Unemployment by sex and age – monthly data

Data - Eurostat

Info

source dataset .html .RData
eurostat une_rt_m 2024-11-17 2024-11-17

LAST_COMPILE

LAST_COMPILE
2024-11-17

Last

Code
une_rt_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024M10 108

s_adj

Code
une_rt_m %>%
  left_join(s_adj, by = "s_adj") %>%
  group_by(s_adj, S_adj) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
s_adj S_adj Nobs
SA Seasonally adjusted data, not calendar adjusted data 243663
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 238356
TC Trend cycle data 222468

geo

Code
une_rt_m %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", 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 .}

unit

Code
une_rt_m %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
unit Unit Nobs
THS_PER Thousand persons 354963
PC_ACT Percentage of population in the labour force 349524

freq

Code
une_rt_m %>%
  left_join(freq, by = "freq") %>%
  group_by(freq, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
freq Freq Nobs
M Monthly 704487

sex

Code
une_rt_m %>%
  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 236643
F Females 233922
M Males 233922

age

Code
une_rt_m %>%
  left_join(age, by = "age") %>%
  group_by(age, Age) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
age Age Nobs
TOTAL Total 237018
Y25-74 From 25 to 74 years 233868
Y_LT25 Less than 25 years 233601

time

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

Young

France, Germany, Spain, Italy, Eurozone

All

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, Netherlands, Sweden

All

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "NL", "SE", "EA20"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

All age, All sex

France, Germany, Spain, Italy, Netherlands, Portugal, EA

All

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "NL", "PT", "EA20"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_7flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

2002-

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "NL", "PT", "EA20"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2002-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))+
  scale_color_identity() + add_7flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_text_repel(data = . %>%
                    filter(date == max(date)), aes(x = date, y = values, label = percent(values)))

2002-

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "NL", "PT", "EA20"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2002-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))+
  scale_color_identity() + add_6flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_label_repel(data = . %>%
                    filter(date == max(date)), aes(x = date, y = values, label = percent(values, acc = .1), color = color))

2007-

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "NL", "PT", "EA20"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2007-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))+
  scale_color_identity() + add_6flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Taux de chômage (% de la population active)") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1),
                     limits = c(0, 0.19)) +
  geom_text_repel(data = . %>%
                    filter(date == max(date)), aes(x = date, y = values, label = percent(values, acc = .1), color = color))

France, Germany, Spain, Italy, Eurozone

All

All age

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Youth

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Younth Unemployment, % of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

2010-

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Youth

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Younth Unemployment, % of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

2014-

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  filter(date >= as.Date("2014-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, Spain, Italy, Netherlands, Portugal

All

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "NL", "PT"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

1998-

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "NL", "PT"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  filter(date >= as.Date("1998-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 4), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

2014-

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "NL", "PT"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  filter(date >= as.Date("2014-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, Portugal

Code
une_rt_m %>%
  filter(geo %in% c("FR", "DE", "PT"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Germany, Euro Area

Code
une_rt_m %>%
  filter(geo %in% c("EA20", "EU15", "DE"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_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(4)[1:3]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.25),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Euro Area, France

All

Code
une_rt_m %>%
  filter(geo %in% c("EA20", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

1998-

Code
une_rt_m %>%
  filter(geo %in% c("EA20", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  filter(date >= as.Date("1998-01-01")) %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = as.Date(paste0(seq(1998, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

2010-

Code
une_rt_m %>%
  filter(geo %in% c("EA20", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, .5),
                     labels = scales::percent_format(accuracy = .1)) +
  geom_text_repel(data = . %>%
                    filter(date == max(date)), aes(x = date, y = values, label = percent(values), color = color))

Euro Area, Bulgaria

All

Code
une_rt_m %>%
  filter(geo %in% c("EA20", "BG"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

2010-

Code
une_rt_m %>%
  filter(geo %in% c("EA20", "BG"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  left_join(geo, by = "geo") %>%
  mutate(values = values/100,
         Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

By age

Euro Area

Code
une_rt_m %>%
  filter(geo %in% c("EA20"),
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(age, by = "age") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Age) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

France

Code
une_rt_m %>%
  filter(geo == "FR",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(age, by = "age") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Age) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Germany

Code
une_rt_m %>%
  filter(geo == "DE",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(age, by = "age") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Age) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

By sex

Euro Area

Code
une_rt_m %>%
  filter(geo %in% c("EA20"),
         age == "TOTAL",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(sex, by = "sex") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Sex) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

France

Code
une_rt_m %>%
  filter(geo == "FR",
         age == "TOTAL",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(sex, by = "sex") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Sex) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Germany

Code
une_rt_m %>%
  filter(geo == "DE",
         age == "TOTAL",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(sex, by = "sex") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Sex) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Italy

Code
une_rt_m %>%
  filter(geo == "IT",
         age == "TOTAL",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(sex, by = "sex") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Sex) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Greece

Code
une_rt_m %>%
  filter(geo == "EL",
         age == "TOTAL",
         unit == "PC_ACT",
         s_adj == "SA") %>%
  month_to_date %>%
  left_join(sex, by = "sex") %>%
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Sex) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Percentage of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))