Last observation: Q: 2026-Q1 (N = 3113) · H: 2025-S2 (N = 16758) · A: 2025 (N = 10857)
First observation: A: 2000 (N = 323) · Q: 2022-Q1 (N = 3042) · H: 2022-S1 (N = 14331)
Last data update: 17 aoû 2026, 02:09. Last compile: 18 aoû 2026, 01:21
Data - ECB
Last observation: Q: 2026-Q1 (N = 3113) · H: 2025-S2 (N = 16758) · A: 2025 (N = 10857)
First observation: A: 2000 (N = 323) · Q: 2022-Q1 (N = 3042) · H: 2022-S1 (N = 14331)
Last data update: 17 aoû 2026, 02:09. Last compile: 18 aoû 2026, 01:21
freq_dominant <- PCT |>
filter(!is.na(OBS_VALUE)) |>
count(FREQ, sort = TRUE) |>
slice(1) |>
pull(FREQ)
convert_fn <- switch(freq_dominant,
"A" = year_to_date, "Q" = quarter_to_date, "M" = month_to_date,
"H" = semester_to_date, "W" = week_to_date, "D" = day_to_date, "B" = day_to_date,
year_to_date)
PCT |>
filter(!is.na(OBS_VALUE), FREQ == freq_dominant) |>
group_by(TIME_PERIOD) |>
summarise(OBS_VALUE = mean(OBS_VALUE, na.rm = TRUE), .groups = "drop") |>
convert_fn() |>
ggplot() + theme_minimal() + xlab("") + ylab("Average value across all series") +
geom_line(aes(x = date, y = OBS_VALUE)) +
scale_x_date(date_labels = "%Y")