Unemployment rate - 3 year average - tipsun10

Data - Eurostat

Author

François Geerolf

Info

DOWNLOAD_TIME

Code 
tibble(DOWNLOAD_TIME = as.Date(file.info("~/iCloud/website/data/eurostat/tipsun10.RData")$mtime)) %>%
  print_table_conditional()
DOWNLOAD_TIME
2026-02-23

Last

Code 
tipsun10 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024 30

geo

All

Code 
tipsun10 %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Eurozone (19 countries)

Code 
tipsun10 %>%
  left_join(geo, by = "geo") %>%
  filter(Geo %in% c("Austria", "Belgium", "Cyprus", "Estonia", "Finland", "France", 
                    "Germany", "Greece", "Ireland", "Italy", "Latvia", "Lithuania", 
                    "Luxembourg", "Malta", "Netherlands", "Portugal", "Slovakia",
                    "Slovenia", "Spain")) %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Non Eurozone (8 countries)

Code 
tipsun10 %>%
  left_join(geo, by = "geo") %>%
  filter(Geo %in% c("Bulgaria", "Croatia", "Czechia", "Denmark", 
                    "Hungary", "Poland", "Romania", "Sweden")) %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

time

Code 
tipsun10 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
time Nobs
2005 1
2006 1
2007 2
2008 2
2009 2
2010 5
2011 30
2012 30
2013 30
2014 30
2015 30
2016 30
2017 30
2018 30
2019 30
2020 30
2021 30
2022 30
2023 30
2024 30

France, Germany, Italy, Spain, Portugal

Code 
tipsun10 %>%
  filter(geo %in% c("FR", "DE", "PT", "ES", "IT")) %>%
  year_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_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-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)) +
  geom_hline(yintercept = 0.1, linetype = "dashed")

France, Germany, Portugal

Code 
tipsun10 %>%
  filter(geo %in% c("FR", "DE", "PT")) %>%
  year_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, 2), "-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)) +
  geom_hline(yintercept = 0.1, linetype = "dashed")

Poland, Hungary, Slovenia

Code 
tipsun10 %>%
  filter(geo %in% c("PL", "HU", "SI")) %>%
  year_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, 2), "-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)) +
  geom_hline(yintercept = 0.1, linetype = "dashed")

Mean, Standard Deviation

All

Viridis

Code 
tipsun10 %>%
  year_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  group_by(date) %>%
  summarise(`Moyenne` = mean(values),
            `Ecart Type` = sd(values)) %>%
  transmute(date, `Moyenne`,
            `Moyenne + SD` = `Moyenne` + `Ecart Type`,
            `Moyenne - SD` = `Moyenne` - `Ecart Type`) %>%
  gather(variable, value, -date) %>%
  mutate(value = value/100) %>%
  ggplot + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_color_manual(values = c(viridis(3)[1], viridis(3)[2], viridis(3)[2])) +
  scale_linetype_manual(values = c("solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0.1, linetype = "dashed")

Colors

Code 
tipsun10 %>%
  year_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  group_by(date) %>%
  summarise(`Moyenne` = mean(values),
            `Ecart Type` = sd(values)) %>%
  transmute(date, `Moyenne`,
            `Moyenne + SD` = `Moyenne` + `Ecart Type`,
            `Moyenne - SD` = `Moyenne` - `Ecart Type`) %>%
  gather(variable, value, -date) %>%
  mutate(value = value/100) %>%
  ggplot + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_color_manual(values = c("#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0.1, linetype = "dashed")

With France

Code 
tipsun10 %>%
  year_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  group_by(date) %>%
  summarise(`Moyenne Europe` = mean(values),
            `Ecart Type` = sd(values),
            `France` = values[geo == "FR"]) %>%
  transmute(date, `Moyenne Europe`,
            `Moyenne Europe + SD` = `Moyenne Europe` + `Ecart Type`,
            `Moyenne Europe - SD` = `Moyenne Europe` - `Ecart Type`,
             `France`) %>%
  gather(variable, value, -date) %>%
  mutate(values = value/100,
         Geo = ifelse(variable == "France", "France", "Europe")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") + add_4flags +
  scale_color_manual(values = c("#ED2939", "#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0.1, linetype = "dashed")

With Germany

Code 
tipsun10 %>%
  year_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  group_by(date) %>%
  summarise(`Moyenne Europe` = mean(values),
            `Ecart Type` = sd(values),
            `France` = values[geo == "FR"],
            `Allemagne` = values[geo == "DE"]) %>%
  transmute(date, `Moyenne Europe`,
            `Moyenne Europe + SD` = `Moyenne Europe` + `Ecart Type`,
            `Moyenne Europe - SD` = `Moyenne Europe` - `Ecart Type`,
             `France`,
             `Allemagne`) %>%
  gather(variable, value, -date) %>%
  mutate(values = value/100,
         Geo = ifelse(variable == "France", "France", "Europe"),
         Geo = ifelse(variable == "Allemagne", "Germany", Geo)) %>%
  ggplot + geom_line(aes(x = date, y = values, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") + add_5flags +
  scale_color_manual(values = c("#000000", "#ED2939", "#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "solid", "solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.15, 0.85),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0.1, linetype = "dashed")