Title: | List of member states of various international organizations |
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Description: | Provides lists of country names and codes for various organizations and country groupings. |
Authors: | CJ Yetman [aut, cre] |
Maintainer: | CJ Yetman <[email protected]> |
License: | GPL-3 |
Version: | 0.0.0.9000 |
Built: | 2024-11-14 05:59:21 UTC |
Source: | https://github.com/cjyetman/memberstates |
Lists of the member states of various international organizations in various country code formats. Suggest new organizations at https://github.com/cjyetman/memberstates/issues
memberstates
memberstates
Nested list
Code for international organization. one of: coe (Council of Europe), eu (European Union), nato (North Atlantic Treaty Organization), oecd (Organisation for Economic Co-operation and Development)
Country code type. One of: country.name, iso3c, ios2c, iso3n, cowc, cown
http://www.oecd.org/about/membersandpartners/list-oecd-member-countries.htm
http://www.coe.int/en/web/about-us/our-member-states
http://www.nato.int/cps/en/natolive/nato_countries.htm
https://europa.eu/european-union/about-eu/countries_en
memberstates$nato$iso3c memberstates$eu$country.name # subestting a data frame (using base R) url <- 'https://raw.githubusercontent.com/datasets/gdp/master/data/gdp.csv' df <- read.csv(url) df <- df[df$Year == max(df$Year), ] df[df$Country.Code %in% memberstates$eu$iso3c, ] ## Not run: # subestting a data frame (using dplyr) library(dplyr) url <- 'https://raw.githubusercontent.com/datasets/gdp/master/data/gdp.csv' read.csv(url) %>% filter(Year == max(Year)) %>% filter(Country.Code %in% memberstates$eu$iso3c) ## End(Not run)
memberstates$nato$iso3c memberstates$eu$country.name # subestting a data frame (using base R) url <- 'https://raw.githubusercontent.com/datasets/gdp/master/data/gdp.csv' df <- read.csv(url) df <- df[df$Year == max(df$Year), ] df[df$Country.Code %in% memberstates$eu$iso3c, ] ## Not run: # subestting a data frame (using dplyr) library(dplyr) url <- 'https://raw.githubusercontent.com/datasets/gdp/master/data/gdp.csv' read.csv(url) %>% filter(Year == max(Year)) %>% filter(Country.Code %in% memberstates$eu$iso3c) ## End(Not run)