On Tue, 23 Oct 2007, Sergey Goriatchev wrote:
> Hello,
>
> I have a question regarding the following output:
>
>> database <- read.delim(file=path.input.file, header=TRUE,
dec=".", sep="\t", na.strings = "#NV")
>> str(database)
> 'data.frame': 314 obs. of 13 variables:
> $ S : Factor w/ 314 levels "307073","400212",..:
147 72 299 137
> 162 62 189 236 134 307 ...
> $ A : Factor w/ 314 levels "Alfa",...: 285 258 197 3 81 162 183
272
> 73 301 ...
> $ M: Factor w/ 19 levels "@NA","A",..: 18 10 11 6 7 12
17 17 11 6 ...
> $ W : num 0 0 0 0 0 ...
> $ T : num 0.0467 0.1095 0.0252 0.0821 -0.0275 ...
> $ C : num 0 0 0 0 0 ...
> $ MF : num -0.658 0.261 0.922 -1.897 -1.884 ...
> $ V : num 0.0585 -1.0852 -0.3156 -1.0592 0.2810 ...
> $ G : num -0.568 -1.302 0.225 -1.473 -0.541 ...
> $ Mo : num 0.34967 0.42807 -0.41407 -0.18216 -0.00305 ...
> $ R : num -0.5413 -2.0000 0.5353 -1.1437 -0.0776 ...
> $ Tr : num -0.12816 1.04148 0.00647 -0.02424 -1.66834 ...
> $ Su : num -1.611 1.160 -0.528 -0.091 -1.148 ...
>> which(is.na(database))
> [1] 675 704 774 887
>
> So, I have 314 observations, but there are unknown NA observations!
> I remove one observation (for certain reasons), and remove the
> corresponding factor level, then:
>> str(database)
> 'data.frame': 313 obs. of 13 variables:
> ....
>> which(is.na(database))
> [1] 673 702 772 885
>
> The removal of ONE observation moves NAs by two positions.
>
> Maybe someone have an idea what these NA observations mean????
If you mean why they move by two positions, I do.
But you can figure this out, if you do this:
which( is.na(database) , arr.ind = TRUE )
and maybe this
row( database )
col( database )
Chuck
> Thanks in advance for your time and help!
>
> Sergey
> University of Zurich
>
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Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901