Unemployment rates by sex, age, citizenship and NUTS 2 regions - lfst_r_lfur2gan

Data - Eurostat

unit

Code
lfst_r_lfur2gan %>%
  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 852024

citizen

Code
lfst_r_lfur2gan %>%
  left_join(citizen, by = "citizen") %>%
  group_by(citizen, Citizen) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
citizen Citizen Nobs
TOTAL Total 168405
NAT Reporting country 151061
FOR Foreign country 148703
NEU27_2020_FOR Non-EU27 countries (from 2020) nor reporting country 146296
EU27_2020_FOR EU27 countries (from 2020) except reporting country 142540
NRP No response 52895
STLS Stateless 42124

sex

Code
lfst_r_lfur2gan %>%
  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 289250
M Males 281926
F Females 280848

age

Code
lfst_r_lfur2gan %>%
  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 175003
Y15-64 From 15 to 64 years 174425
Y20-64 From 20 to 64 years 174020
Y25-54 From 25 to 54 years 171833
Y55-64 From 55 to 64 years 156743

geo

Code
lfst_r_lfur2gan %>%
  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_lfur2gan %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Y15-74 - FOR - Foreign country

Code
lfst_r_lfur2gan %>%
  filter(unit == "PC",
         citizen == "FOR",
         sex == "T",
         age == "Y15-74",
         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(20, 100, 5),
                       values = c(0, 0.1, 0.3, 0.5, 0.7, 0.8, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Unemployment (%) \nForeign country")

Y15-64 - FOR - Foreign country

Code
lfst_r_lfur2gan %>%
  filter(unit == "PC",
         citizen == "FOR",
         sex == "T",
         age == "Y15-64",
         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(20, 100, 5),
                       values = c(0, 0.1, 0.3, 0.5, 0.7, 0.8, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Unemployment (%) \nForeign country")

NAT - National country

Code
lfst_r_lfur2gan %>%
  filter(unit == "PC",
         citizen == "NAT",
         sex == "T",
         age == "Y15-74",
         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, 0.3, 0.5, 0.7, 0.8, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Unemployment (%) \nNational country")