Last observation: Q1 2027 (N = 4) · mars 2027 (N = 4) · 2026 (N = 4)
First observation: 2013 (N = 4) · janv. 2013 (N = 4) · Q1 2013 (N = 4)
Last data update: 14 sept. 2026, 22:35
Last compile: 15 sept. 2026, 01:50
freq_dominant <- EWT |>
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)
EWT |>
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")
EWT |>
filter(REF_AREA == "U2", FREQ == "Q", ACTIVITY == "_T",
TRANSFORMATION == "GY",
EWT_CONCEPT %in% c("INWR", "INWX"), !is.na(OBS_VALUE)) |>
quarter_to_date() |>
mutate(series = recode(EWT_CONCEPT,
"INWR" = "Including one-off payments",
"INWX" = "Excluding one-off payments")) |>
ggplot() + theme_minimal() + xlab("") +
ylab("ECB wage tracker (% year-on-year)") +
geom_hline(yintercept = 3, linetype = "dashed") +
geom_line(aes(x = date, y = OBS_VALUE, color = series)) +
scale_color_manual(values = c("Including one-off payments" = "#003399",
"Excluding one-off payments" = "#b22234")) +
scale_x_date(breaks = as.Date(paste0(seq(2000, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.9), legend.title = element_blank()) +
scale_y_continuous(breaks = seq(0, 12, 1), labels = function(x) paste0(x, "%"))