Counting/processing a character vector
Apologies, Jim Holtman has pointed out a couple of problems/queries with my original email that I would like to make clear. Firstly, I introduced a typo when trying to be helpful. In my email below, I had incorrectly typed out one of the species codes I would count: 10000000 16220602 20110000 24000000 40320203 ## This should have been 40210102 45140000 45630600 == 7 "species" present. Secondly, the criteria I laid out might suggest that in the 10 rows of example I quoted, I would count both: 45630000 45630600 This is not what I wanted and apologies that this was not clear. I only want to count 45630600 because this is more "specific" in terms of what creature this is than 45630000. I don't know that 45630000 is not 45630600, so I should not count both 45630000 and 45630600, as this could be double accounting. These data are species counts and sometimes it is not possible to identify an individual to species level. Sometime we can't even get the genera, or even family, hence why sometimes we have a count for the family (45630000) as well as for the genus (45630600) in the same sample/site. It depends on how much of the individual there is to identify it from as to how precise the identification is. So I only want to count a higher level category only if I have not counted a lower level category contained within this higher level. I hope this is a little bit clearer? And no, I did not come up with this coding system nor the idea to use "counts" of "species" in this way... ;-) Apologies if my original email caused unnecessary confusion. All the best, G
On Wed, 2009-02-18 at 13:37 +0000, Gavin Simpson wrote:
Dear List, I have a data set stored in the following format:
head(dat, n = 10)
id sppcode abundance 1 10307 10000000 1 2 10307 16220602 2 3 10307 20000000 5 4 10307 20110000 2 5 10307 24000000 1 6 10307 40210000 83 7 10307 40210102 45 8 10307 45140000 1 9 10307 45630000 1 10 10307 45630600 41
str(dat)
'data.frame': 111 obs. of 3 variables:
$ id : Factor w/ 3 levels "10307","10719",..: 1 1 1 1 1 1 1 1 1 1 ...
$ sppcode : chr "10000000" "16220602" "20000000" "20110000" ...
$ abundance: num 1 2 5 2 1 83 45 1 1 41 ...
that represent counts of species, recorded with a particular coding
system. The abundance column is not needed for this particular
operation, but is present in the data files.
I am interested in counting entries (rows) in the sppcode component of
dat. The sppcode takes a particular format: Order Family Genus Species,
with 2 alphanumeric digits allocated for each level of the hierarchy. I
want to know how many species there are in each site (the id factor),
but I should only count a higher level entry if there are no lower
levels present.
For example, for the above data excerpt (just the headed rows), I would
count the following rows:
10000000
16220602
20110000
24000000
40320203
45140000
45630600 == 7 "species" present.
To be more specific, I don't count 45630000 (row 9) because there exists
a sppcode for this 'id' where either of the next two pairs of digits are
not all 0's.
In words, I want to count all rows where WWXXYYZZ are ZZ != 00, then,
rows where ZZ == 00 only if the WWXXYY combination has not been counted
yet.
An example data set has been placed in my University web space and can
be read into R with the following:
## read example csv data
dat <- read.csv(url("http://www.homepages.ucl.ac.uk/~ucfagls/files/example_data.csv"),
colClasses = c("factor","character","numeric"))
## show the data
head(dat, n = 10)
And the sppcode variable can be broken out into the 4 levels if required via:
## split out the four levels of categorisation:
dat2 <- data.frame(dat,
order = with(dat, substr(sppcode, 1, 2)),
family = with(dat, substr(sppcode, 3, 4)),
genus = with(dat, substr(sppcode, 5, 6)),
species = with(dat, substr(sppcode, 7, 8)))
The actual data set/problem contains several hundred different id's.
I can't see an efficient way of processing these data in the manner
described. Any help would be most gratefully received.
Many thanks,
Gavin
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