From 5c5d45448cde8c6506986f6afd4d0898e1c71b4f Mon Sep 17 00:00:00 2001
From: Denis DOUILLARD <denis.douillard@developpement-durable.gouv.fr>
Date: Fri, 4 Apr 2025 18:13:52 +0200
Subject: [PATCH] Publication de mars 2025 et modifications mineurs de scripts

---
 export_tableur/neuf.xlsx     |  Bin 777309 -> 785425 bytes
 export_tableur/occasion.xlsx |  Bin 785921 -> 787689 bytes
 export_tableur/tdb.xlsx      |  Bin 52369 -> 52449 bytes
 ortm_rsvero_2025_03.Rmd      | 1076 ++++++++++++++++++++++++++++++++++
 scripts/01_data_prep_neuf.R  |   12 +-
 scripts/02_data_prep_occ.R   |   12 +-
 scripts/03_co2.R             |    7 +-
 scripts/bilan_eco_insee.R    |    8 +-
 8 files changed, 1097 insertions(+), 18 deletions(-)
 create mode 100644 ortm_rsvero_2025_03.Rmd

diff --git a/export_tableur/neuf.xlsx b/export_tableur/neuf.xlsx
index 9e7f001a86c7aeda1fe91a8139ab3aa8767dcd5a..0d42dcc7e8c14a2927202212a4f4b7b4f1fc5ec0 100644
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diff --git a/ortm_rsvero_2025_03.Rmd b/ortm_rsvero_2025_03.Rmd
new file mode 100644
index 0000000..af6a027
--- /dev/null
+++ b/ortm_rsvero_2025_03.Rmd
@@ -0,0 +1,1076 @@
+---
+title: "Mars 2025 : le recul des ventes<br>de véhicules neufs s'accentue"
+author: "Traitement des données, mise en forme et rédaction : <U>[<strong>Denis DOUILLARD</strong>](mailto:statistiques.dreal-pdl@developpement-durable.gouv.fr)</U>"
+date: "Dernière mise à jour : `r format(Sys.time(), '%d %B %Y')`"
+output: 
+  gouvdown::html_gouv:
+    toc: TRUE
+    toc_float: TRUE
+    offline: TRUE
+    include:
+      before_body: header.html
+      after_body: footer.html
+editor_options: 
+  chunk_output_type: console
+---
+<style>
+body {text-align: justify; font-size: 140%;}
+caption {color: #323787; font-size: 140%; font-weight: bold; text-align: center;}
+table {font-size: 85%; border: none;} /* Ne marche pas */
+.table {margin:0px 0px 0px 0px; border:0px solid transparent; box-shadow:0px 0px 0px transparent;}
+.table thead>tr {height: 10px; border-top: 0px solid white;}
+.table thead>tr>th {height: 10px; border: 0px solid #ccc;}
+.table tbody>tr>td {height: 10px; border: 0px solid #ccc;}
+tfoot {font-size: 90%;}
+ul {list-style-position: outside; text-indent: 0em; padding-left: 2rem;}
+ul li {list-style-position: outside; text-indent: 0em; padding-left: 0;}
+li::before{padding: 0; margin: 0;}
+h1 {color: #323787; text-align: left; padding-left: 0px; font-size: 150%}
+h2 {color: #469b36; text-align: left; padding-left: 0px; font-size: 130%}
+h3 {color: #323787; text-align: left; padding-left: 0px; font-size: 100%}
+a:link {color: #323787}        /* Liens non visités */
+a:visited {color: #323787}     /* Liens visités */
+a:hover {background: #469b36}  /* Liens survolés */
+div.tocify {width: 80%; max-width: 280px; max-height: 100%; border: #323787;}
+.tocify-header {text-indent: 0px; text-align: left; font-size: 95%; letter-spacing: -0.6px;}
+.tocify-subheader {text-indent: 0px; text-align: left; font-size: 100%}
+.tocify .tocify-item a, .tocify .list-group-item {text-indent: 0px; padding: 0px;}
+.list-group-item.active, .list-group-item.active:focus, .list-group-item.active:hover {
+    background-color: #323787; border-color: #323787}
+.tocify ul, .tocify li {line-height: 115%;}
+# Modification de la mise en page et correction de bugs du CSS de gouvdown
+# (https://github.com/spyrales/gouvdown/blob/master/inst/resources/css/default.css)
+
+# Adresse du CSS sur le disque dur (à ouvrir et modifier avec le bloc-notes)
+# C:\Users\denis.douillard\Documents\R\win-library\4.1\gouvdown\resources\css\default.css
+# Une copie de ce fichier css se trouve dans la racine du projet. Il s'appelle "default_copie.css"
+# Si la mise en forme des tableaux se trouve modifiée, remplacer le default.css par le default_copie.css
+</style>
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE, cache = FALSE)
+
+library(tidyr)
+library(tidyverse)
+library(dplyr)
+library("RcppRoll")
+library(readxl)
+library(xlsx)
+library(shiny)
+library(rmarkdown)
+library(kableExtra)
+library(formattable)
+library(DT)
+library(ggthemes)
+library(janitor)
+library(plotly)
+library(ggplot2)
+library(ggtext)
+library(openxlsx)
+library(grDevices)
+library(forcats)
+library(grid)
+library(gridtext)
+library(lubridate)
+library(sf)
+library(extrafont)
+library(stringr)
+library(scales)
+library(rlang)
+library(knitr)
+library(kableExtra)
+library(huxtable)
+
+# Séparateur décimal à la française
+options(OutDec= ",")
+
+# Exécution de la datapréparation
+# source("scripts/01_data_prep_neuf.R",encoding = "UTF-8")
+# source("scripts/02_data_prep_occ.R",encoding = "UTF-8")
+# source("scripts/03_co2.R",encoding = "UTF-8")
+# source("scripts/04_tableaux_annexes.R",encoding = "UTF-8")
+# source("scripts/05_series_et_ratios_par_genre_neuf.R",encoding = "UTF-8")
+# source("scripts/06_series_et_ratios_par_genre_occ.R",encoding = "UTF-8")
+
+# Chargement de l'environnement créé lors de la data préparation
+load("data/rsvero.RData")
+
+# Procédure pour changer la police par défaut de ggplot
+library(extrafont)
+font_import(pattern = "Marianne", prompt = TRUE)
+loadfonts(device = "win")
+myFont <- "Marianne"
+windowsFonts(sans = myFont)
+```
+&emsp;
+
+# Faits saillants du mois
+
+**En `r dernier_mois_rsvero_3_bis`, `r prettyNum(neuf_ensemble_bis[13, 2], " ")` véhicules routiers neufs ont été immatriculés dans les Pays de la Loire, en recul de 9,3 % par rapport à `r dernier_mois_rsvero_3_bis_n_1`. Cette baisse est la troisième consécutive et la neuvième des onze derniers mois. En cumul annuel, les ventes se sont repliées de 3,9 % par rapport à la période `r douze_derniers_mois_bis_n_1`.**
+
+**`r prettyNum(occ_ensemble_bis[13, 2], " ")` véhicules d'occasion ont changé de propriétaire ou de locataire en `r dernier_mois_rsvero_3_bis`. C'est 0,7 % de plus qu’en `r dernier_mois_rsvero_3_bis_n_1`. En glissement annuel, `r douze_derniers_mois_bis`, la hausse du marché de la seconde main est identique (`r annexe_3[nb_lignes, 5] %>% pull` par rapport aux douze mois précédents).**
+
+**En `r dernier_mois_rsvero_4`, les modèles électriques ont représenté `r annexe_3[nb_lignes, 6] %>% pull` des ventes de véhicules neufs contre `r annexe_3[nb_lignes-12, 6] %>% pull` un an auparavant. Sur le marché de l'occasion, la part de l'électrique a été `r part_elec[1, 4] %>% pull` fois plus faible (`r annexe_3[nb_lignes, 7] %>% pull`). La chute des achats de véhicules électriques neufs (- 30 % par rapport à `r dernier_mois_rsvero_3_bis_n_1`) est liée au boycottage du constructeur Tesla (deuxième producteur mondial de voitures électriques), dont les ventes se sont effondrées de 41 % en France lors du premier trimestre de 2025.**
+
+**Plus d'un véhicule neuf sur deux a été acquis par une personne morale (`r annexe_3[nb_lignes, 8] %>% pull`). Ce ratio est le plus élevé depuis quatre ans (59,6 % en février 2021). Il a été nettement moins élevé (`r annexe_3[nb_lignes, 9] %>% pull`) sur le marché de la seconde main. En `r dernier_mois_rsvero_4`, les achats de véhicules neufs par les personnes physiques ont chuté de 26 %. Ceux des personnes morales ont progressé de 8 %.**
+
+**Les voitures particulières et commerciales ont représenté `r annexe_3[nb_lignes, 10] %>% pull` des immatriculations neuves et `r annexe_3[nb_lignes, 11] %>% pull` des immatriculations d'occasion. Sur le marché du neuf, leurs ventes ont reculé de 9,3 % par rapport à `r dernier_mois_rsvero_3_bis_n_1`, soit la même variation que celle de l'ensemble des véhicules. Les émissions conventionnelles de CO₂ des voitures neuves, basées sur le cycle de mesure WLTP, se sont élevées en moyenne à 90,6 grammes par kilomètre dans les Pays de la Loire, en hausse de 6,7 % par rapport à `r dernier_mois_rsvero_3_bis_n_1` (84,9 grammes/km). L'augmentation est la conséquence du recul des immatriculations de véhicules électriques.**
+
+**La segmentation des immatriculations en quatorze catégories de véhicules révèle de profondes disparités relatives à l'électrification du parc. Ainsi, en `r dernier_mois_rsvero_4`, les modèles électriques ont rassemblé `r neuf_occ_tableau_synthese[4, 4] %>% pull`des ventes de tricycles et de quadricycles à moteur neufs, `r neuf_occ_tableau_synthese[8, 4] %>% pull`des ventes de véhicules utilitaires dérivés de voitures et `r neuf_occ_tableau_synthese[1, 4] %>% pull`des ventes de voitures particulières mais moins de 4 % de celles de motocyclettes, de camping-cars, de tracteurs routiers, de camions et de tracteurs agricoles.**
+
+**La part des véhicules neufs achetés par les personnes morales varie également fortement selon le genre. En `r dernier_mois_rsvero_4`, elle a été inférieure ou voisine de 50 % pour les voitures, les cyclomoteurs, les motocyclettes, les tricycles/quadricycles à moteur, les remorques légères et les camping cars. Par nature, cette part a été de 100 % pour les véhicules professionnels, tels que les autobus et autocars, les utilitaires dérivés de voitures, les camions, les tracteurs routiers et les remorques lourdes.**
+
+```{r 1_neuf_occ_graph, echo=FALSE, fig.align="center", out.width="100%", fig.width=10, fig.height=4}
+neuf_occ_synthese_ggplot
+```
+&emsp;
+```{r 1bis_neuf_occ_tableau, echo=FALSE}
+neuf_occ_synthese_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - Dans le présent document, il a été choisi de ne pas afficher et de ne pas commenter le cumul des marchés du neuf et de l'occasion. En effet, compte tenu de la part croissante des véhicules achetés par les <U>[<strong>personnes morales</strong>](#Ancre Statut juridique)</U>, la sommation des immatriculations neuves et d'occasion (telle qu'elle aurait pu apparaître dans le tableau ci-dessus) est susceptible de contenir des doubles comptes. Ainsi, en cas d'immatriculations rapprochées, une voiture peut figurer, au cours d'une même période, sous deux statuts différents dans le <U>[<strong>Répertoire statistique des véhicules routiers (RSVéRo)</strong>](#Ancre RSVéRo)</U>, successivement en tant que véhicule neuf et d'occasion. Le phénomène se produit notamment lorsqu'un <U>[<strong>véhicule de démonstration</strong>](#Ancre Véhicules de démonstration)</U>, acheté neuf par un concessionnaire, est rapidement cédé sur le marché de l'occasion. </p>
+
+&emsp;
+
+# 1 – L'ensemble des véhicules routiers
+
+<strong>Définition</strong> - Un véhicule routier est un moyen de transport, configuré pour assurer soit le déplacement sur route de voyageurs ou de marchandises, soit la traction routière de véhicules utilisés pour l'acheminement de biens ou de personnes. Il n'est donc pas nécessairement doté d’un moteur (cf. les <U>[<strong>remorques légères / caravanes</strong>](#Ancre rem_leg)</U> et les <U>[<strong>remorques lourdes</strong>](#Ancre rem_lourde)</U>). Sa finalité première n'est pas toujours le transport en lui-même. C'est le cas des <U>[<strong>campings-cars</strong>](#Ancre camping_car)</U>, des engins de travaux publics, des <U>[<strong>tracteurs agricoles</strong>](#Ancre tra_agr)</U>, des véhicules militaires, etc.
+
+&emsp;
+```{r 86_neuf_ensemble_tableau, echo=FALSE, fig.align="center"}
+neuf_ensemble_kable
+```
+&emsp;
+```{r 87_occ_ensemble_tableau, echo=FALSE, fig.align="center"}
+occ_ensemble_kable
+```
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 88_neuf_ensemble_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_ensemble_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 89_occ_ensemble_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_ensemble_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 90_neuf_ensemble_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_ensemble_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 91_occ_ensemble_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_ensemble_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+<a id="Ancre vpc"></a>
+
+# 2 – Les voitures particulières et commerciales
+
+<strong>Définition</strong> : véhicule routier automobile, autre qu’un deux-roues à moteur ou qu'une voiturette, destiné au transport de voyageurs et conçu pour un nombre de places assises égal au maximum à neuf (y compris celle du conducteur).
+
+&emsp;
+```{r 2_neuf_vpc_tableau, echo=FALSE, fig.align="center"}
+neuf_vpc_kable
+```
+&emsp;
+```{r 3_occ_vpc_tableau, echo=FALSE, fig.align="center"}
+occ_vpc_kable
+```
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 4_neuf_vpc_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_vpc_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 5_occ_vpc_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_vpc_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 6_neuf_vpc_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_vpc_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 7_occ_vpc_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_vpc_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Émissions conventionnelles de CO<sub>2</sub> des voitures particulières et commerciales <span style = 'color:#469b36'>neuves</span>
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r neuf_vpc_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+co2_reg_ggplot
+```
+</div>
+
+<div class = "col-md-6">
+```{r occ_vpc_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+co2_dep_ggplot
+```
+</div>
+</div>
+
+<p style="font-size:85%">
+<strong>&ensp;&nbsp;Note au lecteur</strong> - Les émissions infranationales de CO₂ ne sont disponibles que pour les voitures particulières et commerciales neuves.</p>
+
+&emsp;
+
+# 3 – Les cyclomoteurs
+
+<strong>Définition</strong> : véhicule à moteur, muni de deux ou de trois roues, de cylindrée inférieure à 50 cm³ et dont la vitesse ne peut excéder 50 km/h.
+
+&emsp;
+```{r 8_neuf_cyclo_tableau, echo=FALSE, fig.align="center"}
+neuf_cyclo_kable
+```
+&emsp;
+```{r 9_occ_cyclo_tableau, echo=FALSE, fig.align="center"}
+occ_cyclo_kable
+```
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 10_neuf_cyclo_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_cyclo_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 11_occ_cyclo_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_cyclo_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 12_neuf_cyclo_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_cyclo_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 13_occ_cyclo_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_cyclo_ggplot_personnes_morales
+```
+</div>
+</div>
+&emsp;
+
+# 4 – Les motocyclettes
+
+<strong>Définition</strong> : véhicule à deux roues doté d'un moteur de cylindrée d’au moins 50 cm³ et de vitesse supérieure à 50 km/h.
+
+&emsp;
+```{r 14_neuf_moto_tableau, echo=FALSE, fig.align="center"}
+neuf_moto_kable
+```
+&emsp;
+```{r 15_occ_moto_tableau, echo=FALSE, fig.align="center"}
+occ_moto_kable
+```
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 16_neuf_moto_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_moto_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 17_occ_moto_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_moto_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 18_neuf_moto_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_moto_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 19_occ_moto_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_moto_ggplot_personnes_morales
+```
+</div>
+</div>
+&emsp;
+
+# 5 – Les tricycles et les quadricycles à moteur
+
+<strong>Définition</strong> : véhicule de plus de deux roues (scooter à trois roues, quad, buggy, voiturette, …) pourvu d'un moteur d'une cylindrée supérieure à 50 cm³ et qui peut rouler plus vite que 50 km/h.
+
+&emsp;
+```{r 20_neuf_tri_quadri_tableau, echo=FALSE, fig.align="center"}
+neuf_tri_quadri_kable
+```
+&emsp;
+```{r 21_occ_tri_quadri_tableau, echo=FALSE, fig.align="center"}
+occ_tri_quadri_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du faible nombre d'immatriculations mensuelles de tricycles et de quadricycles à moteur dans les Pays de la Loire, les pourcentages représentés sur les quatre graphiques ci-dessous sont ceux des trois derniers mois (cumul trimestriel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 22_neuf_tri_quadri_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tri_quadri_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 23_occ_tri_quadri_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tri_quadri_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 24_neuf_tri_quadri_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tri_quadri_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 25_occ_tri_quadri_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tri_quadri_ggplot_personnes_morales
+```
+</div>
+</div>
+&emsp;
+
+<a id="Ancre rem_leg"></a>
+
+# 6 – Les remorques légères et les caravanes
+
+<strong>Définition</strong> : remorque dont le poids total autorisé en charge est compris entre 500 kg et 3,5 tonnes, pouvant être tractée avec un permis B pour celles pesant moins de 750 kg.
+
+&emsp;
+```{r 26_neuf_rem_leg_tableau, echo=FALSE, fig.align="center"}
+neuf_rem_leg_kable
+```
+&emsp;
+```{r 27_occ_rem_leg_tableau, echo=FALSE, fig.align="center"}
+occ_rem_leg_kable
+```
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 30_neuf_rem_leg_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_rem_leg_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 31_occ_rem_leg_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_rem_leg_ggplot_personnes_morales
+```
+</div>
+</div>
+&emsp;
+
+<a id="Ancre camping_car"></a>
+
+# 7 – Les camping-cars
+
+<strong>Définition</strong> : véhicule autotracté, parfois dénommé autocaravane, appartenant à la catégorie des <U>[<strong>véhicules automoteurs spécialisés (VASP)</strong>](#Ancre vasp)</U>, conçu pour servir de logement et dont le compartiment arrière habitable comprend les équipements inamovibles suivants : sièges, table, couchettes, coin cuisine et espaces de rangement.
+
+&emsp;
+```{r 32_neuf_camping_car_tableau, echo=FALSE, fig.align="center"}
+neuf_camping_car_kable
+```
+&emsp;
+```{r 33_occ_camping_car_tableau, echo=FALSE, fig.align="center"}
+occ_camping_car_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du faible nombre d'immatriculations mensuelles de camping-cars dans les Pays de la Loire, les pourcentages représentés sur les quatre graphiques ci-dessous sont ceux des trois derniers mois (cumul trimestriel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 34_neuf_camping_car_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_camping_car_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 35_occ_camping_car_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_camping_car_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 36_neuf_camping_car_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_camping_car_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 37_occ_camping_car_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_camping_car_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+# 8 – Les autobus et les autocars
+
+<strong>Définition</strong> : véhicules pour le transport en commun de personnes, d’au moins dix places assises, y compris le conducteur (les véhicules de moins de dix places sont classés parmi les <U>[<strong>voitures particulières et commerciales</strong>](#Ancre vpc)</U>). Les autobus sont destinés principalement au transport urbain ; ils comportent des places assises et debout. Les autocars sont utilisés en transport collectif routier ou touristique, avec des places assises uniquement.
+
+&emsp;
+```{r 38_neuf_tcp_tableau, echo=FALSE, fig.align="center"}
+neuf_tcp_kable
+```
+&emsp;
+```{r 39_occ_tcp_tableau, echo=FALSE, fig.align="center"}
+occ_tcp_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du très faible nombre d'immatriculations mensuelles d'autobus et d'autocars dans les Pays de la Loire, les pourcentages représentés sur les quatre graphiques ci-dessous sont ceux des douze derniers mois (cumul annuel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 40_neuf_tcp_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tcp_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 41_occ_tcp_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tcp_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 42_neuf_tcp_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tcp_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 43_occ_tcp_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tcp_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+# 9 – Les utilitaires dérivés de voitures particulières (UDVP)
+
+<strong>Définition</strong> : automobile, appartenant à la catégorie des <U>[<strong>véhicules automoteurs spécialisés (VASP)</strong>](#Ancre vasp)</U>, dont la banquette arrière et les points d’ancrage de ceinture ont été retirés afin d’avoir une plus grande capacité de transport.
+
+&emsp;
+```{r 44_neuf_udvp_tableau, echo=FALSE, fig.align="center"}
+neuf_udvp_kable
+```
+&emsp;
+```{r 45_udvp_cyclo_tableau, echo=FALSE, fig.align="center"}
+occ_udvp_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du faible nombre d'immatriculations mensuelles d'utilitaires dérivés de voitures particulières dans les Pays de la Loire, les pourcentages représentés sur les quatre graphiques ci-dessous sont ceux des trois derniers mois (cumul trimestriel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 46_neuf_udvp_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_udvp_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 47_occ_udvp_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_udvp_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 48_neuf_udvp_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_udvp_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 49_occ_udvp_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_udvp_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+# 10 – Les camionnettes
+
+<strong>Définition</strong> : véhicule routier rigide automobile, conçu exclusivement ou principalement pour le transport de marchandises° et dont le poids total autorisé en charge est inférieur ou égal à 3,5 tonnes.
+
+<p style="font-size:85%">° Cette définition réglementaire est très éloignée de la réalité des faits. Dans la pratique, les camionnettes utilisées en transport public de marchandises ne représentent qu'environ 1 % des véhicules utilitaires légers en circulation sur le territoire national. L’essentiel du parc de camionnettes est la propriété de particuliers, d’administrations ou d’entreprises sans rapport avec le transport (secteurs de la construction, du commerce, de l’agriculture, …). </p>
+
+&emsp;
+```{r 50_neuf_vul_tableau, echo=FALSE, fig.align="center"}
+neuf_vul_kable
+```
+&emsp;
+```{r 51_occ_vul_tableau, echo=FALSE, fig.align="center"}
+occ_vul_kable
+```
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 52_neuf_vul_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_vul_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 53_occ_vul_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_vul_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 54_neuf_vul_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_vul_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 55_occ_vul_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_vul_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+# 11 – Les camions
+
+<strong>Définition</strong> : véhicule routier rigide automobile, conçu exclusivement ou principalement pour le transport de marchandises et dont le poids total autorisé en charge excède 3,5 tonnes.
+
+&emsp;
+```{r 56_neuf_camion_tableau, echo=FALSE, fig.align="center"}
+neuf_camion_kable
+```
+&emsp;
+```{r 57_occ_camion_tableau, echo=FALSE, fig.align="center"}
+occ_camion_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du faible nombre d'immatriculations mensuelles de camions dans les Pays de la Loire, les pourcentages représentés sur les quatre graphiques ci-dessous sont ceux des trois derniers mois (cumul trimestriel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 58_neuf_camion_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_camion_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 59_occ_camion_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_camion_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 60_neuf_camion_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_camion_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 61_occ_camion_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_camion_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+# 12 – Les tracteurs routiers
+
+<strong>Définition</strong> : véhicule routier à moteur conçu exclusivement ou principalement pour le remorquage d’autres véhicules routiers non automobiles (essentiellement des semi-remorques).
+
+&emsp;
+```{r 62_neuf_tra_rou_tableau, echo=FALSE, fig.align="center"}
+neuf_tra_rou_kable
+```
+&emsp;
+```{r 63_occ_tra_rou_tableau, echo=FALSE, fig.align="center"}
+occ_tra_rou_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du faible nombre d'immatriculations mensuelles de tracteurs routiers dans les Pays de la Loire, les pourcentages représentés sur les quatre graphiques ci-dessous sont ceux des trois derniers mois (cumul trimestriel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 64_neuf_tra_rou_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tra_rou_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 65_occ_tra_rou_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tra_rou_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 66_neuf_tra_rou_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tra_rou_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 67_occ_tra_rou_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tra_rou_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+<a id="Ancre rem_lourde"></a>
+
+# 13 – Les remorques lourdes
+
+<strong>Définition</strong> : véhicule routier d’au moins 3,5 tonnes de poids total autorisé en charge conçu pour le transport de marchandises, également connu sous l'appelation remorque routière.
+
+&emsp;
+```{r 68_neuf_rem_lourde_tableau, echo=FALSE, fig.align="center"}
+neuf_rem_lourde_kable
+```
+&emsp;
+```{r 69_occ_rem_lourde_tableau, echo=FALSE, fig.align="center"}
+occ_rem_lourde_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du très faible nombre d'immatriculations mensuelles de remorques lourdes dans les Pays de la Loire, les valeurs représentées sur les deux graphiques ci-dessous sont celles des douze derniers mois (cumul annuel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 72_neuf_rem_lourde_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_rem_lourde_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 73_occ_rem_lourde_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_rem_lourde_ggplot_personnes_morales
+```
+</div>
+</div>
+&emsp;
+
+<a id="Ancre vasp"></a>
+
+# 14 – Les véhicules automoteurs spécialisés (hors UDVP et camping-cars)
+
+<strong>Définition</strong> : véhicule à moteur destiné à des usages complémentaires au transport (engin de travaux publics, ambulance, véhicule de pompiers, benne à ordures ménagères, fourgon funéraire, dépanneuse, food-truck, petit engin de maintenance de voirie, …).
+
+&emsp;
+```{r 74_neuf_vasp_tableau, echo=FALSE, fig.align="center"}
+neuf_vasp_kable
+```
+&emsp;
+```{r 75_occ_vasp_tableau, echo=FALSE, fig.align="center"}
+occ_vasp_kable
+```
+&emsp;
+<p style="font-size:85%">
+<strong>Note au lecteur</strong> - En raison du faible nombre d'immatriculations mensuelles de VASP (hors UDVP et camping-cars) dans les Pays de la Loire, les pourcentages représentés sur les quatre graphiques ci-dessous sont ceux des trois derniers mois (cumul trimestriel glissant).</p>
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 76_neuf_vasp_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_vasp_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 77_occ_vasp_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_vasp_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 78_neuf_vasp_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_vasp_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 79_occ_vasp_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_vasp_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+<a id="Ancre tra_agr"></a>
+
+# 15 – Les tracteurs agricoles
+
+<strong>Définition</strong> : véhicule automoteur, dont la vitesse ne peut excéder 40 km/h, conçu pour tirer ou actionner tout matériel normalement destiné à des travaux agricoles ou forestiers.
+
+&emsp;
+```{r 80_neuf_tra_agr_tableau, echo=FALSE, fig.align="center"}
+neuf_tra_agr_kable
+```
+&emsp;
+```{r 81_occ_tra_agr_tableau, echo=FALSE, fig.align="center"}
+occ_tra_agr_kable
+```
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Structure selon la source d'énergie dans les Pays de la Loire
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 82_neuf_tra_agr_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tra_agr_ggplot_energie
+```
+</div>
+
+<div class = "col-md-6">
+```{r 83_occ_tra_agr_graph_energie, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tra_agr_ggplot_energie
+```
+</div>
+</div>
+
+&emsp;
+<p style="color: #323787; font-size: 115%; font-weight: bold; text-align: center;">
+Part des véhicules achetés par les personnes morales
+</p>
+
+<div class = "row">
+<div class = "col-md-6">
+```{r 84_neuf_tra_agr_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+neuf_tra_agr_ggplot_personnes_morales
+```
+</div>
+
+<div class = "col-md-6">
+```{r 85_occ_tra_agr_graph_personnes_morales, echo=FALSE, fig.align="center", fig.height=4.5}
+occ_tra_agr_ggplot_personnes_morales
+```
+</div>
+</div>
+
+&emsp;
+
+# Séries mensuelles
+
+```{r 86_annexe_1, echo=FALSE, fig.align="center"}
+annexe_1_kable
+```
+&emsp;
+```{r 87_annexe_3, echo=FALSE, fig.align="center"}
+annexe_2_kable
+```
+&emsp;
+```{r 88_annexe_3, echo=FALSE, fig.align="center"}
+annexe_3_kable
+```
+&emsp;
+```{r 89_co2, echo=FALSE, fig.align="center"}
+co2_kable
+```
+&emsp;
+
+# Téléchargement des données
+
+Les variables disponibles sont la catégorie de véhicules, le mois, le département, la source d’énergie et la personnalité juridique. Chaque fichier contient dix-sept onglets (un pour chacune des quatorze catégories, deux onglets relatifs à l'ensemble des véhicules et un dernier onglet portant spécifiquement sur `r dernier_mois_rsvero_3_bis`).
+
+<div class = "row">
+<div class = "col-md-4">
+<div align = "justify">Ouvrir ou enregistrer ci-contre les séries mensuelles, au format tableur (xlsx), sur la période allant de janvier 2016 à `r dernier_mois_rsvero_3_bis` :</div>
+</div>
+
+<div class = "col-md-1">
+</div>
+
+<div class = "col-md-3">
+<a href="export_tableur/neuf.xlsx"
+   download="neuf.xlsx"><div style = "padding: 10px 0px 2px 0px;background: #469b36;border-radius: 8px"><span style="font-size:0.9em; color:white"><div align = "center"><b>Immatriculations<p>neuves</b></div></span></div></a>
+</div>
+
+<div class = "col-md-1">
+</div>
+
+<div class = "col-md-3">
+<a href="export_tableur/occasion.xlsx"
+   download="occasion.xlsx"><div style = "padding: 10px 0px 2px 0px;background: #469b36;border-radius: 8px"><span style="font-size:0.9em; color:white"><div align = "center"><b>Immatriculations<p>d'occasion</b></div></span></div></a>
+</div>
+</div>
+
+&emsp;
+
+&emsp;
+
+# Annexes méthodologiques
+<a id="Ancre RSVéRo"></a>
+
+## Le champ couvert par le RSVéRo
+Le RSVéRo est un acronyme désignant le Répertoire statistique des véhicules routiers. C'est un dispositif du ministère de la Transition écologique et de la Cohésion des territoires. Il recense les véhicules routiers immatriculés sur le territoire français à partir des informations provenant du système d’immatriculation des véhicules (SIV) et transmises par le ministère de l’Intérieur (agence nationale des titres sécurisés). Les données présentées ici ne comprennent pas les véhicules en transit temporaire (TT), importés en transit (IT), immatriculés en W (prototypes en cours d’études ou d’essais techniques) ou en WW (certificats provisoires en attente de formalités).
+
+Le présent document, portant sur les immatriculations mensuelles de véhicules routiers dans les Pays de la Loire, est mis à jour aux alentours du 10 de chaque mois. Il exploite les données, extraites du RSVéRo, envoyées mensuellement par le service de la donnée et des études statistiques (SDES) aux directions régionales de l’environnement, de l’aménagement et du logement (DREAL[^1]).
+<a id="Ancre Véhicules de démonstration"></a>
+
+&emsp;
+
+### Les véhicules neufs
+Un véhicule est administrativement considéré comme neuf lorsqu'il n'a jamais roulé, quel que soit le statut juridique de son acquéreur (personne physique ou morale). Le marché du neuf inclut les véhicules dits de démonstration, immatriculés par les concessionnaires dans le cadre d'opérations de présentation et d’essai auprès de leur clientèle. Ces véhicules représentent 10 à 15 % de l’ensemble des immatriculations neuves. En général, dans un court laps de temps, les concessionnaires les écoulent sur le marché de la seconde main sous l'appelation <i>occasion zéro kilomètre</i> (en réalité moins de 100 km, cf. paragraphe ci-dessous).
+
+&emsp;
+
+### Les véhicules d’occasion
+La seconde main est constituée des opérations de changement de propriétaire et des premières immatriculations en France de véhicules d’occasion importés. En janvier 2025, les changements de locataire de longue durée ont intégré le champ de l'occasion, afin de tenir compte de l'essor de la relocation de véhicules électriques. Ne sont pas pris en compte les changements de domicile, d’état civil ou de raison sociale des propriétaires, les déclarations de cession ou les déclarations d’achat des professionnels de l’automobile non suivies d’un changement de propriétaire. La seconde main comprend en revanche les <i>voitures zéro kilomètre</i>. Il s'agit d'anciens véhicules de démonstration (cf. définition au paragraphe ci-dessus), ayant à ce titre fait l'objet d'une première immatriculation. Ultérieurement revendus par les concessionnaires avec un très faible kilométrage et à un tarif nettement inférieur à celui du neuf, ils changent alors légalement de statut administratif et intègrent le champ des véhicules d’occasion.
+
+<a id="Ancre Statut juridique"></a>
+
+### La personnalité juridique du propriétaire du véhicule
+Le RSVéRo permet de scinder les immatriculations de véhicules selon le statut juridique du titulaire de la <i>carte grise</i>[^2]. La personnalité juridique comprend deux modalités : personne physique et personne morale. Une personne physique est un être humain (particulier ou entreprise individuelle), dotée de droits et de devoirs. Une personne morale est un groupement, généralement composé de plusieurs personnes physiques, œuvrant vers un but commun. C'est un ensemble protéiforme (État, administrations, établissements publics, collectivités locales, sociétés, associations, …).
+
+En France, environ 50 % des véhicules neufs sont achetés par des personnes morales. Cette moitié se répartit en quatre ensembles de parts comparables : les loueurs automobiles de courte durée, les loueurs de longue durée, les constructeurs (qui immatriculent des véhicules pour les exposer) et les autres personnes morales (entreprises de transport routier, du BTP, du commerce, de l'agriculture, …).
+
+&emsp;
+
+## La structure énergétique des immatriculations
+Dans le document, la segmentation des motorisations est issue du regroupement en cinq modalités de la trentaine de codes à deux caractères qui figurent dans la nomenclature officielle des sources d'énergie des véhicules routiers. Ce code se retrouve sur le certificat d’immatriculation de chaque véhicule.
+
+&emsp;
+
+<div class = "row">
+<div class = "col-md-6">
+
+### Essence
+Cette modalité comprend les deux codes suivants :
+
+* ES --> Essence
+
+* EH --> Essence-électricité (hybride non rechargeable)
+
+&emsp;
+
+### Gazole 
+Cette modalité regroupe les motorisations suivantes :
+
+* GO --> Gazole
+
+* GH --> Gazole-électricité (hybride non rechargeable)
+
+&emsp;
+
+### Électricité et hydrogène
+Cette modalité correspond aux véhicules "zéro émission" qui, dans le système de classement Crit'air[^3], disposent d'une vignette de couleur verte. Elle associe deux alternatives aux énergies carbonées :
+
+* EL --> Électricité
+
+* H2 --> Hydrogène.
+
+Par simplification, compte tenu du caractère quasi exclusif de l'électricité dans cette modalité[^4], sa dénomination a été raccourcie dans l'ensemble du document en <i>Électricité</i>.
+
+</div>
+
+<div class = "col-md-6">
+
+### Hybride rechargeable
+Cette modalité rassemble deux catégories de véhicules hybrides, combinant un moteur thermique classique (sans-plomb ou diesel) et un moteur électrique alimenté par une batterie rechargeable :
+
+* EE --> Essence-électricité (rechargeable)
+
+* GL --> Gazole-électricité (rechargeable)
+
+&emsp;
+
+### Autres motorisations
+Cette dernière modalité est hétéroclite. Elle est essentiellement composée de véhicules à bicarburation essence-GPL (gaz de pétrole liquéfié), correspondant au code EG. Leurs ventes profitent d’un prix du GPL presque moitié moins cher que celui du sans plomb et du gazole. La modalité comprend également les codes suivants (liste non exhaustive) :
+
+* AC --> Air comprimé
+
+* ET --> Ethanol
+
+* FE --> Superéthanol
+
+* GA --> Gazogène
+
+* GN --> Gaz naturel
+
+</div>
+
+&emsp;
+
+## Les émissions conventionnelles de CO₂
+Les rejets de dioxyde de carbone des voitures neuves sont mesurés selon la norme d’homologation WLTP (worldwide light vehicles test procedures). Exprimés en gramme de CO₂ par kilomètre, ils sont mentionnés sur le certificat d’immatriculation du véhicule. Le protocole WLTP repose sur des tests, réalisés majoritairement en laboratoire, destinés à évaluer la consommation d’énergie, les émissions à l’échappement (pour les modèles thermiques) et l’autonomie (pour les modèles électriques) des voitures mises sur le marché. En Europe, la norme WLTP est entrée en vigueur en 2018 en remplacement du cycle NEDC, qui était obsolète et très peu fidèle aux conditions réelles de circulation.
+
+Les émissions infranationales (régionales et départementales) de CO₂, fournies mensuellement par le SDES aux DREAL, sont disponibles pour une seule catégorie (les voitures particulières et commerciales) et un seul segment (les véhicules neufs).
+
+&emsp;
+
+[^1]: <span style="font-size:85%;"> Une des missions des DREAL est de promouvoir la décarbonation des transports par le développement des mobilités actives (vélo, marche), des transports collectifs en site propre, de la mobilité électrique et des usages mutualisés de l'automobile (covoiturage, autopartage).</span>
+[^2]: <span style="font-size:85%;"> La carte grise est l'appelation usuelle du certificat d'immatriculation. Elle peut être définie comme la carte d’identité d'un véhicule.</span>
+[^3]: <span style="font-size:85%;"> Le certificat qualité de l’air Crit'Air est une vignette sécurisée, à coller sur le pare-brise. Il indique la classe environnementale du véhicule. Il existe six classes de certificats, du moins polluant (vignette verte) au plus polluant (vignette grise). Il est obligatoire pour circuler dans les zones à faibles émissions instaurées sur certains territoires ou pour circuler lorsque le préfet instaure la circulation différenciée lors d'épisodes de pollution.</span>
+[^4]: <span style="font-size:85%;"> En 2023, 306 voitures neuves à hydrogène ont été immatriculées en France, soit 0,1 % des voitures "zéro émission".</span>
diff --git a/scripts/01_data_prep_neuf.R b/scripts/01_data_prep_neuf.R
index a936dd4..b6818bc 100644
--- a/scripts/01_data_prep_neuf.R
+++ b/scripts/01_data_prep_neuf.R
@@ -2883,7 +2883,7 @@ ggplot(neuf_vpc_graph_52_FE_bis)+
 # Graphiques du type de motorisation (un graphique par genre de véhicule) ----
 
 ## Positionnement de l'étiquette des années sur l'axe des abcisses en fonction du dernier mois 
-hjust_aaaa <- ifelse(months(ym(dernier_mois_rsvero_2)) %in% c("mai", "juin", "juillet", "août", "septembre"), 0.03, -0.7)
+hjust_aaaa <- ifelse(months(ym(dernier_mois_rsvero_2)) %in% c("mai", "juin", "juillet", "août", "septembre"), 0.03, -0.65)
 
 ## Voiture particulière et commerciale
 neuf_vpc_graph_energie <- neuf_data_raw %>%
@@ -3680,7 +3680,7 @@ neuf_cyclo_ggplot_personnes_morales <- ggplot(data=neuf_cyclo_graph_personnes_mo
   labs(title = "Cyclomoteurs <span style = 'color:#469b36'>neufs</span>",
        caption = "Source : SDES - Répertoire statistique des véhicules routiers (RSVéRo)")+
   annotation_custom(grobTree(textGrob("En déc. 2017 et 2024, dans\nla plupart des régions,\nles achats de cyclomoteurs\nneufs par les personnes\nmorales ont été trois\nà dix fois supérieurs\nà leur niveau habituel.",
-                                      x=0.4,  y=0.71, hjust=0.5, gp=gpar(col="black", fontsize=11, fontface="plain"))))
+                                      x=0.38,  y=0.71, hjust=0.5, gp=gpar(col="black", fontsize=11, fontface="plain"))))
 
 
 ## Motocyclette
@@ -3707,14 +3707,14 @@ neuf_moto_ggplot_personnes_morales <- ggplot(data=neuf_moto_graph_personnes_mora
   scale_color_manual(values=c("#323787", "#469b36", "#ff6600"))+
   geom_line(linewidth=1.1)+
   #geom_point(size=2, stroke=1.5, pch=21, fill="white")+
-  scale_y_continuous(breaks = seq(0, 0.6, 0.1), limits = c(0, 0.6), expand = c(0, 0), labels = scales::percent_format(accuracy = 1L))+
+  scale_y_continuous(breaks = seq(0, 0.72, 0.12), limits = c(0, 0.72), expand = c(0, 0), labels = scales::percent_format(accuracy = 1L))+
   guides(color=guide_legend(nrow=3, byrow=TRUE))+
   #scale_x_date(breaks = breaks_width("6 months"), expand = c(0, 0), labels = label_date_short()) +
   scale_x_date(breaks = breaks_width("1 years"), expand = c(0, 0), labels = label_date_short()) +
   theme(panel.background = element_rect("#dad6e9"),
         panel.grid.major = element_line("white"),
         panel.grid.minor = element_blank(),
-        legend.position = c(0.8, 0.835),
+        legend.position = c(0.18, 0.835),
         legend.spacing.x = unit(0.1, "cm"),
         legend.spacing.y = unit(0.1, "cm"),
         legend.key.size = unit(0.3, "cm"),
@@ -3792,7 +3792,7 @@ neuf_tri_quadri_ggplot_personnes_morales <- ggplot(data=neuf_tri_quadri_graph_pe
   theme(panel.background = element_rect("#dad6e9"),
         panel.grid.major = element_line("white"),
         panel.grid.minor = element_blank(),
-        legend.position = c(0.84, 0.87),
+        legend.position = c(0.84, 0.13),
         legend.spacing.x = unit(0.1, "cm"),
         legend.spacing.y = unit(0.1, "cm"),
         legend.key.size = unit(0.3, "cm"),
@@ -4511,7 +4511,7 @@ rm(neuf_tableau_synthese_part_52, neuf_tableau_synthese_electrique, neuf_tableau
 # mutate(Ensemble = rowSums(across(2:15))) %>%
 
 # Ajouter une ligne qui somme des lignes
-# add_row(nom_variable = Ensemble, summarise(., across(where(is.numeric), sum))) %>%
+# add_row(nom_variable = "Ensemble", summarise(., across(where(is.numeric), sum))) %>%
 
 # Exemple de code pour extraire un chiffre
 # neuf_vpc_bis[2, 2] %>% pull %>% round(1)
diff --git a/scripts/02_data_prep_occ.R b/scripts/02_data_prep_occ.R
index 4f10a39..84a3343 100644
--- a/scripts/02_data_prep_occ.R
+++ b/scripts/02_data_prep_occ.R
@@ -2928,7 +2928,7 @@ ggplot(occ_vpc_graph_52_FE_bis)+
 # Graphiques du type de motorisation (un graphique par genre de véhicule) ----
 
 ## Positionnement de l'étiquette des années sur l'axe des abcisses en fonction du dernier mois 
-hjust_aaaa <- ifelse(months(ym(dernier_mois_rsvero_2)) %in% c("mai", "juin", "juillet", "août", "septembre"), 0.03, -0.7)
+hjust_aaaa <- ifelse(months(ym(dernier_mois_rsvero_2)) %in% c("mai", "juin", "juillet", "août", "septembre"), 0.03, -0.65)
 
 ## Voiture particulière et commerciale
 occ_vpc_graph_energie <- occ_data_raw %>%
@@ -3644,14 +3644,14 @@ occ_vpc_ggplot_personnes_morales <- ggplot(data=occ_vpc_graph_personnes_morales,
   scale_color_manual(values=c("#323787", "#469b36", "#ff6600"))+
   geom_line(linewidth=1.1)+
   #geom_point(size=2, stroke=1.5, pch=21, fill="white")+
-  scale_y_continuous(breaks = seq(0.01, 0.08, 0.01), limits = c(0.01, 0.08), expand = c(0, 0), labels = scales::percent_format(accuracy = 1L))+
+  scale_y_continuous(breaks = seq(0.015, 0.085, 0.01), limits = c(0.015, 0.085), expand = c(0, 0), labels = function(x) paste0(x*100, " %"))+
   guides(color=guide_legend(nrow=3, byrow=TRUE))+
   #scale_x_date(breaks = breaks_width("6 months"), expand = c(0, 0), labels = label_date_short()) +
   scale_x_date(breaks = breaks_width("1 years"), expand = c(0, 0), labels = label_date_short()) +
   theme(panel.background = element_rect("#dad6e9"),
         panel.grid.major = element_line("white"),
         panel.grid.minor = element_blank(),
-        legend.position = c(0.18, 0.855),
+        legend.position = c(0.19, 0.855),
         legend.spacing.x = unit(0.1, "cm"),
         legend.spacing.y = unit(0.1, "cm"),
         legend.key.size = unit(0.3, "cm"),
@@ -3671,7 +3671,7 @@ occ_vpc_ggplot_personnes_morales <- ggplot(data=occ_vpc_graph_personnes_morales,
   labs(title = "Voitures particulières et commerciales <span style = 'color:#469b36'>d'occasion</span>",
        caption = "Source : SDES - Répertoire statistique des véhicules routiers (RSVéRo)")+
   annotation_custom(grobTree(textGrob("En juin et juillet 2024, un\ngrand groupe automobile\na acheté 35 000 voitures de\ncourtoisie à l'occasion d'un rappel\nde 530 000 airbags défectueux.",
-                                      x=0.72,  y=0.83, hjust=0.5, gp=gpar(col="black", fontsize=11, fontface="plain"))))
+                                      x=0.71,  y=0.83, hjust=0.5, gp=gpar(col="black", fontsize=11, fontface="plain"))))
 
 
 ## Cyclomoteur
@@ -3725,7 +3725,7 @@ occ_cyclo_ggplot_personnes_morales <- ggplot(data=occ_cyclo_graph_personnes_mora
   labs(title = "Cyclomoteurs <span style = 'color:#469b36'>d'occasion</span>",
        caption = "Source : SDES - Répertoire statistique des véhicules routiers (RSVéRo)")+
   annotation_custom(grobTree(textGrob("En décembre 2022,\nplus de 2 000 scooters\nélectriques d'occasion\nont été vendus à des\npersonnes morales\nen Seine-Saint-Denis.",
-                                      x=0.63,  y=0.75, hjust=0.5, gp=gpar(col="black", fontsize=11, fontface="plain"))))
+                                      x=0.61,  y=0.75, hjust=0.5, gp=gpar(col="black", fontsize=11, fontface="plain"))))
 
 # annotation_custom(grobTree(textGrob("En décembre 2022,\ntous les départements\nd'Île-de-France\nont enregistré un nombre\ninhabituel de cyclomoteurs\nvendus à des personnes\nmorales.",
 #                                     x=0.65,  y=0.705, hjust=0.5, gp=gpar(col="black", fontsize=12, fontface="plain"))))
@@ -4440,7 +4440,7 @@ neuf_occ_graph_synthese <- bind_cols(neuf_graph_synthese, occ_graph_synthese) %>
   mutate(date_2 = ym(date))
 
 ## Positionnement de l'étiquette des années sur l'axe des abcisses en fonction du dernier mois 
-hjust_aaaa_bis <- ifelse(months(ym(dernier_mois_rsvero_2)) %in% c("mai", "juin", "juillet", "août", "septembre"), -0.1, -1.6)
+hjust_aaaa_bis <- ifelse(months(ym(dernier_mois_rsvero_2)) %in% c("mai", "juin", "juillet", "août", "septembre"), -0.1, -1.55)
 
 ## Mise en forme du graphique
 neuf_occ_synthese_ggplot <- ggplot(data=neuf_occ_graph_synthese, aes(x=date_2, y=immat/1000, color=neuf_occ, group=neuf_occ))+
diff --git a/scripts/03_co2.R b/scripts/03_co2.R
index 6f78b0b..9a740d3 100644
--- a/scripts/03_co2.R
+++ b/scripts/03_co2.R
@@ -38,6 +38,9 @@ rm(co2_reg, co2_dep)
 co2_reg_graph <- co2 %>%
   filter(zone %in% c("Pays de la Loire", "France"))
 
+## Positionnement de l'étiquette des années sur l'axe des abcisses en fonction du dernier mois 
+hjust_aaaa_ter <- ifelse(months(ym(dernier_mois_rsvero_2)) %in% c("mai", "juin", "juillet", "août", "septembre"), -0.1, -1.6)
+
 ## Mise en forme du graphique
 co2_reg_ggplot <- ggplot(data=co2_reg_graph, aes(x=date_2, y=co2, color=zone, group=zone))+
   scale_color_manual(values=c("#323787", "#469b36"))+
@@ -58,7 +61,7 @@ co2_reg_ggplot <- ggplot(data=co2_reg_graph, aes(x=date_2, y=co2, color=zone, gr
         legend.title = element_blank(),
         legend.text = element_text(size=13),
         legend.background = element_rect(fill=NA),
-        axis.text.x = element_text(size=11, hjust=hjust_aaaa_bis, color="black"),
+        axis.text.x = element_text(size=11, hjust=hjust_aaaa_ter, color="black"),
         axis.text.y = element_text(size=12, color="black"),
         axis.line.x = element_line(color="black"),
         axis.line.y = element_line(color="black"),
@@ -102,7 +105,7 @@ co2_dep_ggplot <- ggplot(data=co2_dep_graph, aes(x=date_2, y=co2, color=zone, gr
         legend.title = element_blank(),
         legend.text = element_text(size=13),
         legend.background = element_rect(fill=NA),
-        axis.text.x = element_text(size=11, hjust=hjust_aaaa_bis, color="black"),
+        axis.text.x = element_text(size=11, hjust=hjust_aaaa_ter, color="black"),
         axis.text.y = element_text(size=12, color="black"),
         axis.line.x = element_line(color="black"),
         axis.line.y = element_line(color="black"),
diff --git a/scripts/bilan_eco_insee.R b/scripts/bilan_eco_insee.R
index db20410..6e76f08 100644
--- a/scripts/bilan_eco_insee.R
+++ b/scripts/bilan_eco_insee.R
@@ -44,7 +44,7 @@ options(OutDec= ",")
 # Par exemple, passer de "stat_ dreal_n_2016 _1 à 2023_8.xlsx" à "stat_dreal_n_2016_1_2023_08.xlsx
 
 # Création de la liste de tous les fichiers RSVéRO déposés dans le dossier dédié
-liste_fichiers_neuf <- list.files("X:/SCTE/DEP/Donnees_confidentielles/Conjoncture/rsvero",
+liste_fichiers_neuf <- list.files("X:/SCTE/CSD/DONNEES_CONFIDENTIELLES/_niveau_2/Conjoncture/rsvero",
                                   include.dirs = FALSE, full.names = FALSE, pattern = "stat_dreal_n_2016_1_")
 
 # Extraction des sept derniers caractères du fichier RSVéRO le plus récent
@@ -54,7 +54,7 @@ dernier_mois_rsvero <- liste_fichiers_neuf %>%
   max()
 
 # Reconstitution (par concaténation) du nom du fichier RSVéRO le plus récent
-neuf_file <- paste0("X:/SCTE/DEP/Donnees_confidentielles/Conjoncture/rsvero/stat_dreal_n_2016_1_",dernier_mois_rsvero,".xlsx")
+neuf_file <- paste0("X:/SCTE/CSD/DONNEES_CONFIDENTIELLES/_niveau_2/Conjoncture/rsvero/stat_dreal_n_2016_1_",dernier_mois_rsvero,".xlsx")
 
 # Ouverture du fichier RSVéRO, recodage de la variable énergie et création de la segmentation des véhicules en 14 postes
 neuf_data_raw_large <- read_excel(neuf_file) %>%
@@ -105,7 +105,7 @@ neuf_data_raw <- neuf_data_raw_large %>%
 # Traitement pour la partie immatriculations de véhicules du bilan économique de l'Insee ----
 bilan_eco_insee <- neuf_data_raw %>%
   mutate("Année" = str_sub(date, start = 1L, end = 4L)) %>%
-  filter(REG == 52, `Année` %in% c("2021", "2022", "2023")) %>%
+  filter(REG == 52, `Année` %in% c("2021", "2022", "2023", "2024")) %>%
   group_by(`Année`, energie) %>%
   summarise(immat = sum(immat, na.rm = T)) %>%
   spread(key = energie, value = "immat") %>%
@@ -120,7 +120,7 @@ bilan_eco_insee <- neuf_data_raw %>%
 
 bilan_eco_insee_2 <- neuf_data_raw %>%
   mutate("Année" = str_sub(date, start = 1L, end = 4L)) %>%
-  filter(REG == 52, `Année` %in% c("2021", "2022", "2023")) %>%
+  filter(REG == 52, `Année` %in% c("2021", "2022", "2023", "2024")) %>%
   group_by(`Année`, energie) %>%
   summarise(immat = sum(immat, na.rm = T)) %>%
   spread(key = energie, value = "immat") %>%
-- 
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