Addition of ISO Country Codes (Char and Num) to gapminder data objects

R/gapminder.R

@@ -3,14 +3,16 @@
 #' Excerpt of the Gapminder data on life expectancy, GDP per capita, and
 #' population by country.
 #' 
-#' @format The main data frame \code{gapminder} has 1704 rows and 6 variables:
+#' @format The main data frame \code{gapminder} has 1704 rows and 8 variables:
 #' \describe{ 
 #'   \item{country}{factor with 142 levels}
 #'   \item{continent}{factor with 5 levels}
 #'   \item{year}{ranges from 1952 to 2007 in increments of 5 years}
 #'   \item{lifeExp}{life expectancy at birth, in years}
 #'   \item{pop}{population}
-#'   \item{gdpPercap}{GDP per capita (US$, inflation-adjusted)}
+#'   \item{gdpPercap}{GDP per capita}
+#'   \item{isoChar}{ISO alpha-3 country code}
+#'   \item{isoNum}{ISO numeric-3 country code}
 #'   }
 #'   
 #' The supplemental data frame \code{\link{gapminder_unfiltered}} was not

README.Rmd

@@ -15,16 +15,18 @@ set.seed(1)
 
 Excerpt from the [Gapminder](http://www.gapminder.org/data/) data. The main object in this package is the `gapminder` data frame or "tibble". There are other goodies, such as the data in tab delimited form, a larger unfiltered dataset, and premade color schemes for the countries and continents.
 
-The `gapminder` data frames include six variables, ([Gapminder.org documentation page](http://www.gapminder.org/data/documentation/)):
-
-| variable    | meaning                  |
-|:------------|:-------------------------|
-| country     |                          |
-| continent   |                          |
-| year        |                          |
-| lifeExp     | life expectancy at birth |
-| pop         | total population         |
-| gdpPercap   | per-capita GDP           |
+The `gapminder` data frames include eight variables, ([Gapminder.org documentation page](http://www.gapminder.org/data/documentation/)):
+
+| variable      | meaning                    |
+| :------------ | :------------------------- |
+| country       |                            |
+| continent     |                            |
+| year          |                            |
+| lifeExp       | life expectancy at birth   |
+| pop           | total population           |
+| gdpPercap     | per-capita GDP             |
+| isoChar       | ISO alpha-3 country code   |
+| isoNum        | ISO numeric-3 country code |
 
 Per-capita GDP (Gross domestic product) is given in units of [international dollars](http://en.wikipedia.org/wiki/Geary%E2%80%93Khamis_dollar), "a hypothetical unit of currency that has the same purchasing power parity that the U.S. dollar had in the United States at a given point in time" -- 2005, in this case.
 
@@ -59,7 +61,7 @@ gapminder %>%
     filter(year == 2007) %>%
     group_by(continent) %>%
     summarise(lifeExp = median(lifeExp))
-    
+
 library("ggplot2")
 ggplot(gapminder, aes(x = continent, y = lifeExp)) +
   geom_boxplot(outlier.colour = "hotpink") +
@@ -132,6 +134,8 @@ Description:
     - `pop`: population
     - `gdpPercap`: GDP per capita
     - `lifeExp`: life expectancy
+    - `isoChar`: ISO alpha-3 country code
+    - `isoNum`: ISO numeric-3 country code
 
 There are 12 rows for each country in `gapminder`, i.e. complete data for 1952, 1955, ..., 2007.
 
@@ -154,13 +158,13 @@ If you want to practice importing from file, various tab delimited files are inc
   * [`gapminder.tsv`](inst/gapminder.tsv): the same dataset available via `library("gapminder"); gapminder`
   * [`gapminder-unfiltered.tsv`](inst/gapminder-unfiltered.tsv): the larger dataset available via `library("gapminder"); gapminder_unfiltered`.
   * [`continent-colors.tsv`](inst/continent-colors.tsv) and [`country-colors.tsv`](inst/country-colors.tsv): color schemes
-  
+
 Here in the source, these delimited files can be found:
 
   * in the [`inst/`](inst) sub-directory
-  
+
 Once you've installed the `gapminder` package they can be found locally and used like so:
-  
+
 ```{r}
 gap_tsv <- system.file("gapminder.tsv", package = "gapminder")
 gap_tsv <- read.delim(gap_tsv)
@@ -177,4 +181,4 @@ gap_bigger_tsv %>% # Bhutan IS here though! :)
 
 ## License
 
-Gapminder's data is released under the Creative Commons Attribution 3.0 Unported license. See their [terms of use](https://docs.google.com/document/pub?id=1POd-pBMc5vDXAmxrpGjPLaCSDSWuxX6FLQgq5DhlUhM). 
+Gapminder's data is released under the Creative Commons Attribution 3.0 Unported license. See their [terms of use](https://docs.google.com/document/pub?id=1POd-pBMc5vDXAmxrpGjPLaCSDSWuxX6FLQgq5DhlUhM).

README.md

@@ -6,16 +6,18 @@ gapminder
 
 Excerpt from the [Gapminder](http://www.gapminder.org/data/) data. The main object in this package is the `gapminder` data frame or "tibble". There are other goodies, such as the data in tab delimited form, a larger unfiltered dataset, and premade color schemes for the countries and continents.
 
-The `gapminder` data frames include six variables, ([Gapminder.org documentation page](http://www.gapminder.org/data/documentation/)):
-
-| variable  | meaning                  |
-|:----------|:-------------------------|
-| country   |                          |
-| continent |                          |
-| year      |                          |
-| lifeExp   | life expectancy at birth |
-| pop       | total population         |
-| gdpPercap | per-capita GDP           |
+The `gapminder` data frames include eight variables, ([Gapminder.org documentation page](http://www.gapminder.org/data/documentation/)):
+
+| variable  | meaning                    |
+|:----------|:---------------------------|
+| country   |                            |
+| continent |                            |
+| year      |                            |
+| lifeExp   | life expectancy at birth   |
+| pop       | total population           |
+| gdpPercap | per-capita GDP             |
+| isoChar   | ISO alpha-3 country code   |
+| isoNum    | ISO numeric-3 country code |
 
 Per-capita GDP (Gross domestic product) is given in units of [international dollars](http://en.wikipedia.org/wiki/Geary%E2%80%93Khamis_dollar), "a hypothetical unit of currency that has the same purchasing power parity that the U.S. dollar had in the United States at a given point in time" -- 2005, in this case.
 
@@ -64,7 +66,7 @@ gapminder %>%
 ## 3      Asia 72.3960
 ## 4    Europe 78.6085
 ## 5   Oceania 80.7195
-    
+
 library("ggplot2")
 ggplot(gapminder, aes(x = continent, y = lifeExp)) +
   geom_boxplot(outlier.colour = "hotpink") +
@@ -149,6 +151,8 @@ Description:
     -   `pop`: population
     -   `gdpPercap`: GDP per capita
     -   `lifeExp`: life expectancy
+    -   `isoChar`: ISO alpha-3 country code
+    -   `isoNum`: ISO numeric-3 country code
 
 There are 12 rows for each country in `gapminder`, i.e. complete data for 1952, 1955, ..., 2007.
 

data-raw/10_add-iso-codes-to-data.R

@@ -0,0 +1,49 @@
+#' ---
+#' date: "`r format(Sys.Date())`"
+#' output:
+#'   html_document:
+#'     keep_md: TRUE
+#' ---
+#' 
+
+suppressPackageStartupMessages(library(dplyr))
+library(countrycode)
+load(file = file.path("..", "data", "gapminder.rdata"))
+
+
+# Modifying `countrycode.rdata`
+## Using the `countrycode` package, we can add ISO Alpha-3 and ISO Numeric-3
+## country codes for each observation
+gapminder <- gapminder %>%
+  mutate(isoChar = countrycode(gapminder$country, "country.name", "iso3c"),
+         isoNum = countrycode(gapminder$country, "country.name", "iso3n"))
+
+## Is there an ISO code matched to each observation?
+(sum(is.na(gapminder$isoNum) == TRUE)) # 0 (No non-matches)
+(sum(is.na(gapminder$isoChar) == TRUE)) # 0 (No non-matches)
+
+## Writing data
+save(gapminder, file = file.path("..", "data", "gapminder.rdata"))
+write.table(gapminder, file = file.path("..", "inst", "gapminder.tsv"), 
+            quote=FALSE, sep='\t')
+
+# Modifying `gapminder_unfiltered.rdata`
+load(file = file.path("..", "data", "gapminder_unfiltered.rdata"))
+
+## Adding ISO codes
+gapminder_unfiltered <- gapminder_unfiltered %>%
+  mutate(isoChar = countrycode(gapminder_unfiltered$country,
+                                "country.name", "iso3c"),
+         isoNum = countrycode(gapminder_unfiltered$country,
+                               "country.name", "iso3n"))
+
+## Is there an ISO code matched to each observation?
+(sum(is.na(gapminder_unfiltered$isoNum) == TRUE)) # 0 (No non-matches)
+(sum(is.na(gapminder_unfiltered$isoChar) == TRUE)) # 0 (No non-matches)
+
+## Writing data
+save(gapminder_unfiltered, file = file.path("..", "data",
+                                            "gapminder_unfiltered.rdata"))
+write.table(gapminder_unfiltered, 
+            file= file.path("..", "inst", "gapminder_unfiltered.tsv"), 
+            quote=FALSE, sep='\t')

data-raw/README.md

@@ -8,6 +8,7 @@ Cleaning history
 -   2010: The first time I documented cleaning this dataset. I started with delimited files I exported from Excel. Not present in this repo.
 -   2014: I re-cleaned the data and (mostly) forced myself to pull it straight out of the spreadsheets. Used the `gdata` package. It was kind of painful, due to encoding and other issues. See the scripts in this state in [v0.1.0](https://github.com/jennybc/gapminder/tree/v0.1.0/data-raw).
 -   2015: I revisited the cleaning and switched to `readxl`. This was much less painful. Present day.
+-   2016: Added ISO country codes.
 
 | r\_script                                                               | notebook                                                                  | tsv                                                                                                  |
 |:------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------|