Last observation: 2024-01-01 (N = 4)
First observation: 2019-01-01 (N = 4)
Last data update: 02 aoû 2026, 11:04. Last compile: 18 aoû 2026, 00:39
Données - INSEE
Last observation: 2024-01-01 (N = 4)
First observation: 2019-01-01 (N = 4)
Last data update: 02 aoû 2026, 11:04. Last compile: 18 aoû 2026, 00:39
Salaires de la fonction publique: html
ECRT2026 |>
group_by(variable) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
print_table_conditional()| variable | Nobs |
|---|---|
| Employés et ouvriers | 6 |
| Ensemble | 6 |
| Professions de la santé | 6 |
| Professions intermédiaires et cadres hors professions de la santé | 6 |
ECRT2026 |>
group_by(date) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
print_table_conditional()| date | Nobs |
|---|---|
| 2019-01-01 | 4 |
| 2020-01-01 | 4 |
| 2021-01-01 | 4 |
| 2022-01-01 | 4 |
| 2023-01-01 | 4 |
| 2024-01-01 | 4 |
ECRT2026 |>
filter(sheet == "F28",
variable %in% c("Ensemble", "Ensemble des fonctionnaires")) |>
mutate(value = as.numeric(value)) |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
#scale_color_manual(values = viridis(8)[1:7]) +
geom_line(aes(x = date, y = value, color = variable)) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.2)) +
scale_x_date(breaks = seq(1950, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(1000, 20000, 20),
labels = scales::dollar_format(accuracy = 1, pre = "", su = "€"))
ECRT2026 |>
filter(sheet == "F28",
variable %in% c("Ensemble", "Ensemble des fonctionnaires")) |>
mutate(value = as.numeric(value)) |>
group_by(variable) |>
mutate(value = 100*value/value[1]) |>
ggplot() + theme_minimal() + xlab("") + ylab("") +
#scale_color_manual(values = viridis(8)[1:7]) +
geom_line(aes(x = date, y = value, color = variable)) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.8)) +
scale_x_date(breaks = seq(1950, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(80, 200, 1))