Unemployment rates by sex, age, country of birth and NUTS 2 regions (1999-2019) - lfst_r_lfur2gac

Data - Eurostat

Author

unit

Code

lfst_r_lfur2gac %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

unit	Unit	Nobs
PC	Percentage	812409

c_birth

Code

lfst_r_lfur2gac %>%
  group_by(c_birth) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

c_birth	Nobs
TOTAL	168405
NAT	156768
FOR	155269
NEU27_2020_FOR	139825
EU27_2020_FOR	136645
NRP	55497

sex

Code

lfst_r_lfur2gac %>%
  left_join(sex, by = "sex") %>%
  group_by(sex, Sex) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

sex	Sex	Nobs
T	Total	273484
F	Females	269543
M	Males	269382

age

Code

lfst_r_lfur2gac %>%
  left_join(age, by = "age") %>%
  group_by(age, Age) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

age	Age	Nobs
Y15-74	From 15 to 74 years	165283
Y15-64	From 15 to 64 years	164821
Y20-64	From 20 to 64 years	164231
Y25-54	From 25 to 54 years	162323
Y55-64	From 55 to 64 years	155751

geo

Code

lfst_r_lfur2gac %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

time

Code

lfst_r_lfur2gac %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

20-64

Total

Code

lfst_r_lfur2gac %>%
  filter(c_birth == "TOTAL",
         sex == "T",
         age == "Y20-64",
         nchar(geo) == 4,
         time == "2019") %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -13.5, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::percent_format(accuracy = 1),
                       breaks = 0.01*seq(0, 100, 5),
                       values = c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Chômage")

Foreign

Code

lfst_r_lfur2gac %>%
  filter(c_birth == "FOR",
         sex == "T",
         age == "Y20-64",
         nchar(geo) == 4,
         time == "2018") %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -13.5, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::percent_format(accuracy = 1),
                       breaks = 0.01*seq(0, 100, 5),
                       values = c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Chômage (né étranger)")

25-54

Total

Code

lfst_r_lfur2gac %>%
  filter(c_birth == "TOTAL",
         sex == "T",
         age == "Y25-54",
         nchar(geo) == 4,
         time == "2019") %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -13.5, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::percent_format(accuracy = 1),
                       breaks = 0.01*seq(0, 100, 5),
                       values = c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Chômage")