LFS by sex and age - indicators

Data - OECD

Author

Info

source	dataset	.html	.RData
oecd	LFS_SEXAGE_I_R	2024-09-11	2024-04-15

Data on employment

Code

load_data("employment.RData")
employment %>%
  arrange(-(dataset == "LFS_SEXAGE_I_R")) %>%
  source_dataset_file_updates()

source	dataset	.html	.RData
bls	jt	2024-05-01	NA
bls	la	2024-06-19	NA
bls	ln	2024-06-19	NA
eurostat	nama_10_a10_e	2024-09-14	2024-09-14
eurostat	nama_10_a64_e	2024-09-14	2024-09-14
eurostat	namq_10_a10_e	2024-09-14	2024-09-14
eurostat	une_rt_m	2024-09-15	2024-09-14
oecd	ALFS_EMP	2024-04-16	2024-05-12
oecd	EPL_T	2024-04-16	2023-12-10
oecd	LFS_SEXAGE_I_R	2024-09-11	2024-04-15
oecd	STLABOUR	2024-09-11	2024-06-30

Données sur l’emploi

source	dataset	.html	.RData
insee	CHOMAGE-TRIM-NATIONAL	2024-09-14	2024-09-14
insee	CNA-2014-EMPLOI	2024-06-07	2024-09-14
insee	DEMANDES-EMPLOIS-NATIONALES	2024-09-14	2024-09-14
insee	EMPLOI-BIT-TRIM	2024-06-07	2024-09-14
insee	EMPLOI-SALARIE-TRIM-NATIONAL	2024-09-14	2024-09-14
insee	TAUX-CHOMAGE	2024-09-14	2024-09-14
insee	TCRED-EMPLOI-SALARIE-TRIM	2024-09-14	2024-09-14

LAST_COMPILE

LAST_COMPILE
2024-09-15

Last

obsTime	Nobs
2022	12100

SEX

Code

LFS_SEXAGE_I_R %>%
  left_join(LFS_SEXAGE_I_R_var$SEX, by = "SEX") %>%
  group_by(SEX, Sex) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

SEX	Sex	Nobs
MW	All persons	153275
MEN	Men	152299
WOMEN	Women	150636

AGE

Code

LFS_SEXAGE_I_R %>%
  left_join(LFS_SEXAGE_I_R_var$AGE, by = "AGE") %>%
  group_by(AGE, Age) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

SERIES

Code

LFS_SEXAGE_I_R %>%
  left_join(LFS_SEXAGE_I_R_var$SERIES, by = "SERIES") %>%
  group_by(SERIES, Series) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

SERIES	Series	Nobs
LFPR	Labour force participation rate	156928
EPR	Employment/population ratio	156551
UR	Unemployment rate	142731

FREQUENCY

Code

LFS_SEXAGE_I_R %>%
  left_join(LFS_SEXAGE_I_R_var$FREQUENCY, by = "FREQUENCY") %>%
  group_by(FREQUENCY, Frequency) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

FREQUENCY	Frequency	Nobs
A	Annual	456210

COUNTRY

Code

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

obsTime

Code

LFS_SEXAGE_I_R %>%
  group_by(obsTime) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(obsTime)) %>%
  print_table_conditional()

Denmark, France, United States

25-54

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MW",
         COUNTRY %in% c("DNK", "USA", "FRA")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Location = Country, date, obsValue) %>%
  arrange(Location, date) %>%
  mutate(obsValue = obsValue/100) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color, linetype = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, 25-54") +
  add_3flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

25-64

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2564",
         SEX == "MW",
         COUNTRY %in% c("DNK", "USA", "FRA")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Location = Country, date, obsValue) %>%
  arrange(Location, date) %>%
  mutate(obsValue = obsValue/100) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color, linetype = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, 25-64") +
  add_3flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

20-64

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2064",
         SEX == "MW",
         COUNTRY %in% c("DNK", "USA", "FRA")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Location = Country, date, obsValue) %>%
  arrange(Location, date) %>%
  mutate(obsValue = obsValue/100) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color, linetype = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, 20-64") +
  add_3flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Unemployment Rate

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "UR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("DNK", "USA", "FRA")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Location = Country, date, obsValue) %>%
  arrange(Location, date) %>%
  mutate(obsValue = obsValue/100) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color, linetype = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Unemployment Rate") +
  add_3flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Germany, France, Italy, United States, Spain

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "900000",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "USA")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(COUNTRY, Location = Country, date, obsValue) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(obsValue = obsValue/100) %>%
  mutate(color = ifelse(COUNTRY == "USA", color2, color)) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, Total") +
  add_5flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1975-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "900000",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1975-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(COUNTRY, Location = Country, date, obsValue) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(COUNTRY == "USA", color2, color)) %>%
  mutate(obsValue = obsValue/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, Total") +
  add_5flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1995-

English

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "900000",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(COUNTRY, Location = Country, date, obsValue) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(COUNTRY == "USA", color2, color)) %>%
  mutate(obsValue = obsValue/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, Total") +
  add_5flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

French

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "900000",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(COUNTRY, Location = Country, date, obsValue) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(COUNTRY == "USA", color2, color)) %>%
  mutate(obsValue = obsValue/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Taux d'emploi") +
  add_5flags +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Germany, France, Italy, Greece, Spain

Total

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "900000",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "GRC")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Location = Country, date, obsValue) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(obsValue = obsValue/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, Total") +
  add_5flags +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

25-64

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "GRC")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#ED2939", "#000000", "#0D5EAF", "#009246", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, 25-64") +
  geom_image(data = . %>%
               filter(date == as.Date("2012-01-01")) %>%
               mutate(date = as.Date("2012-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

2000-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "GRC")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#ED2939", "#000000", "#0D5EAF", "#009246", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, 25-64") +
  geom_image(data = . %>%
               filter(date == as.Date("2012-01-01")) %>%
               mutate(date = as.Date("2012-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

15-64

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "GRC")) %>%
  year_to_date %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#ED2939", "#000000", "#0D5EAF", "#009246", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, 25-64") +
  geom_image(data = . %>%
               filter(date == as.Date("2012-01-01")) %>%
               mutate(date = as.Date("2012-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

2002-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  mutate(obsValue = obsValue/100) %>%
  rename(Location = Country) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location ==  "United States", color2, color)) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() +
  theme_minimal() + xlab("") + ylab("Employment / Population, 15-64") +
  add_5flags +
  scale_x_date(breaks = seq(1960, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Unemployment rate, 25-64

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "UR", 
         AGE == "2564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "GRC")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#ED2939", "#000000", "#0D5EAF", "#009246", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Unemployment Rate, 25-64") +
  geom_image(data = . %>%
               filter(date == as.Date("2014-01-01")) %>%
               mutate(date = as.Date("2014-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Unemployment rate, 15-24

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "UR", 
         AGE == "1524",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "GRC")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#ED2939", "#000000", "#0D5EAF", "#009246", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Unemployment Rate, 15-24") +
  geom_image(data = . %>%
               filter(date == as.Date("2013-01-01")) %>%
               mutate(date = as.Date("2013-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Employment / Population, Men, 25-54

Number of observations

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  group_by(COUNTRY, Country) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Country))),
         Flag = paste0('<img src="../../icon/flag/round/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Table: 1970, 1980, 1990, 2000, 2010

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         obsTime %in% c("1970", "1980", "1990", "2000", "2010")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(COUNTRY, Country, obsTime, obsValue) %>%
  mutate(obsValue = round(obsValue, 1)) %>%
  spread(obsTime, obsValue) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Country))),
         Flag = paste0('<img src="../../icon/flag/round/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Table: 2003, 2007, 2011, 2015, 2019

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         obsTime %in% c("2003", "2007", "2011", "2015", "2019")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(COUNTRY, Country, obsTime, obsValue) %>%
  mutate(obsValue = round(obsValue, 1)) %>%
  spread(obsTime, obsValue) %>%
  arrange(-`2019`) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Country))),
         Flag = paste0('<img src="../../icon/flag/round/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Germany, France, Italy, Greece, United States

1960-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA", "GRC", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", "#009246", "#B22234")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2013-01-01")) %>%
               mutate(image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

2000-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "ESP", "FRA", "GRC", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#0D5EAF", "#009246", "#FFC400", "#B22234")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2011-01-01")) %>%
               mutate(image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Germany, France, Italy, Greece, Spain

1960-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#ED2939", "#000000", "#0D5EAF", "#009246", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2012-01-01")) %>%
               mutate(date = as.Date("2012-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

2000-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA", "ESP", "GRC")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#ED2939", "#000000", "#0D5EAF", "#009246", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2012-01-01")) %>%
               mutate(date = as.Date("2012-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

G7, North America, OECD, Oceania

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("G7", "NAM", "OECD", "OCE")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#C60B1E", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2)) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Germany, France, Italy

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Europe, United States, United Kingdom

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("EUR", "GBR", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1980-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#FFCC00", "#CF142B", "#3C3B6E")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Europe, United States

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("EUR", "EU16", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#B22234")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.8)) +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Germany, France, Italy, United States

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#B22234")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Finland, Sweden, United States

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("USA", "FIN", "SWE")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#003580", "#FECC00", "#B22234")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Australia, Germany, Japan

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("AUS", "JPN", "DEU")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#00008B", "#000000", "#BC002D")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Italy, Netherlands, Spain

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "NLD", "ESP")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#009246", "#21468B", "#C60B1E")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Norway, Portugal

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("FRA", "NOR", "PRT")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#EF2B2D", "#006600")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Belgium, Canada, Ireland, Korea

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "MEN",
         COUNTRY %in% c("BEL", "CAN", "IRL", "KOR")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#000000", "#FF0000", "#FF883E", "#013478")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Europe, United States, United Kingdom

Employment Rate, 25-64, Men

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2564",
         SEX == "MEN",
         COUNTRY %in% c("EUR", "GBR", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1980-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#FFCC00", "#CF142B", "#3C3B6E")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Employment Rate, 25-64, Men and Women

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2564",
         SEX == "MW",
         COUNTRY %in% c("EUR", "GBR", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1980-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#FFCC00", "#CF142B", "#3C3B6E")) +
  theme_minimal() + xlab("") + ylab("Employment / Population, Men, 25-54") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Unemployment Rate, 25-64, Men and Women

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "UR", 
         AGE == "2564",
         SEX == "MW",
         COUNTRY %in% c("EUR", "GBR", "USA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1980-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#FFCC00", "#CF142B", "#3C3B6E")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("1997-01-01")) %>%
               mutate(date = as.Date("1997-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

United States, Greece, Italy

Employment / Population ratio

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("USA", "GRC", "ITA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#0D5EAF", "#006600", "#C60B1E")) +
  theme_minimal() + xlab("") + ylab("Employment / Population") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Greece, Portugal, Spain

Employment / Population ratio

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("GRC", "PRT", "ESP")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#0D5EAF", "#006600", "#C60B1E")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Men

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MEN",
         COUNTRY %in% c("GRC", "PRT", "ESP")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#0D5EAF", "#006600", "#C60B1E")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Women

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "WOMEN",
         COUNTRY %in% c("GRC", "PRT", "ESP")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#0D5EAF", "#006600", "#C60B1E")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Unemployment Rate

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "UR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("GRC", "PRT", "ESP")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#0D5EAF", "#006600", "#C60B1E")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Labour force participation rate - LFPR

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "LFPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("GRC", "PRT", "ESP")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#0D5EAF", "#006600", "#C60B1E")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Germany, France, Italy

Employment / Population ratio

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Men

15-64

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

25-64

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2564",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Women

15-64

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "WOMEN",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

25-64

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2564",
         SEX == "WOMEN",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

25-54

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "2554",
         SEX == "WOMEN",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Unemployment Rate

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "UR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Labour force participation rate - LFPR

All

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "LFPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Men

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "LFPR", 
         AGE == "1564",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

Italy, Germany, Greece, Spain, Portugal, France

EP - All

FLAGS

2000-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1990-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1980-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1980-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1970-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1970-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1960-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1960-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2021-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

FLAGS & legends

2000-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1990-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1980-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MW",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1980-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

EP - Men

FLAGS

2000-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Employment / Population (Men, 15-64)") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1990-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("Employment / Population (Men, 15-64)") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

1980-

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "MEN",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("1980-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  select(Country, date, obsValue) %>%
  arrange(Country, date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#0D5EAF", 
                                "#CE2B37", "#006600", "#FFC400")) +
  theme_minimal() + xlab("") + ylab("") +
  geom_image(data = . %>%
               filter(date == as.Date("2019-01-01")) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/round/", str_to_lower(Country), ".png")),
             aes(x = date, y = obsValue/100, image = image), asp = 1.5) +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

EP - Women

Code

LFS_SEXAGE_I_R %>%
  filter(SERIES == "EPR", 
         AGE == "1564",
         SEX == "WOMEN",
         COUNTRY %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  arrange(date) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue/100, color = Country, linetype = Country)) + 
  scale_color_manual(values = viridis(7)[1:6]) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.2),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 5),
                     labels = scales::percent_format(accuracy = 1))

France and Germany

LFP 25-54

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "2554", 
         SEX == "MW", 
         COUNTRY %in% c("DEU", "FRA"),
         SERIES == "LFPR") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Country)) +
  scale_color_manual(values = c("#ED2939", "#000000")) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 90, 1),
                     labels = percent_format(accuracy = 1)) +
  ylab("Labor Force Participation Rate (25-54)") + xlab("")

LFP 15-64

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "1564", 
         SEX == "MW", 
         COUNTRY %in% c("DEU", "FRA"),
         SERIES == "LFPR") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Country)) +
     scale_color_manual(values = c("#ED2939", "#000000")) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 90, 1),
                     labels = percent_format(accuracy = 1)) +
  ylab("Labor Force Participation Rate (15-64)") + xlab("")

LFP 65+

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "6599", 
         SEX == "MW", 
         COUNTRY %in% c("DEU", "FRA"),
         SERIES == "LFPR") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Country, linetype = Country)) +
     scale_color_manual(values = c("#ED2939", "#000000")) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 90, 1),
                     labels = percent_format(accuracy = 1)) +
  ylab("Labor Force Participation Rate (65+)") + xlab("")

LFP 65-69

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "6569", 
         SEX == "MW", 
         COUNTRY %in% c("DEU", "FRA"),
         SERIES == "LFPR") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Country, linetype = Country)) +
     scale_color_manual(values = c("#ED2939", "#000000")) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 90, 1),
                     labels = percent_format(accuracy = 1)) +
  ylab("Labor Force Participation Rate (65-69)") + xlab("")

EP 65-69

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "6569", 
         SEX == "MW", 
         COUNTRY %in% c("DEU", "FRA"),
         SERIES == "EPR") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Country, linetype = Country)) +
     scale_color_manual(values = c("#ED2939", "#000000")) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 90, 1),
                     labels = percent_format(accuracy = 1)) +
  ylab("Employment/Population Ratio (65-69)") + xlab("")

EP 25-54

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "2554", 
         SEX == "MW", 
         COUNTRY %in% c("DEU", "FRA"),
         SERIES == "EPR") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Country)) +
     scale_color_manual(values = c("#ED2939", "#000000")) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 90, 1),
                     labels = percent_format(accuracy = 1)) +
  ylab("Employment / Population Ratio (25-54)") + xlab("")

LFP, 25-54, Women

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "2554", 
         SEX == "WOMEN", 
         COUNTRY %in% c("DEU", "FRA"),
         SERIES == "LFPR") %>%
  left_join(LFS_SEXAGE_I_R_var$COUNTRY, by = "COUNTRY") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Country)) +
     scale_color_manual(values = c("#ED2939", "#000000")) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 90, 1),
                     labels = percent_format(accuracy = 1)) +
  ylab("Labor Force Participation Rate (25-54)") + xlab("")

Germany (Men, Women, All)

Code

LFS_SEXAGE_I_R %>%
  filter(AGE == "2554", 
         SEX %in% c("MW", "MEN", "WOMEN"), 
         COUNTRY %in% c("DEU"),
         SERIES == "EPR") %>%
  left_join(LFS_SEXAGE_I_R_var$SEX, by = "SEX") %>%
  year_to_date %>%
  mutate(obsValue = obsValue/100) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Sex)) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920,   2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.2),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(10, 100, 5),
                     labels = percent_format(accuracy = 1)) +
  ylab("Employment / Population Ratio (25-54)") + xlab("")