Last observation: Q2 2026 (N = 280) · juil. 2026 (N = 292) · 2015 (N = 1)
First observation: 1974 (N = 1) · janv. 1990 (N = 24) · Q1 1990 (N = 280)
Last data update: 23 sept. 2026, 22:30
Last compile: 24 sept. 2026, 00:52
| dataset | LAST_DOWNLOAD |
|---|---|
| DEFAILLANCES-ENTREPRISES | NA |
| 2025-02-04 14:34:02 |
`DEFAILLANCES-ENTREPRISES` |>
group_by(IDBANK, TITLE_FR) |>
summarise(Nobs = n()) |>
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}`DEFAILLANCES-ENTREPRISES` |>
group_by(CORRECTION) |>
summarise(Nobs = n()) |>
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| CORRECTION | Nobs |
|---|---|
| BRUT | 160852 |
| CVS-CJO | 5268 |
| RECALAGE | 42 |
`DEFAILLANCES-ENTREPRISES` |>
group_by(FREQ, Freq) |>
summarise(Nobs = n()) |>
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| FREQ | Freq | Nobs |
|---|---|---|
| M | Mensuelle | 125240 |
| T | Trimestrielle | 40880 |
| A | Annuelle | 42 |
`DEFAILLANCES-ENTREPRISES` |>
group_by(ACTIVITE_CREAT_ENT, Activite_creat_ent) |>
summarise(Nobs = n()) |>
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| ACTIVITE_CREAT_ENT | Activite_creat_ent | Nobs |
|---|---|---|
| ENS | Ensemble | 66502 |
| AZ | A10 AZ - Agriculture, sylviculture et pêche | 9060 |
| BE | A10 BE - Industrie | 9060 |
| FZ | A10 FZ - Construction | 9060 |
| G | A21 G - Commerce et réparation automobile | 9060 |
| H | A21 H - Transports | 9060 |
| I | A21 I - Hébergement, restauration | 9060 |
| JZ | A10 JZ - Information et communication | 9060 |
| KZ | A10 KZ - Activités financières et d'assurance | 9060 |
| LZ | A10 LZ - Activités immobilières | 9060 |
| MN | A10 MN - Activités spécialisées, scientifiques et techniques et activités de services administratifs et de soutien | 9060 |
| PQS | A21 P à S - Enseignement, santé humaine, action sociale et services aux ménages | 9060 |
`DEFAILLANCES-ENTREPRISES` |>
group_by(REF_AREA) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
print_table_conditional()`DEFAILLANCES-ENTREPRISES` |>
group_by(TIME_PERIOD) |>
summarise(Nobs = n()) |>
arrange(desc(TIME_PERIOD)) |>
print_table_conditional()`DEFAILLANCES-ENTREPRISES` |>
filter(REF_AREA == "FE",
NATURE == "VALEUR_ABSOLUE",
TIME_PERIOD %in% c("2017-01", "2021-06"),
CORRECTION == "CVS-CJO",
FREQ == "M") |>
select(TIME_PERIOD, ACTIVITE_CREAT_ENT, Activite_creat_ent, OBS_VALUE) |>
spread(TIME_PERIOD, OBS_VALUE) |>
mutate(Croissance = round(100*(`2021-06`/`2017-01`-1), 1)) |>
arrange(Croissance) |>
print_table_conditional()| ACTIVITE_CREAT_ENT | Activite_creat_ent | 2017-01 | 2021-06 | Croissance |
|---|---|---|---|---|
| I | A21 I - Hébergement, restauration | 607 | 178 | -70.7 |
| PQS | A21 P à S - Enseignement, santé humaine, action sociale et services aux ménages | 444 | 141 | -68.2 |
| BE | A10 BE - Industrie | 334 | 129 | -61.4 |
| FZ | A10 FZ - Construction | 1013 | 452 | -55.4 |
| ENS | Ensemble | 4621 | 2100 | -54.6 |
| G | A21 G - Commerce et réparation automobile | 1046 | 475 | -54.6 |
| MN | A10 MN - Activités spécialisées, scientifiques et techniques et activités de services administratifs et de soutien | 498 | 275 | -44.8 |
| JZ | A10 JZ - Information et communication | 109 | 61 | -44.0 |
| H | A21 H - Transports | 152 | 92 | -39.5 |
| KZ | A10 KZ - Activités financières et d'assurance | 98 | 62 | -36.7 |
| AZ | A10 AZ - Agriculture, sylviculture et pêche | 129 | 99 | -23.3 |
| LZ | A10 LZ - Activités immobilières | 150 | 127 | -15.3 |
`DEFAILLANCES-ENTREPRISES` |>
filter(REF_AREA == "FE",
NATURE == "VALEUR_ABSOLUE",
ACTIVITE_CREAT_ENT %in% c("ENS", "BE", "AZ"),
CORRECTION == "CVS-CJO",
FREQ == "M") |>
month_to_date() |>
ggplot() + ylab("Défaillances d'entreprises") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Activite_creat_ent)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.8),
legend.title = element_blank()) +
scale_y_log10(breaks = c(100, 200, 300, 500, 800, 10, 20, 30, 50, 1000, 2000, 3000, 5000, 10000),
labels = dollar_format(accuracy = 1, prefix = ""))
`DEFAILLANCES-ENTREPRISES` |>
filter(REF_AREA == "FE",
NATURE == "VALEUR_ABSOLUE",
ACTIVITE_CREAT_ENT %in% c("ENS", "BE", "AZ"),
CORRECTION == "CVS-CJO",
FREQ == "M") |>
month_to_date() |>
filter(date >= as.Date("2017-01-01")) |>
group_by(ACTIVITE_CREAT_ENT) |>
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2017-01-01")]) |>
ggplot() + ylab("Défaillances d'entreprises (100 = 2017)") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Activite_creat_ent)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2100, 1) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.2),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(10, 200, 10),
labels = dollar_format(accuracy = 1, prefix = ""))