[R-sig-Geo] merging data with SpatialPolygonsDataFrame

[Dylan Beaudette]

On Thursday 24 January 2008, Roger Bivand wrote:
> 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

I think so. 

I was (trying to) describe the process of joining, either 1:1 or many:1, the 
att table associated with an sp object and some other data frame.

merge() seems to work fine, but the order of the rows are different from the 
original data frame attached to the sp object.

My question was on the best way to 'update' the data frame attached to an sp 
object, based on the results from a merge() with some other data.

does that help?

cheers,

Dylan


> > 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(x=veg at data, 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:
> > v at data <- combined[order(combined$ID),]
> >
> >
> > In summary, is there a safer or preferred way to do this?
> >
> > thanks,
> >
> > Dylan



-- 
Dylan Beaudette
Soil Resource Laboratory
http://casoilresource.lawr.ucdavis.edu/
University of California at Davis
530.754.7341