Last observation: 2024 (N = 4847)
First observation: 2013 (N = 3472)
Last data update: 14 aoû 2026, 22:27. Last compile: 18 aoû 2026, 00:01
Data - Eurostat
Last observation: 2024 (N = 4847)
First observation: 2013 (N = 3472)
Last data update: 14 aoû 2026, 22:27. Last compile: 18 aoû 2026, 00:01
demo_r_find3 |>
filter(indic_de == "AGEMOTH",
nchar(geo) == 5,
time == "2018") |>
select(geo, Geo, values) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}demo_r_find3 |>
filter(indic_de == "AGEMOTH",
nchar(geo) == 5,
time == "2018") |>
select(geo, values) |>
right_join(europe_NUTS3, by = "geo") |>
filter(long >= -15, lat >= 33, values <= 80000) |>
ggplot(aes(x = long, y = lat, group = group, fill = values)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::dollar_format(accuracy = 1, prefix = "", suffix = ""),
breaks = seq(20, 40, 2),
direction = -1) +
theme_void() + theme(legend.position = c(0.25, 0.85)) +
labs(fill = "Mean Age of Birth")
demo_r_find3 |>
filter(indic_de == "MEDAGEMOTH",
nchar(geo) == 5,
time == "2018") |>
select(geo, Geo, values) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}demo_r_find3 |>
filter(indic_de == "MEDAGEMOTH",
nchar(geo) == 5,
time == "2018") |>
select(geo, values) |>
right_join(europe_NUTS3, by = "geo") |>
filter(long >= -15, lat >= 33, values <= 80000) |>
ggplot(aes(x = long, y = lat, group = group, fill = values)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::dollar_format(accuracy = 1, prefix = "", suffix = ""),
breaks = seq(20, 40, 2),
direction = -1) +
theme_void() + theme(legend.position = c(0.25, 0.85)) +
labs(fill = "Median Age of Birth")
demo_r_find3 |>
filter(indic_de == "TOTFERRT",
nchar(geo) == 5,
time == "2018") |>
select(geo, Geo, values) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}demo_r_find3 |>
filter(indic_de == "TOTFERRT",
nchar(geo) == 5,
time == "2018") |>
select(geo, values) |>
right_join(europe_NUTS3, by = "geo") |>
filter(long >= -15, lat >= 33, values <= 80000) |>
ggplot(aes(x = long, y = lat, group = group, fill = values)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::dollar_format(accuracy = .1, prefix = "", suffix = ""),
values = c(0, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5, 1),
breaks = seq(0, 4, 0.5),
direction = -1) +
theme_void() + theme(legend.position = c(0.25, 0.85)) +
labs(fill = "Fertility Rate")