source | dataset | .html | .RData |
---|---|---|---|
wdi | NY.GDP.PCAP.CD | 2024-11-15 | 2024-11-17 |
GDP per capita (current USD)
Data - WDI
Info
Data on macro
source | dataset | .html | .RData |
---|---|---|---|
eurostat | nama_10_a10 | 2024-11-08 | 2024-10-08 |
eurostat | nama_10_a10_e | 2024-11-08 | 2024-11-09 |
eurostat | nama_10_gdp | 2024-11-08 | 2024-10-08 |
eurostat | nama_10_lp_ulc | 2024-11-08 | 2024-10-08 |
eurostat | namq_10_a10 | 2024-11-16 | 2024-11-16 |
eurostat | namq_10_a10_e | 2024-11-16 | 2024-11-16 |
eurostat | namq_10_gdp | 2024-11-05 | 2024-10-08 |
eurostat | namq_10_lp_ulc | 2024-11-05 | 2024-11-04 |
eurostat | namq_10_pc | 2024-11-05 | 2024-11-08 |
eurostat | nasa_10_nf_tr | 2024-11-05 | 2024-10-08 |
eurostat | nasq_10_nf_tr | 2024-11-05 | 2024-10-09 |
fred | gdp | 2024-11-09 | 2024-11-09 |
oecd | QNA | 2024-06-06 | 2024-11-16 |
oecd | SNA_TABLE1 | 2024-11-16 | 2024-11-16 |
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 | 2024-11-15 | 2024-11-17 |
wdi | NY.GDP.PCAP.KD | 2024-09-18 | 2024-09-18 |
wdi | NY.GDP.PCAP.PP.CD | 2024-11-17 | 2024-11-17 |
wdi | NY.GDP.PCAP.PP.KD | 2024-11-16 | 2024-11-16 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-17 |
Last
Code
%>%
NY.GDP.PCAP.CD group_by(year) %>%
summarise(Nobs = n()) %>%
arrange(desc(year)) %>%
head(1) %>%
print_table_conditional()
year | Nobs |
---|---|
2023 | 233 |
Nobs - Javascript
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
NY.GDP.PCAP.CD left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date filter(iso2c %in% c("XC", "US"),
>= as.Date("2008-01-01")) %>%
date 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
Code
%>%
NY.GDP.PCAP.CD left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date filter(iso2c %in% c("XC", "US"),
>= as.Date("2008-01-01")) %>%
date 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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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-
Code
%>%
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
Code
%>%
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-
Code
%>%
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
Code
<- geom_image(data = . %>%
add_5flags 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-
Code
%>%
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
Code
%>%
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-
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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
Code
%>%
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-
Code
%>%
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
Code
%>%
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))