Last observation: déc. 1998 (N = 3)
First observation: janv. 1971 (N = 2)
Last data update: 14 sept. 2026, 23:09
Last compile: 16 sept. 2026, 20:16
`REVALORISATION-PENSIONS` |>
group_by(IDBANK, TITLE_FR) |>
summarise(Nobs = n(),
date1 = first(TIME_PERIOD),
date2 = last(TIME_PERIOD)) |>
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}`REVALORISATION-PENSIONS` |>
group_by(TIME_PERIOD) |>
summarise(Nobs = n()) |>
arrange(desc(TIME_PERIOD)) |>
print_table_conditional()`REVALORISATION-PENSIONS` |>
month_to_date() |>
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Ipc_revalorisation)) +
scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 5),
labels = dollar_format(accuracy = 1, prefix = ""))
`REVALORISATION-PENSIONS` |>
month_to_date() |>
group_by(IPC_REVALORISATION) |>
arrange(date) |>
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("1981-01-01")]) |>
ggplot() + ylab("Indice des prix") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Ipc_revalorisation)) +
scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(0, 200, 5),
labels = dollar_format(accuracy = 1, prefix = ""))