Prix au m^2 par arrondissement - arrdt
Data - Immobilier
Info
Données sur l’immobilier
| source | dataset | .html | .RData |
|---|---|---|---|
| acpr | as151 | 2024-06-19 | 2024-04-05 |
| bdf | BSI1 | 2025-01-05 | 2025-01-05 |
| bdf | CPP | 2025-01-05 | 2024-07-01 |
| bdf | FM | 2025-01-05 | 2025-01-05 |
| bdf | immobilier | 2025-01-05 | 2024-11-19 |
| bdf | MIR | 2025-01-05 | 2024-07-01 |
| bdf | MIR1 | 2024-11-29 | 2024-12-09 |
| bdf | RPP | 2025-01-05 | 2024-11-19 |
| cgedd | nombre-vente-maison-appartement-ancien | 2024-09-26 | 2024-09-26 |
| insee | CONSTRUCTION-LOGEMENTS | 2024-12-29 | 2024-12-29 |
| insee | ENQ-CONJ-ART-BAT | 2024-12-29 | 2024-12-29 |
| insee | ENQ-CONJ-IND-BAT | 2024-12-29 | 2024-12-29 |
| insee | ENQ-CONJ-PROMO-IMMO | 2024-12-29 | 2024-12-29 |
| insee | ENQ-CONJ-TP | 2024-12-29 | 2024-12-29 |
| insee | ILC-ILAT-ICC | 2024-12-29 | 2024-12-29 |
| insee | INDICES_LOYERS | 2024-12-29 | 2024-12-29 |
| insee | IPLA-IPLNA-2015 | 2024-12-29 | 2024-12-29 |
| insee | IRL | 2024-12-29 | 2024-12-29 |
| insee | PARC-LOGEMENTS | 2024-12-29 | 2023-12-03 |
| insee | SERIES_LOYERS | 2024-12-29 | 2024-12-29 |
| insee | t_dpe_val | 2024-12-29 | 2024-12-21 |
| notaires | arrdt | 2024-06-30 | 2025-01-05 |
| notaires | dep | 2024-06-30 | 2024-09-08 |
Data on housing
| source | dataset | .html | .RData |
|---|---|---|---|
| bdf | RPP | 2025-01-05 | 2024-11-19 |
| bis | LONG_PP | 2024-12-29 | 2024-05-10 |
| bis | SELECTED_PP | 2024-12-29 | 2024-10-31 |
| ecb | RPP | 2024-12-29 | 2024-12-29 |
| eurostat | ei_hppi_q | 2024-12-29 | 2024-12-29 |
| eurostat | hbs_str_t223 | 2024-11-23 | 2024-12-29 |
| eurostat | prc_hicp_midx | 2024-11-01 | 2025-01-05 |
| eurostat | prc_hpi_q | 2024-12-29 | 2024-10-09 |
| fred | housing | 2025-01-05 | 2025-01-05 |
| insee | IPLA-IPLNA-2015 | 2024-12-29 | 2024-12-29 |
| oecd | housing | 2024-09-15 | 2020-01-18 |
| oecd | SNA_TABLE5 | 2024-09-11 | 2023-10-19 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2025-01-05 |
Last
Code
arrdt %>%
group_by(date) %>%
summarise(Nobs = n()) %>%
arrange(desc(date)) %>%
head(1) %>%
print_table_conditional()| date | Nobs |
|---|---|
| 2024-07-01 | 21 |
Exemples
2008-
Code
arrdt %>%
filter(date %in% c(as.Date("2008-01-01"), max(date))) %>%
spread(date, value) %>%
#setNames(c("Arrondissement", "2021T3", "2023T2")) %>%
mutate(`Croissance (%)` = round(100*(.[[3]]/.[[2]]-1), 1),
`Croissance (€)` = round(.[[3]]-.[[2]])) %>%
arrange(-`Croissance (%)`) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}2009Q2-
Code
arrdt %>%
filter(date %in% c(as.Date("2009-04-01"), max(date))) %>%
mutate(date = paste0("Prix m2 ", date)) %>%
spread(date, value) %>%
#setNames(c("Arrondissement", "2021T3", "2023T2")) %>%
mutate(`Croissance (%)` = round(100*(.[[3]]/.[[2]]-1), 1),
`Croissance (€)` = round(.[[3]]-.[[2]])) %>%
arrange(-`Croissance (%)`) %>%
rename(arrdt = Location) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}2008-2020
Code
arrdt %>%
filter(date %in% c(as.Date("2008-01-01"), as.Date("2020-01-01"))) %>%
spread(date, value) %>%
#setNames(c("Arrondissement", "2021T3", "2023T2")) %>%
mutate(`Croissance (%)` = round(100*(.[[3]]/.[[2]]-1), 1),
`Croissance (€)` = round(.[[3]]-.[[2]])) %>%
arrange(-`Croissance (%)`) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}2022T2-2023T2
Code
arrdt %>%
filter(date %in% c(as.Date("2022-04-01"), as.Date("2023-04-01"))) %>%
spread(date, value) %>%
#setNames(c("Arrondissement", "2021T3", "2023T2")) %>%
mutate(`Croissance (%)` = round(100*(.[[3]]/.[[2]]-1), 1),
`Croissance (€)` = round(.[[3]]-.[[2]])) %>%
arrange(-`Croissance (%)`) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}2021T3-2023T2
Code
arrdt %>%
filter(date %in% c(as.Date("2021-07-01"), as.Date("2023-04-01"))) %>%
spread(date, value) %>%
#setNames(c("Arrondissement", "2021T3", "2023T2")) %>%
mutate(`Croissance (%)` = round(100*(.[[3]]/.[[2]]-1), 1),
`Croissance (€)` = round(.[[3]]-.[[2]])) %>%
arrange(-`Croissance (%)`) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}100 = 2008
Code
arrdt %>%
filter(Location %in% c("Centre", "6e", "10e")) %>%
group_by(Location) %>%
mutate(value = 100*value/value[date == as.Date("2008-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Location)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix au mètre carré (2008 = 100") +
scale_y_log10(breaks = seq(0, 7000, 10))
Carte arrondissements
Code
i_g("bib/france/arrondissements-paris-2.jpg")
Prix mètre carré
13ème, 14ème, 15ème arrondissement
All
Code
arrdt %>%
filter(Location %in% c("13e", "14e", "15e")) %>%
group_by(Location) %>%
ggplot + geom_line(aes(x = date, y = value, color = gsub("e", "ème arrondissement", Location))) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix au mètre carré") +
scale_y_log10(breaks = seq(0, 17000, 1000),
labels = dollar_format(p = "", su = "€", a = 1))
2014-
Code
arrdt %>%
filter(Location %in% c("13e", "14e", "15e")) %>%
group_by(Location) %>%
filter(date >= as.Date("2014-01-01")) %>%
ggplot + geom_line(aes(x = date, y = value, color = gsub("e", "ème arrondissement", Location))) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix au mètre carré") +
scale_y_log10(breaks = seq(0, 17000, 1000),
labels = dollar_format(p = "", su = "€", a = 1))
2018-
Code
arrdt %>%
filter(Location %in% c("13e", "14e", "15e")) %>%
group_by(Location) %>%
filter(date >= as.Date("2018-01-01")) %>%
ggplot + geom_line(aes(x = date, y = value, color = gsub("e", "ème arrondissement", Location))) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix au mètre carré") +
scale_y_log10(breaks = seq(0, 17000, 200),
labels = dollar_format(p = "", su = "€", a = 1))
16ème, 6ème, 7ème arrondissement
Value
Code
arrdt %>%
filter(Location %in% c("16e", "6e", "7e")) %>%
group_by(Location) %>%
ggplot + geom_line(aes(x = date, y = value, color = gsub("e", "ème arrondissement", Location))) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix au mètre carré") +
scale_y_log10(breaks = seq(0, 17000, 1000),
labels = dollar_format(p = "", su = "€", a = 1))
100 = 2008
Code
arrdt %>%
filter(Location %in% c("16e", "6e", "7e")) %>%
group_by(Location) %>%
mutate(value = 100*value/value[date == as.Date("2008-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = gsub("e", "ème arrondissement", Location))) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix au mètre carré (2008 = 100)") +
scale_y_log10(breaks = seq(0, 7000, 10))
6ème, 5ème, 14ème arrondissement
Value
Code
arrdt %>%
filter(Location %in% c("6e", "5e", "14e")) %>%
group_by(Location) %>%
ggplot + geom_line(aes(x = date, y = value, color = gsub("e", "ème arrondissement", Location))) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix au mètre carré") +
scale_y_log10(breaks = seq(0, 17000, 1000),
labels = dollar_format(p = "", su = "€", a = 1))
100 = 2008
Code
arrdt %>%
filter(Location %in% c("6e", "5e", "14e")) %>%
group_by(Location) %>%
mutate(value = 100*value/value[date == as.Date("2008-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = gsub("e", "ème arrondissement", Location))) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix au mètre carré (2008 = 100)") +
scale_y_log10(breaks = seq(0, 7000, 10))
1er, 2ème, 3ème arrondissement
Value
Code
arrdt %>%
filter(Location %in% c("1er", "2e", "3e")) %>%
mutate(Location = case_when(Location == "1er" ~ "1er arrondissement",
Location == "2e" ~ "2ème arrondissement",
Location == "3e" ~ "3ème arrondissement")) %>%
group_by(Location) %>%
ggplot + geom_line(aes(x = date, y = value, color = Location)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Prix au mètre carré") +
scale_y_log10(breaks = seq(0, 17000, 1000),
labels = dollar_format(p = "", su = "€", a = 1))
100 = 2008
Code
arrdt %>%
filter(Location %in% c("1er", "2e", "3e")) %>%
mutate(Location = case_when(Location == "1er" ~ "1er arrondissement",
Location == "2e" ~ "2ème arrondissement",
Location == "3e" ~ "3ème arrondissement")) %>%
group_by(Location) %>%
mutate(value = 100*value/value[date == as.Date("2008-01-01")]) %>%
ggplot + geom_line(aes(x = date, y = value, color = Location)) +
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2050, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.85),
legend.title = element_blank()) +
xlab("") + ylab("Indice des prix au mètre carré (2008 = 100)") +
scale_y_log10(breaks = seq(0, 7000, 10))