source | dataset | .html | .RData |
---|---|---|---|
2024-09-15 | 2024-09-18 |
GDP per capita, PPP (constant 2011 international D)
Data - WDI
Info
Data on macro
source | dataset | .html | .RData |
---|---|---|---|
2024-09-15 | 2024-09-15 | ||
2024-09-15 | 2024-09-18 | ||
2024-09-15 | 2024-09-15 | ||
2024-09-15 | 2024-09-15 | ||
2024-09-15 | 2024-09-18 | ||
2024-09-15 | 2024-09-15 | ||
2024-09-04 | 2024-09-15 | ||
2024-09-15 | 2024-09-15 | ||
2024-08-21 | 2024-09-15 | ||
2024-09-15 | 2024-09-15 | ||
2024-09-02 | 2024-09-02 | ||
2024-08-29 | 2024-09-18 | ||
2024-06-06 | 2024-06-30 | ||
2024-09-15 | 2024-06-30 | ||
2024-09-15 | 2024-06-30 | ||
2024-07-01 | 2024-04-11 | ||
2024-07-01 | 2024-06-30 | ||
2024-09-18 | 2024-09-18 | ||
2024-09-18 | 2024-09-18 | ||
2024-09-18 | 2024-09-18 | ||
2024-09-18 | 2024-09-18 | ||
2024-09-18 | 2024-09-18 | ||
2024-09-18 | 2024-09-18 | ||
2024-09-15 | 2024-09-18 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-09-18 |
Last
Code
%>%
NY.GDP.PCAP.PP.KD group_by(year) %>%
summarise(Nobs = n()) %>%
arrange(desc(year)) %>%
head(1) %>%
print_table_conditional()
year | Nobs |
---|---|
2023 | 233 |
Nobs - Javascript
Code
%>%
NY.GDP.PCAP.PP.KD 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 .} {
1990, 2019, growth 1990-2019
Code
%>%
NY.GDP.PCAP.PP.KD filter(year %in% c(1990, 2019)) %>%
left_join(iso2c, by = "iso2c") %>%
spread(year, value) %>%
mutate(growth = round(100*(`2019`/`1990`-1),1)) %>%
mutate(`1990` = round(`1990`),
`2019` = round(`2019`)) %>%
arrange(-growth) %>%
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 .} {
Euro Area vs. US
Base 100
Code
%>%
NY.GDP.PCAP.PP.KD 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.PP.KD 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("$", round(dollar, digits = -2), " /hab")))
Germany, France
All
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("DE", "FR")) %>%
%>%
year_to_date left_join(iso2c, by = "iso2c") %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_2flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(10000, 70000, 10000), seq(10000, 60000, 5000)),
labels = dollar_format(acc = 1))
GDP Per capita - PPP VS current (USD)
Log
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("DE", "FR")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = gsub("Germany", "Allemagne", Iso2c),
variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date filter(date >= as.Date("1990-01-01")) %>%
ggplot(.) + xlab("") + ylab("PIB Par habitant ($ constants)") + theme_minimal() + add_4flags +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#000000", "#ED2939", "#000000", "#ED2939")) +
scale_linetype_manual(values = c("solid", "solid", "dashed", "dashed")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 200000, 2000),
labels = dollar_format(a = 1))
Linear
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("DE", "FR")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = gsub("Germany", "Allemagne", Iso2c),
variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#000000", "#ED2939", "#000000", "#ED2939")) +
scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = seq(1950, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 200000, 2000),
labels = dollar_format(a = 1))
Switzerland, France
All
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("CH", "FR")) %>%
%>%
year_to_date left_join(iso2c, by = "iso2c") %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_2flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(10000, 70000, 10000), seq(10000, 50000, 5000)),
labels = dollar_format(acc = 1))
GDP Per capita - PPP VS current (USD)
Log
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("CH", "FR")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = gsub("Switzerland", "Suisse", Iso2c),
variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#002395", "#FF0000", "#002395", "#FF0000")) +
scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 200000, 5000),
labels = dollar_format(a = 1))
Linear
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("CH", "FR")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = gsub("Switzerland", "Suisse", Iso2c),
variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#002395", "#FF0000", "#002395", "#FF0000")) +
scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = seq(1950, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 200000, 5000),
labels = dollar_format(a = 1))
Euro area vs. US
Base 100 = 1999
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "XC")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
%>%
year_to_date filter(date >= as.Date("1999-01-01")) %>%
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, PPP, 100 = 1999") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_2flags +
scale_x_date(breaks = c(seq(1999, 2100, 5), seq(2002, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(100, 400, 5))
GDP Per capita - PPP VS current (USD)
All
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("US", "XC")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
== "XC" ~ "Zone euro"),
iso2c variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 200000, 5000),
labels = dollar_format(a = 1))
1990-
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("US", "XC")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
== "XC" ~ "Zone euro"),
iso2c variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date filter(date >= as.Date("1990-01-01")) %>%
ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 200000, 5000),
labels = dollar_format(a = 1))
1999-
Value
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("US", "XC")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
== "XC" ~ "Zone euro"),
iso2c variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date filter(date >= as.Date("1999-01-01")) %>%
ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = c(seq(1999, 2100, 5), seq(2002, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 200000, 5000),
labels = dollar_format(a = 1))
Base = 100
Code
%>%
NY.GDP.PCAP.PP.KD bind_rows(NY.GDP.PCAP.KD) %>%
filter(iso2c %in% c("US", "XC")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
== "XC" ~ "Zone euro"),
iso2c variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
== "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
variable %>%
year_to_date filter(date >= as.Date("1999-01-01")) %>%
group_by(variable2) %>%
arrange(date) %>%
mutate(value = 100*value/value[1]) %>%
ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() +
geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) +
scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.85)) +
scale_x_date(breaks = c(seq(1999, 2100, 5), seq(2002, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(100, 300, 10))
Euro area vs. US vs. France
Linear
Code
%>%
NY.GDP.PCAP.PP.KD # 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, PPP") +
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 = 1990
Code
%>%
NY.GDP.PCAP.PP.KD 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, PPP, 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, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(100, 400, 10))
Base 100 = 2006
Code
%>%
NY.GDP.PCAP.PP.KD 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, PPP, 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, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(10, 400, 2))
Base 100 = 2007
Code
%>%
NY.GDP.PCAP.PP.KD 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, PPP, 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, 2))
Base 100 = 2008
Code
%>%
NY.GDP.PCAP.PP.KD 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, PPP, 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, 2))
Italy, France, US, Switzerland, Spain, US
Linear
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "ES", "IT", "FR", "CH", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_6flags +
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))
Log
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "ES", "IT", "FR", "CH", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_6flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 80000, 5000),
labels = dollar_format(acc = 1))
Base 100 = 1990
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "ES", "IT", "FR", "CH", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date group_by(iso2c, Iso2c) %>%
arrange(date) %>%
mutate(value = 100*value/value[1]) %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP, 100 = 1990") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_6flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(100, 400, 10))
Italy, France, US, UK, Switzerland, Spain - Compare
Linear
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "GB", "ES", "IT", "FR", "CH")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_6flags +
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))
Log
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "GB", "ES", "IT", "FR", "CH")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_6flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 80000, 5000),
labels = dollar_format(acc = 1))
Poland, Portugal, Spain
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("PL", "HU", "FR")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date group_by(iso2c) %>%
mutate(value = 100*value /value[date == as.Date("1991-01-01")]) %>%
filter(date >= as.Date("1990-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = Iso2c)) +
xlab("") + ylab("GDP per capita (constant 2010 USD)") + theme_minimal() +
scale_color_manual(values = c("#002395", "#436F4D", "#DC143C")) + add_3flags +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.8)) +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 400, 10))
Japan
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("JP")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date 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, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 200000, 1000),
labels = dollar_format(a = 1))
France, Germany
Linear
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("FR", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_2flags +
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))
Log
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("FR", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_2flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 80000, 2000),
labels = dollar_format(acc = 1))
Index = 100
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("FR", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
group_by(iso2c) %>%
mutate(value = 100*value/value[year == 1990]) %>%
%>%
year_to_date ggplot(.) + xlab("") + ylab("PPP GDP per capita (1990 = 100)") + theme_minimal() +
geom_line(aes(x = date, y = value, color = Iso2c)) +
scale_color_manual(values = c("#002395", "#000000")) + add_2flags +
theme(legend.position = "none") +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(100, 200, 5))
China, France, Germany
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("CN", "FR", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
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))
Italy, Portugal, Spain
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("ES", "IT", "PT")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
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))
Spain, United Kingdom, United States
Linear
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "GB", "ES")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
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))
Log
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("US", "GB", "ES")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
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 = seq(0, 80000, 5000),
labels = dollar_format(acc = 1))
Argentina, Chile, Venezuela
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("AR", "CL", "VE")) %>%
left_join(iso2c, by = "iso2c") %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
geom_line(aes(x = date, y = value, color = color)) +
theme_minimal() + scale_color_identity() + add_2flags +
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))
Greece, Hong Kong, Mexico
Linear
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("GR", "HK", "MX")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c = ifelse(iso2c == "HK", "Hong Kong", Iso2c)) %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
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))
Log
Code
%>%
NY.GDP.PCAP.PP.KD filter(iso2c %in% c("GR", "HK", "MX")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c = ifelse(iso2c == "HK", "Hong Kong", Iso2c)) %>%
%>%
year_to_date left_join(colors, by = c("Iso2c" = "country")) %>%
ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
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 = seq(0, 80000, 5000),
labels = dollar_format(acc = 1))