Conjoncture dans les travaux publics

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee ENQ-CONJ-TP 2024-11-05 2024-11-09

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 2024-11-09 2024-11-09
insee ENQ-CONJ-ART-BAT 2024-11-09 2024-11-09
insee ENQ-CONJ-IND-BAT 2024-11-09 2024-11-09
insee ENQ-CONJ-PROMO-IMMO 2024-11-09 2024-11-09
insee ENQ-CONJ-TP 2024-11-05 2024-11-09
insee ILC-ILAT-ICC 2024-11-05 2024-11-09
insee INDICES_LOYERS 2024-11-05 2024-11-09
insee IPLA-IPLNA-2015 2024-11-05 2024-11-09
insee IRL 2024-11-05 2024-11-09
insee PARC-LOGEMENTS 2024-11-05 2023-12-03
insee SERIES_LOYERS 2024-11-05 2024-11-09
insee t_dpe_val 2024-11-05 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",
         CORRECTION == "CVS") %>%
  left_join(CLIENTELE_ECB, by = "CLIENTELE_ECB") %>%
  quarter_to_date %>%
  arrange(desc(date)) %>%
  mutate(OBS_VALUE = OBS_VALUE / 100) %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE, color = Clientele_ecb)) +
  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))