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

Data - Eurostat

Author

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	883742

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	175200
NAT	Reporting country	156671
FOR	Foreign country	154280
NEU27_2020_FOR	Non-EU27 countries (from 2020) nor reporting country	151824
EU27_2020_FOR	EU27 countries (from 2020) except reporting country	147860
NRP	No response	54133
STLS	Stateless	43774

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	299999
M	Males	292427
F	Females	291316

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	181475
Y15-64	From 15 to 64 years	180890
Y20-64	From 20 to 64 years	180463
Y25-54	From 25 to 54 years	178195
Y55-64	From 55 to 64 years	162719

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")