DPE - Analyse de la base dpe_all

Data - ADEME

Author

[1] "fr_CA.UTF-8"

Info

source	dataset	.html	.RData
ademe	dpe_all	2024-06-17	NA

Données sur l’energie

source	dataset	.html	.RData
insee	econ-gen-solde-ech-ext-2	2024-06-19	2023-11-01
insee	IPPMP-NF	2024-06-19	2024-06-19
insee	t_5404	2024-06-19	2021-08-01
sdes	bilan_energetique	2024-06-18	2022-04-16

Data on energy

source	dataset	.html	.RData
ec	WOB	2024-06-17	2024-01-03
eurostat	ei_isen_m	2024-06-18	2024-06-08
eurostat	nrg_bal_c	2023-12-31	2024-06-08
eurostat	nrg_pc_202	2024-06-19	2024-06-08
eurostat	nrg_pc_203	2023-06-11	2024-06-07
eurostat	nrg_pc_203_c	2024-06-19	2024-06-08
eurostat	nrg_pc_203_h	2024-06-19	2024-06-18
eurostat	nrg_pc_203_v	2024-06-19	2024-06-08
eurostat	nrg_pc_204	2024-06-19	2024-06-18
eurostat	nrg_pc_205	2023-06-11	2024-06-08
fred	energy	2024-06-18	2024-06-07
iea	world_energy_balances_highlights_2022	2024-06-18	2023-04-24
wb	CMO	2024-06-18	2024-05-23
wdi	EG.GDP.PUSE.KO.PP.KD	2024-06-18	2024-04-14
wdi	EG.USE.PCAP.KG.OE	2024-06-18	2024-04-14
yahoo	energy	2024-06-18	2024-05-27

DPE par mois

Environ 200,000 - 250,000 DPE / mois.

Table

Code

DPE_par_mois %>%
  print_table_conditional()

Graph

Code

DPE_par_mois %>%
  filter(year_month <= as.Date("2023-12-01")) %>%
  ggplot + geom_line(aes(x = year_month, y = Nobs)) + 
  theme_minimal() + xlab("") + ylab("Nombre de DPE / mois") +
  scale_x_date(breaks = seq.Date(as.Date("2019-12-01"), as.Date("2024-01-01"), "1 month"),
               labels = date_format("%B %y")) +
  scale_y_continuous(labels = dollar_format(pre = "")) +
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))

Version DPE

Code

version_DPE %>%
  print_table_conditional()

Modèle_DPE	Version_DPE	Nobs
DPE 3CL 2021 méthode logement	1.0	351141
DPE 3CL 2021 méthode logement	1.1	248248
DPE 3CL 2021 méthode logement	2.0	315044
DPE 3CL 2021 méthode logement	2.1	1276721
DPE 3CL 2021 méthode logement	2.2	2668459
DPE 3CL 2021 méthode logement	2.3	1436940

Version DPE par mois

Table

Code

version_DPE_par_mois %>%
  print_table_conditional()

Graph

Code

version_DPE_par_mois %>%
  filter(year_month <= as.Date("2023-12-01")) %>%
  ggplot + geom_line(aes(x = year_month, y = Nobs, color = Version_DPE)) + 
  theme_minimal() + xlab("") + ylab("Nombre de DPE / mois, par version") +
  scale_x_date(breaks = seq.Date(as.Date("2019-12-01"), as.Date("2024-01-01"), "1 month"),
               labels = date_format("%B %y")) +
  scale_y_continuous(labels = dollar_format(pre = ""),
                     breaks = seq(0, 500000, 50000)) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank(),
        legend.direction = "horizontal",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))

Graph Stocked

Code

version_DPE_par_mois %>%
  filter(year_month <= as.Date("2023-12-01")) %>%
  ggplot + geom_area(aes(x = year_month, y = Nobs, fill = Version_DPE), alpha = 0.5) + 
  theme_minimal() + xlab("") + ylab("Nombre de DPE / mois, par version") +
  scale_x_date(breaks = seq.Date(as.Date("2019-12-01"), as.Date("2024-01-01"), "1 month"),
               labels = date_format("%B %y")) +
  scale_y_continuous(labels = dollar_format(pre = ""),
                     breaks = seq(0, 500000, 50000)) + 
  #ofce::theme_ofce(base_family = "arial") +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank(),
        legend.direction = "horizontal",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))