Last observation: T: 2026-Q1 (N = 115)
First observation: T: 1982-Q1 (N = 110)
Last data update: 17 aoû 2026, 01:04. Last compile: 18 aoû 2026, 03:05
Données - INSEE
Last observation: T: 2026-Q1 (N = 115)
First observation: T: 1982-Q1 (N = 110)
Last data update: 17 aoû 2026, 01:04. Last compile: 18 aoû 2026, 03:05
| source | dataset | Title | Updated |
|---|---|---|---|
| insee | TAUX-CHOMAGE | Taux de chômage localisé | 2026-08-16 |
| source | dataset | Title | Updated |
|---|---|---|---|
| insee | TAUX-CHOMAGE | Taux de chômage localisé | 2026-08-16 |
| insee | CHOMAGE-TRIM-NATIONAL | Chômage, taux de chômage par sexe et âge (sens BIT) (1975-) | 2026-08-16 |
| insee | CNA-2014-EMPLOI | Emploi intérieur, durée effective travaillée et productivité horaire | 2026-08-16 |
| insee | DEMANDES-EMPLOIS-NATIONALES | Demandeurs d'emploi inscrits à Pôle Emploi | 2026-08-17 |
| insee | EMPLOI-BIT-TRIM | Emploi, activité, sous-emploi par secteur d’activité (sens BIT) | 2026-08-16 |
| insee | EMPLOI-SALARIE-TRIM-NATIONAL | Estimations d'emploi salarié par secteur d'activité | 2026-08-16 |
| insee | TCRED-EMPLOI-SALARIE-TRIM | Estimations d'emploi salarié par secteur d'activité et par département | 2026-08-16 |
`TAUX-CHOMAGE` |>
group_by(LAST_UPDATE) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
print_table_conditional()| LAST_UPDATE | Nobs |
|---|---|
| 2026-06-19 | 19715 |
`TAUX-CHOMAGE` |>
group_by(IDBANK, TITLE_FR) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
print_table_conditional()`TAUX-CHOMAGE` |>
group_by(REF_AREA) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
print_table_conditional()`TAUX-CHOMAGE` |>
group_by(TIME_PERIOD) |>
summarise(Nobs = n()) |>
arrange(desc(TIME_PERIOD)) |>
print_table_conditional()`TAUX-CHOMAGE` |>
quarter_to_date() |>
filter(date == as.Date("2019-07-01")) |>
mutate(OBS_VALUE = OBS_VALUE |> as.numeric()) |>
select(REF_AREA, TITLE_FR, OBS_VALUE) |>
arrange(-OBS_VALUE) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}`TAUX-CHOMAGE` |>
quarter_to_date() |>
filter(date == as.Date("2019-10-01"),
grepl("D", REF_AREA)) |>
mutate(value = as.numeric(OBS_VALUE),
depts_code = substr(REF_AREA, 2, 3)) |>
select(depts_code, value) |>
right_join(france, by = "depts_code") |>
ggplot(aes(long, lat, group = group, fill = value/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(0, 20, 2),
name = "Chômage") +
labs(x = "", y = "", title = "") +
theme_minimal() + theme(axis.text.x = element_blank(),
axis.text.y = element_blank())
`TAUX-CHOMAGE` |>
quarter_to_date() |>
filter(date == as.Date("2010-01-01"),
grepl("D", REF_AREA)) |>
mutate(value = as.numeric(OBS_VALUE),
depts_code = substr(REF_AREA, 2, 3)) |>
select(depts_code, value) |>
right_join(france, by = "depts_code") |>
ggplot(aes(long, lat, group = group, fill = value/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(0, 20, 2),
name = "Chômage") +
labs(x = "", y = "", title = "") +
theme_minimal() + theme(axis.text.x = element_blank(),
axis.text.y = element_blank())
`TAUX-CHOMAGE` |>
quarter_to_date() |>
filter(date == as.Date("2000-01-01"),
grepl("D", REF_AREA)) |>
mutate(value = as.numeric(OBS_VALUE),
depts_code = substr(REF_AREA, 2, 3)) |>
select(depts_code, value) |>
right_join(france, by = "depts_code") |>
ggplot(aes(long, lat, group = group, fill = value/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(0, 20, 2),
name = "Chômage") +
labs(x = "", y = "", title = "") +
theme_minimal() + theme(axis.text.x = element_blank(),
axis.text.y = element_blank())
`TAUX-CHOMAGE` |>
quarter_to_date() |>
filter(date == as.Date("1990-01-01"),
grepl("D", REF_AREA)) |>
mutate(value = as.numeric(OBS_VALUE),
depts_code = substr(REF_AREA, 2, 3)) |>
select(depts_code, value) |>
right_join(france, by = "depts_code") |>
ggplot(aes(long, lat, group = group, fill = value/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(0, 20, 2),
name = "Chômage") +
labs(x = "", y = "", title = "") +
theme_minimal() + theme(axis.text.x = element_blank(),
axis.text.y = element_blank())
`TAUX-CHOMAGE` |>
quarter_to_date() |>
filter(date == as.Date("1982-01-01"),
grepl("D", REF_AREA)) |>
mutate(value = as.numeric(OBS_VALUE),
depts_code = substr(REF_AREA, 2, 3)) |>
select(depts_code, value) |>
right_join(france, by = "depts_code") |>
ggplot(aes(long, lat, group = group, fill = value/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(0, 20, 2),
name = "Chômage") +
labs(x = "", y = "", title = "") +
theme_minimal() + theme(axis.text.x = element_blank(),
axis.text.y = element_blank())
`TAUX-CHOMAGE` |>
quarter_to_date() |>
filter(REF_AREA %in% c("D92", "D93", "D75")) |>
ggplot() + geom_line(aes(x = date, y = OBS_VALUE/100, color = REF_AREA)) +
theme_minimal() + xlab("") + ylab("Taux de chômage") +
scale_x_date(breaks = seq(1960, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
labels = percent_format(accuracy = 1)) +
theme(legend.position = c(0.15, 0.8),
legend.title = element_blank())