GDP per capita (current USD)

Data - WDI

Info

source	dataset	.html	.RData
wdi	NY.GDP.PCAP.CD	2024-09-18	2024-10-15

Data on macro

source	dataset	.html	.RData
eurostat	nama_10_a10	2024-10-09	2024-10-08
eurostat	nama_10_a10_e	2024-10-09	2024-10-08
eurostat	nama_10_gdp	2024-10-09	2024-10-08
eurostat	nama_10_lp_ulc	2024-10-09	2024-10-08
eurostat	namq_10_a10	2024-10-09	2024-10-08
eurostat	namq_10_a10_e	2024-10-09	2024-10-08
eurostat	namq_10_gdp	2024-10-09	2024-10-08
eurostat	namq_10_lp_ulc	2024-10-09	2024-10-09
eurostat	namq_10_pc	2024-10-09	2024-10-08
eurostat	nasa_10_nf_tr	2024-10-09	2024-10-08
eurostat	nasq_10_nf_tr	2024-10-09	2024-10-09
fred	gdp	2024-08-29	2024-09-18
oecd	QNA	2024-06-06	2024-06-30
oecd	SNA_TABLE1	2024-09-15	2024-06-30
oecd	SNA_TABLE14A	2024-09-15	2024-06-30
oecd	SNA_TABLE2	2024-07-01	2024-04-11
oecd	SNA_TABLE6A	2024-07-01	2024-06-30
wdi	NE.RSB.GNFS.ZS	2024-09-18	2024-09-18
wdi	NY.GDP.MKTP.CD	2024-09-18	2024-09-26
wdi	NY.GDP.MKTP.PP.CD	2024-09-18	2024-09-18
wdi	NY.GDP.PCAP.CD	2024-09-18	2024-10-15
wdi	NY.GDP.PCAP.KD	2024-09-18	2024-09-18
wdi	NY.GDP.PCAP.PP.CD	2024-10-09	2024-10-15
wdi	NY.GDP.PCAP.PP.KD	2024-09-18	2024-09-18

LAST_COMPILE

LAST_COMPILE
2024-10-15

Last

NY.GDP.PCAP.CD %>%
  group_by(year) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(year)) %>%
  head(1) %>%
  print_table_conditional()

year	Nobs
2023	234

Nobs - Javascript

NY.GDP.PCAP.CD %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c, Iso2c) %>%
  mutate(value = round(value)) %>%
  summarise(Nobs = n(),
            `Year 1` = first(year),
            `GDP Per Capita 1` = first(value) %>% paste0("$ ", .),
            `Year 2` = last(year),
            `GDP Per Capita 2` = last(value) %>% paste0("$ ", .)) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Iso2c)),
         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 .}

Japan

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("JP")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + geom_line(aes(x = date, y = value)) +
  xlab("") + ylab("GDP per capita") + theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000, 200000),
                labels = dollar_format(acc = 1))

Ranking

All

NY.GDP.PCAP.CD %>%
  group_by(year) %>%
  arrange(-value) %>%
  mutate(rank = 1:n()) %>%
  filter(iso2c %in% c("CH", "FR", "DE", "IT")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = rank) %>%
  ggplot(.) + xlab("") + ylab("Rank") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1950, 2025, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_reverse(breaks = c(1, seq(5, 50,5)))

Euro Area vs. US

Base 100

NY.GDP.PCAP.CD %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(iso2c %in% c("XC", "US"),
         date >= as.Date("2008-01-01")) %>%
  group_by(iso2c) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "US", color2, color)) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(70, 200, 5)) + 
  xlab("") + ylab("PIB/habitant en $ (100 = 2008)")

Avec dollars

NY.GDP.PCAP.CD %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(iso2c %in% c("XC", "US"),
         date >= as.Date("2008-01-01")) %>%
  group_by(iso2c) %>%
  arrange(date) %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "US", color2, color)) %>%
  ungroup %>%
  mutate(dollar = value,
         value = 100*value/value[2]) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 200, 5)) + 
  xlab("") + ylab("PIB/habitant en $ (100 = Zone Euro, 2008)") + 
  geom_text_repel(data = . %>% filter(year(date) %in% seq(2008, 2022, 2)),
                                      aes(x = date, y = value, label = paste0("$", round(dollar, digits = -2), " /hab")))

Euro area vs. US vs. France

Linear

NY.GDP.PCAP.CD %>%
  # XC: Euro area
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Base 100 = 1960

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, 100 = 1960") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks =c(100, 200, 400, 800, 1000, 2000, 4000, 8000, 10000, 20000))

Base 100 = 1990

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  filter(date >= as.Date("1990-01-01")) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, 100 = 1990") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 400, 10))

Base 100 = 2006

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  filter(date >= as.Date("2006-01-01")) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, 100 = 2006") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 400, 5))

Base 100 = 2007

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  filter(date >= as.Date("2007-01-01")) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, 100 = 2007") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 400, 5))

Base 100 = 2008

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  filter(date >= as.Date("2008-01-01")) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, 100 = 2008") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 400, 5))

Switzerland, France, Germany, USA

1970-

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CH", "FR", "DE", "US")) %>%
  year_to_date %>%
  #filter(date >= as.Date("1970-01-01")) %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "FR", color2, color)) %>%
  arrange(date) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") + 
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1963, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

Switzerland, France, Germany, Italy, UK

All

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CH", "FR", "DE", "IT", "GB", "US")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "FR", color2, color)) %>%
  arrange(date) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") + 
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2020, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

1990-

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CH", "FR", "DE", "IT", "GB", "US")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "FR", color2, color)) %>%
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10000, 100000, 10000),
                labels = dollar_format(acc = 1))

Switzerland, France, Germany, Italy, UK

All

add_5flags <- geom_image(data = . %>%
                           group_by(date) %>%
                           filter(n() == 5) %>%
                           arrange(value) %>%
                           mutate(dist = min(value[2]-value[1],value[3]-value[2],value[4]-value[3],value[5]-value[4])) %>%
                           arrange(-dist, date) %>%
                           head(5) %>%
                           mutate(image = paste0("../../icon/flag/round/", str_to_lower(gsub(" ", "-", Iso2c)), ".png")),
                         aes(x = date, y = value, image = image), asp = 1.5, size = 0.02)
NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CH", "FR", "DE", "IT", "GB")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "FR", color2, color)) %>%
  arrange(date) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") + 
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1950, 2020, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

1990-

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CH", "FR", "DE", "IT", "GB")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "FR", color2, color)) %>%
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10000, 100000, 10000),
                labels = dollar_format(acc = 1))

Switzerland, France

All

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CH", "FR")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "FR", color2, color)) %>%
  
  arrange(date) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") + 
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2020, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

1990-

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CH", "FR")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10000, 100000, 10000),
                labels = dollar_format(acc = 1))

United States, Japan, China, Europe

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "JP", "CN", "EU")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

United States, Japan, China, Europe, France, Germany

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "JP", "CN", "EU", "FR", "DE")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

United States, Japan, China

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "JP", "CN")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

China, France, Germany

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("CN", "FR", "DE")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

Italy, Portugal, Spain

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("ES", "IT", "PT")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

Spain, United Kingdom, United States

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("US", "GB", "ES")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

Argentina, Chile, Venezuela

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("AR", "CL", "VE")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

United States, France, Greece

All

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("GR", "FR", "US")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))

2000-

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("GR", "FR", "US")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  filter(date >= as.Date("2000-01-01")) %>%
  mutate(color = ifelse(iso2c == "US", color2, color)) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(10000, 70000, 5000),
                labels = dollar_format(acc = 1))

Greece, Hong Kong, Mexico

NY.GDP.PCAP.CD %>%
  filter(iso2c %in% c("GR", "HK", "MX")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000),
                labels = dollar_format(acc = 1))