Prix de l’immobilier
Data - BDF
François Geerolf
Info
| source | dataset | .html | .RData |
|---|---|---|---|
| bdf | RPP | 2024-05-08 | 2024-05-10 |
Données sur l’immobilier
| source | dataset | .html | .RData |
|---|---|---|---|
| acpr | as151 | 2024-04-05 | 2024-04-05 |
| bdf | BSI1 | 2024-05-08 | 2024-05-08 |
| bdf | CPP | 2024-05-10 | 2024-05-10 |
| bdf | FM | 2024-05-10 | 2024-05-08 |
| bdf | immobilier | 2024-05-10 | 2024-05-07 |
| bdf | MIR | 2024-05-10 | 2024-05-10 |
| bdf | MIR1 | 2024-05-10 | 2024-05-10 |
| bdf | RPP | 2024-05-08 | 2024-05-10 |
| insee | CONSTRUCTION-LOGEMENTS | 2024-05-09 | 2024-05-09 |
| insee | ENQ-CONJ-ART-BAT | 2024-05-09 | 2023-10-25 |
| insee | ENQ-CONJ-IND-BAT | 2024-05-09 | 2024-05-09 |
| insee | ENQ-CONJ-PROMO-IMMO | 2024-05-09 | 2024-05-09 |
| insee | ENQ-CONJ-TP | 2024-05-09 | 2024-05-09 |
| insee | ILC-ILAT-ICC | 2024-05-09 | 2024-05-09 |
| insee | INDICES_LOYERS | 2024-05-09 | 2024-05-09 |
| insee | IPLA-IPLNA-2015 | 2024-05-09 | 2024-05-09 |
| insee | IRL | 2024-05-09 | 2024-05-09 |
| insee | PARC-LOGEMENTS | 2024-05-09 | 2023-12-03 |
| insee | SERIES_LOYERS | 2024-05-09 | 2024-05-09 |
| insee | t_dpe_val | 2024-05-09 | 2024-03-04 |
| notaires | arrdt | 2024-04-08 | 2024-04-08 |
| notaires | dep | 2024-04-08 | 2024-04-08 |
Data on housing
| source | dataset | .html | .RData |
|---|---|---|---|
| bdf | RPP | 2024-05-08 | 2024-05-10 |
| bis | LONG_PP | 2024-04-19 | 2024-04-19 |
| bis | SELECTED_PP | 2024-04-19 | 2024-04-19 |
| ecb | RPP | 2024-04-19 | 2024-04-19 |
| eurostat | ei_hppi_q | 2024-05-09 | 2024-05-09 |
| eurostat | hbs_str_t223 | 2024-05-09 | 2024-05-09 |
| eurostat | prc_hicp_midx | 2024-05-09 | 2024-05-09 |
| eurostat | prc_hpi_q | 2024-05-09 | 2024-05-09 |
| fred | housing | 2024-04-26 | 2024-04-26 |
| insee | IPLA-IPLNA-2015 | 2024-05-09 | 2024-05-09 |
| oecd | housing | 2024-04-16 | 2020-01-18 |
| oecd | SNA_TABLE5 | 2024-04-16 | 2023-10-19 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2024-05-10 |
Last
| date | Nobs |
|---|---|
| 2023-10-01 | 4 |
variable
RPP %>%
left_join(RPP_var, by = "variable") %>%
group_by(variable, Variable) %>%
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}| variable | Variable | Nobs |
|---|---|---|
| RPP.Q.FR.N.ED.00.1.00 | Indices des prix des logements anciens, Ensemble des logements, France métropolitaine | 111 |
| RPP.Q.FR.N.EF.CC.1.00 | Indices des prix des logements anciens, Appartements, Paris | 127 |
| RPP.Q.FR.N.EF.CS.1.00 | Indices des prix des logements anciens, Appartements, Ile de France Petite Couronne | 127 |
| RPP.Q.FR.N.NF.00.1.00 | Prix au mètre carré des appartements neufs, France entière | 116 |
| RPP.Q.FR.N.NF.CR.1.00 | Prix au mètre carré des appartements neufs, Ile de France | 76 |
| RPP.Q.FR.N.NH.00.1.00 | Prix de vente moyen d’une maison neuve, France entière | 116 |
| RPP.Q.FR.N.NH.CR.1.00 | Prix de vente moyen d’une maison neuve, Ile de France | 76 |
RPP_DWELLING
RPP %>%
left_join(RPP_var, by = "variable") %>%
left_join(RPP_DWELLING, by = "RPP_DWELLING") %>%
group_by(RPP_DWELLING, Rpp_dwelling) %>%
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}| RPP_DWELLING | Rpp_dwelling | Nobs |
|---|---|---|
| ED | Residential property prices, Existing dwellings | 111 |
| EF | Residential property prices, Existing flats | 254 |
| NF | Residential property prices, New flats | 192 |
| NH | Residential property prices, New houses | 192 |
RPP_GEO_COV
RPP %>%
left_join(RPP_var, by = "variable") %>%
left_join(RPP_GEO_COV, by = "RPP_GEO_COV") %>%
group_by(RPP_GEO_COV, Rpp_geo_cov) %>%
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}| RPP_GEO_COV | Rpp_geo_cov | Nobs |
|---|---|---|
| 00 | Whole country | 343 |
| CC | Capital city | 127 |
| CR | Capital Region | 152 |
| CS | Capital city and suburbs | 127 |
RPP_SOURCE
RPP %>%
left_join(RPP_var, by = "variable") %>%
left_join(RPP_SOURCE, by = "RPP_SOURCE") %>%
group_by(RPP_SOURCE, Rpp_source) %>%
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}| RPP_SOURCE | Rpp_source | Nobs |
|---|---|---|
| 1 | NSI | 749 |
Prix au mètre carré des appartements neufs
France entière, Ile de France
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING == "NF") %>%
mutate(Variable = gsub("Prix au mètre carré des appartements neufs, ", "", Variable)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix au mètre carré des appartements neufs") +
scale_y_log10(breaks = seq(0, 7000, 500),
labels = dollar_format(suffix = " €/m2", prefix = "", accuracy = 1))
Indices de prix des logements anciens
100 = 2009
Log
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
group_by(Variable) %>%
mutate(value = 100*value/value[date == as.Date("2008-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_log10(breaks = seq(0, 7000, 10))
Lineaire
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_continuous(breaks = seq(0, 7000, 10))
100 = 2015
Log
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_log10(breaks = seq(0, 7000, 10))
Lineaire
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_continuous(breaks = seq(0, 7000, 10))
100 = 2001
Log
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
group_by(Variable) %>%
filter(date >= as.Date("2001-01-01")) %>%
mutate(value = 100*value/value[date == as.Date("2001-01-01")]) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_log10(breaks = seq(0, 7000, 10))
Lineaire
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
group_by(Variable) %>%
filter(date >= as.Date("2001-01-01")) %>%
mutate(value = 100*value/value[date == as.Date("2001-01-01")]) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_continuous(breaks = seq(0, 7000, 10))
100 = 1998
Lineaire
plot_lineaire <- RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
group_by(Variable) %>%
filter(date >= as.Date("1998-01-01")) %>%
mutate(value = 100*value/value[date == as.Date("1998-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_continuous(breaks = seq(0, 7000, 50))
plot_lineaire
100 = 1999
Lineaire
plot_lineaire <- RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
group_by(Variable) %>%
filter(date >= as.Date("1999-01-01")) %>%
mutate(value = 100*value/value[date == as.Date("1999-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1999, 2030, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_continuous(breaks = seq(0, 7000, 50))
plot_lineaire
100 = 2000
Paris, IDF, France
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF"),
date >= as.Date("2000-01-01")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
group_by(Variable) %>%
mutate(value = 100*value/value[date == as.Date("2000-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens") +
scale_y_log10(breaks = seq(0, 7000, 50))
Paris, France
Lineaire
plot_lineaire <- RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF"),
date >= as.Date("1999-01-01"),
RPP_GEO_COV %in% c("CC", "00")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
group_by(Variable) %>%
mutate(value = 100*value/value[date == as.Date("1999-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() + xlab("") + ylab("Indice des prix des logements anciens") +
scale_x_date(breaks = seq(1999, 2030, 5) %>% paste0(., "-01-01") %>% as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(0, 7000, 50))
plot_lineaire
100 = 2007
Paris, IDF, France
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF"),
date >= as.Date("2008-01-01")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
group_by(Variable) %>%
mutate(value = 100*value/value[date == as.Date("2008-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens (2008 = 100") +
scale_y_log10(breaks = seq(0, 7000, 10))
Paris, France
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING %in% c("ED", "EF"),
date >= as.Date("2008-01-01"),
RPP_GEO_COV %in% c("CC", "00")) %>%
mutate(Variable = gsub("Indices des prix des logements anciens, ", "", Variable)) %>%
group_by(Variable) %>%
mutate(value = 100*value/value[date == as.Date("2008-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix des logements anciens (2008 = 100") +
scale_y_log10(breaks = seq(0, 7000, 10))
Prix de vente moyen d’une maison neuve
RPP %>%
left_join(RPP_var, by = "variable") %>%
filter(RPP_DWELLING == "NH") %>%
mutate(Variable = gsub("Prix de vente moyen d'une maison neuve, ","", Variable)) %>%
ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix de vente moyen d'une maison neuve") +
scale_y_log10(breaks = seq(0, 7000, 20))