On Thu, 24 Jan 2008, Dylan Beaudette wrote:
>
> Hi Roger. Thanks for contributing some answers to this.
>
> I was recently working with a colleague on developing some sample exercises
> for new students. Since joining new attribute data to a GIS layer's table is
> a very common operation we included some samples on how to do this within R.
> You have hinted at some possible ways to do it above, but do you have a 'best
> practices' approach to doing this using 'sp' methods and objects?
>
> For example:
>
> # contains an attribute col named 'veg_code'
> veg <- readOGR(something.shp)
>
> # code meanings: indexed by 'veg_code'
> codes <- read.dbf(table.dbf)
>
> # what is the best way to join up the attributes in 'veg' with the rows
> in 'codes' ?
Hi Dylan,
This is a different question, but I won't break it out of this thread yet.
You are doing look-up on codes to give labels to veg$veg_code, right?
veg$veg_code are integer indices to codes$V1 (say V1, I don't know what it
is). If length(unique(veg$veg_code)) == length(codes$V1), and
sort(unique(veg$veg_code)) is 1:length(codes$V1), you should think of the
factor as your friend:
veg$veg_code_factor <- factor(veg$veg_code, labels=as.character(codes$V1))
If not, you need another layer using perhaps order() or match() on the
matching substring of codes$V1 to find out which value of veg$veg_code
should have which label in as.character(codes$V1). Alternatively use the
levels= argument to factor().
Something like:
set.seed(1)
veg_code <- rpois(100, 4)
table(veg_code)
V1 <- paste("code", 0:10)
V1
levs <- 0:10
veg_code_factor <- factor(veg_code, levels=levs, labels=V1)
table(veg_code_factor, veg_code)
No merging or messing with veg itself is needed, apart from adding a
single extra factor column. The factor abstraction is a great strength of
the S language.
Have I misunderstood you?
Roger
>
>
> As of now we are using merge to replace the dataframe slot of the original
> file. We first re-order the results from merge to match the original row
> ordering:
>
>
> # an example file:
> veg <- readOGR(dsn='ArcGISLabData/BrownsPond/', layer='vegevector')
>
> # some example codes
> veg_codes <- data.frame(code=1:4, meaning=c('code 1','code 2','code 3','code
> 4'))
>
> # join the original data table with the veg codes table
> combined <- merge([EMAIL PROTECTED], y=veg_codes, by.x='CODE', by.y='code')
>
>
> # overwrite the original data frame with the combined version
> # note that the original order needs to be restored
> # since the original data was sorted on 'ID', we can use that to restore
> # the correct order in the 'combined' dataframe:
> [EMAIL PROTECTED] <- combined[order(combined$ID),]
>
>
> In summary, is there a safer or preferred way to do this?
>
> thanks,
>
> Dylan
>
>
>
>
>
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>
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>
>
--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: [EMAIL PROTECTED]
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