Activity rates by sex, age, educational attainment level, citizenship and NUTS 2 regions - lfst_r_lfp2actrtn

Data - Eurostat

Author

citizen

Code

lfst_r_lfp2actrtn %>%
  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	592922
NAT	Reporting country	535401
FOR	Foreign country	493005
NEU27_2020_FOR	Non-EU27 countries (from 2020) nor reporting country	471755
EU27_2020_FOR	EU27 countries (from 2020) except reporting country	449218
NRP	No response	144194
STLS	Stateless	92341

isced11

Code

lfst_r_lfp2actrtn %>%
  left_join(isced11, by = "isced11") %>%
  group_by(isced11, Isced11) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

isced11	Isced11	Nobs
TOTAL	All ISCED 2011 levels	677021
ED3_4	Upper secondary and post-secondary non-tertiary education (levels 3 and 4)	637295
ED0-2	Less than primary, primary and lower secondary education (levels 0-2)	621080
ED5-8	Tertiary education (levels 5-8)	618930
NRP	No response	224450
UNK	Unknown	60

age

Code

lfst_r_lfp2actrtn %>%
  left_join(age, by = "age") %>%
  group_by(age, Age) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

age	Age	Nobs
Y15-64	From 15 to 64 years	736839
Y20-64	From 20 to 64 years	721146
Y25-54	From 25 to 54 years	706995
Y55-64	From 55 to 64 years	613856

sex

Code

lfst_r_lfp2actrtn %>%
  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	953991
F	Females	912432
M	Males	912413

unit

Code

lfst_r_lfp2actrtn %>%
  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	2778836

geo

Code

lfst_r_lfp2actrtn %>%
  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_lfp2actrtn %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Education Foreign: levels 0-2

Code

lfst_r_lfp2actrtn %>%
  filter(unit == "PC",
         sex == "T",
         isced11 == "ED0-2",
         citizen == "TOTAL",
         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, 10),
                       values = c(0, 0.1, 0.3, 0.4, 0.5, 0.6, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Activity \nPrimary Education (%)")

Upper secondary and post-secondary non-tertiary education (levels 3 and 4)

Education Foreign: levels 3-4

Code

lfst_r_lfp2actrtn %>%
  filter(unit == "PC",
         sex == "T",
         isced11 == "ED3_4",
         citizen == "TOTAL",
         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, 10),
                       values = c(0, 0.5, 0.6, 0.7, 0.8, 0.9, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Activity \nSecondary Education (%)")

Education Foreign: levels 5-8

Code

lfst_r_lfp2actrtn %>%
  filter(unit == "PC",
         sex == "T",
         isced11 == "ED5-8",
         citizen == "TOTAL",
         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, 10),
                       values = c(0, 0.5, 0.6, 0.7, 0.8, 0.9, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Activity \nTertiary Education (%)")