Enquête annuelle du SGACPR sur le financement de l’habitat 2020

Data - ACPR

Author

François Geerolf

Info

source dataset .html .RData
acpr as124 2025-08-24 2021-12-26
acpr as151 2025-08-24 2024-04-05
  • Enquête sur le financement de l’habitat. html / xlsx

Production

Code 
i_g("bib/acpr/ACPR_production.png")

Encours

Code 
i_g("bib/acpr/ACPR_encours.png")

variable

Code 
as124 %>%
  group_by(Variable, Line) %>%
  summarise(Nobs = n()) %>%
  arrange(Line) %>%
  print_table_conditional()

year

Code 
as124 %>%
  group_by(year) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(year)) %>%
  print_table_conditional()
year Nobs
2020 74
2019 76
2018 76
2017 76
2016 76
2015 76
2014 76
2013 76
2012 76
2011 76
2010 76
2009 70
2008 70
2007 70
2006 70
2005 70
2004 70
2003 70
2002 70
2001 70

Taux d’effort moyen

Code 
as124 %>%
  year_to_date2 %>%
  filter(Line == 32) %>%
  ggplot + geom_line(aes(x = date, y = value)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  xlab("") + ylab("Taux d'effort moyen (%)") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = percent_format(a = 1))

Durée moyenne des prêts

Code 
as124 %>%
  year_to_date2 %>%
  filter(Line == 27) %>%
  ggplot + geom_line(aes(x = date, y = value)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  xlab("") + ylab("Durée moyenne des prêts") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = seq(0, 100, 1),
                     labels = dollar_format(a = 1, su = " ans", pre = ""))

Taux d’endettement moyen des emprunteurs à l’octroi

Code 
as124 %>%
  year_to_date2 %>%
  filter(Line == 43) %>%
  filter(value >0) %>%
  ggplot + geom_line(aes(x = date, y = value)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  xlab("") + ylab("Taux d'endettement moyen des emprunteurs à l'octroi") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_continuous(breaks = seq(0, 100, .2),
                     labels = dollar_format(a = .1, su = " ans", pre = ""))

Taux d’apport - Evolution

Legend

Code 
as124 %>%
  year_to_date2 %>%
  filter(Line %in% c(38, 39, 40, 41)) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Taux d'apport (%)") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

Nouvelle

Code 
date0 <- as.Date("2020-12-31")
date1 <- as.Date("2021-12-31")
as124 %>%
  year_to_date2 %>%
  filter(Line %in% c(38, 39, 40, 41)) %>%
  ggplot + geom_line(aes(x = date, y = value, color = paste0(Line))) +
  annotate("text", x = as.Date("2006-12-31"), y = 0.55, label= "Apport > 15% ", color = viridis(5)[1]) + 
  annotate("text", x = as.Date("2016-12-31"), y = 0.17, label= "5% < Apport < 15%", color = viridis(5)[2]) + 
  annotate("text", x = as.Date("2015-12-31"), y = 0.27, label= "0% < Apport < 5%", color = viridis(5)[3]) + 
  annotate("text", x = as.Date("2017-12-31"), y = 0.08, label= "Apport < 0% ", color = viridis(5)[4]) + 
  theme_minimal() + xlab("") + ylab("Part des emprunteurs (%)") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = "none")

Taux d’effort

Legend

Code 
date0 <- as.Date("2020-12-31")
date1 <- as.Date("2021-12-31")
as124 %>%
  year_to_date2 %>%
  filter(Line %in% c(31, 32, 33, 34)) %>%
  mutate(Variable = factor(Variable, 
                           levels=c("Taux d'effort < 20%",
                                    "20% < Taux d'effort < 30%",
                                    "30% < Taux d'effort ≤ 35%",
                                    "Taux d'effort > 35%"))) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Part des emprunteurs (%)") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank())

Nouvelle

Code 
date0 <- as.Date("2020-12-31")
date1 <- as.Date("2021-12-31")
as124 %>%
  year_to_date2 %>%
  filter(Line %in% c(31, 32, 33, 34)) %>%
  mutate(Variable = factor(Variable, 
                           levels=c("Taux d'effort < 20%",
                                    "20% < Taux d'effort < 30%",
                                    "30% < Taux d'effort ≤ 35%",
                                    "Taux d'effort > 35%"))) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Part des emprunteurs (%)") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank())