{"id":129,"date":"2012-06-29T01:37:37","date_gmt":"2012-06-28T22:37:37","guid":{"rendered":"http:\/\/ekqvist.goeuropeinfo.com\/rbloggerqvist\/?p=129"},"modified":"2012-06-29T01:37:37","modified_gmt":"2012-06-28T22:37:37","slug":"r-and-population-maps-in-finland-31-5-2012","status":"publish","type":"post","link":"https:\/\/science.ekqvist.fi\/blogi\/r-and-data-visualization\/r-and-population-maps-in-finland-31-5-2012\/","title":{"rendered":"R and population maps in Finland 31.5.2012"},"content":{"rendered":"

This example source is almost same like this<\/a>. I used at first time sorvi-package. In this example I modified little bit original and try to compare MML and GADM shape – files. As we know there is some need to updates into GADM shapefiles (as you will see). Datafiles source date is 31.05.2012 from V\u00e4est\u00f6rekisterikeskus<\/a>. Thanks to Louhos -people and their invaluable work within open -data project.<\/p>\n

# library sorvi You will find there<\/a><\/p>\n

library(sorvi)
\nlibrary(rgeos)
\nlibrary(rgdal)
\nif (!gpclibPermit()) { gpclibPermit() }<\/p>\n

# Finland map and municipility data at gadm-format
\ngadm <- GetGADM(“FIN_adm”, “Kunta”)<\/p>\n

##now we use also MML as data source (shape) because of compare shape files
\n# (C) MML 2011
\ndata(MML)
\nsp <- MML[[“1_milj_Shape_etrs_shape”]][[“kunta1_p”]]<\/p>\n

# vaestorekisteri population data from data source vrk.fi\u00a0 31.05.2012
\nvrek <- GetPopulationRegister(“http:\/\/vrk.fi\/default.aspx?docid=6706&site=3&id=0”)<\/p>\n

# Attach vrk data into map object and
\n# set population as zero where na
\ngadm$asukkaita <- log10(rowSums(vrek[gadm$Kunta, c(“Miehet”, “Naiset”)]))
\ngadm$asukkaita[is.na(gadm$asukkaita)] <- 0<\/p>\n

sp$asukkaita <- log10(rowSums(vrek[sp$Kunta, c(“Miehet”, “Naiset”)]))
\nsp$asukkaita[is.na(sp$asukkaita)] <- 0<\/p>\n

# male and female share
\ngadm$miehet.osuus <- vrek[gadm$Kunta, “Miehet”]\/vrek[gadm$Kunta, “Yhteensa”]
\ngadm$naiset.osuus <- vrek[gadm$Kunta, “Naiset”]\/vrek[gadm$Kunta, “Yhteensa”]<\/p>\n

gadm_summary_male <- summary(vrek[gadm$Kunta, “Miehet”]\/vrek[gadm$Kunta, “Yhteensa”])
\ngadm_summary_female <- summary(vrek[gadm$Kunta, “Naiset”]\/vrek[gadm$Kunta, “Yhteensa”])<\/p>\n

sp$miehet.osuus <- vrek[sp$Kunta, “Miehet”]\/vrek[sp$Kunta, “Yhteensa”]
\nsp$naiset.osuus <- vrek[sp$Kunta, “Naiset”]\/vrek[sp$Kunta, “Yhteensa”]<\/p>\n

sp_summary_male <- summary(vrek[sp$Kunta, “Miehet”]\/vrek[sp$Kunta, “Yhteensa”])
\nsp_summary_female <- summary(vrek[sp$Kunta, “Naiset”]\/vrek[sp$Kunta, “Yhteensa”])<\/p>\n

#some summary stat<\/p>\n

gadm_summary_male
\ngadm_summary_female
\nsp_summary_male
\nsp_summary_female<\/p>\n

hist_gadm_male <- hist(gadm$miehet.osuus)
\nhist_gadm_female <- hist(gadm$naiset.osuus)
\nhist_sp_male <- hist(sp$miehet.osuus)
\nhist_sp_female <- hist(sp$naiset.osuus)<\/p>\n

plot(density(gadm$miehet.osuus,na.rm=TRUE))
\nplot(density(gadm$naiset.osuus,na.rm=TRUE))
\nplot(density(sp$miehet.osuus,na.rm=TRUE))
\nplot(density(sp$naiset.osuus,na.rm=TRUE))<\/p>\n

#saving hist figure into file …\\r_maps
\njpeg(“…\/hist.jpg”)
\nlayout(matrix(1:4,2,2))
\nhist_gadm_male <- hist(gadm$miehet.osuus)
\nhist_gadm_female <- hist(gadm$naiset.osuus)
\nhist_sp_male <- hist(sp$miehet.osuus)
\nhist_sp_female <- hist(sp$naiset.osuus)
\ndev.off()<\/p>\n

\"\"<\/a><\/p>\n

#saving density figre into file …\\r_maps (replace … as your fav. folder)
\njpeg(“…\/density.jpg”)
\nlayout(matrix(1:4,2,2))
\nplot(density(gadm$miehet.osuus,na.rm=TRUE))
\nplot(density(gadm$naiset.osuus,na.rm=TRUE))
\nplot(density(sp$miehet.osuus,na.rm=TRUE))
\nplot(density(sp$naiset.osuus,na.rm=TRUE))
\ndev.off()<\/p>\n

\"\"<\/a><\/p>\n

# set share\u00a0 50% male\/female
\n# where na
\ngadm$miehet.osuus[is.na(gadm$miehet.osuus)] <- 0.5
\ngadm$naiset.osuus[is.na(gadm$naiset.osuus)] <- 0.5<\/p>\n

#same with MML<\/p>\n

sp$miehet.osuus[is.na(sp$miehet.osuus)] <- 0.5
\nsp$naiset.osuus[is.na(sp$naiset.osuus)] <- 0.5<\/p>\n

# border of interval GADM
\nvarname1 <- “naiset.osuus”
\ninterval1 <- max(abs(gadm[[varname1]] – 0.5))
\nat1 <- seq(0.5 – interval1, 0.5 + interval1, length = 100)<\/p>\n

#border of interval MML<\/p>\n

varname2 <- “naiset.osuus”
\ninterval2 <- max(abs(sp[[varname2]] – 0.5))
\nat2 <- seq(0.5 – interval2, 0.5 + interval2, length = 100)<\/p>\n

#PLOTTING INTO FILE<\/p>\n

jpeg(“j:\/todo\/r_maps\/gadm_280612.jpg”)
\nq1 <- PlotShape(gadm, varname1, type = “twoway”, at = at1, main = “Share of women (red) and men (blue) 31.05.2012 n=437 (GADM)”)
\ndev.off()<\/p>\n

jpeg(“j:\/todo\/r_maps\/mml_280612.jpg”)
\nq2 <- PlotShape(sp, varname2, type = “twoway”, at = at2, main = “Share of women (red) and men (blue) 31.05.2012 n=337 (MML)”)
\ndev.off()<\/p>\n

#Which one is best?<\/p>\n

\"\"<\/a><\/p>\n

GADM projection is not like “normal” and MML coastline is little bit odd, but I am patiently looking forward to improvement\u00a0 into this issue….<\/p>\n

ME\/290612<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

This example source is almost same like this. I used at first time sorvi-package. In this example I modified little bit original and try to compare MML and GADM shape – files. As we know there is some need to updates into GADM shapefiles (as you will see). Datafiles source date is 31.05.2012 from V\u00e4est\u00f6rekisterikeskus. […] Read More<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"gallery","meta":[],"categories":[19,22,23],"tags":[34,47,48],"_links":{"self":[{"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/posts\/129"}],"collection":[{"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/comments?post=129"}],"version-history":[{"count":0,"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/posts\/129\/revisions"}],"wp:attachment":[{"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/media?parent=129"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/categories?post=129"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/science.ekqvist.fi\/blogi\/wp-json\/wp\/v2\/tags?post=129"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}