EU Salary Race: Average Full-Time Adjusted Wages Across Europe
What is this?
Eurostat publishes yearly average full-time adjusted
salaries (nama_10_fte) for every EU/EFTA country.
This vignette pulls that series directly from the Eurostat API and turns
it into three progressively more polished visualisations: an interactive
time series, an animated bar chart, and a “bar chart race” — with Greece
highlighted in red against the rest of Europe in gray.
Packages
# install.packages(c("dplyr", "tidyr", "countrycode", "plotly",
# "eurostat", "gganimate", "gifski", "scales", "ragg"))
library(dplyr)
library(tidyr)
library(countrycode) # geo codes -> country names / ISO codes
library(plotly) # interactive charts
library(eurostat) # Eurostat data API
library(gganimate) # animation
library(gifski) # GIF renderer
library(scales) # axis formattingThe data
get_eurostat() downloads the raw dataset table by its
Eurostat code. We keep only country-level rows (dropping the
EU27_2020 and EA20 aggregates), derive a
plain-language country name and ISO code with countrycode,
and rank countries by salary within each year.
df_eusalary <- get_eurostat("nama_10_fte", filters = list(unit = "EUR"))
df_eusalary <- df_eusalary[!df_eusalary$geo %in% c("EU27_2020", "EA20"), ]
df_eusalary$year <- lubridate::year(df_eusalary$time)
df_eusalary$country <- countrycode(df_eusalary$geo, origin = "eurostat", destination = "country.name")
df_eusalary$iso <- countrycode(df_eusalary$geo, origin = "eurostat", destination = "iso2c")
df_eusalary$rank <- NA
df_eusalary$color <- NA
for (i in unique(df_eusalary$year)) {
df_eusalary[df_eusalary$year %in% i, "rank"] <-
rank(-df_eusalary[df_eusalary$year %in% i, "values"], ties.method = "min")
}
df_eusalary[df_eusalary$country %in% "Greece", "color"] <- "#E74C3C"
df_eusalary[!df_eusalary$country %in% "Greece", "color"] <- "gray70"
title <- "Average full time adjusted salary [nama_10_fte]"
head(df_eusalary[, c("country", "year", "values", "rank")], 12)## # A tibble: 12 × 4 ## country year values rank #### 1 Belgium 1995 27855 3 ## 2 Belgium 1996 27875 3 ## 3 Belgium 1997 27774 3 ## 4 Belgium 1998 28200 3 ## 5 Belgium 1999 29691 3 ## 6 Belgium 2000 30506 4 ## 7 Belgium 2001 31777 3 ## 8 Belgium 2002 32985 3 ## 9 Belgium 2003 33678 3 ## 10 Belgium 2004 34447 4 ## 11 Belgium 2005 35009 4 ## 12 Belgium 2006 36327 4
Each row is one country in one year, with:
| Column | Description |
|---|---|
country |
Country name (derived from Eurostat’s geo code) |
year |
Year of observation |
values |
Average full-time adjusted salary, in EUR |
rank |
Country’s salary rank within that year (1 = highest) |
color |
Highlight color — red for Greece, gray for everyone else |
Building the visualisations
Step 1 — interactive time series
A line per country lets you trace how each economy moved over time, and hovering reveals the exact value.
colors <- c("#e6194b", "#3cb44b", "#ffe119", "#0082c8", "#f58231", "#911eb4", "#46f0f0",
"#f032e6", "#d2f53c", "#fabebe", "#008080", "#e6beff", "#aa6e28", "#fffac8",
"#800000", "#aaffc3", "#808000", "#ffd8b1", "#000080", "#808080", "#ffffff",
"#000000")
plot_ly(df_eusalary[df_eusalary$values > 0, ],
x = ~year,
y = ~values,
color = ~country,
mode = "lines+markers",
type = "scatter",
text = ~paste("Year:", year,
"<br>Value:", values,
"<br>Country Name:", country),
hoverinfo = "text",
colors = colors,
showlegend = TRUE,
marker = list(size = 8)) %>%
plotly::layout(title = "",
autosize = TRUE,
margin = list(l = 50, r = 50, b = 50, t = 50, pad = 0),
legend = list(orientation = "vertical", xanchor = "right", x = 30, y = 1),
xaxis = list(title = "Year", tickangle = -90),
yaxis = list(title = ""),
font = list(size = 20, color = "gray25", weight = "bold"))Step 2 — animated bar chart
Sliding a frame argument to plot_ly turns a
static bar chart into a play/pause animation stepping through each
year.
plot_ly(df_eusalary,
x = ~country,
y = ~values,
frame = ~year,
ids = ~country,
type = "bar",
text = ~paste("Year:", year,
"<br>Value:", values,
"<br>Country:", country),
hoverinfo = "text",
colors = colors,
showlegend = FALSE) %>%
layout(
title = title,
xaxis = list(title = "", tickangle = -90),
yaxis = list(title = "Euro"),
font = list(size = 20, color = "gray25", weight = "bold"),
margin = list(l = 50, r = 50, b = 200, t = 100)
) %>%
animation_opts(
frame = 500,
transition = 500,
easing = "linear",
redraw = FALSE,
mode = "immediate"
)Step 3 — bar chart race, ranked
Instead of plotting by country name, we plot by rank, so
the bars physically reorder every year as economies overtake each other.
Greece is layered on top in red so it’s always visible against the gray
field.
plot_ly() %>%
add_bars(
data = df_eusalary[df_eusalary$color == "gray70", ],
x = ~rank,
y = ~values,
frame = ~year,
ids = ~rank,
marker = list(color = "gray70"),
text = ~country,
hoverinfo = "text",
textposition = "outside",
textangle = 90,
showlegend = FALSE
) %>%
add_bars(
data = df_eusalary[df_eusalary$color %in% "#E74C3C", ],
x = ~rank,
y = ~values,
frame = ~year,
ids = ~rank,
marker = list(color = "#E74C3C"),
text = ~country,
hoverinfo = "text",
textposition = "outside",
textangle = 90,
showlegend = FALSE
) %>%
layout(
xaxis = list(title = "Rank", tickmode = "array"),
yaxis = list(title = "Euro"),
title = title,
margin = list(l = 50, r = 50, b = 200, t = 100),
font = list(size = 20, color = "gray25", weight = "bold")
) %>%
animation_opts(frame = 1000, transition = 0, easing = "linear", redraw = TRUE)Step 4 — dark themed GIF with gganimate
The interactive versions above are great for exploring in a browser,
but a rendered GIF is easier to share. ggplot2 +
gganimate recreates the same ranked race as a horizontal
bar chart with a dark background, country labels, and a large year
watermark.
p <- ggplot(df_eusalary, aes(x = rank, y = values, fill = color, group = country)) +
geom_col(width = 0.85, show.legend = FALSE) +
geom_text(aes(y = 0, label = country, color = color),
hjust = 1, nudge_y = -400,
size = 3.8, fontface = "bold", show.legend = FALSE) +
geom_text(aes(label = comma(values, accuracy = 1)),
hjust = 0, nudge_y = 400,
color = "gray80", size = 3.2) +
scale_fill_identity() +
scale_color_identity() +
scale_x_reverse(breaks = NULL) +
scale_y_continuous(
labels = comma,
breaks = seq(0, 100000, by = 20000),
limits = c(-8000, NA),
expand = expansion(mult = c(0, 0.08))
) +
geom_text(
data = df_eusalary %>% dplyr::distinct(year),
aes(x = 23, y = 85000, label = year),
inherit.aes = FALSE,
hjust = 1, vjust = 1,
size = 20, color = "white", alpha = 0.15,
fontface = "bold"
) +
coord_flip(clip = "off") +
labs(title = title,
x = NULL,
y = "Euros",
caption = "Source: Eurostat | Greece highlighted in red") +
theme_minimal(base_size = 10) +
theme(
plot.background = element_rect(fill = "#0F1923", color = NA),
panel.background = element_rect(fill = "#0F1923", color = NA),
panel.grid.major.x = element_line(color = "#1E2D3D", linewidth = 0.4),
panel.grid.major.y = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.minor.x = element_line(color = "#1E2D3D", linewidth = 0.4),
axis.text.x = element_text(color = "#90A4AE", size = 10),
axis.text.y = element_blank(),
plot.title = element_text(color = "white", face = "bold", size = 10,
margin = margin(12, 0, 2, 0)),
plot.subtitle = element_text(color = "gray80", face = "bold", size = 10,
hjust = 0.98,
margin = margin(0, 0, 6, 0)),
plot.caption = element_text(color = "#546E7A", size = 8, hjust = 1,
margin = margin(8, 0, 8, 0)),
plot.margin = margin(10, 30, 10, 120)) +
transition_states(year, transition_length = 0, state_length = 5) +
ease_aes("cubic-in-out")
animate(p,
nframes = 100,
fps = 10,
duration = 20,
width = 1200,
height = 1000,
units = "px",
device = "ragg_png",
renderer = gifski_renderer("eu_salary_race.gif"))
Note: rendering the GIF takes a couple of minutes and requires an internet connection to reach the Eurostat API. The GIF is written to the working directory (
getwd()).
What the chart shows
- Northern and Western European economies (e.g. Denmark, Luxembourg, Ireland) consistently occupy the top ranks across the whole period.
- Greece sits in the lower half of the ranking throughout, and its relative position (highlighted in red) makes the post-2010 economic crisis visible as a plateau while other countries continue climbing.
- Ranks shuffle more among mid-table countries than at the extremes — the top and bottom of the distribution are comparatively stable year to year.
Customising it
Highlight a different country
Change the animation speed
Further reading
- Eurostat
nama_10_ftedataset — average full-time adjusted salary series eurostatR package — programmatic access to Eurostat data- gganimate documentation — all transition types and rendering options
Rendered with R 4.6.1 · plotly · ggplot2 · gganimate · eurostat