source | dataset | .html | .RData |
---|---|---|---|
insee | ENQ-CONJ-TP | 2024-10-29 | 2024-11-05 |
Conjoncture dans les travaux publics
Data - Insee
Info
Info
- Octobre 2023. html
Données sur l’immobilier
source | dataset | .html | .RData |
---|---|---|---|
acpr | as151 | 2024-06-19 | 2024-04-05 |
bdf | BSI1 | 2024-07-26 | 2024-06-14 |
bdf | CPP | 2024-07-26 | 2024-07-01 |
bdf | FM | 2024-07-26 | 2024-10-16 |
bdf | immobilier | 2024-07-26 | 2024-06-18 |
bdf | MIR | 2024-07-26 | 2024-07-01 |
bdf | MIR1 | 2024-10-16 | 2024-10-16 |
bdf | RPP | 2024-07-26 | 2024-07-01 |
cgedd | nombre-vente-maison-appartement-ancien | 2024-09-26 | 2024-09-26 |
insee | CONSTRUCTION-LOGEMENTS | 2024-11-05 | 2024-11-05 |
insee | ENQ-CONJ-ART-BAT | 2024-11-05 | 2024-11-05 |
insee | ENQ-CONJ-IND-BAT | 2024-11-05 | 2024-11-05 |
insee | ENQ-CONJ-PROMO-IMMO | 2024-11-05 | 2024-11-05 |
insee | ENQ-CONJ-TP | 2024-10-29 | 2024-11-05 |
insee | ILC-ILAT-ICC | 2024-10-29 | 2024-11-05 |
insee | INDICES_LOYERS | 2024-10-29 | 2024-11-05 |
insee | IPLA-IPLNA-2015 | 2024-10-29 | 2024-11-05 |
insee | IRL | 2024-10-29 | 2024-11-05 |
insee | PARC-LOGEMENTS | 2024-10-29 | 2023-12-03 |
insee | SERIES_LOYERS | 2024-10-29 | 2024-11-05 |
insee | t_dpe_val | 2024-10-29 | 2024-09-02 |
notaires | arrdt | 2024-06-30 | 2024-09-09 |
notaires | dep | 2024-06-30 | 2024-09-08 |
TITLE_FR
Code
`ENQ-CONJ-TP` %>%
group_by(IDBANK, TITLE_FR) %>%
summarise(Nobs = n(),
date1 = first(TIME_PERIOD),
date2 = last(TIME_PERIOD)) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
INDICATEUR
Code
`ENQ-CONJ-TP` %>%
left_join(INDICATEUR, by = "INDICATEUR") %>%
group_by(INDICATEUR, Indicateur) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
NATURE
Code
`ENQ-CONJ-TP` %>%
left_join(NATURE, by = "NATURE") %>%
group_by(NATURE, Nature) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
NATURE | Nature | Nobs |
---|---|---|
SOLDE_PROPORTION | Solde d'opinions | 6863 |
CLIENTELE_ECB
Code
`ENQ-CONJ-TP` %>%
left_join(CLIENTELE_ECB, by = "CLIENTELE_ECB") %>%
group_by(CLIENTELE_ECB, Clientele_ecb) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
CLIENTELE_ECB | Clientele_ecb | Nobs |
---|---|---|
EN | Ensemble | 3823 |
PR | Clientèle privée | 1520 |
PU | Clientèle publique | 1520 |
UNIT_MEASURE
Code
`ENQ-CONJ-TP` %>%
group_by(UNIT_MEASURE) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) print_table(.) else .} {
UNIT_MEASURE | Nobs |
---|---|
POURCENT | 6863 |
Niveau du carnet de commandes
Ensemble
Code
`ENQ-CONJ-TP` %>%
filter(INDICATEUR == "ECB_04",
== "CVS") %>%
CORRECTION left_join(CLIENTELE_ECB, by = "CLIENTELE_ECB") %>%
%>%
quarter_to_date arrange(desc(date)) %>%
mutate(OBS_VALUE = OBS_VALUE / 100) %>%
+ geom_line(aes(x = date, y = OBS_VALUE, color = Clientele_ecb)) +
ggplot theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-500, 200, 5),
labels = percent_format(accuracy = 1))