countriesCoarseLessIslands: a coarse resolution world map, a vector map of 177 country boundaries, suitable for global maps

Description

A 'SpatialPolygonsDataFrame' [package "sp"] object containing a simplified world map. Polygons are attributed with country codes. 177 countries. Based on Natural Earth data.

Usage

data(countriesCoarseLessIslands)

Arguments

format

The format is: Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots ..@ data :'data.frame': 178 obs. of 51 variables: .. ..$ ISO3 : Factor w/ 174 levels "-99","AFG","AGO",..: 1 1 1 1 2 3 4 5 6 7 ... .. ..$ ScaleRank : int [1:178] 1 1 1 1 1 1 1 1 1 1 ... .. ..$ LabelRank : int [1:178] 1 1 1 1 1 1 1 1 1 1 ... .. ..$ FeatureCla : Factor w/ 1 level "Admin-0 countries": 1 1 1 1 1 1 1 1 1 1 ... .. ..$ SOVEREIGNT : Factor w/ 172 levels "Afghanistan",..: 169 80 112 137 1 4 2 160 6 7 ... .. ..$ SOV_A3 : Factor w/ 172 levels "AFG","AGO","ALB",..: 133 86 38 141 1 2 3 4 5 6 ... .. ..$ ADM0_DIF : num [1:178] 0 0 0 0 0 0 0 0 0 0 ... .. ..$ LEVEL : num [1:178] 2 2 2 2 2 2 2 2 2 2 ... .. ..$ TYPE : Factor w/ 6 levels "Country","County",..: 4 6 6 4 6 6 6 6 6 6 ... .. ..$ ADMIN : Factor w/ 177 levels "Afghanistan",..: 174 83 116 141 1 4 2 164 6 7 ... .. ..$ ADM0_A3 : Factor w/ 177 levels "AFG","AGO","ALB",..: 137 89 39 145 1 2 3 4 5 6 ... .. ..$ GEOU_DIF : num [1:178] 0 0 0 0 0 0 0 0 0 0 ... .. ..$ GEOUNIT : Factor w/ 177 levels "Afghanistan",..: 174 83 116 141 1 4 2 165 6 7 ... .. ..$ GU_A3 : Factor w/ 177 levels "AFG","AGO","ALB",..: 137 89 39 145 1 2 3 4 5 6 ... .. ..$ SU_DIF : num [1:178] 0 0 0 0 0 0 0 0 0 0 ... .. ..$ SUBUNIT : Factor w/ 177 levels "Afghanistan",..: 174 83 116 141 1 4 2 165 6 7 ... .. ..$ SU_A3 : Factor w/ 177 levels "AFG","AGO","ALB",..: 137 89 39 145 1 2 3 4 5 6 ... .. ..$ NAME : Factor w/ 177 levels "Afghanistan",..: 173 85 109 144 1 4 2 165 6 7 ... .. ..$ ABBREV : Factor w/ 177 levels "Afg.","Alb.",..: 173 85 108 143 1 4 2 163 6 7 ... .. ..$ POSTAL : Factor w/ 172 levels "A","AE","AF",..: 168 82 33 138 3 5 4 2 7 8 ... .. ..$ NAME_FORMA : Factor w/ 151 levels "Arab Republic of Egypt",..: NA NA NA 114 30 55 54 NA 2 56 ... .. ..$ TERR_ : Factor w/ 6 levels "Commonwealth of U.S.A.",..: 3 NA NA NA NA NA NA NA NA NA ... .. ..$ NAME_SORT : Factor w/ 177 levels "Afghanistan",..: 174 88 40 143 1 4 2 165 6 7 ... .. ..$ MAP_COLOR : num [1:178] 4 11 8 2 7 1 6 3 13 10 ... .. ..$ POP_EST : num [1:178] -99 1804838 265100 3500000 28400000 ... .. ..$ GDP_MD_EST : num [1:178] 900 5352 3600 -99 22270 ... .. ..$ FIPS_10_ : num [1:178] -99 0 -99 -99 0 0 0 0 0 0 ... .. ..$ ISO_A2 : Factor w/ 174 levels "-99","AE","AF",..: 1 1 1 1 3 6 4 2 8 5 ... .. ..$ ISO_A3 : Factor w/ 174 levels "-99","AFG","AGO",..: 1 1 1 1 2 3 4 5 6 7 ... .. ..$ ISO_N3 : num [1:178] -99 -99 -99 -99 4 24 8 784 32 51 ... .. ..$ ISO2 : Factor w/ 222 levels "AD","AE","AF",..: NA NA NA NA 3 9 6 2 10 7 ... .. ..$ Name : Factor w/ 232 levels "Afghanistan",..: NA NA NA NA 1 6 2 215 9 10 ... .. ..$ FIPS : Factor w/ 222 levels "AA","AC","AE",..: NA NA NA NA 4 10 7 3 12 8 ... .. ..$ Numeric : num [1:178] NA NA NA NA 4 24 8 784 32 51 ... .. ..$ GEO3major : Factor w/ 7 levels "7","Africa","Asia and the Pacific",..: NA NA NA NA 3 2 4 7 5 4 ... .. ..$ GEO3 : Factor w/ 23 levels "Arabian Peninsula",..: NA NA NA NA 16 19 7 1 15 9 ... .. ..$ IMAGE24 : Factor w/ 25 levels "Asia-Stan","Brazil",..: NA NA NA NA 8 20 4 13 17 18 ... .. ..$ GLOCAF : Factor w/ 19 levels "Brazil","Canada",..: NA NA NA NA 14 17 4 9 13 5 ... .. ..$ Stern : Factor w/ 13 levels "Australasia",..: NA NA NA NA 4 11 6 13 9 6 ... .. ..$ SRESmajor : Factor w/ 4 levels "ALM","ASIA","OECD90",..: NA NA NA NA 2 1 4 1 1 4 ... .. ..$ SRES : Factor w/ 11 levels "Central and Eastern Europe (EEU)",..: NA NA NA NA 9 10 1 4 3 5 ... .. ..$ GBD : Factor w/ 21 levels "Asia Pacific, High Income",..: NA NA NA NA 4 18 8 15 13 2 ... .. ..$ AVOIDnumeric : num [1:178] NA NA NA NA 21 24 25 30 26 25 ... .. ..$ AVOIDname : Factor w/ 30 levels "Australia","Brazil",..: NA NA NA NA 19 27 7 15 25 7 ... .. ..$ Vulnerability.Name: Factor w/ 234 levels "Afghanistan",..: NA NA NA NA 1 6 2 220 9 10 ... .. ..$ GIS.Country : Factor w/ 234 levels "Afghanistan",..: NA NA NA NA 1 6 2 219 9 10 ... .. ..$ CNTRY_NAME : Factor w/ 233 levels "Afghanistan",..: NA NA NA NA 1 6 2 218 9 10 ... .. ..$ GMI_CNTRY : Factor w/ 225 levels "ABW","AFG","AGO",..: NA NA NA NA 2 3 5 8 9 10 ... .. ..$ LDC : Factor w/ 2 levels "LDC","other": NA NA NA NA 1 1 2 2 2 2 ... .. ..$ SID : Factor w/ 2 levels "other","SID": NA NA NA NA 1 1 1 1 1 1 ... .. ..$ LLDC : Factor w/ 2 levels "LLDC","other": NA NA NA NA 1 2 2 2 2 1 ... ..@ polygons :List of 177

source

http://www.naturalearthdata.com/downloads/110m-cultural-vectors/110m-admin-0-countries/

Details

Derived fron version 1.4.0 of Natural Earth data 1:110 m data. The different country boundaries in rworldmap are processed from Natural Earth Data as follows : All : ~ rename any non-ASCII country names that cause R trouble ~ rename Curacao which is particularly troublesome ! ~ check polygon geometries using checkPolygonsHoles ~ set projections, e.g. proj4string(countriesCoarse) <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") ~ set polygon IDs to country names (from ADMIN field) ~ copy ISO_A3 to ISO3 ~ replace missing ISO3 codes (6 in this version) with ADM0_A3 ~ check for duplicate ISO3 codes (2 in this version) ~ set ISO3 for Gaza to Gaza and 'Ashmore and Cartier Islands' to Ashm ~ replace POP_EST of -99 with NA ~ join on countryRegions data countriesCoarseLessIslands : ne_110 countriesCoarse : ne_110 plus extra countries from ne_50 plus Tuvalu from ne_10 countriesLow : ne_50 plus Tuvalu from ne_10 countriesHigh (in package rworldxtra) : ne_10

Examples

Run this code

data(countriesCoarseLessIslands)

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