Unemployment by sex and age – monthly data - une_rt_m

Name: Unemployment by sex and age – monthly data
Creator: François Geerolf
License: https://creativecommons.org/licenses/by/4.0/

Data - Eurostat

Author

François Geerolf

Structure

Young

France, Germany, Spain, Italy, Eurozone

All

Code

une_rt_m |>
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA21"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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", "EA21"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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", "EA21"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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", "EA21"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  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_flags +
  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", "EA21"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  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_flags +
  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", "EA21"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  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_flags +
  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", "EA21"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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", "EA21"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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", "EA21"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  add_flag_color("Geo") |>
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "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_flags +
  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", "EA21"),
         age == "Y_LT25",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  filter(date >= as.Date("2010-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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", "EA21"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  add_flag_color("Geo") |>
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "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_flags +
  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() |>
  
  add_flag_color("Geo") |>
  mutate(values = values/100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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() |>
  
  add_flag_color("Geo") |>
  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_flags +
  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() |>
  
  add_flag_color("Geo") |>
  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_flags +
  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() |>
  
  add_flag_color("Geo") |>
  mutate(values = values/100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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("EA21", "EU15", "DE"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line() + theme_minimal()  +
  aes(x = date, y = values, color = color) +
  scale_color_identity() + add_flags +
  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))

Spain, France

1998-

Code

une_rt_m |>
  filter(geo %in% c("ES", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("1998-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1998, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, % of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_label(data = . %>%
                    filter(date == max(date)), aes(x = date, y = values, label = percent(values), color = color))

2010-

Code

une_rt_m |>
  filter(geo %in% c("ES", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("2010-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  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))

2017-

Code

une_rt_m |>
  filter(geo %in% c("ES", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("2017-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Unemployment, % of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     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, France

All

Code

une_rt_m |>
  filter(geo %in% c("EA21", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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("EA21", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("1998-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1998, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, % of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_label(data = . %>%
                    filter(date == max(date)), aes(x = date, y = values, label = percent(values), color = color))

2010-

Code

une_rt_m |>
  filter(geo %in% c("EA21", "FR"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("2010-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  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, France, Spain

All

Code

une_rt_m |>
  filter(geo %in% c("EA21", "FR", "ES"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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("EA21", "FR", "ES"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("1998-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1998, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  xlab("") + ylab("Unemployment, % of active population") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_label(data = . %>%
                    filter(date == max(date)), aes(x = date, y = values, label = percent(values), color = color))

2010-

Code

une_rt_m |>
  filter(geo %in% c("EA21", "FR","ES"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("2010-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  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))

2017-

Code

une_rt_m |>
  filter(geo %in% c("EA21", "FR","ES"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("2017-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Unemployment, % 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("EA21", "BG"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  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("EA21", "BG"),
         age == "TOTAL",
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  filter(date >= as.Date("2010-01-01")) |>
  
  mutate(values = values/100,
         Geo = ifelse(geo == "EA21", "Europe", Geo)) |>
  add_flag_color("Geo") |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  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("EA21"),
         sex == "T",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  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() |>
  
  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() |>
  
  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("EA21"),
         age == "TOTAL",
         unit == "PC_ACT",
         s_adj == "SA") |>
  month_to_date() |>
  
  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() |>
  
  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() |>
  
  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() |>
  
  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() |>
  
  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))

Euro-area slack

Euro area unemployment rate since 1998

Code

une_rt_m |>
  filter(geo == "EA21", age == "TOTAL", sex == "T",
         unit == "PC_ACT", s_adj == "SA") |>
  month_to_date() |>
  filter(!is.na(values)) |>
  mutate(values = values / 100) |>
  ggplot() + theme_minimal() + xlab("") +
  ylab("Euro area unemployment rate") +
  geom_hline(yintercept = 0.072, linetype = "dashed") +
  geom_line(aes(x = date, y = values)) +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 3), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01 * seq(0, 20, 1),
                     labels = scales::percent_format(accuracy = 1))

Euro area and big four since 2002

Code

une_rt_m |>
  filter(geo %in% c("EA21", "FR", "DE", "IT", "ES"),
         age == "TOTAL", sex == "T", unit == "PC_ACT", s_adj == "SA") |>
  month_to_date() |>
  filter(!is.na(values), date >= as.Date("2002-01-01")) |>
  mutate(Geo = ifelse(geo == "EA21", "Europe", Geo),
         Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  add_flag_color("Geo") |>
  mutate(values = values / 100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) +
  theme_minimal() + scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 3), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Unemployment rate (% of active population)") +
  scale_y_continuous(breaks = 0.01 * seq(0, 30, 5),
                     labels = scales::percent_format(accuracy = 1))

Related Data

Indicateurs et chiffres clés de l’emploi

source	dataset	Title	Updated
eurostat	lfsa_ergaed	Employment rates by sex, age and educational attainment level (%) - lfsa_ergaed	2026-09-11
eurostat	lfsq_ergaed	Employment rates by sex, age and educational attainment level (%) - lfsq_ergaed	2026-09-11
eurostat	une_rt_m	Unemployment by sex and age – monthly data - une_rt_m	2026-09-17
insee	CHOMAGE-TRIM-NATIONAL	Chômage, taux de chômage par sexe et âge (sens BIT) (1975-) - CHOMAGE-TRIM-NATIONAL	2026-09-20
insee	DEMANDES-EMPLOIS-NATIONALES	Demandeurs d’emploi inscrits à Pôle Emploi - DEMANDES-EMPLOIS-NATIONALES	2026-09-20
insee	EMPLOI-BIT-TRIM	Emploi, activité, sous-emploi par secteur d’activité (sens BIT) - EMPLOI-BIT-TRIM	2026-09-20
insee	EMPLOI-SALARIE-TRIM-NATIONAL	Estimations d’emploi salarié par secteur d’activité - EMPLOI-SALARIE-TRIM-NATIONAL	2026-09-20
insee	TAUX-CHOMAGE	Taux de chômage localisé - TAUX-CHOMAGE	2026-09-20

Employment Data Analysis

source	dataset	Title	Updated
eurostat	une_rt_m	Unemployment by sex and age – monthly data - une_rt_m	2026-09-17
oecd	FTPT_COMMON_INC	Incidence of full-time and part-time employment based on OECD-harmonized definition - FTPT_COMMON_INC	2026-09-18
oecd	STLABOUR	Short-Term Labour Market Statistics - STLABOUR	2026-08-02

Is there slack in the Euro area?

source	dataset	Title	Updated
ameco	AVGDGP	Gap between actual and potential gross domestic product at 2015 reference levels - AVGDGP	2026-08-02
ameco	ZNAWRU	Non-accelerating wage rate of unemployment - ZNAWRU	2026-08-02
ecb	BLS	Bank Lending Survey Statistics - BLS	2026-09-20
eurostat	edat_lfse_18	Participation rate of young persons in education and training by labour status (incl. NEET rates) - edat_lfse_18	2026-09-11
eurostat	ei_bsin_m_r2	Business surveys - NACE Rev. 2 activity - Industry - monthly data - ei_bsin_m_r2	2026-09-09
eurostat	lfsa_urgaed	Unemployment rates by sex, age and educational attainment level (%) - lfsa_urgaed	2026-09-11
eurostat	lfsi_sla_q	Labour market transitions - quarterly data - lfsi_sla_q	2026-09-11
eurostat	migr_emi2	Emigration by age and sex - migr_emi2	2026-09-09
eurostat	tipslm80	Youth unemployment rate - % of active population aged 15-24 - tipslm80	2026-09-11
eurostat	une_rt_m	Unemployment by sex and age – monthly data - une_rt_m	2026-09-17
oecd	EO_GAP	Output gap as a percentage of potential GDP - GAP - EO - EO_GAP	2026-08-02
oecd	INVPT_I	Incidence of involuntary part time workers - INVPT_I	2026-08-02
oecd	QNA_EXPENDITURE_CAPITA	Quarterly National Accounts, GDP Per Capita - QNA_EXPENDITURE_CAPITA	2026-09-20

Indicateurs Macroéconomiques France

source	dataset	Title	Updated
bdf	BPM6	Balance des paiements - 6ème manuel - BPM6	2026-09-20
bdf	CFT	Comptes Financiers Trimestriels - CFT	2026-08-10
eurostat	lfsq_ergaed	Employment rates by sex, age and educational attainment level (%) - lfsq_ergaed	2026-09-11
eurostat	une_rt_m	Unemployment by sex and age – monthly data - une_rt_m	2026-09-17
insee	CHOMAGE-TRIM-NATIONAL	Chômage, taux de chômage par sexe et âge (sens BIT) (1975-) - CHOMAGE-TRIM-NATIONAL	2026-09-20
insee	CNA-2014-FBCF-SI	Formation brute de capital fixe (FBCF) par secteur institutionnel - CNA-2014-FBCF-SI	2026-09-20
insee	CNT-2020-CB	Comptes des branches - CNT-2020-CB	2026-09-20
insee	CNT-2020-CSI	Comptes de secteurs institutionnels - CNT-2020-CSI	2026-09-20
insee	CNT-2020-OPERATIONS	Opérations sur biens et services - CNT-2020-OPERATIONS	2026-09-20
insee	CNT-2020-PIB-EQB-RF	Équilibre du produit intérieur brut - CNT-2020-PIB-EQB-RF	2026-09-20
insee	CONSO-MENAGES-2014	Consommation des ménages en biens - CONSO-MENAGES-2014	2026-09-20
insee	CONSO-MENAGES-2020	Consommation des ménages en biens - CONSO-MENAGES-2020	2026-09-20
insee	DEMANDES-EMPLOIS-NATIONALES	Demandeurs d’emploi inscrits à Pôle Emploi - DEMANDES-EMPLOIS-NATIONALES	2026-09-20
insee	EMPLOI-SALARIE-TRIM-NATIONAL	Estimations d’emploi salarié par secteur d’activité - EMPLOI-SALARIE-TRIM-NATIONAL	2026-09-20
insee	ICA-2015-IND-CONS	Indices de chiffre d’affaires dans l’industrie et la construction - ICA-2015-IND-CONS	2026-09-20
insee	conso-mensuelle	Consommation de biens, données mensuelles - conso-mensuelle	2026-08-02
insee	econ-gen-solde-ech-ext-2	Solde des échanges extérieurs et principales composantes - econ-gen-solde-ech-ext-2	2026-08-02
insee	t_conso_vol	Dépenses de consommation des ménages - volumes aux prix de l’année précédente chaînés (données CVS-CJO), base 2014 - t_conso_vol	2026-09-03
insee	t_recapAgent_val	Récapitulatif des séries des comptes d’agents - t_recapAgent_val	2026-09-03
insee	t_zonexp_val	Exportations - Par zone - valeurs aux prix courants - t_zonexp_val	2026-09-03
wdi	NY.GDP.PCAP.PP.CD	GDP per capita, PPP (current international D) - NY.GDP.PCAP.PP.CD	2026-09-20
wdi	NY.GDP.PCAP.PP.KD	GDP per capita, PPP (constant 2011 international D) - NY.GDP.PCAP.PP.KD	2026-09-20

Insights into Unemployment Rates

source	dataset	Title	Updated
eurostat	une_rt_m	Unemployment by sex and age – monthly data - une_rt_m	2026-09-17
oecd	STLABOUR	Short-Term Labour Market Statistics - STLABOUR	2026-08-02