This package contains the entire European Commission Annual macro-economic (AMECO) database in a format amenable to analysis in R.
Install it from either CRAN or Github:
# From CRAN
install.packages("ameco")
# From Github
devtools::install_github("expersso/ameco")
The dataset is in a clean, long format:
library(dplyr)
library(ameco)
head(ameco)
## # A tibble: 6 x 8
## code country sub.chapter title unit cntry year value
## <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
## 1 EU28.1.0.0.0.NPTD European~ 01 Populati~ Total~ 1000~ EU28 1960 409118
## 2 EU15.1.0.0.0.NPTD European~ 01 Populati~ Total~ 1000~ EU15 1960 316765
## 3 EA19.1.0.0.0.NPTD Euro area 01 Populati~ Total~ 1000~ EA19 1960 265029
## 4 EA12.1.0.0.0.NPTD Euro are~ 01 Populati~ Total~ 1000~ EA12 1960 252350
## 5 DU15.1.0.0.0.NPTD EU15 (in~ 01 Populati~ Total~ 1000~ DU15 1960 299421
## 6 DA12.1.0.0.0.NPTD EA12 (in~ 01 Populati~ Total~ 1000~ DA12 1960 235006
Filtering with the sub.chapter
variable allows you to easily find the
variable of interest:
ameco %>%
filter(sub.chapter == "01 Population") %>%
.$title %>%
unique()
## [1] "Total population (National accounts)"
## [2] "Total population"
## [3] "Population: 0 to 14 years"
## [4] "Population: 15 to 64 years"
## [5] "Population: 65 years and over"
Being interested in the total population of a few countries, we can easily subset the data and plot the results:
library(ggplot2)
ameco %>%
filter(title == "Total population",
year == 2015,
cntry %in% c("USA", "JPN", "DEU", "FRA", "ESP", "ITA")) %>%
ggplot(aes(x = reorder(country, -value), y = value / 1000)) +
geom_bar(stat = "identity") +
theme_bw() +
labs(x = NULL, y = "Population (millions)", title = "Total population")
This package is not affiliated with, nor endorsed by, the European Commission. I aim to update it whenever the AMECO database is updated. If you ever see that it is out-of-date, don’t hesitate to send a pull request and/or remind me to update it.