Enquête annuelle du SGACPR sur le financement de l’habitat 2019 - financement_habitat_2019

Data - ACPR

Author

François Geerolf

date

Code 
financement_habitat_2019 %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
date Nobs
2001-12-31 90
2002-12-31 90
2003-12-31 90
2004-12-31 90
2005-12-31 90
2006-12-31 90
2007-12-31 90
2008-12-31 90
2009-12-31 90
2010-12-31 90
2011-12-31 90
2012-12-31 90
2013-12-31 90
2014-12-31 90
2015-12-31 90
2016-12-31 90
2017-12-31 90
2018-12-31 90
2019-12-31 90

variable

Code 
financement_habitat_2019 %>%
  group_by(Variable, Line) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

Taux d’apport - Evolution

Legend

Code 
financement_habitat_2019 %>%
  filter(Line %in% c(41, 42, 43, 44)) %>%
  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),
                     limits = c(0, 0.7)) +
  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")
financement_habitat_2019 %>%
  filter(Line %in% c(41, 42, 43, 44)) %>%
  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

Code 
date0 <- as.Date("2020-12-31")
date1 <- as.Date("2021-12-31")
financement_habitat_2019 %>%
  filter(Line %in% c(34, 35, 36, 37)) %>%
  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())

Taux d’endettement moyen à l’octroi

Code 
date0 <- as.Date("2020-12-31")
date1 <- as.Date("2021-12-31")
financement_habitat_2019 %>%
  filter(Line %in% c(34, 35, 36, 37)) %>%
  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())