GDP per capita in PPS
Data - Eurostat
Info
LAST_DOWNLOAD
Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/tec00114.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2024-10-09 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2024-11-22 |
Last
Code
tec00114 %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2023 | 42 |
Info
- Volume indices of real expenditure per capita (in PPS_EU27_2020=100)
na_item
Code
tec00114 %>%
left_join(na_item, by = "na_item") %>%
group_by(na_item, Na_item) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| na_item | Na_item | Nobs |
|---|---|---|
| VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 504 |
time
Code
tec00114 %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2023 | 42 |
| 2022 | 42 |
| 2021 | 42 |
| 2020 | 42 |
| 2019 | 42 |
| 2018 | 42 |
| 2017 | 42 |
| 2016 | 42 |
| 2015 | 42 |
| 2014 | 42 |
| 2013 | 42 |
| 2012 | 42 |
geo
Code
tec00114 %>%
left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}Germany, France, Italy
Code
tec00114 %>%
filter(geo %in% c("FR", "DE", "IT", "ES")) %>%
select(time, na_item, geo, values) %>%
year_to_date %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
scale_color_identity() + add_4flags +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.85),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(0, 200, 2))
Poland, Hungary, Greece
Code
tec00114 %>%
filter(geo %in% c("EL", "PL", "HU")) %>%
select(time, na_item, geo, values) %>%
year_to_date %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("PIB/hab., Parité de Pouvoir d'Achat (EU-27 2020 = 100)") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.85),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(0, 200, 2))
Poland, Hungary, Greece, Germany, France, Italy, Spain, Netherlands
Code
tec00114 %>%
filter(geo %in% c("EL", "PL", "HU", "FR", "DE", "IT", "ES", "NL")) %>%
select(time, na_item, geo, values) %>%
year_to_date %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
scale_color_identity() + add_8flags +
theme_minimal() + xlab("") + ylab("PIB/hab., Parité de Pouvoir d'Achat (EU-27 2020 = 100)") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 5)) +
geom_hline(yintercept = 100, linetype = "dashed")
Poland, Greece, Germany, France, Italy, Spain
Code
load_data("eurostat/geo_fr.RData")
geo_fr <- geo %>%
setNames(c("geo", "Geo_fr"))
load_data("eurostat/geo.RData")
tec00114 %>%
filter(geo %in% c("EL", "PL", "FR", "DE", "IT", "ES")) %>%
select(time, na_item, geo, values) %>%
year_to_date %>%
left_join(geo, by = "geo") %>%
left_join(geo_fr, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
scale_color_identity() + add_6flags +
theme_minimal() + xlab("") + ylab("PIB/hab., Parité de Pouvoir d'Achat (EU-27 2020 = 100)") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 5)) +
geom_hline(yintercept = 100, linetype = "dashed") +
geom_text(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = Geo_fr, color = color))
Poland, Hungary, Greece, Germany, France, Italy, Spain, United States
Code
tec00114 %>%
filter(geo %in% c("EL", "PL", "HU", "FR", "DE", "IT", "ES", "US")) %>%
select(time, na_item, geo, values) %>%
year_to_date %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
scale_color_identity() + add_8flags +
theme_minimal() + xlab("") + ylab("PIB/hab., Parité de Pouvoir d'Achat (EU-27 2020 = 100)") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 5)) +
geom_hline(yintercept = 100, linetype = "dashed")
Germany, France, Italy, United States, Switzerland, United Kingdom
Code
tec00114 %>%
filter(geo %in% c("FR", "DE", "IT", "UK", "CH", "US")) %>%
select(time, na_item, geo, values) %>%
year_to_date %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
scale_color_identity() + add_6flags +
theme_minimal() + xlab("") + ylab("PIB/hab., Parité de Pouvoir d'Achat (EU-27 2020 = 100)") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 5)) +
geom_hline(yintercept = 100, linetype = "dashed")