Last observation: 2026M07 (N = 18)
First observation: 1983M01 (N = 174)
Last data update: 14 aoû 2026, 22:31. Last compile: 18 aoû 2026, 00:40
Data - Eurostat
Last observation: 2026M07 (N = 18)
First observation: 1983M01 (N = 174)
Last data update: 14 aoû 2026, 22:31. Last compile: 18 aoû 2026, 00:40
ei_lmhu_m |>
filter(geo %in% c("FR", "DE", "ES", "IT", "US"),
indic == "LM-UN-T-TOT",
s_adj == "SA") |>
month_to_date() |>
left_join(colors, by = c("Geo" = "country")) |>
mutate(values = values/1000) |>
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + scale_color_identity() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1983, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Unemployed persons (millions, SA)")
ei_lmhu_m |>
filter(geo == "FR",
indic %in% c("LM-UN-M-TOT", "LM-UN-F-TOT"),
s_adj == "SA") |>
month_to_date() |>
mutate(values = values/1000,
Sex = ifelse(indic == "LM-UN-M-TOT", "Males", "Females")) |>
ggplot() + geom_line(aes(x = date, y = values, color = Sex)) +
theme_minimal() +
theme(legend.position = c(0.15, 0.85),
legend.title = element_blank()) +
scale_x_date(breaks = as.Date(paste0(seq(1983, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Unemployed persons (millions, SA)")
ei_lmhu_m |>
filter(geo == "FR",
indic %in% c("LM-UN-T-LE25", "LM-UN-T-GT25"),
s_adj == "SA") |>
month_to_date() |>
mutate(values = values/1000,
Age = ifelse(indic == "LM-UN-T-LE25", "Under 25", "Over 25")) |>
ggplot() + geom_line(aes(x = date, y = values, color = Age)) +
theme_minimal() +
theme(legend.position = c(0.15, 0.85),
legend.title = element_blank()) +
scale_x_date(breaks = as.Date(paste0(seq(1983, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Unemployed persons (millions, SA)")
latest_m <- ei_lmhu_m |>
filter(indic == "LM-UN-T-TOT",
s_adj == "SA",
geo %in% c("FR", "DE", "ES", "IT", "US", "UK", "EU27_2020"),
!is.na(values)) |>
summarise(m = max(time)) |>
pull(m)
ei_lmhu_m |>
filter(indic %in% c("LM-UN-T-TOT", "LM-UN-M-TOT", "LM-UN-F-TOT"),
s_adj == "SA",
geo %in% c("FR", "DE", "ES", "IT", "US", "UK", "EU27_2020"),
time == latest_m) |>
select(Geo, Indic, values) |>
spread(Indic, values) |>
print_table_conditional()| Geo | Unemployment according to ILO definition - females | Unemployment according to ILO definition - males | Unemployment according to ILO definition - total |
|---|---|---|---|
| European Union - 27 countries (from 2020) | 6364 | 6954 | 13317 |
| France | 1216 | 1419 | 2635 |
| Germany | 712 | 984 | 1696 |
| Italy | 678 | 780 | 1458 |
| Spain | 1351 | 1202 | 2553 |
| United States | 3275 | 3813 | 7088 |