Conjoncture dans l’industrie du bâtiment - ENQ-CONJ-IND-BAT

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee ENQ-CONJ-IND-BAT 2024-11-22 2024-12-22

Données sur l’immobilier

source dataset .html .RData
acpr as151 2024-06-19 2024-04-05
bdf BSI1 2024-12-09 2024-12-09
bdf CPP 2024-07-26 2024-07-01
bdf FM 2024-12-22 2024-12-22
bdf immobilier 2024-11-19 2024-11-19
bdf MIR 2024-07-26 2024-07-01
bdf MIR1 2024-11-29 2024-12-09
bdf RPP 2024-11-19 2024-11-19
cgedd nombre-vente-maison-appartement-ancien 2024-09-26 2024-09-26
insee CONSTRUCTION-LOGEMENTS 2024-12-22 2024-12-22
insee ENQ-CONJ-ART-BAT 2024-12-22 2024-12-22
insee ENQ-CONJ-IND-BAT 2024-11-22 2024-12-22
insee ENQ-CONJ-PROMO-IMMO 2024-11-22 2024-12-22
insee ENQ-CONJ-TP 2024-11-22 2024-12-22
insee ILC-ILAT-ICC 2024-11-22 2024-12-22
insee INDICES_LOYERS 2024-11-22 2024-12-22
insee IPLA-IPLNA-2015 2024-11-22 2024-12-22
insee IRL 2024-11-22 2024-12-22
insee PARC-LOGEMENTS 2024-11-22 2023-12-03
insee SERIES_LOYERS 2024-11-22 2024-12-22
insee t_dpe_val 2024-11-22 2024-12-21
notaires arrdt 2024-06-30 2024-09-09
notaires dep 2024-06-30 2024-09-08

LAST_UPDATE

Code 
`ENQ-CONJ-IND-BAT` %>%
  group_by(LAST_UPDATE) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
LAST_UPDATE Nobs
2024-12-19 59307
2024-10-24 10398
2016-10-25 1336

TITLE_FR

Code 
`ENQ-CONJ-IND-BAT` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

INDICATEUR

Code 
`ENQ-CONJ-IND-BAT` %>%
  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-IND-BAT` %>%
  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 63090
PROPORTION Proportion 7014
INDICE Indice 937

UNIT_MEASURE

Code 
`ENQ-CONJ-IND-BAT` %>%
  group_by(UNIT_MEASURE) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
UNIT_MEASURE Nobs
MOIS 3582
POURCENT 66522
SO 937

TIME_PERIOD / date

Code 
`ENQ-CONJ-IND-BAT` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

Difficultés de recrutement

ECB_DREC_ENT

Brut

Code 
`ENQ-CONJ-IND-BAT` %>%
  filter(INDICATEUR == "ECB_DREC_ENT",
         CORRECTION == "BRUT") %>%
  left_join(ACTIVITE_ECB, by = "ACTIVITE_ECB") %>%
  quarter_to_date() %>%
  arrange(desc(date)) %>%
  mutate(OBS_VALUE = OBS_VALUE / 100) %>%
  ggplot + theme_minimal() + xlab("") + ylab("Difficultés de recrutement (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Activite_ecb)) +
  scale_x_date(breaks = seq(1960, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-500, 200, 5),
                     labels = percent_format(accuracy = 1))

CVS

Code 
`ENQ-CONJ-IND-BAT` %>%
  filter(INDICATEUR == "ECB_DREC_ENT",
         CORRECTION == "CVS") %>%
  left_join(ACTIVITE_ECB, by = "ACTIVITE_ECB") %>%
  quarter_to_date() %>%
  arrange(desc(date)) %>%
  mutate(OBS_VALUE = OBS_VALUE / 100) %>%
  ggplot + theme_minimal() + xlab("") + ylab("Difficultés de recrutement (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Activite_ecb)) +
  scale_x_date(breaks = seq(1960, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-500, 200, 5),
                     labels = percent_format(accuracy = 1))

Par Type

Code 
`ENQ-CONJ-IND-BAT` %>%
  filter(INDICATEUR %in% c("ECB_DMAN", "ECB_DQUA", "ECB_DSPE", "ECB_DTEC")) %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  quarter_to_date() %>%
  mutate(OBS_VALUE = OBS_VALUE / 100) %>%
  ggplot + theme_minimal() + xlab("") + ylab("Difficultés de recrutement (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Indicateur)) +
  scale_x_date(breaks = seq(1960, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.65, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-500, 200, 5),
                     labels = percent_format(accuracy = 1))