Last observation: M: 2026-06-30 (N = 73) · Q: 2026-03-31 (N = 97)
First observation: M: 1989-12-31 (N = 8) · Q: 2008-03-31 (N = 97)
Last data update: 16 aoû 2026, 00:27. Last compile: 18 aoû 2026, 00:11
Données - BDF
Last observation: M: 2026-06-30 (N = 73) · Q: 2026-03-31 (N = 97)
First observation: M: 1989-12-31 (N = 8) · Q: 2008-03-31 (N = 97)
Last data update: 16 aoû 2026, 00:27. Last compile: 18 aoû 2026, 00:11
| LAST_DOWNLOAD |
|---|
| 2026-08-15 |
SC1 |>
filter(REF_AREA == "FR",
SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
SEC_ITEM == "F33000",
DATA_TYPE_SEC == "1",
CURRENCY == "Z01",
SERIES_DENOM == "E",
SEC_SUFFIX == "Z",
FREQ == "Q") |>
mutate(Secteur = recode(SEC_ISSUING_SECTOR,
"100Z" = "Ensemble des résidents",
"1100" = "Sociétés non financières",
"122Z" = "Établissements de crédit",
"123Z" = "Autres organismes financiers",
"1300" = "Administrations publiques")) |>
arrange(date) |>
ggplot() + geom_line(aes(x = date, y = value / 1000, color = Secteur)) +
theme_minimal() + xlab("") + ylab("Md €") +
scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(labels = dollar_format(prefix = "", suffix = " Md€")) +
theme(legend.position = c(0.25, 0.75),
legend.title = element_blank())
SC1 |>
filter(REF_AREA == "FR",
SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
SEC_ITEM == "F33000",
DATA_TYPE_SEC == "1",
CURRENCY == "Z01",
SERIES_DENOM == "E",
SEC_SUFFIX == "Z",
FREQ == "Q") |>
filter(date >= Sys.Date() - years(5)) |>
mutate(Secteur = recode(SEC_ISSUING_SECTOR,
"100Z" = "Ensemble des résidents",
"1100" = "Sociétés non financières",
"122Z" = "Établissements de crédit",
"123Z" = "Autres organismes financiers",
"1300" = "Administrations publiques")) |>
arrange(date) |>
ggplot() + geom_line(aes(x = date, y = value / 1000, color = Secteur)) +
theme_minimal() + xlab("") + ylab("Md €") +
scale_x_date(breaks = "6 months",
labels = date_format("%b %Y")) +
scale_y_continuous(labels = dollar_format(prefix = "", suffix = " Md€")) +
theme(legend.position = c(0.25, 0.75),
legend.title = element_blank(),
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
SC1 |>
filter(REF_AREA == "FR",
SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
SEC_ITEM == "F33000",
DATA_TYPE_SEC == "4",
CURRENCY == "Z01",
SERIES_DENOM == "M",
SEC_SUFFIX == "Z",
FREQ == "M") |>
mutate(Secteur = recode(SEC_ISSUING_SECTOR,
"100Z" = "Ensemble des résidents",
"1100" = "Sociétés non financières",
"122Z" = "Établissements de crédit",
"123Z" = "Autres organismes financiers",
"1300" = "Administrations publiques")) |>
arrange(date) |>
ggplot() + geom_line(aes(x = date, y = value / 1000, color = Secteur)) +
theme_minimal() + xlab("") + ylab("Cumul sur 12 mois, Md €") +
scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(labels = dollar_format(prefix = "", suffix = " Md€")) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black") +
theme(legend.position = c(0.25, 0.8),
legend.title = element_blank())
SC1 |>
filter(REF_AREA == "FR",
SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
SEC_ITEM == "F33000",
DATA_TYPE_SEC == "1",
CURRENCY == "Z01",
SERIES_DENOM == "E",
SEC_SUFFIX == "Z",
FREQ == "Q") |>
mutate(Secteur = recode(SEC_ISSUING_SECTOR,
"100Z" = "Ensemble des résidents",
"1100" = "Sociétés non financières",
"122Z" = "Établissements de crédit",
"123Z" = "Autres organismes financiers",
"1300" = "Administrations publiques")) |>
filter(date == max(date)) |>
transmute(Secteur, `Encours (Md €)` = round(value / 1000, 1), Date = date) |>
arrange(desc(`Encours (Md €)`)) |>
print_table_conditional()| Secteur | Encours (Md €) | Date |
|---|---|---|
| Ensemble des résidents | 5748.5 | 2026-03-31 |
| Administrations publiques | 3138.3 | 2026-03-31 |
| Établissements de crédit | 1506.0 | 2026-03-31 |
| Sociétés non financières | 742.3 | 2026-03-31 |
| Autres organismes financiers | 361.9 | 2026-03-31 |