Taux d’intérêt - France

Data - BDF

Author

François Geerolf

Info

theme Title .html
taux-dinteret Données de taux d'intérêt 2025-01-22

LAST_COMPILE

source dataset .html .RData
bdf MIR1 2025-01-22 2025-01-22

Last

date Nobs
2025-01-31 5
2024-12-31 5

BS_COUNT_SECTOR

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(BS_COUNT_SECTOR, by = "BS_COUNT_SECTOR") %>%
  group_by(BS_COUNT_SECTOR, Bs_count_sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
BS_COUNT_SECTOR Bs_count_sector Nobs
2230U6 Ménages et SNF résidents 1418
2250U6 Ménages et ISBLSM résidents 1174
2254U6 Particuliers résidents 496

FREQ

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(FREQ, by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
FREQ Freq Nobs
M Mensuel 3088

BS_ITEM

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(BS_ITEM, by = "BS_ITEM") %>%
  group_by(BS_ITEM, Bs_item) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

MATURITY_ORIG

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(MATURITY_ORIG, by = "MATURITY_ORIG") %>%
  group_by(MATURITY_ORIG, Maturity_orig) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

DATA_TYPE_MIR

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(DATA_TYPE_MIR, by = "DATA_TYPE_MIR") %>%
  group_by(DATA_TYPE_MIR, Data_type_mir) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
DATA_TYPE_MIR Data_type_mir Nobs
R Taux annuel 3088

REF_AREA

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
REF_AREA Ref_area Nobs
FR France 3088

Taux de rémunération

Nobs

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  filter(grepl("Taux moyen de rémunération annuel", Variable)) %>%
  group_by(variable, Variable) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
variable Variable Nobs
NA NA NA
:--------: :--------: :----:

Taux de rémunération des dépôts + immobilier

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.L20.A.C.A.2300U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L20.L.C.A.2300U6.EUR.O", variable)) %>%
  na.omit %>%
  left_join(MIR1_var, by = "variable") %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.55, 0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, .1),
                labels = percent_format(accuracy = .1))

Taux

Nobs

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  filter(FREQ == "M",
         REF_AREA == "FR",
         BS_ITEM == "A22") %>%
  group_by(variable, Variable) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
variable Variable Nobs
NA NA NA
:--------: :--------: :----:

Livrets réglementés

-Info. html

Taux SNF

Table SNF

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  filter(BS_COUNT_SECTOR == "2240U6") %>%
  group_by(Variable) %>%
  summarise(Nobs = n(),
            date = last(date),
            value = last(value)) %>%
  print_table_conditional
Variable Nobs date value
NA NA NA NA
:--------: :----: :----: :-----:

Catégories montants

Tous

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A20.A.R.0.2240U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A20.A.R.1.2240U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A20.A.R.A.2240U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(AMOUNT_CAT, by = "AMOUNT_CAT") %>%
  arrange(desc(date)) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Amount_cat)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1))

2010-

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A20.A.R.0.2240U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A20.A.R.1.2240U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A20.A.R.A.2240U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(AMOUNT_CAT, by = "AMOUNT_CAT") %>%
  arrange(desc(date)) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Amount_cat)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.5),
                labels = percent_format(accuracy = .1))

Catégories montants

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A20.A.R.0.2240U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A20.A.R.1.2240U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A20.A.R.A.2240U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  left_join(AMOUNT_CAT, by = "AMOUNT_CAT") %>%
  arrange(desc(date)) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Amount_cat)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1))

Livrets réglementés (avec LDDS)

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.L23FRLA.D.R.A.2230U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23RJ.A.R.A.2300.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLJ.A.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLP.H.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L22FRSP.H.R.A.2250U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  arrange(desc(date)) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.17),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux de rémunération annuel (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1))

Livrets réglementés

Tous

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.L23FRLA.D.R.A.2230U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23RJ.A.R.A.2300.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLJ.A.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLP.H.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L22FRSP.H.R.A.2250U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  arrange(desc(date)) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.17),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux de rémunération annuel (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1))

2000-

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.L23FRLA.D.R.A.2230U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23RJ.A.R.A.2300.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLJ.A.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLP.H.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L22FRSP.H.R.A.2250U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  arrange(desc(date)) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux de rémunération annuel (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1))

2010-

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.L23FRLA.D.R.A.2230U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23RJ.A.R.A.2300.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLJ.A.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLP.H.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L22FRSP.H.R.A.2250U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  arrange(desc(date)) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.8),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux de rémunération annuel (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.5),
                labels = percent_format(accuracy = .1))

2018-

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.L23FRLA.D.R.A.2230U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23RJ.A.R.A.2300.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLJ.A.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L23FRLP.H.R.A.2250U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.L22FRSP.H.R.A.2250U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  arrange(desc(date)) %>%
  filter(date >= as.Date("2018-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.8),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux de rémunération annuel (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.5),
                labels = percent_format(accuracy = .1))

Taux crédits habitat

Tous

Code 
MIR1 %>%
  left_join(MIR1_var, by = "variable") %>%
  filter(FREQ == "M",
         REF_AREA == "FR",
         BS_REP_SECTOR == "B",
         BS_ITEM == "A2C",
         DATA_TYPE_MIR == "R",
         AMOUNT_CAT == "A",
         BS_COUNT_SECTOR == "2250U6",
         CURRENCY_TRANS == "EUR",
         IR_BUS_COV == "N") %>%
  left_join(MATURITY_ORIG, by = "MATURITY_ORIG") %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Maturity_orig)) +
  
  theme_minimal() + xlab("") + ylab("Taux d'intérêt (%)") +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.15),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1))

Tous

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A22.K.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.F.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.A.R.A.2254U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.15),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1))

2016-

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A22.K.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.F.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.A.R.A.2254U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  filter(date >= as.Date("2016-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, .1),
                labels = percent_format(accuracy = .1))

2018-

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A22.K.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.F.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.A.R.A.2254U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  filter(date >= as.Date("2018-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, .1),
                labels = percent_format(accuracy = .1))

Taux de rémunération des dépôts + immobilier

Tous

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.A.N30.A.R.A.2230U6.EUR.O", variable) |
           grepl("MIR1.M.FR.B.A22.A.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.L21.A.R.A.2230U6.EUR.O", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.55, 0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1),
                limits = c(0, 0.07))

Part des renégociations

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A22PR.A.W.A.2254FR.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  na.omit %>%
  ggplot + geom_line(aes(x = date, y = value/100)) +
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.15),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Part des renégo dans le total des crédits à l'habitat (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                labels = percent_format(accuracy = 1))

Volumes de crédit

Crédits à la consommation

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A2Z.A.R.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A2B.A.R.A.2254U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(accuracy = 1),
                limits = c(0.03, 0.15))

Crédits nouveaux à l’habitat

Tous

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A22HR.A.5.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.A.5.A.2254U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(0, 100, 2))

2015-

Code 
MIR1 %>%
  filter(grepl("MIR1.M.FR.B.A22HR.A.5.A.2254U6.EUR.N", variable) |
           grepl("MIR1.M.FR.B.A22.A.5.A.2254U6.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(0, 100, 2))

Taux d’usure

2017-

Code 
MIR1 %>%
  filter(grepl("MIR1.Q.FR.R.A22FRF.Q.U.A.2254FR.EUR.N", variable) |
           grepl("MIR1.Q.FR.R.A22FRF.R.U.A.2254FR.EUR.N", variable) |
           grepl("MIR1.Q.FR.R.A22FRF.S.U.A.2254FR.EUR.N", variable)) %>%
  left_join(MIR1_var, by = "variable") %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) +
  theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Taux d'intérêt (%)") +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.1),
                labels = percent_format(accuracy = .1))

Pour en savoir plus…

Données sur les taux d’intérêt

source dataset .html .RData
bdf FM 2025-01-22 2025-01-22
bdf MIR 2025-01-22 2024-07-01
bdf MIR1 2025-01-22 2025-01-22
bis CBPOL_D 2025-01-10 2024-05-10
bis CBPOL_M 2025-01-10 2024-04-19
ecb FM 2025-01-10 2025-01-10
ecb MIR 2024-06-19 2025-01-10

Données sur l’immobilier

source dataset .html .RData
acpr as151 2024-06-19 2024-04-05
bdf BSI1 2025-01-13 2025-01-13
bdf CPP 2025-01-05 2024-07-01
bdf FM 2025-01-22 2025-01-22
bdf immobilier 2025-01-05 2024-11-19
bdf MIR 2025-01-22 2024-07-01
bdf MIR1 2025-01-22 2025-01-22
bdf RPP 2025-01-05 2024-11-19
cgedd nombre-vente-maison-appartement-ancien 2024-09-26 2024-09-26
insee CONSTRUCTION-LOGEMENTS 2025-01-07 2025-01-05
insee ENQ-CONJ-ART-BAT 2025-01-07 2025-01-05
insee ENQ-CONJ-IND-BAT 2025-01-07 2025-01-05
insee ENQ-CONJ-PROMO-IMMO 2025-01-07 2025-01-05
insee ENQ-CONJ-TP 2025-01-07 2025-01-05
insee ILC-ILAT-ICC 2025-01-07 2025-01-05
insee INDICES_LOYERS 2025-01-07 2025-01-05
insee IPLA-IPLNA-2015 2025-01-07 2025-01-05
insee IRL 2025-01-07 2025-01-05
insee PARC-LOGEMENTS 2025-01-07 2023-12-03
insee SERIES_LOYERS 2025-01-07 2025-01-05
insee t_dpe_val 2025-01-07 2025-01-13
notaires arrdt 2025-01-05 2025-01-05
notaires dep 2025-01-05 2025-01-05