Population density by metropolitan regions - met_d3dens

Data - Eurostat

Info

Last observation: Annual: 2023 (N = 319)

First observation: Annual: 2018 (N = 356)

Last data update: 23 jul 2026, 23:04. Last compile: 24 jul 2026, 02:34

Structure

freq

metroreg

Capital Metropolitan Regions

Paris, Berlin, Madrid, Rome, London

met_d3dens %>%
  filter(metroreg %in% c("FR001MC", "DE001MC", "ES001MC", "IT001MC", "UK001MC")) %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Metroreg)) +
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(2018, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.7),
        legend.title = element_blank()) +
  xlab("") + ylab("Population density (inhabitants per km²)")

Top 15 Densest Metropolitan Regions

latest_y <- met_d3dens %>%
  filter(!is.na(values)) %>%
  summarise(m = max(time)) %>%
  pull(m)

met_d3dens %>%
  filter(time == latest_y,
         grepl("M$|MC$", metroreg)) %>%
  select(metroreg, Metroreg, values) %>%
  arrange(-values) %>%
  slice(1:15) %>%
  print_table_conditional()

metroreg	Metroreg	values
NL001M	s' Gravenhage	2786
IT003M	Napoli	2539
PL004M	Wroclaw	2347
DE546M	Wuppertal	2136
CH002M	Genève	2116
MT001MC	Valletta	2048
NO001MC	Oslo	1664
PL007M	Szczecin	1659
IT002M	Milano	1586
DE036M	Mönchengladbach	1579
NL507M	Leiden	1545
DE011M	Düsseldorf	1341
DE017M	Bielefeld	1306
RO001MC	Bucuresti	1306
EL001MC	Athina	1302

Decreasing Density

met_d3dens %>%
  filter(time == latest_y) %>%

  select(metroreg, Metroreg, values) %>%
  arrange(-values) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}