Unemployment by sex, age, country of birth and NUTS 2 regions - lfst_r_lfu2gac

Data - Eurostat

Author

François Geerolf

Info

Last observation: Annual: 2025 (N = 33,020)

First observation: Annual: 1999 (N = 22,942)

Last data update: 23 jul 2026, 22:40. Last compile: 24 jul 2026, 02:28

Structure

France: Males vs. Females

Y15-74

Code

lfst_r_lfu2gac %>%
  filter(geo == "FR",
         age == "Y15-74",
         sex %in% c("F", "M"),
         c_birth == "TOTAL") %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Sex)) +
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployed persons (thousands)") +
  theme(legend.position = c(0.25, 0.85), legend.title = element_blank())

France: NUTS2 Regions

Ile de France, Grand Est, Nouvelle-Aquitaine

Code

lfst_r_lfu2gac %>%
  filter(geo %in% c("FR10", "FRF", "FRI"),
         age == "Y15-74",
         sex == "T",
         c_birth == "TOTAL") %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Geo)) +
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployed persons (thousands)") +
  theme(legend.position = c(0.3, 0.85), legend.title = element_blank())

National Totals

France, Germany, Italy, Spain, Portugal

Code

lfst_r_lfu2gac %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "PT"),
         age == "Y15-74",
         sex == "T",
         c_birth == "TOTAL") %>%
  year_to_date %>%

  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) +
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployed persons (thousands)")

France: Country of Birth

Nationals vs. Foreign-born

Code

lfst_r_lfu2gac %>%
  filter(geo == "FR",
         age == "Y15-74",
         sex == "T",
         c_birth %in% c("NAT", "FOR")) %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = C_birth)) +
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployed persons (thousands)") +
  theme(legend.position = c(0.25, 0.85), legend.title = element_blank())

Latest Year, National Totals

Code

latest_y_lfu <- lfst_r_lfu2gac %>%
  filter(age == "Y15-74",
         sex == "T",
         c_birth == "TOTAL",
         geo %in% c("FR", "DE", "IT", "ES", "PT"),
         !is.na(values)) %>%
  summarise(m = max(time)) %>%
  pull(m)

lfst_r_lfu2gac %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "PT"),
         age == "Y15-74",
         sex %in% c("F", "M", "T"),
         c_birth == "TOTAL",
         time == latest_y_lfu) %>%
  select(sex, Sex, Geo, values) %>%
  spread(Geo, values) %>%
  print_table_conditional()

sex	Sex	France	Germany	Italy	Portugal	Spain
F	Females	1181.1	723.4	744.5	180.2	1396.4
M	Males	1270.1	968.7	831.1	156.8	1211.7
T	Total	2451.2	1692.1	1575.6	337.1	2608.1