A data frame with one observations per country or region. It contains the following variables:
name
Name of country or region (following ISO 3166 official short names in English - see https://www.iso.org/obp/ui/#search/code/ and United Nations Multilingual Terminology Database - see https://unterm.un.org/unterm).
country_code
Numerical Location Code (3-digit codes following ISO 3166-1 numeric standard) - see http://en.wikipedia.org/wiki/ISO_3166-1_numeric.
reg_code
Code of the regions.
reg_name
Name of the regions.
area_code
Area code.
area_name
Area names, such as Africa
, Asia
, Europe
Latin America and the Caribbean
, Northern America
, Oceania
, World
.
location_type
Code giving the type of the observation: 0=World, 2=Major Area, 3=Region, 4=Country/Area, 5=Development group, 12=Special groupings. Other numbers are allowed and they can be used for aggregation, see below.
agcode_1500000
, agcode_1501000
, agcode_1502000
, agcode_1503000
, agcode_1517000
, agcode_1518000
, agcode_1524000
, agcode_1636000
, agcode_1637000
, agcode_1829000
, agcode_1830000
, agcode_1832000
, agcode_1833000
, agcode_1835000
, agcode_901000
, agcode_902000
, agcode_917000
, agcode_918000
, agcode_921000
, agcode_927000
, agcode_934000
, agcode_941000
, agcode_947000
, agcode_948000
, tree_level
Optional columns that can be used for aggregations. To aggregate a region with country_code
=\(x\), get the value of its location_type
, say \(y\). Then look for the column agcode_y
and locate all records with agcode_y
=\(x\) that have location_type
=4, see Example below.