[R] How to read a shapefile with areas other than the one used by default in the spplot?

[Bert Gunter]

1. Wrong list. You should post on r-sig-geo instead.

2. As you use ggplot, why aren't you using ggmap() ?

Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Wed, Mar 25, 2020 at 6:34 AM Yana Borges <borges.yana using gmail.com> wrote:
>
> Hello!
> I send the same question I asked in the stackoverflow, if you don't mind.
> It is possible that it is something simple, but I really did not succeed.
>
> I need to make a map as it is in the script I send below. The shapefile I
> am using, as well as the data, are attached.
> My problem: I want the divisions by Regional Health (RS), and not by
> municipality, which are 399. There are 22 Health Regionals, but I can't
> identify them on the map. In the shp file there is this subdivision, but I
> was unable to insert it that way.
> How do I read by RS and not by municipality (default)?
>
> I used the packages ggplot2, factoextra and rgdal
>
> Thank you!
>
> prec <- readxl::read_xlsx('Cluster\\municipios.xlsx', sheet =
> "Obito0a6dias2",col_names = T)
> tard <- readxl::read_xlsx('Cluster\\municipios.xlsx', sheet =
> "Obito7a27dias2",col_names = T)
> pop <- readxl::read_xlsx('Cluster\\municipios.xlsx', sheet =
> "pop2",col_names = T)
> # TAXAS
> taxa.prec <- data.frame(prec[1:22,2:18]/pop[1:22,2:18]*1000,row.names
> = prec$mun)
> taxa.tard <- data.frame(tard[1:22,2:18]/pop[1:22,2:18]*1000,row.names
> = prec$mun)
> `# head(taxa.prec)
> ################### Dados ######################
> txp     <- txt  <- res.hc  <- grupo  <- list()
> dados <- taxa.grupos <- plot <- list()
> for (i in 1:ncol(taxa.prec)) {
> txp[[i]]    <- scale(taxa.prec[,i])
> txt[[i]]    <- scale(taxa.tard[,i])
> res.hc[[i]] <- hclust(dist(data.frame(txp[[i]],
>                                     txt[[i]],
>                                     row.names = prec$mun)),
>                     method = "ward.D2")
> grupo[[i]]  <- cutree(res.hc[[i]], k = 4)
> dados[[i]]  <- data.frame(RS = 1:22,taxap = taxa.prec[,i],
>                         taxat = taxa.tard[,i],
>                         Grupo=factor(grupo[[i]]),
>                         row.names = prec$mun)
> taxa.grupos[[i]] <- aggregate(cbind(taxap, taxat) ~ grupo[[i]],
> dados[[i]], mean)
> taxa.grupos[[i]]$media.pt <- apply(taxa.grupos[[i]][2:3], 1, mean)}
> names(dados) <- 2000:2016
>
> mapa <- maptools::readShapePoly('Cluster\\PR\\rs_pr\\RS.shp')
>
> gp <- list(gp1=list(),gp2=list(),gp3=list(),gp4=list())for (i in 1:17) {
>  for (j in 1:4) {
>  gp$gp1[[i]] <- which(dados[[i]]$Grupo == 1)
>  gp$gp2[[i]] <- which(dados[[i]]$Grupo == 2)
>  gp$gp3[[i]] <- which(dados[[i]]$Grupo == 3)
>  gp$gp4[[i]] <- which(dados[[i]]$Grupo == 4) }}
>
> aux <- matrix(0, ncol=17, nrow=399)
> for (i in 1:17) {for (j in 1:4) {
>     aux[,i][mapa$RS %in% gp[[j]][[i]]] <- taxa.grupos[[i]]$media.pt[j]}}
> mapa using data[6:22] <- aux
>
>  ############# Mapas em cores####
> corDegrade <- colorRampPalette(c("#FFFF99", "orange","red", "darkred"))
> x11()spplot(mapa, zcol=c(6:22), col.regions =corDegrade(16),
>    layout(matrix(c(1:20),nrow = 5,ncol = 4, byrow = TRUE)),
>    names.attr = c(2000:2016))
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