Last observation: 2024 (N = 20968)
First observation: 1995 (N = 12204)
Last data update: 14 aoû 2026, 20:54. Last compile: 18 aoû 2026, 03:57
Data - Eurostat
Last observation: 2024 (N = 20968)
First observation: 1995 (N = 12204)
Last data update: 14 aoû 2026, 20:54. Last compile: 18 aoû 2026, 03:57
PPPs are nothing more than price relatives that show the ratio of the prices in national currencies of the same good or service in different countries. For example, if the price of a litre of Coca Cola is 2.30 euros in France and 2.00 dollars in the United States, then the PPP for Coca Cola between France and the United States is the ratio 2.30 euros to 2.00 dollars or 1.15 euros to the dollar. This means that for every dollar spent on Coca Cola in the United States, 1.15 euros would have to be spent in France to obtain the same quantity and quality – or, in other words, the same volume - of Coca Cola.
include_graphics("https://ec.europa.eu/eurostat/documents/4187653/11581511/Map+AIC+per+capita+2020.jpg/fbd93f3e-ebe8-29bc-8cd3-8d790990ca30?t=1624002507913")
include_graphics("https://ec.europa.eu/eurostat/documents/4187653/11581511/AIC+GDP+per+capita+2020.jpg/c1f554b3-807e-d0b7-1337-333e3eef5d17?t=1624002507551")
prc_ppp_ind |>
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="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) |>
select(Flag, everything()) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}prc_ppp_ind |>
filter(ppp_cat == "GDP",
geo %in% c("FR", "DE", "IT"),
na_item == "PPP_EU27_2020") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, .05))
prc_ppp_ind |>
filter(ppp_cat == "E01",
geo %in% c("FR", "DE", "IT"),
na_item == "PPP_EU27_2020") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, .05))
prc_ppp_ind |>
filter(ppp_cat == "E011",
geo %in% c("FR", "DE", "IT"),
na_item == "PPP_EU27_2020") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, .05))
prc_ppp_ind |>
filter(ppp_cat == "A01",
geo %in% c("FR", "DE", "IT"),
na_item == "PPP_EU27_2020") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, .05))
prc_ppp_ind |>
filter(ppp_cat == "A010405",
geo %in% c("FR", "DE", "IT"),
na_item == "PPP_EU27_2020") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, .05))
prc_ppp_ind |>
filter(ppp_cat == "A010405",
geo %in% c("FR", "DE", "IT"),
na_item == "PLI_EU28") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, 5))
prc_ppp_ind |>
filter(ppp_cat == "A0104",
geo %in% c("FR")) |>
left_join(na_item, by = "na_item") |>
group_by(na_item, Na_item) |>
summarise(Nobs = n(),
first = first(time),
last = last(time)) |>
print_table_conditional()| na_item | Na_item | Nobs | first | last |
|---|---|---|---|---|
| EXP_EUR | Nominal expenditure (in euro) | 30 | 1995 | 2024 |
| EXP_EUR_HAB | Nominal expenditure per inhabitant (in euro) | 30 | 1995 | 2024 |
| EXP_NAC | Nominal expenditure in national currency | 30 | 1995 | 2024 |
| EXP_NAC_PC_GDP | Nominal expenditure as a percentage of GDP (GDP=100) | 30 | 1995 | 2024 |
| EXP_PPS_EU15 | Real expenditure (in PPS_EU15) | 26 | 1995 | 2020 |
| EXP_PPS_EU15_HAB | Real expenditure per capita (in PPS_EU15) | 26 | 1995 | 2020 |
| EXP_PPS_EU27_2007 | Real expenditure (in PPS_EU27_2007) | 22 | 1999 | 2020 |
| EXP_PPS_EU27_2007_HAB | Real expenditure per capita (in PPS_EU27_2007) | 22 | 1999 | 2020 |
| EXP_PPS_EU27_2020 | Real expenditure (in PPS_EU27_2020) | 22 | 2003 | 2024 |
| EXP_PPS_EU27_2020_HAB | Real expenditure per capita (in PPS_EU27_2020) | 22 | 2003 | 2024 |
| EXP_PPS_EU28 | Real expenditure (in PPS_EU28) | 18 | 2003 | 2020 |
| EXP_PPS_EU28_HAB | Real expenditure per capita (in PPS_EU28) | 18 | 2003 | 2020 |
| PLI_EU15 | Price level indices (EU15=100) | 26 | 1995 | 2020 |
| PLI_EU27_2007 | Price level indices (EU27_2007=100) | 22 | 1999 | 2020 |
| PLI_EU27_2020 | Price level indices (EU27_2020=100) | 22 | 2003 | 2024 |
| PLI_EU28 | Price level indices (EU28=100) | 18 | 2003 | 2020 |
| PPP_EU15 | Purchasing power parities (EU15=1) | 26 | 1995 | 2020 |
| PPP_EU27_2007 | Purchasing power parities (EU27_2007=1) | 22 | 1999 | 2020 |
| PPP_EU27_2020 | Purchasing power parities (EU27_2020=1) | 22 | 2003 | 2024 |
| PPP_EU28 | Purchasing power parities (EU28=1) | 18 | 2003 | 2020 |
| VI_PPS_EU15_HAB | Volume indices of real expenditure per capita (in PPS_EU15=100) | 26 | 1995 | 2020 |
| VI_PPS_EU27_2007_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2007=100) | 22 | 1999 | 2020 |
| VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 22 | 2003 | 2024 |
| VI_PPS_EU28_HAB | Volume indices of real expenditure per capita (in PPS_EU28=100) | 18 | 2003 | 2020 |
prc_ppp_ind |>
filter(ppp_cat == "A0104",
time == "2019",
geo %in% c("FR", "DE", "IT")) |>
select(na_item, geo, values) |>
left_join(na_item, by = "na_item") |>
spread(geo, values) |>
print_table_conditional()| na_item | Na_item | DE | FR | IT |
|---|---|---|---|---|
| EXP_EUR | Nominal expenditure (in euro) | 4.23638e+05 | 3.51945e+05 | 2.45174e+05 |
| EXP_EUR_HAB | Nominal expenditure per inhabitant (in euro) | 5.09800e+03 | 5.22200e+03 | 4.10500e+03 |
| EXP_NAC | Nominal expenditure in national currency | 4.23638e+05 | 3.51945e+05 | 2.45174e+05 |
| EXP_NAC_PC_GDP | Nominal expenditure as a percentage of GDP (GDP=100) | 1.20000e+01 | 1.45000e+01 | 1.36000e+01 |
| EXP_PPS_EU15 | Real expenditure (in PPS_EU15) | 4.44869e+05 | 3.51894e+05 | 3.01783e+05 |
| EXP_PPS_EU15_HAB | Real expenditure per capita (in PPS_EU15) | 5.40000e+03 | 5.20000e+03 | 5.10000e+03 |
| EXP_PPS_EU27_2007 | Real expenditure (in PPS_EU27_2007) | 3.98668e+05 | 3.15349e+05 | 2.70442e+05 |
| EXP_PPS_EU27_2007_HAB | Real expenditure per capita (in PPS_EU27_2007) | 4.80000e+03 | 4.70000e+03 | 4.50000e+03 |
| EXP_PPS_EU27_2020 | Real expenditure (in PPS_EU27_2020) | 3.66991e+05 | 2.90292e+05 | 2.48953e+05 |
| EXP_PPS_EU27_2020_HAB | Real expenditure per capita (in PPS_EU27_2020) | 4.40000e+03 | 4.30000e+03 | 4.20000e+03 |
| EXP_PPS_EU28 | Real expenditure (in PPS_EU28) | 3.96960e+05 | 3.13998e+05 | 2.69284e+05 |
| EXP_PPS_EU28_HAB | Real expenditure per capita (in PPS_EU28) | 4.80000e+03 | 4.70000e+03 | 4.50000e+03 |
| PLI_EU15 | Price level indices (EU15=100) | 9.52000e+01 | 1.00000e+02 | 8.12000e+01 |
| PLI_EU27_2007 | Price level indices (EU27_2007=100) | 1.06300e+02 | 1.11600e+02 | 9.07000e+01 |
| PLI_EU27_2020 | Price level indices (EU27_2020=100) | 1.15400e+02 | 1.21200e+02 | 9.85000e+01 |
| PLI_EU28 | Price level indices (EU28=100) | 1.06700e+02 | 1.12100e+02 | 9.10000e+01 |
| PPP_EU15 | Purchasing power parities (EU15=1) | 9.52275e-01 | 1.00014e+00 | 8.12416e-01 |
| PPP_EU27_2007 | Purchasing power parities (EU27_2007=1) | 1.06263e+00 | 1.11605e+00 | 9.06566e-01 |
| PPP_EU27_2020 | Purchasing power parities (EU27_2020=1) | 1.15436e+00 | 1.21238e+00 | 9.84818e-01 |
| PPP_EU28 | Purchasing power parities (EU28=1) | 1.06720e+00 | 1.12085e+00 | 9.10466e-01 |
| VI_PPS_EU15_HAB | Volume indices of real expenditure per capita (in PPS_EU15=100) | 1.10000e+02 | 1.07000e+02 | 1.04000e+02 |
| VI_PPS_EU27_2007_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2007=100) | 1.13000e+02 | 1.10000e+02 | 1.07000e+02 |
| VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 1.12000e+02 | 1.09000e+02 | 1.05000e+02 |
| VI_PPS_EU28_HAB | Volume indices of real expenditure per capita (in PPS_EU28=100) | 1.13000e+02 | 1.10000e+02 | 1.07000e+02 |
prc_ppp_ind |>
filter(ppp_cat == "A0104",
geo %in% c("FR", "DE", "IT"),
na_item == "PPP_EU27_2020") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, .05))
prc_ppp_ind |>
filter(ppp_cat == "A0104",
geo %in% c("FR", "DE", "IT"),
na_item == "PLI_EU28") |>
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() + theme_minimal() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("") +
scale_y_continuous(breaks = seq(0, 4000, 5))
prc_ppp_ind |>
filter(ppp_cat == "E011",
time == "2019",
geo %in% c("FR", "DE", "IT")) |>
select(na_item, geo, values) |>
left_join(na_item, by = "na_item") |>
spread(geo, values) |>
print_table_conditional()| na_item | Na_item | DE | FR | IT |
|---|---|---|---|---|
| EXP_EUR | Nominal expenditure (in euro) | 1.813709e+06 | 1.262531e+06 | 1.067942e+06 |
| EXP_EUR_HAB | Nominal expenditure per inhabitant (in euro) | 2.182700e+04 | 1.873300e+04 | 1.788000e+04 |
| EXP_NAC | Nominal expenditure in national currency | 1.813709e+06 | 1.262531e+06 | 1.067942e+06 |
| EXP_NAC_PC_GDP | Nominal expenditure as a percentage of GDP (GDP=100) | 5.130000e+01 | 5.190000e+01 | 5.920000e+01 |
| EXP_PPS_EU15 | Real expenditure (in PPS_EU15) | 1.864692e+06 | 1.224870e+06 | 1.156464e+06 |
| EXP_PPS_EU15_HAB | Real expenditure per capita (in PPS_EU15) | 2.240000e+04 | 1.820000e+04 | 1.940000e+04 |
| EXP_PPS_EU27_2007 | Real expenditure (in PPS_EU27_2007) | 1.750377e+06 | 1.149779e+06 | 1.085567e+06 |
| EXP_PPS_EU27_2007_HAB | Real expenditure per capita (in PPS_EU27_2007) | 2.110000e+04 | 1.710000e+04 | 1.820000e+04 |
| EXP_PPS_EU27_2020 | Real expenditure (in PPS_EU27_2020) | 1.694399e+06 | 1.113009e+06 | 1.050850e+06 |
| EXP_PPS_EU27_2020_HAB | Real expenditure per capita (in PPS_EU27_2020) | 2.040000e+04 | 1.650000e+04 | 1.760000e+04 |
| EXP_PPS_EU28 | Real expenditure (in PPS_EU28) | 1.747649e+06 | 1.147987e+06 | 1.083875e+06 |
| EXP_PPS_EU28_HAB | Real expenditure per capita (in PPS_EU28) | 2.100000e+04 | 1.700000e+04 | 1.810000e+04 |
| PLI_EU15 | Price level indices (EU15=100) | 9.730000e+01 | 1.031000e+02 | 9.230000e+01 |
| PLI_EU27_2007 | Price level indices (EU27_2007=100) | 1.036000e+02 | 1.098000e+02 | 9.840000e+01 |
| PLI_EU27_2020 | Price level indices (EU27_2020=100) | 1.070000e+02 | 1.134000e+02 | 1.016000e+02 |
| PLI_EU28 | Price level indices (EU28=100) | 1.038000e+02 | 1.100000e+02 | 9.850000e+01 |
| PPP_EU15 | Purchasing power parities (EU15=1) | 9.726590e-01 | 1.030750e+00 | 9.234540e-01 |
| PPP_EU27_2007 | Purchasing power parities (EU27_2007=1) | 1.036180e+00 | 1.098060e+00 | 9.837640e-01 |
| PPP_EU27_2020 | Purchasing power parities (EU27_2020=1) | 1.070410e+00 | 1.134340e+00 | 1.016260e+00 |
| PPP_EU28 | Purchasing power parities (EU28=1) | 1.037800e+00 | 1.099780e+00 | 9.853000e-01 |
| VI_PPS_EU15_HAB | Volume indices of real expenditure per capita (in PPS_EU15=100) | 1.140000e+02 | 9.200000e+01 | 9.800000e+01 |
| VI_PPS_EU27_2007_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2007=100) | 1.210000e+02 | 9.800000e+01 | 1.040000e+02 |
| VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 1.240000e+02 | 1.000000e+02 | 1.070000e+02 |
| VI_PPS_EU28_HAB | Volume indices of real expenditure per capita (in PPS_EU28=100) | 1.210000e+02 | 9.800000e+01 | 1.040000e+02 |
prc_ppp_ind |>
filter(ppp_cat == "GDP",
time == "2019",
geo %in% c("FR", "DE", "IT")) |>
select(na_item, geo, values) |>
left_join(na_item, by = "na_item") |>
spread(geo, values) |>
print_table_conditional()| na_item | Na_item | DE | FR | IT |
|---|---|---|---|---|
| EXP_EUR | Nominal expenditure (in euro) | 3.534880e+06 | 2.432207e+06 | 1.804067e+06 |
| EXP_EUR_HAB | Nominal expenditure per inhabitant (in euro) | 4.254100e+04 | 3.608800e+04 | 3.020400e+04 |
| EXP_NAC | Nominal expenditure in national currency | 3.534880e+06 | 2.432207e+06 | 1.804067e+06 |
| EXP_NAC_PC_GDP | Nominal expenditure as a percentage of GDP (GDP=100) | 1.000000e+02 | 1.000000e+02 | 1.000000e+02 |
| EXP_PPS_EU15 | Real expenditure (in PPS_EU15) | 3.491826e+06 | 2.442710e+06 | 1.976043e+06 |
| EXP_PPS_EU15_HAB | Real expenditure per capita (in PPS_EU15) | 4.200000e+04 | 3.620000e+04 | 3.310000e+04 |
| EXP_PPS_EU27_2007 | Real expenditure (in PPS_EU27_2007) | 3.282758e+06 | 2.296457e+06 | 1.857731e+06 |
| EXP_PPS_EU27_2007_HAB | Real expenditure per capita (in PPS_EU27_2007) | 3.950000e+04 | 3.410000e+04 | 3.110000e+04 |
| EXP_PPS_EU27_2020 | Real expenditure (in PPS_EU27_2020) | 3.202761e+06 | 2.240495e+06 | 1.812460e+06 |
| EXP_PPS_EU27_2020_HAB | Real expenditure per capita (in PPS_EU27_2020) | 3.850000e+04 | 3.320000e+04 | 3.030000e+04 |
| EXP_PPS_EU28 | Real expenditure (in PPS_EU28) | 3.276610e+06 | 2.292156e+06 | 1.854252e+06 |
| EXP_PPS_EU28_HAB | Real expenditure per capita (in PPS_EU28) | 3.940000e+04 | 3.400000e+04 | 3.100000e+04 |
| PLI_EU15 | Price level indices (EU15=100) | 1.012000e+02 | 9.960000e+01 | 9.130000e+01 |
| PLI_EU27_2007 | Price level indices (EU27_2007=100) | 1.077000e+02 | 1.059000e+02 | 9.710000e+01 |
| PLI_EU27_2020 | Price level indices (EU27_2020=100) | 1.104000e+02 | 1.086000e+02 | 9.950000e+01 |
| PLI_EU28 | Price level indices (EU28=100) | 1.079000e+02 | 1.061000e+02 | 9.730000e+01 |
| PPP_EU15 | Purchasing power parities (EU15=1) | 1.012330e+00 | 9.957000e-01 | 9.129690e-01 |
| PPP_EU27_2007 | Purchasing power parities (EU27_2007=1) | 1.076800e+00 | 1.059110e+00 | 9.711130e-01 |
| PPP_EU27_2020 | Purchasing power parities (EU27_2020=1) | 1.103700e+00 | 1.085570e+00 | 9.953690e-01 |
| PPP_EU28 | Purchasing power parities (EU28=1) | 1.078820e+00 | 1.061100e+00 | 9.729350e-01 |
| VI_PPS_EU15_HAB | Volume indices of real expenditure per capita (in PPS_EU15=100) | 1.140000e+02 | 9.800000e+01 | 9.000000e+01 |
| VI_PPS_EU27_2007_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2007=100) | 1.210000e+02 | 1.040000e+02 | 9.500000e+01 |
| VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 1.220000e+02 | 1.050000e+02 | 9.600000e+01 |
| VI_PPS_EU28_HAB | Volume indices of real expenditure per capita (in PPS_EU28=100) | 1.210000e+02 | 1.050000e+02 | 9.600000e+01 |
prc_ppp_ind |>
filter(ppp_cat == "E011",
time == "2019",
geo %in% c("FR", "DE", "IT")) |>
select(na_item, geo, values) |>
left_join(na_item, by = "na_item") |>
spread(geo, values) |>
print_table_conditional()| na_item | Na_item | DE | FR | IT |
|---|---|---|---|---|
| EXP_EUR | Nominal expenditure (in euro) | 1.813709e+06 | 1.262531e+06 | 1.067942e+06 |
| EXP_EUR_HAB | Nominal expenditure per inhabitant (in euro) | 2.182700e+04 | 1.873300e+04 | 1.788000e+04 |
| EXP_NAC | Nominal expenditure in national currency | 1.813709e+06 | 1.262531e+06 | 1.067942e+06 |
| EXP_NAC_PC_GDP | Nominal expenditure as a percentage of GDP (GDP=100) | 5.130000e+01 | 5.190000e+01 | 5.920000e+01 |
| EXP_PPS_EU15 | Real expenditure (in PPS_EU15) | 1.864692e+06 | 1.224870e+06 | 1.156464e+06 |
| EXP_PPS_EU15_HAB | Real expenditure per capita (in PPS_EU15) | 2.240000e+04 | 1.820000e+04 | 1.940000e+04 |
| EXP_PPS_EU27_2007 | Real expenditure (in PPS_EU27_2007) | 1.750377e+06 | 1.149779e+06 | 1.085567e+06 |
| EXP_PPS_EU27_2007_HAB | Real expenditure per capita (in PPS_EU27_2007) | 2.110000e+04 | 1.710000e+04 | 1.820000e+04 |
| EXP_PPS_EU27_2020 | Real expenditure (in PPS_EU27_2020) | 1.694399e+06 | 1.113009e+06 | 1.050850e+06 |
| EXP_PPS_EU27_2020_HAB | Real expenditure per capita (in PPS_EU27_2020) | 2.040000e+04 | 1.650000e+04 | 1.760000e+04 |
| EXP_PPS_EU28 | Real expenditure (in PPS_EU28) | 1.747649e+06 | 1.147987e+06 | 1.083875e+06 |
| EXP_PPS_EU28_HAB | Real expenditure per capita (in PPS_EU28) | 2.100000e+04 | 1.700000e+04 | 1.810000e+04 |
| PLI_EU15 | Price level indices (EU15=100) | 9.730000e+01 | 1.031000e+02 | 9.230000e+01 |
| PLI_EU27_2007 | Price level indices (EU27_2007=100) | 1.036000e+02 | 1.098000e+02 | 9.840000e+01 |
| PLI_EU27_2020 | Price level indices (EU27_2020=100) | 1.070000e+02 | 1.134000e+02 | 1.016000e+02 |
| PLI_EU28 | Price level indices (EU28=100) | 1.038000e+02 | 1.100000e+02 | 9.850000e+01 |
| PPP_EU15 | Purchasing power parities (EU15=1) | 9.726590e-01 | 1.030750e+00 | 9.234540e-01 |
| PPP_EU27_2007 | Purchasing power parities (EU27_2007=1) | 1.036180e+00 | 1.098060e+00 | 9.837640e-01 |
| PPP_EU27_2020 | Purchasing power parities (EU27_2020=1) | 1.070410e+00 | 1.134340e+00 | 1.016260e+00 |
| PPP_EU28 | Purchasing power parities (EU28=1) | 1.037800e+00 | 1.099780e+00 | 9.853000e-01 |
| VI_PPS_EU15_HAB | Volume indices of real expenditure per capita (in PPS_EU15=100) | 1.140000e+02 | 9.200000e+01 | 9.800000e+01 |
| VI_PPS_EU27_2007_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2007=100) | 1.210000e+02 | 9.800000e+01 | 1.040000e+02 |
| VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 1.240000e+02 | 1.000000e+02 | 1.070000e+02 |
| VI_PPS_EU28_HAB | Volume indices of real expenditure per capita (in PPS_EU28=100) | 1.210000e+02 | 9.800000e+01 | 1.040000e+02 |
prc_ppp_ind |>
filter(ppp_cat == "A01",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
left_join(geo, by = "geo") |>
select(-ppp_cat, -time, -na_item) |>
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
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 .}europe_NUTS0_new <- prc_ppp_ind |>
filter(ppp_cat == "A01",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
select(geo, values) |>
right_join(europe_NUTS0 |>
filter(long >= -10,
lat >= 20), by = "geo") |>
group_by(geo, values) |>
summarise(long = mean(long), lat = mean(lat))
prc_ppp_ind |>
filter(ppp_cat == "A01",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
select(geo, values) |>
right_join(europe_NUTS0 |>
filter(long >= -10,
lat >= 20), by = "geo") |>
ggplot(aes(x = long, y = lat)) +
geom_polygon(aes(group = group, fill = values)) + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = dollar_format(a = 1, p = "", su = ""),
breaks = seq(20, 140, 20)) +
geom_text(aes(label = values), data = europe_NUTS0_new, size = 3, hjust = 0.5) +
theme_void() + theme(legend.position = c(0.25, 0.85)) +
labs(fill = "Actual Individual Consumption")
europe_NUTS0_new <- prc_ppp_ind |>
filter(ppp_cat == "A01",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
select(geo, values) |>
right_join(europe_NUTS0 |>
filter(long >= -10,
lat >= 20), by = "geo") |>
group_by(geo, values) |>
summarise(long = mean(long), lat = mean(lat))
prc_ppp_ind |>
filter(ppp_cat == "A01",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
select(geo, values) |>
right_join(europe_NUTS0 |>
filter(long >= -10,
lat >= 20), by = "geo") |>
ggplot(aes(x = long, y = lat)) +
geom_polygon(aes(group = group, fill = values)) + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = dollar_format(a = 1, p = "", su = ""),
breaks = seq(20, 140, 20)) +
theme_void() + theme(legend.position = c(0.25, 0.85)) +
labs(fill = "Actual Individual Consumption")
prc_ppp_ind |>
filter(ppp_cat == "A01",
geo == "FR",
time %in% c("1995", "2005", "2015", "2019")) |>
left_join(na_item, by = "na_item") |>
select(-ppp_cat, -geo) |>
spread(time, values) |>
print_table_conditional()| freq | na_item | Na_item | 1995 | 2005 | 2015 | 2019 |
|---|---|---|---|---|---|---|
| A | EXP_EUR | Nominal expenditure (in euro) | 8.36517e+05 | 1.216638e+06 | 1.536678e+06 | 1.682473e+06 |
| A | EXP_EUR_HAB | Nominal expenditure per inhabitant (in euro) | 1.40810e+04 | 1.932300e+04 | 2.317300e+04 | 2.496400e+04 |
| A | EXP_NAC | Nominal expenditure in national currency | 8.32116e+05 | 1.216638e+06 | 1.536678e+06 | 1.682473e+06 |
| A | EXP_NAC_PC_GDP | Nominal expenditure as a percentage of GDP (GDP=100) | 6.86000e+01 | 6.900000e+01 | 6.980000e+01 | 6.920000e+01 |
| A | EXP_PPS_EU15 | Real expenditure (in PPS_EU15) | 7.76118e+05 | 1.225393e+06 | 1.590973e+06 | 1.708868e+06 |
| A | EXP_PPS_EU15_HAB | Real expenditure per capita (in PPS_EU15) | 1.31000e+04 | 1.950000e+04 | 2.400000e+04 | 2.540000e+04 |
| A | EXP_PPS_EU27_2007 | Real expenditure (in PPS_EU27_2007) | 7.26182e+05 | 1.157023e+06 | 1.480920e+06 | 1.593008e+06 |
| A | EXP_PPS_EU27_2007_HAB | Real expenditure per capita (in PPS_EU27_2007) | 1.22000e+04 | 1.840000e+04 | 2.230000e+04 | 2.360000e+04 |
| A | EXP_PPS_EU27_2020 | Real expenditure (in PPS_EU27_2020) | 7.16257e+05 | 1.102496e+06 | 1.390155e+06 | 1.534814e+06 |
| A | EXP_PPS_EU27_2020_HAB | Real expenditure per capita (in PPS_EU27_2020) | 1.21000e+04 | 1.750000e+04 | 2.100000e+04 | 2.280000e+04 |
| A | EXP_PPS_EU28 | Real expenditure (in PPS_EU28) | 7.24752e+05 | 1.155054e+06 | 1.477967e+06 | 1.590082e+06 |
| A | EXP_PPS_EU28_HAB | Real expenditure per capita (in PPS_EU28) | 1.22000e+04 | 1.830000e+04 | 2.230000e+04 | 2.360000e+04 |
| A | PLI_EU15 | Price level indices (EU15=100) | 1.07800e+02 | 9.930000e+01 | 9.660000e+01 | 9.850000e+01 |
| A | PLI_EU27_2007 | Price level indices (EU27_2007=100) | 1.15200e+02 | 1.052000e+02 | 1.038000e+02 | 1.056000e+02 |
| A | PLI_EU27_2020 | Price level indices (EU27_2020=100) | 1.16800e+02 | 1.104000e+02 | 1.105000e+02 | 1.096000e+02 |
| A | PLI_EU28 | Price level indices (EU28=100) | 1.15400e+02 | 1.053000e+02 | 1.040000e+02 | 1.058000e+02 |
| A | PPP_EU15 | Purchasing power parities (EU15=1) | 1.07215e+00 | 9.928560e-01 | 9.658730e-01 | 9.845540e-01 |
| A | PPP_EU27_2007 | Purchasing power parities (EU27_2007=1) | 1.14588e+00 | 1.051530e+00 | 1.037650e+00 | 1.056160e+00 |
| A | PPP_EU27_2020 | Purchasing power parities (EU27_2020=1) | 1.16176e+00 | 1.103530e+00 | 1.105400e+00 | 1.096210e+00 |
| A | PPP_EU28 | Purchasing power parities (EU28=1) | 1.14814e+00 | 1.053320e+00 | 1.039720e+00 | 1.058100e+00 |
| A | VI_PPS_EU15_HAB | Volume indices of real expenditure per capita (in PPS_EU15=100) | 1.01000e+02 | 9.900000e+01 | 1.020000e+02 | 1.010000e+02 |
| A | VI_PPS_EU27_2007_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2007=100) | 1.16000e+02 | 1.120000e+02 | 1.100000e+02 | 1.070000e+02 |
| A | VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 1.20000e+02 | 1.160000e+02 | 1.120000e+02 | 1.090000e+02 |
| A | VI_PPS_EU28_HAB | Volume indices of real expenditure per capita (in PPS_EU28=100) | 1.17000e+02 | 1.120000e+02 | 1.100000e+02 | 1.070000e+02 |
prc_ppp_ind |>
filter(ppp_cat == "A01",
geo == "DE",
time %in% c("1995", "2005", "2015", "2019")) |>
left_join(na_item, by = "na_item") |>
select(-ppp_cat, -geo) |>
spread(time, values) |>
print_table_conditional()| freq | na_item | Na_item | 1995 | 2005 | 2015 | 2019 |
|---|---|---|---|---|---|---|
| A | EXP_EUR | Nominal expenditure (in euro) | 1.327190e+06 | 1.596749e+06 | 2.030164e+06 | 2.313943e+06 |
| A | EXP_EUR_HAB | Nominal expenditure per inhabitant (in euro) | 1.632300e+04 | 1.963100e+04 | 2.485300e+04 | 2.784800e+04 |
| A | EXP_NAC | Nominal expenditure in national currency | 1.271492e+06 | 1.596749e+06 | 2.030164e+06 | 2.313943e+06 |
| A | EXP_NAC_PC_GDP | Nominal expenditure as a percentage of GDP (GDP=100) | 6.690000e+01 | 6.870000e+01 | 6.580000e+01 | 6.550000e+01 |
| A | EXP_PPS_EU15 | Real expenditure (in PPS_EU15) | 1.210057e+06 | 1.667670e+06 | 2.175706e+06 | 2.393417e+06 |
| A | EXP_PPS_EU15_HAB | Real expenditure per capita (in PPS_EU15) | 1.490000e+04 | 2.050000e+04 | 2.660000e+04 | 2.880000e+04 |
| A | EXP_PPS_EU27_2007 | Real expenditure (in PPS_EU27_2007) | 1.132201e+06 | 1.574623e+06 | 2.025206e+06 | 2.231144e+06 |
| A | EXP_PPS_EU27_2007_HAB | Real expenditure per capita (in PPS_EU27_2007) | 1.390000e+04 | 1.940000e+04 | 2.480000e+04 | 2.690000e+04 |
| A | EXP_PPS_EU27_2020 | Real expenditure (in PPS_EU27_2020) | 1.116726e+06 | 1.500417e+06 | 1.901082e+06 | 2.149639e+06 |
| A | EXP_PPS_EU27_2020_HAB | Real expenditure per capita (in PPS_EU27_2020) | 1.370000e+04 | 1.840000e+04 | 2.330000e+04 | 2.590000e+04 |
| A | EXP_PPS_EU28 | Real expenditure (in PPS_EU28) | 1.129971e+06 | 1.571943e+06 | 2.021167e+06 | 2.227047e+06 |
| A | EXP_PPS_EU28_HAB | Real expenditure per capita (in PPS_EU28) | 1.390000e+04 | 1.930000e+04 | 2.470000e+04 | 2.680000e+04 |
| A | PLI_EU15 | Price level indices (EU15=100) | 1.097000e+02 | 9.570000e+01 | 9.330000e+01 | 9.670000e+01 |
| A | PLI_EU27_2007 | Price level indices (EU27_2007=100) | 1.172000e+02 | 1.014000e+02 | 1.002000e+02 | 1.037000e+02 |
| A | PLI_EU27_2020 | Price level indices (EU27_2020=100) | 1.188000e+02 | 1.064000e+02 | 1.068000e+02 | 1.076000e+02 |
| A | PLI_EU28 | Price level indices (EU28=100) | 1.175000e+02 | 1.016000e+02 | 1.004000e+02 | 1.039000e+02 |
| A | PPP_EU15 | Purchasing power parities (EU15=1) | 1.050770e+00 | 9.574730e-01 | 9.331060e-01 | 9.667950e-01 |
| A | PPP_EU27_2007 | Purchasing power parities (EU27_2007=1) | 1.123030e+00 | 1.014050e+00 | 1.002450e+00 | 1.037110e+00 |
| A | PPP_EU27_2020 | Purchasing power parities (EU27_2020=1) | 1.138590e+00 | 1.064200e+00 | 1.067900e+00 | 1.076430e+00 |
| A | PPP_EU28 | Purchasing power parities (EU28=1) | 1.125240e+00 | 1.015780e+00 | 1.004450e+00 | 1.039020e+00 |
| A | VI_PPS_EU15_HAB | Volume indices of real expenditure per capita (in PPS_EU15=100) | 1.150000e+02 | 1.050000e+02 | 1.130000e+02 | 1.150000e+02 |
| A | VI_PPS_EU27_2007_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2007=100) | 1.330000e+02 | 1.180000e+02 | 1.220000e+02 | 1.220000e+02 |
| A | VI_PPS_EU27_2020_HAB | Volume indices of real expenditure per capita (in PPS_EU27_2020=100) | 1.360000e+02 | 1.230000e+02 | 1.250000e+02 | 1.240000e+02 |
| A | VI_PPS_EU28_HAB | Volume indices of real expenditure per capita (in PPS_EU28=100) | 1.330000e+02 | 1.180000e+02 | 1.220000e+02 | 1.220000e+02 |
prc_ppp_ind |>
filter(ppp_cat == "GDP",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
left_join(geo, by = "geo") |>
select(-ppp_cat, -time, -na_item) |>
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
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 .}europe_NUTS0_new <- prc_ppp_ind |>
filter(ppp_cat == "GDP",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
select(geo, values) |>
right_join(europe_NUTS0 |>
filter(long >= -10,
lat >= 20), by = "geo") |>
group_by(geo, values) |>
summarise(long = mean(long), lat = mean(lat))
prc_ppp_ind |>
filter(ppp_cat == "GDP",
na_item == "VI_PPS_EU28_HAB",
time == "2019") |>
select(geo, values) |>
right_join(europe_NUTS0 |>
filter(long >= -10,
lat >= 20), by = "geo") |>
ggplot(aes(x = long, y = lat)) +
geom_polygon(aes(group = group, fill = values)) + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = dollar_format(a = 1, p = "", su = ""),
breaks = seq(20, 260, 20)) +
geom_text(aes(label = values), data = europe_NUTS0_new, size = 3, hjust = 0.5) +
theme_void() + theme(legend.position = c(0.25, 0.85)) +
labs(fill = "Gross Domestic Product")