Employment rates by sex, age and citizenship (%) - lfsq_ergan

Data - Eurostat

unit

Code
lfsq_ergan %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
unit Unit Nobs
PC Percentage 1846759

sex

Code
lfsq_ergan %>%
  left_join(sex, by = "sex") %>%
  group_by(sex, Sex) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
sex Sex Nobs
T Total 628938
F Females 608988
M Males 608833

age

Code
lfsq_ergan %>%
  left_join(age, by = "age") %>%
  group_by(age, Age) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

citizen

Code
lfsq_ergan %>%
  left_join(citizen, by = "citizen") %>%
  group_by(citizen, Citizen) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
citizen Citizen Nobs
TOTAL Total 359740
NAT Reporting country 333598
FOR Foreign country 324256
NEU27_2020_FOR Non-EU27 countries (from 2020) nor reporting country 317344
EU27_2020_FOR EU27 countries (from 2020) except reporting country 301058
NRP No response 109873
STLS Stateless 100890

geo

Code
lfsq_ergan %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

age

Code
lfsq_ergan %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional

France, Germany, Portugal

25-54, Men

Code
lfsq_ergan %>%
  filter(geo %in% c("FR", "DE", "PT", "EA19"),
         sex == "M",
         citizen == "TOTAL",
         age == "Y25-54") %>%
  quarter_to_date %>%
  left_join(geo, by = "geo") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 2),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.15, 0.55),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rate, 25-54, Women (%)")

25-54, Total

Code
lfsq_ergan %>%
  filter(geo %in% c("FR", "DE", "PT", "EA19"),
         sex == "T",
         citizen == "TOTAL",
         age == "Y25-54") %>%
  quarter_to_date %>%
  left_join(geo, by = "geo") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 2),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.15, 0.55),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rate, 25-54, Total (%)")

25-54, Female

Code
lfsq_ergan %>%
  filter(geo %in% c("FR", "DE", "PT", "EA19"),
         sex == "F",
         citizen == "TOTAL",
         age == "Y25-54") %>%
  quarter_to_date %>%
  left_join(geo, by = "geo") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 2),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.15, 0.55),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rate, 25-54, Female (%)")

France, Italy, Greece

25-54, Men

Code
lfsq_ergan %>%
  filter(geo %in% c("FR", "IT", "EL", "EA19"),
         sex == "M",
         citizen == "TOTAL",
         age == "Y25-54") %>%
  quarter_to_date %>%
  left_join(geo, by = "geo") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.15, 0.55),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rate, 25-54, Men (%)")

25-54, Total

Code
lfsq_ergan %>%
  filter(geo %in% c("FR", "IT", "EL", "EA19"),
         sex == "T",
         citizen == "TOTAL",
         age == "Y25-54") %>%
  quarter_to_date %>%
  left_join(geo, by = "geo") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.15, 0.55),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rate, 25-54, Total (%)")

25-54, Women

Code
lfsq_ergan %>%
  filter(geo %in% c("FR", "IT", "EL", "EA19"),
         sex == "F",
         citizen == "TOTAL",
         age == "Y25-54") %>%
  quarter_to_date %>%
  left_join(geo, by = "geo") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.15, 0.55),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rate, 25-54, Women (%)")