Last observation: 2026 (N = 102)
First observation: 2005 (N = 31)
Last data update: 14 aoû 2026, 19:23. Last compile: 18 aoû 2026, 03:55
Data - Eurostat
Last observation: 2026 (N = 102)
First observation: 2005 (N = 31)
Last data update: 14 aoû 2026, 19:23. Last compile: 18 aoû 2026, 03:55
prc_hpi_inw |>
filter(geo %in% c("FR", "DE", "ES", "IT"),
purchase == "DW_NEW") |>
year_to_date() |>
left_join(colors, by = c("Geo" = "country")) |>
mutate(values = values/1000) |>
ggplot() + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + scale_color_identity() + add_flags +
scale_x_date(breaks = as.Date(paste0(seq(2005, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Weight of newly built dwellings in the HPI") +
scale_y_continuous(labels = scales::percent_format(accuracy = 1))
prc_hpi_inw |>
filter(geo == "FR",
purchase %in% c("DW_NEW", "DW_EXST")) |>
year_to_date() |>
mutate(values = values/1000) |>
ggplot() + geom_line(aes(x = date, y = values, color = Purchase)) +
theme_minimal() +
theme(legend.position = c(0.5, 0.5),
legend.title = element_blank()) +
scale_x_date(breaks = as.Date(paste0(seq(2005, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Weight in the House Price Index") +
scale_y_continuous(labels = scales::percent_format(accuracy = 1))
prc_hpi_inw |>
filter(time == "2020") |>
mutate(values = round(values),
Geo = ifelse(geo == "DE", "Germany", Geo)) |>
select(geo, Geo, purchase, values) |>
spread(purchase, values) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}