 34 0 0
1 1 0 1
4 4 0 1
9 9 0 NA
13 13 0 NA
23 23 0 NA
28 28 0 NA
30 30 0 NA
19 19 1 0
2 2 1 1
5 5 1 1
6 6 1 1
15 15 1 1
18 18 1 1
32 32 1 1
16 16 1 NA
#Now I wish to count howmany records have a=1 AND b=0. From the lower
section of that sorted dataframe we see the answer is 1 (record # 19). But
instead I'm seeing 2. Probably counting record # 16 also.
na.omit(length(sno[a==1 & b==0]))
[1] 2
I'd be grateful to anyone who can point out what I'm doing wrong.
Regards.
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