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Young people neither in employment nor in education and training in Europe, 2000-2016
################################################################################
#
# ikashnitsky.github.io 2017-07-18
# Accessing Eurostat data using the `eurostat` R package
# Young people neither in employment nor in education and training in Europe
# Ilya Kashnitsky, ilya.kashnitsky@gmail.com
#
################################################################################
library(tidyverse)
library(lubridate)
library(forcats)
library(eurostat)
library(geofacet)
library(viridis)
library(ggthemes)
library(extrafont)
# Find the needed dataset code
# http://ec.europa.eu/eurostat/web/regions/data/database
# download fertility rates for countries
neet <- get_eurostat("edat_lfse_22")
# if the automated download does not work, the data can be grabbed manually at
# http://ec.europa.eu/eurostat/estat-navtree-portlet-prod/BulkDownloadListing
neet %>%
filter(geo %>% paste %>% nchar == 2,
sex == "T", age == "Y18-24") %>%
group_by(geo) %>%
mutate(avg = values %>% mean()) %>%
ungroup() %>%
ggplot(aes(x = time %>% year(),
y = values))+
geom_path(aes(group = 1))+
geom_point(aes(fill = values), pch = 21)+
scale_x_continuous(breaks = seq(2000, 2015, 5),
labels = c("2000", "'05", "'10", "'15"))+
scale_y_continuous(expand = c(0, 0), limits = c(0, 40))+
scale_fill_viridis("NEET, %", option = "B")+
facet_geo(~ geo, grid = "eu_grid1")+
labs(x = "Year",
y = "NEET, %",
title = "Young people neither in employment nor in education and training in Europe",
subtitle = "Data: Eurostat Regional Database, 2000-2016",
caption = "ikashnitsky.github.io")+
theme_few(base_family = "Roboto Condensed", base_size = 15)+
theme(axis.text = element_text(size = 10),
panel.spacing.x = unit(1, "lines"),
legend.position = c(0, 0),
legend.justification = c(0, 0))
@briatte
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briatte commented Jul 19, 2017

Great example of using facet_geo on EU countries, thanks for sharing!

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