<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/young-people-neither-in-employment-nor-in-education-and-training-in-europe-2000-2016/"></div></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="https://ikashnitsky.github.io/2017/neet-in-europe/"> Ilya Kashnitsky</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<h1>R Documentation at Stack Overflow</h1>
<p>One of the nice features of <code>R</code> is the ease of data acquisition. I am now working on the examples of data acquisition form different sources within an R session. Soon I am going publish a long-read with an overview of demographic data acquisition in R.</p>
<p>Please consider contributing your examples to the <a rel="nofollow" href="https://stackoverflow.com/documentation/r/10800" target="_blank">Data aquisition topic</a>.</p>
<h1>NEET in Europe</h1>
<p>As an example of Eurostat data usage I chose to show the dynamics of NEET (Young people neither in employment nor in education and training) in European countries. The example is using the brilliant <code>geofact</code> package.</p>
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<pre><code>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 &lt;- get_eurostat(&quot;edat_lfse_22&quot;)

# 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 == &quot;T&quot;, age == &quot;Y18-24&quot;) %>%
        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(&quot;2000&quot;, &quot;'05&quot;, &quot;'10&quot;, &quot;'15&quot;))+
        scale_y_continuous(expand = c(0, 0), limits = c(0, 40))+
        scale_fill_viridis(&quot;NEET, %&quot;, option = &quot;B&quot;)+
        facet_geo(~ geo, grid = &quot;eu_grid1&quot;)+
        labs(x = &quot;Year&quot;,
             y = &quot;NEET, %&quot;,
             title = &quot;Young people neither in employment nor in education and training in Europe&quot;,
             subtitle = &quot;Data: Eurostat Regional Database, 2000-2016&quot;,
             caption = &quot;ikashnitsky.github.io&quot;)+
        theme_few(base_family =  &quot;Roboto Condensed&quot;, base_size = 15)+
        theme(axis.text = element_text(size = 10),
              panel.spacing.x = unit(1, &quot;lines&quot;),
              legend.position = c(0, 0),
              legend.justification = c(0, 0))
</code></pre>
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<p><a rel="nofollow" href="https://i2.wp.com/ikashnitsky.github.io/images/170718/neet-in-europe.png?ssl=1" target="_blank"><img alt="fig1" src="https://i2.wp.com/ikashnitsky.github.io/images/170718/neet-in-europe.png?w=456&ssl=1" data-recalc-dims="1"></a></p>
<p><strong>The whole code may be downloaded from <a rel="nofollow" href="https://gist.github.com/ikashnitsky/5e073ccebbf1617e79d7d3cc080aceed" target="_blank">the gist</a></strong></p>
	<p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://ikashnitsky.github.io/2017/neet-in-europe/"> Ilya Kashnitsky</a></strong>.</div>
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