source | dataset | .html | .RData |
---|---|---|---|
insee | ENQ-CONJ-TP | 2024-04-18 | 2024-05-09 |
source | dataset | .html | .RData |
---|---|---|---|
acpr | as151 | 2024-04-05 | 2024-04-05 |
bdf | BSI1 | 2024-05-08 | 2024-05-08 |
bdf | CPP | 2024-05-08 | 2024-05-08 |
bdf | FM | 2024-05-08 | 2024-05-08 |
bdf | immobilier | 2024-05-08 | 2024-05-07 |
bdf | MIR | 2024-05-08 | 2024-05-08 |
bdf | MIR1 | 2024-05-08 | 2024-05-08 |
bdf | RPP | 2024-05-08 | 2024-05-08 |
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 | 2024-04-18 | 2024-05-09 |
insee | ILC-ILAT-ICC | 2024-04-18 | 2024-05-09 |
insee | INDICES_LOYERS | 2024-04-18 | 2024-05-09 |
insee | IPLA-IPLNA-2015 | 2024-04-18 | 2024-05-09 |
insee | IRL | 2024-04-18 | 2024-05-09 |
insee | PARC-LOGEMENTS | 2024-04-18 | 2023-12-03 |
insee | SERIES_LOYERS | 2024-04-18 | 2024-05-09 |
insee | t_dpe_val | 2024-04-18 | 2024-03-04 |
notaires | arrdt | 2024-04-08 | 2024-04-08 |
notaires | dep | 2024-04-08 | 2024-04-08 |
`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 | 5849 |
`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 | 2841 |
PR | Clientèle privée | 1504 |
PU | Clientèle publique | 1504 |
`ENQ-CONJ-TP` %>%
group_by(UNIT_MEASURE) %>%
summarise(Nobs = n()) %>%
{if (is_html_output()) print_table(.) else .}
UNIT_MEASURE | Nobs |
---|---|
POURCENT | 5849 |
`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))