countryRegions: Regional Classification Table

Description

A number of regional classifications exist, e.g. SRES, Stern, etc. This table can be used to find which grouping a country belongs to, given its country code. A variety of different codes or groupings can be used.

Arguments

Format

A data frame with the following variables.

ISO3: ISO 3 letter country code
ADMIN: country name
REGION: 7 region continent classification
continent: 6 continents classification
GEO3major: Global Environment Outlook GEO3 major region names
GEO3: Global Environment Outlook GEO3 major region names
IMAGE24: Image24 region names
GLOCAF: GLOCAF region names
Stern: Stern report region names
SRESmajor: SRES major region names
SRES: SRES region names
GBD: Global Burden of Disease GBD region names
AVOIDnumeric: numeric codes for AVOID regions
AVOIDname: AVOID regions
LDC: UN Least Developed Countries
SID: UN Small Island Developing states
LLDC: UN Landlocked Developing Countries

Details

Joined onto vector country maps. Used by country2Region and mapByRegion.

Examples

Run this code


data(countryRegions,envir=environment(),package="rworldmap")
str(countryRegions)

#joining example data onto the regional classifications
data(countryExData,envir=environment(),package="rworldmap")
dF <- merge(countryExData,countryRegions,by.x='ISO3V10',by.y='ISO3')
#plotting ENVHEALTH for Least Developed Countries (LDC) against others
#plot( dF$ENVHEALTH ~ dF$LDC)
#points( y=dF$ENVHEALTH, x=dF$LDC)

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