initial commit

.Rbuildignore

+^propre\.ecln\.Rproj$
+^\.Rproj\.user$
+^devstuff\.R$
+^data-raw$
+^extdata$
+^LICENSE\.md$

.gitignore

+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+extdata/
+data/

DESCRIPTION

+Package: propre.ecln
+Title: What the Package Does (One Line, Title Case)
+Version: 0.0.0.9000
+Authors@R: 
+    person(given = "Maël",
+           family = "THEULIERE",
+           role = c("aut", "cre"),
+           email = "mael.theuliere@gmail.com",
+           comment = c(ORCID = "0000-0002-5146-699X"))
+Description: What the package does (one paragraph).
+License: GPL (>= 3)
+Encoding: UTF-8
+LazyData: true
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.1.1
+Imports: 
+    COGiter,
+    dplyr,
+    lubridate,
+    stringr,
+    forcats,
+    ggforce,
+    ggplot2,
+    glue,
+    gouvdown,
+    scales,
+    magrittr,
+    rlang,
+    kableExtra,
+    knitr,
+    tidyr
+Remotes: 
+    MaelTheuliere/COGiter
+Depends: 
+    R (>= 2.10)

LICENSE.md

+GNU General Public License
+==========================
+
+_Version 3, 29 June 2007_  
+_Copyright © 2007 Free Software Foundation, Inc. &lt;<http://fsf.org/>&gt;_
+
+Everyone is permitted to copy and distribute verbatim copies of this license
+document, but changing it is not allowed.
+
+## Preamble
+
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+Nothing in this License shall be construed as excluding or limiting any implied
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+
+### 12. No Surrender of Others' Freedom
+
+If conditions are imposed on you (whether by court order, agreement or otherwise)
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+
+### 13. Use with the GNU Affero General Public License
+
+Notwithstanding any other provision of this License, you have permission to link or
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+
+### 14. Revised Versions of this License
+
+The Free Software Foundation may publish revised and/or new versions of the GNU
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+
+Each version is given a distinguishing version number. If the Program specifies that
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+Software Foundation.
+
+If the Program specifies that a proxy can decide which future versions of the GNU
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+
+Later license versions may give you additional or different permissions. However, no
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+
+### 15. Disclaimer of Warranty
+
+THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW.
+EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
+PROVIDE THE PROGRAM “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER
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+
+### 16. Limitation of Liability
+
+IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY
+COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS
+PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL,
+INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE
+PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE
+OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE
+WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGES.
+
+### 17. Interpretation of Sections 15 and 16
+
+If the disclaimer of warranty and limitation of liability provided above cannot be
+given local legal effect according to their terms, reviewing courts shall apply local
+law that most closely approximates an absolute waiver of all civil liability in
+connection with the Program, unless a warranty or assumption of liability accompanies
+a copy of the Program in return for a fee.
+
+_END OF TERMS AND CONDITIONS_
+
+## How to Apply These Terms to Your New Programs
+
+If you develop a new program, and you want it to be of the greatest possible use to
+the public, the best way to achieve this is to make it free software which everyone
+can redistribute and change under these terms.
+
+To do so, attach the following notices to the program. It is safest to attach them
+to the start of each source file to most effectively state the exclusion of warranty;
+and each file should have at least the “copyright” line and a pointer to
+where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+If the program does terminal interaction, make it output a short notice like this
+when it starts in an interactive mode:
+
+    <program>  Copyright (C) <year>  <name of author>
+    This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type 'show c' for details.
+
+The hypothetical commands `show w` and `show c` should show the appropriate parts of
+the General Public License. Of course, your program's commands might be different;
+for a GUI interface, you would use an “about box”.
+
+You should also get your employer (if you work as a programmer) or school, if any, to
+sign a “copyright disclaimer” for the program, if necessary. For more
+information on this, and how to apply and follow the GNU GPL, see
+&lt;<http://www.gnu.org/licenses/>&gt;.
+
+The GNU General Public License does not permit incorporating your program into
+proprietary programs. If your program is a subroutine library, you may consider it
+more useful to permit linking proprietary applications with the library. If this is
+what you want to do, use the GNU Lesser General Public License instead of this
+License. But first, please read
+&lt;<http://www.gnu.org/philosophy/why-not-lgpl.html>&gt;.

NAMESPACE

+# Generated by roxygen2: do not edit by hand
+
+export("%>%")
+export(FormatCaractere)
+export(FormatDate)
+export(creer_graphique_evolution_annuelle)
+export(data_prep)
+export(graphique_evolution_trim)
+export(graphique_investissement_locatif)
+export(graphique_series_temporelles)
+export(graphique_series_temporelles_prix)
+export(tableau_synthese_annuel)
+export(tableau_synthese_trimestrielle)
+importFrom(COGiter,filtrer_cog)
+importFrom(dplyr,arrange)
+importFrom(dplyr,bind_rows)
+importFrom(dplyr,case_when)
+importFrom(dplyr,distinct)
+importFrom(dplyr,filter)
+importFrom(dplyr,full_join)
+importFrom(dplyr,mutate)
+importFrom(dplyr,pull)
+importFrom(dplyr,select)
+importFrom(forcats,fct_drop)
+importFrom(forcats,fct_inorder)
+importFrom(forcats,fct_recode)
+importFrom(forcats,fct_relevel)
+importFrom(ggforce,geom_mark_circle)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,coord_flip)
+importFrom(ggplot2,facet_wrap)
+importFrom(ggplot2,geom_area)
+importFrom(ggplot2,geom_bar)
+importFrom(ggplot2,geom_label)
+importFrom(ggplot2,geom_line)
+importFrom(ggplot2,geom_point)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,guides)
+importFrom(ggplot2,labs)
+importFrom(ggplot2,margin)
+importFrom(ggplot2,position_dodge)
+importFrom(ggplot2,scale_x_date)
+importFrom(ggplot2,scale_y_continuous)
+importFrom(ggplot2,theme)
+importFrom(glue,glue)
+importFrom(gouvdown,gouv_colors)
+importFrom(gouvdown,scale_color_gouv_discrete)
+importFrom(gouvdown,scale_fill_gouv_discrete)
+importFrom(grid,unit)
+importFrom(kableExtra,add_header_above)
+importFrom(kableExtra,add_indent)
+importFrom(kableExtra,kable_styling)
+importFrom(kableExtra,row_spec)
+importFrom(knitr,kable)
+importFrom(lubridate,"%m-%")
+importFrom(lubridate,`%m+%`)
+importFrom(lubridate,days)
+importFrom(lubridate,month)
+importFrom(lubridate,quarter)
+importFrom(lubridate,year)
+importFrom(lubridate,years)
+importFrom(lubridate,ymd)
+importFrom(magrittr,"%>%")
+importFrom(rlang,.data)
+importFrom(scales,dollar_format)
+importFrom(scales,format_format)
+importFrom(stringr,str_c)
+importFrom(stringr,str_replace)
+importFrom(stringr,str_split_fixed)
+importFrom(tidyr,spread)

R/FormatDate.R

+#' Conversion d'une date au mois ou trimestre en format date au jour.
+#'
+#' @param Periode caractère une date en format anneetrimestre ou anneemois
+#' @param Periodicite caractère Trim si la date est en trimestre, Mois pour une date au mois
+#' @param sep le séparateur entre l'année et le mois/trimestre
+#'
+#' @return une date au format date
+#' @importFrom dplyr case_when
+#' @importFrom lubridate ymd days `%m+%`
+#' @importFrom stringr str_split_fixed str_c str_replace
+#' @export
+#'
+#' @examples
+#' FormatDate("2010-10", Periodicite = "Mois")
+
+#' @importFrom dplyr case_when
+#' @importFrom lubridate ymd days
+#' @importFrom stringr str_split_fixed str_c str_replace
+FormatDate<-function(Periode,Periodicite,sep="-") {
+
+  Periode1=stringr::str_split_fixed(Periode,sep,2)[,1]
+  Periode2=stringr::str_split_fixed(Periode,sep,2)[,2]
+
+  if (Periodicite=="Trim") {
+    return(
+      lubridate::ymd(dplyr::case_when(
+        Periode2 %in% c("Q1","T1","1") ~ stringr::str_c(Periode1,"0331"),
+        Periode2 %in% c("Q2","T2","2") ~ stringr::str_c(Periode1,"0630"),
+        Periode2 %in% c("Q3","T3","3") ~ stringr::str_c(Periode1,"0930"),
+        Periode2 %in% c("Q4","T4","4") ~ stringr::str_c(Periode1,"1231")
+      )
+      ))
+  }
+  if (Periodicite=="Mois") {
+    return(
+      lubridate::ymd(stringr::str_c(stringr::str_replace(Periode,sep,""),"01"))  %m+%  months(1) %m+% lubridate::days(-1)
+    )
+  }
+}
+
+
+#' conversion d'une variable date en nommage trimestriel
+#'
+#' @param Periode date à convertire
+#'
+#' @return une chaine de caractère
+#' @importFrom dplyr case_when
+#' @importFrom lubridate year month
+#' @export
+#'
+#' @examples
+#' FormatCaractere("2010-10-01")
+FormatCaractere<-function(Periode) {
+  trim<-  dplyr::case_when(
+    lubridate::month(Periode) <=3 ~ "T1",
+    lubridate::month(Periode) <=6 ~ "T2",
+    lubridate::month(Periode) <=9 ~ "T3",
+    lubridate::month(Periode) <=12 ~ "T4"
+  )
+  return(
+    paste0(lubridate::year(Periode),trim)
+  )
+}
+

R/creer_graphique_evolution_annuelle.R

+#' graphique barre sur un an
+#'
+#' @param data Le dataframe.
+#' @param type_logement Collectifs ou individuels.
+#' @param type_zone Liste des types de zonage à intégrer dans la facette.
+#' @param titre Le titre du graphique.
+#' @param bas_de_page Le bas de page du graphique.
+#'
+#' @return Un graphique ggplot2.
+#' @importFrom dplyr filter mutate arrange
+#' @importFrom ggplot2 ggplot aes geom_bar coord_flip geom_label facet_wrap scale_y_continuous labs position_dodge
+#' @importFrom scales format_format
+#' @importFrom lubridate %m-%
+#' @export
+creer_graphique_evolution_annuelle<-function(data = indic_ecln,
+                                             type_zone = c("R\u00e9gions","D\u00e9partements"),
+                                             type_logement = "collectif",
+                                             titre="",
+                                             bas_de_page=""){
+  indic<-c("Encours - Appartements",
+           "Mises en vente - Appartements",
+           "Ventes - Appartements")
+  if (type_logement=="individuel") {
+    indic<- c("Encours - Maisons",
+              "Mises en vente - Maisons",
+              "Ventes - Maisons")
+  }
+
+  df <- data %>%
+    dplyr::filter(.data$Indicateur %in% indic,
+                  .data$TypeZone %in% type_zone,
+                  .data$TypeIndicateur=="Cumul annuel",
+                  .data$Periode==max(.data$Periode)|.data$Periode==max(.data$Periode) %m-% years(1)) %>%
+    dplyr::mutate(Periode=FormatCaractere(.data$Periode),
+                  Indicateur=str_split_fixed(.data$Indicateur," - ",2)[,1]) %>%
+    dplyr::arrange(.data$Zone)
+
+    ggplot2::ggplot(data = df, ggplot2::aes(x=.data$Periode,weight=.data$Valeur,fill=.data$Indicateur)) +
+    ggplot2::geom_bar(position=ggplot2::position_dodge())+
+    ggplot2::coord_flip()+
+    ggplot2::geom_label(data=df,
+                        ggplot2::aes(label=format(round(.data$Valeur),big.mark = " "),
+                                     x=.data$Periode,
+                                     y=.data$Valeur,
+                                     group=.data$Indicateur),
+                        position=position_dodge(0.9),
+                        color="white",
+                        fill="grey",
+                        alpha=.2,
+                        fontface="bold",
+                        hjust=1.2
+    )+
+    ggplot2::facet_wrap(~.data$Zone,scales="free",ncol=4)+
+    ggplot2::scale_y_continuous(labels=scales::format_format(big.mark=" "))+
+    ggplot2::labs(title=titre,subtitle="R\u00e9alis\u00e9es sur les 12 derniers mois",x="Trimestre",y="",
+                  caption=bas_de_page,fill="")
+}

R/data_prep.R

+#' datapreparation des données
+#'
+#' @param reg code region
+#' @param abc TRUE si on veut garder les zonages abc
+#' @param zone_a_secretiser listes des zonages à secretiser
+#' @param marches_a_secretiser liste des marchés à secretiser : individuel, collectif, tous
+#'
+#' @importFrom COGiter filtrer_cog
+#' @importFrom dplyr filter mutate arrange bind_rows
+#' @importFrom forcats fct_relevel fct_drop fct_inorder
+#' @importFrom lubridate years
+#' @importFrom stringr str_split_fixed
+#' @importFrom rlang .data
+#' @return un dataframe filtré sur la région souhaitée
+#' @export
+data_prep <- function(reg, abc = TRUE, zone_a_secretiser = "", marches_a_secretiser = "") {
+
+
+
+  if (abc == FALSE) {
+    result <- indic_ecln %>%
+      COGiter::filtrer_cog(reg = reg, garder_supra = ">") %>%
+      dplyr::mutate(TypeZone = forcats::fct_relevel(.data$TypeZone, "France", "R\u00e9gions", "D\u00e9partements", "Epci")) %>%
+      dplyr::arrange(.data$TypeZone, .data$Zone) %>%
+      dplyr::mutate(
+        Zone = forcats::fct_drop(.data$Zone),
+        Zone = forcats::fct_inorder(.data$Zone),
+        marche = stringr::str_split_fixed(.data$Indicateur, "-", n = 2)[, 2],
+        Valeur = ifelse(.data$Zone %in% zone_a_secretiser &
+                          .data$marche %in% marches_a_secretiser,
+        NA,
+        .data$Valeur
+        ),
+        TauxEvolution12Mois = ifelse(.data$Zone %in% zone_a_secretiser &
+                                       .data$marche %in% marches_a_secretiser,
+        NA,
+        .data$TauxEvolution12Mois
+        )
+      )
+  }
+  if (abc == TRUE) {
+    result <- indic_ecln %>%
+      COGiter::filtrer_cog(reg = reg, garder_supra = ">")
+
+    abc <- indic_ecln %>%
+      dplyr::filter(.data$TypeZone == "ABC")
+
+    result <- dplyr::bind_rows(result, abc)
+    dplyr::mutate(TypeZone = forcats::fct_relevel(as.factor(.data$TypeZone), "France", "R\u00e9gions", "D\u00e9partements", "Epci", "ABC")) %>%
+      dplyr::arrange(.data$TypeZone, .data$Zone) %>%
+      dplyr::mutate(
+        Zone = forcats::fct_drop(.data$Zone),
+        Zone = forcats::fct_inorder(.data$Zone),
+        marche = stringr::str_split_fixed(.data$Indicateur, "-", n = 2)[, 2],
+        Valeur = ifelse(.data$Zone %in% zone_a_secretiser &
+                          .data$marche %in% marches_a_secretiser,
+        NA,
+        .data$Valeur
+        ),
+        TauxEvolution12Mois = ifelse(.data$Zone %in% zone_a_secretiser &
+                                       .data$marche %in% marches_a_secretiser,
+        NA,
+        .data$TauxEvolution12Mois
+        )
+      )
+  }
+  return(result)
+}

R/globals.R

+utils::globalVariables(
+  c("liste_zone","indic_ecln","%m-%")
+)

R/graphique_evolution_trim.R

+#' graphique sur un territoire sur un indicateur en moyenne annuelle et valeur trimestrielle
+#'
+#' @param data Le dataframe avec les données ecln.
+#' @param indicateur  L'indicateur à visualiser.
+#' @param zone Le territoire sur lequel visualiser l'indicateur.
+#' @param titre Le titre du graphique.
+#'
+#' @return  un ggplot2
+#' @export
+#' @importFrom dplyr select distinct pull filter mutate
+#' @importFrom forcats fct_recode
+#' @importFrom ggforce geom_mark_circle
+#' @importFrom ggplot2 ggplot aes geom_line geom_point margin theme labs guides scale_y_continuous scale_x_date
+#' @importFrom glue glue
+#' @importFrom gouvdown gouv_colors scale_color_gouv_discrete scale_fill_gouv_discrete
+#' @importFrom grid unit
+#' @importFrom lubridate quarter year
+#' @importFrom stringr str_c
+graphique_evolution_trim <- function(data = indic_ecln,
+                                     indicateur = "Ventes - Logements",
+                                     zone = "Pays de la Loire",
+                                     titre = "Ventes de logements neufs en Pays de la Loire") {
+  per <- data %>%
+    dplyr::select(.data$Periode) %>%
+    dplyr::distinct() %>%
+    dplyr::pull(.data$Periode)
+
+  max_date <- max(per)
+
+  sous_titre <- glue::glue("Au {label_rang(lubridate::quarter(max_date))} trimestre {lubridate::year(max_date)}")
+  label <- data %>%
+    dplyr::filter(
+      .data$Zone == zone,
+      .data$Indicateur == indicateur
+    ) %>%
+    dplyr::filter(.data$Periode == max(.data$Periode)) %>%
+    dplyr::mutate(
+      Valeur = ifelse(.data$TypeIndicateur == "Cumul annuel", .data$Valeur / 4, .data$Valeur),
+      TypeIndicateur = forcats::fct_recode(.data$TypeIndicateur,
+        "Moyenne annuelle" = "Cumul annuel",
+        "Valeur trimestrielle" = "Trimestriel"
+      )
+    ) %>%
+    dplyr::mutate(
+      description = stringr::str_c(
+        format(round(.data$Valeur), big.mark = " "),
+        "\n",
+        ifelse(.data$TauxEvolution12Mois > 0, "+", ""),
+        format(round(.data$TauxEvolution12Mois, 1), big.mark = " ", decimal.mark = ","),
+        " %"
+      ),
+      label = ifelse(.data$TypeIndicateur %in% c("Valeur trimestrielle"),
+        FormatCaractere(.data$Periode),
+        "Moyenne\nannuelle"
+      )
+    )
+
+  gg <- data %>%
+    dplyr::filter(
+      .data$Zone == zone,
+      .data$Indicateur == indicateur
+    ) %>%
+    dplyr::mutate(
+      Valeur = ifelse(.data$TypeIndicateur == "Cumul annuel", .data$Valeur / 4, .data$Valeur),
+      TypeIndicateur = forcats::fct_recode(.data$TypeIndicateur,
+        "Moyenne annuelle" = "Cumul annuel",
+        "Valeur trimestrielle" = "Trimestriel"
+      )
+    ) %>%
+    ggplot2::ggplot() +
+    ggplot2::aes(x = .data$Periode, y = .data$Valeur, group = .data$TypeIndicateur, linetype = .data$TypeIndicateur, color = .data$TypeIndicateur) +
+    ggplot2::geom_line() +
+    ggplot2::geom_point(data = label, ggplot2::aes(x = .data$Periode, y = .data$Valeur, group = .data$TypeIndicateur, color = .data$TypeIndicateur)) +
+    ggforce::geom_mark_circle(
+      data = label, ggplot2::aes(
+        label = .data$label,
+        fill = .data$TypeIndicateur,
+        description = .data$description
+      ),
+      label.buffer = grid::unit(5, "mm"),
+      expand = grid::unit(2, "mm"),
+      label.margin = ggplot2::margin(2, 5, 2, 5, "mm"),
+      label.colour = "white",
+      alpha = .5,
+      label.fill = gouvdown::gouv_colors("bleu_france")
+    ) +
+    ggplot2::theme(legend.position = "bottom") +
+    gouvdown::scale_color_gouv_discrete(palette = "pal_gouv_qual2") +
+    gouvdown::scale_fill_gouv_discrete(palette = "pal_gouv_qual2") +
+    ggplot2::labs(
+      x = "",
+      y = "Nombre de ventes",
+      title = titre,
+      subtitle = sous_titre,
+      caption = "Source : ECLN\nMoyenne Annuelle : Valeur observ\u00e9e en moyenne sur les 4 derniers trimestres"
+    ) +
+    ggplot2::guides(fill = F) +
+    ggplot2::scale_y_continuous(labels = function(l) format(l, scientific = FALSE, big.mark = " ", decimal.mark = ","), limits = c(0, NA)) +
+    ggplot2::scale_x_date(date_breaks = "1 year", date_labels = "%Y", limits = c(min(per), max(per) + months(12)))
+
+  return(gg)
+}

R/graphique_investissement_locatif.R

+#' Graphique d'évolution de l'investissement locatif
+#'
+#' @param data le dataframe avec les données ecln
+#' @param type_logement Appartements ou Maisons
+#' @param type_indicateur cumul annuel ou valeur trimestrielle
+#' @param type_zone liste des types de zonage à intégrer dans la facette
+#' @param titre titre du graphique
+#' @param soustitre sous titre du graphique
+#' @param bas_de_page bas de page
+#'
+#' @return Un graphique ggplot2.
+#' @export
+#' @importFrom dplyr filter mutate
+#' @importFrom forcats fct_drop
+#' @importFrom ggplot2 ggplot aes geom_area scale_x_date scale_y_continuous labs facet_wrap
+#' @importFrom scales format_format
+#' @importFrom stringr str_split_fixed
+#'
+#' @examples
+graphique_investissement_locatif <- function(data = indic_ecln,
+                                             type_logement = "Appartements",
+                                             type_zone = c("R\u00e9gions","D\u00e9partements"),
+                                             type_indicateur = "Cumul annuel",
+                                             titre = "",
+                                             soustitre = "",
+                                             bas_de_page = "") {
+  indic <- c(
+    "Ventes hors investissement locatif - Appartements",
+    "Ventes en investissement locatif - Appartements"
+  )
+  if (type_logement == "Maisons") {
+    indic <- c(
+      "Ventes hors investissement locatif - Maisons",
+      "Ventes en investissement locatif - Maisons"
+    )
+  }
+
+  data_prep <- data %>%
+    dplyr::filter(
+      .data$Indicateur %in% indic,
+      .data$TypeIndicateur == type_indicateur,
+      .data$TypeZone %in% type_zone
+    ) %>%
+    dplyr::mutate(
+      Zone = forcats::fct_drop(.data$Zone),
+      Indicateur = stringr::str_split_fixed(.data$Indicateur, " - ", 2)[, 1]
+    )
+
+
+  p <- ggplot2::ggplot(
+    data = data_prep,
+    ggplot2::aes(
+      x = .data$Periode,
+      y = .data$Valeur,
+      color = .data$Indicateur,
+      fill = .data$Indicateur,
+      group = .data$Indicateur
+    )
+  ) +
+    ggplot2::geom_area(alpha = .5) +
+    ggplot2::scale_x_date(date_labels = "%y", date_breaks = "1 year") +
+    ggplot2::scale_y_continuous(labels = scales::format_format(big.mark = " ")) +
+    ggplot2::labs(
+      title = titre,
+      subtitle = soustitre,
+      x = "",
+      y = "",
+      fill = "",
+      color = "",
+      caption = bas_de_page
+    )
+  if (nlevels(data_prep$Zone) > 1) {
+    p <- p + ggplot2::facet_wrap(~Zone, scales = "free", ncol = 4)
+  }
+  return(p)
+}

R/graphique_series_temporelles.R

+#' graphique en série temporelle à facette
+#'
+#' @param data Le dataframe avec les données ecln.
+#' @param type_logement Appartements ou Maisons.
+#' @param indicateurs Un vecteur d'indicateur à visualiser dans le graphique.
+#' @param type_zone Liste des types de zonage à intégrer dans la facette.
+#' @param titre Le titre du graphique.
+#' @param bas_de_page Le bas de page du graphique.
+#' @param ncol_facet Le nombre de colonnes dans la facette.
+#' @return Un graphique ggplot2.
+#' @export
+#' @importFrom dplyr filter mutate
+#' @importFrom ggplot2 ggplot aes geom_line facet_wrap scale_y_continuous scale_x_date labs
+#' @importFrom gouvdown scale_color_gouv_discrete
+#' @importFrom scales format_format
+#' @examples
+graphique_series_temporelles<-function(data=indic_ecln,
+                                       type_logement="Appartements",
+                                       indicateurs = c("Encours","Mises en vente","Ventes"),
+                                       type_zone = c("R\u00e9gions","D\u00e9partements"),
+                                       titre="",
+                                       bas_de_page="",
+                                       ncol_facet=4
+){
+  indic <- paste0(indicateurs," - ",type_logement)
+  gg <- data %>%
+    dplyr::filter(.data$Indicateur %in% indic,
+                  .data$TypeZone %in% type_zone,
+                  .data$TypeIndicateur=="Cumul annuel") %>%
+    dplyr::mutate(Indicateur=str_split_fixed(.data$Indicateur," - ",2)[,1]) %>%
+    ggplot2::ggplot() +
+    ggplot2::aes(x=.data$Periode,y=.data$Valeur,color=.data$Indicateur,fill=.data$Indicateur,group=.data$Indicateur) +
+    ggplot2::geom_line(size=1.2)+
+    ggplot2::facet_wrap(~.data$Zone,scales="free",ncol=ncol_facet)+
+    ggplot2::scale_y_continuous(labels=scales::format_format(big.mark=" "),limits=c(0,NA)) +
+    ggplot2::scale_x_date(date_labels="%y",date_breaks = "1 year") +
+    gouvdown::scale_color_gouv_discrete(palette = "pal_gouv_qual2") +
+    ggplot2::labs(title=titre,
+                  x="",
+                  y="",
+                  fill="",
+                  color="",
+                  caption=bas_de_page)
+  return(gg)
+}

R/graphique_series_temporelles_prix.R

+#' graphique sur l'évolution du prix de vente des biens.
+#'
+#' @param data Le dataframe.
+#' @param type_logement Appartements ou Maisons.
+#' @param type_indicateur Cumul annuel ou valeur trimestrielle.
+#' @param type_zone Liste des types de zonage à intégrer dans la facette.
+#' @param titre Le titre du graphique.
+#' @param bas_de_page Le bas de page du graphique.
+#'
+#' @return Un graphique ggplot2.
+#' @export
+#' @importFrom dplyr filter mutate
+#' @importFrom forcats fct_drop
+#' @importFrom ggplot2 ggplot aes geom_line geom_point theme scale_x_date scale_y_continuous labs facet_wrap
+#' @importFrom scales dollar_format
+#' @importFrom stringr str_split_fixed
+#' @importFrom gouvdown scale_color_gouv_discrete
+#' @examples
+graphique_series_temporelles_prix<-function(data=indic_ecln,
+                                            type_logement="Appartements",
+                                            type_zone = c("R\u00e9gions","D\u00e9partements"),
+                                            type_indicateur = "Cumul annuel",
+                                            titre="",
+                                            bas_de_page=""){
+  indic<-c("PrixM2 - Appartements")
+  if (type_logement=="Maisons") {
+    indic<- c("PrixPar - Maisons")
+  }
+
+  data_prep<-data %>%
+    dplyr::filter(.data$Indicateur %in% indic,
+                  .data$TypeIndicateur == type_indicateur,
+                  .data$TypeZone %in% type_zone) %>%
+    dplyr::mutate(Zone = forcats::fct_drop(.data$Zone),
+           Indicateur=stringr::str_split_fixed(.data$Indicateur," - ",2)[,1])
+
+
+  p<-ggplot2::ggplot(data_prep,
+                     ggplot2::aes(x=.data$Periode,
+                y=.data$Valeur,
+                color=.data$Indicateur,
+                fill=.data$Indicateur,
+                group=.data$Indicateur)) +
+    ggplot2::geom_line(size=1.2)+
+    ggplot2::geom_point(data=  data %>%
+                 dplyr::filter(.data$Indicateur %in% indic,
+                               .data$TypeIndicateur == type_indicateur,
+                               .data$TypeZone %in% type_zone,
+                               .data$Periode==max(.data$Periode)))+
+    ggplot2::theme(legend.position = "none")+
+    ggplot2::scale_x_date(date_labels="%y",date_breaks = "1 year")+
+    ggplot2::scale_y_continuous(labels=scales::dollar_format(big.mark=" ",decimal_mark=",",prefix="",suffix=" \u20ac"))+
+    gouvdown::scale_color_gouv_discrete(palette = "pal_gouv_qual2") +
+    ggplot2::labs(title=titre,
+         x="",
+         y="",
+         fill="",
+         color="",
+         caption=bas_de_page)
+  if (nlevels(data_prep$Zone)>1){
+    p<-p+ggplot2::facet_wrap(~Zone,scales="fixed",ncol=4)
+  }
+  return(p)
+}

R/indic_ecln.R

+#' Table contenant les différents indicateurs de la source ecln utiles pour la publication.
+#'
+#' @encoding UTF-8
+#' @format  Table de `r nrow(indic_ecln)` lignes et `r ncol(indic_ecln)` colonnes:
+#' \describe{
+#'   \item{TypeZone}{Type de territoire}
+#'   \item{CodeZone}{Code du territoire}
+#'   \item{Zone}{Libellé du territoire}
+#'   \item{TypeIndicateur}{valeur cumulée sur 12 mois ou trimestrielle}
+#'   \item{Indicateur}{Liste des indicateurs}
+#'   \item{Periode}{Trimestre d'observation}
+#'   \item{valeur}{Valeur de l'indicateur pour la modalité de variable}
+#'   \item{TauxEvolution12Mois}{Evolution de l'indicateur sur 12 mois glissant}
+#' }
+#' @source \url{https://www.statistiques.developpement-durable.gouv.fr/enquete-sur-la-commercialisation-des-logements-neufs-ecln}
+"indic_ecln"

R/label_rang.R

+label_rang <- function(x) {
+  if (x == 1) {
+    res <- paste0(x,"er")
+  }
+  if (x == 2) {
+    res <- paste0(x,"nd")
+  }
+  if (x > 2) {
+    res <- paste0(x,"\u00e8me")
+  }
+  return(res)
+}

R/tableau_synthese_annuelle.R

+#' tableau de synthèse des données en cumul annuel
+#'
+#' @param data Le dataframe.
+#' @param type_logement Collectifs ou individuels.
+#' @param type_zone Liste des types de zonage à intégrer dans la facette.
+#' @return Un table kable
+#' @importFrom dplyr filter mutate pull select full_join arrange
+#' @importFrom kableExtra kable_styling row_spec add_header_above add_indent
+#' @importFrom knitr kable
+#' @importFrom stringr str_split_fixed
+#' @importFrom tidyr spread
+#' @export
+tableau_synthese_annuel<-function(data = indic_ecln,
+                                  type_zone = c("France","R\u00e9gions","D\u00e9partements"),
+                                  type_logement = "collectif"
+                                  ){
+  indic<-c("Encours - Appartements",
+           "Mises en vente - Appartements",
+           "Ventes - Appartements",
+           "PrixM2 - Appartements")
+  if (type_logement=="individuel") {
+    indic<- c("Encours - Maisons",
+              "Mises en vente - Maisons",
+              "Ventes - Maisons",
+              "PrixPar - Maisons")
+  }
+  input<-indic_ecln %>%
+    dplyr::filter(.data$Indicateur %in% indic,
+                  .data$TypeZone %in% type_zone,
+                  .data$TypeIndicateur=="Cumul annuel",
+                  .data$Periode==max(.data$Periode)) %>%
+    dplyr::mutate(Indicateur=stringr::str_split_fixed(.data$Indicateur,"-",2)[,1])
+
+  nombre_zone <- length(unique(input$CodeZone))
+  nombre_fr_dep_reg <- length(unique(input %>% dplyr::filter(.data$TypeZone %in% c("R\u00e9gions","D\u00e9partements")) %>% dplyr::pull(.data$CodeZone)))
+  res<- input %>%
+    dplyr::select(.data$TypeZone,.data$Zone,.data$Indicateur,.data$Valeur) %>%
+    tidyr::spread(.data$Indicateur,.data$Valeur) %>%
+    dplyr::full_join(
+      input %>%
+        dplyr::select(.data$TypeZone,.data$Zone,.data$Indicateur,.data$TauxEvolution12Mois) %>%
+        tidyr::spread(.data$Indicateur,.data$TauxEvolution12Mois),
+      by=c("TypeZone","Zone")
+    ) %>%
+    dplyr::arrange(.data$Zone) %>%
+    dplyr::select(2,6,10,4,8,3,7,5,9) %>%
+    knitr::kable("html",col.names=c("Zone","Sur les 12 derniers mois","Evolution sur un an (en %)",
+                             "Sur les 12 derniers mois","Evolution sur un an (en %)",
+                             "En fin de p\u00e9riode","Evolution sur un an (en %)",
+                             "Prix moyen sur les 12 derniers mois (en €)","Evolution sur un an (en %)"),
+          digits=c(0,0,1,0,1,0,1,0,1),
+          format.args=list(big.mark=" ",decimal.mark=",")) %>%
+    kableExtra::kable_styling(font_size = 12) %>%
+    kableExtra::row_spec(1:2, bold = T, background = "#f0f0f5") %>%
+    kableExtra::add_header_above(c(" "=1, "Ventes" = 2, "Mises en vente" = 2, "Encours" = 2,"Prix au m2"=2)) %>%
+    kableExtra::add_indent(c(3:nombre_zone))
+  if("ABC" %in% type_zone){
+    res<-res %>%
+      kableExtra::row_spec(nombre_fr_dep_reg:nombre_zone, bold = T, background = "#bebece")
+  }
+  return(res)
+}

R/tableau_synthese_trimestrielle.R

+#' Création du tableau de synthèse trimestrielle
+#'
+#' @param data Le dataframe.
+#' @param type_logement Collectifs ou individuels.
+#'
+#' @return un tableau kable
+#' @export
+#' @importFrom dplyr filter mutate select full_join arrange
+#' @importFrom kableExtra kable_styling row_spec add_header_above
+#' @importFrom knitr kable
+#' @importFrom stringr str_split_fixed
+#' @importFrom tidyr spread
+tableau_synthese_trimestrielle<-function(data = indic_ecln,
+                                         type_logement="collectif"){
+
+  indic<-c("Encours - Appartements",
+           "Mises en vente - Appartements",
+           "Ventes - Appartements",
+           "PrixM2 - Appartements")
+  if (type_logement=="individuel") {
+    indic<- c("Encours - Maisons",
+              "Mises en vente - Maisons",
+              "Ventes - Maisons",
+              "PrixPar - Maisons")
+  }
+  indic_ecln %>%
+    dplyr::filter(.data$Indicateur %in% indic,
+                  .data$TypeZone %in% c("France","Régions"),
+                  .data$TypeIndicateur != "Cumul annuel",
+                  .data$Periode==max(.data$Periode)) %>%
+    dplyr::mutate(Indicateur=str_split_fixed(.data$Indicateur,"-",2)[,1]) %>%
+    dplyr::select(.data$TypeZone,.data$Zone,.data$Indicateur,.data$Valeur) %>%
+    tidyr::spread(.data$Indicateur,.data$Valeur) %>%
+    dplyr::full_join(
+      indic_ecln %>%
+        dplyr::filter(.data$Indicateur %in% indic,
+                      .data$TypeZone %in% c("France","Régions"),
+                      .data$TypeIndicateur!="Cumul annuel",
+                      .data$Periode==max(.data$Periode)) %>%
+        dplyr::mutate(Indicateur=stringr::str_split_fixed(.data$Indicateur,"-",2)[,1]) %>%
+        dplyr::select(.data$TypeZone,.data$Zone,.data$Indicateur,.data$TauxEvolution12Mois) %>%
+        spread(.data$Indicateur,.data$TauxEvolution12Mois),
+      by=c("TypeZone","Zone")
+    ) %>%
+    dplyr::arrange(.data$Zone) %>%
+    dplyr::select(2,6,10,4,8,3,7,5,9) %>%
+    knitr::kable("html",col.names=c("Zone","Sur le dernier trimestre","Evolution sur un an (en %)",
+                             "Sur le dernier trimestre","Evolution sur un an (en %)",
+                             "En fin de p\u00e9riode","Evolution sur un an (en %)",
+                             "Prix moyen sur le dernier trimestre (en €)","Evolution sur un an (en %)"),
+          digits=c(0,0,1,0,1,0,1,0,1),
+          format.args=list(big.mark=" ",decimal.mark=",")) %>%
+    kableExtra::kable_styling(font_size = 12) %>%
+    kableExtra::row_spec(1:2, bold = T, background = "#f0f0f5") %>%
+    kableExtra::add_header_above(c(" "=1, "Ventes" = 2, "Mises en vente" = 2, "Encours" = 2,"Prix au m2"=2))
+}

R/utils-pipe.R

+#' Pipe operator
+#'
+#' See \code{magrittr::\link[magrittr:pipe]{\%>\%}} for details.
+#'
+#' @name %>%
+#' @rdname pipe
+#' @keywords internal
+#' @export
+#' @importFrom magrittr %>%
+#' @usage lhs \%>\% rhs
+NULL

data-raw/data-raw-ecln-sas-R.R

+## code to prepare `data-raw-ecln-sas.R` dataset goes here
+
+library(magrittr)
+library(haven)
+library(readxl)
+library(lubridate)
+library(conflicted)
+# devtool::install_github("MaelTheuliere/COGiter")
+library(COGiter)
+library(purrr)
+library(dplyr)
+library(tidyr)
+library(forcats)
+library(lubridate)
+library(stringr)
+library(glue)
+library(dtplyr)
+options(scipen = 999)
+conflict_prefer("filter", "dplyr")
+conflict_prefer("lag", "dplyr")
+conflict_prefer("union", "dplyr")
+conflict_prefer("setdiff", "dplyr")
+source("R/FormatDate.R")
+
+trimestre <- fs::dir_ls(path = "extdata", type = "directory") %>%
+  stringr::str_replace_all("extdata/","") %>%
+  max()
+trimestre_date <- FormatDate(trimestre, Periodicite = "Trim", sep = "T")
+
+trimestre_min <- FormatCaractere(trimestre_date-years(5)-months(3))
+file_sas <- glue("extdata/{trimestre}/stat_info_data_regionaux.sas7bdat")
+file_redressement <- glue("extdata/{trimestre}/{trimestre}rd1-commercialisation-lgts-neufs.xls")
+
+ECLN <- read_sas(file_sas)
+# Rajout du taux de redressement sur les mises en vente et le stoc --------
+valeur_redressees <- excel_sheets(path = file_redressement)[4:length(excel_sheets(path = file_redressement))] %>%
+  map(~ read_excel(
+    path = file_redressement, sheet = .x,
+    range = "B10:Q10",
+    col_names = F
+  ) %>%
+    select(1:5, 12:14) %>%
+    setNames(nm = c(
+      "Annee", "Periode", "Mises en vente - Appartements", "c_nb_resa", "Encours - Appartements",
+      "Mises en vente - Maisons", "i_nb_resa", "Encours - Maisons"
+    )) %>%
+    mutate(
+      Periode = paste0(Annee, Periode),
+      REG = .x
+    ) %>%
+    select(REG, everything(), -Annee, -c_nb_resa, -i_nb_resa)) %>%
+  bind_rows() %>%
+  gather(Indicateur, Valeur, -REG, -Periode)
+
+# calcul des indicateurs sur la carte des communes contenue dans ecln
+# passage des données au cog à jour
+
+indic_ecln <- ECLN %>%
+  select(DEPCOM = code_insee, Periode = trim_mev, id_type_lgt, mev_t) %>%
+  as_tibble() %>%
+  filter(Periode >= trimestre_min) %>%
+  group_by(id_type_lgt, DEPCOM, Periode) %>%
+  summarise(mev_t = sum(mev_t, na.rm = T)) %>%
+  ungroup() %>%
+  full_join(ECLN %>%
+              select(DEPCOM = code_insee, Periode = trimestre_enquete, everything()) %>%
+              filter(Periode >= trimestre_min) %>%
+              mutate(
+                nb_lgt_inv = nb_lgt_inv_t1 + nb_lgt_inv_t2 + nb_lgt_inv_t3 + nb_lgt_inv_t4 + nb_lgt_inv_t5 + nb_lgt_inv_t6,
+                nb_hors_resa_inv = nb_resa - nb_lgt_inv
+              ) %>%
+              group_by(id_type_lgt, DEPCOM, Periode) %>%
+              summarise(
+                nb_resa = sum(nb_resa, na.rm = T),
+                nb_resa_inv = sum(nb_lgt_inv, na.rm = T),
+                nb_hors_resa_inv = sum(nb_hors_resa_inv, na.rm = T),
+                stock_fin = sum(stock_fin, na.rm = T),
+                prix = sum(prix, na.rm = T),
+                surface = sum(surface, na.rm = T)
+              ) %>%
+              ungroup()) %>%
+  gather(Indicateur, Valeur, mev_t:surface) %>%
+  mutate(
+    Periode = factor(Periode),
+    id_type_lgt = factor(id_type_lgt),
+    DEPCOM = factor(DEPCOM),
+    id_type_lgt = fct_recode(id_type_lgt, Maisons = "1", Appartements = "2"),
+    Indicateur = fct_recode(factor(Indicateur), `Mises en vente` = "mev_t", Ventes = "nb_resa", `Ventes en investissement locatif` = "nb_resa_inv", `Ventes hors investissement locatif` = "nb_hors_resa_inv", Encours = "stock_fin", Prix = "prix", Surface = "surface"),
+    Indicateur = str_c(Indicateur, " - ", id_type_lgt)
+  ) %>%
+  select(-id_type_lgt) %>%
+  mutate(Valeur = ifelse(is.na(Valeur),0,Valeur)) %>%
+  passer_au_cog_a_jour(code_commune = DEPCOM, aggrege = T, garder = F) %>%
+  right_join(communes %>% select(DEPCOM)) %>%
+  complete(DEPCOM, Periode, Indicateur,
+           fill = list(Valeur = 0)
+  ) %>%
+  filter(!is.na(Indicateur), !is.na(Periode)) %>%
+  passer_au_cog_a_jour(code_commune = DEPCOM, aggrege = T, garder = T) %>%
+  select(REG, DEPCOM, Periode, Indicateur, Valeur) %>%
+  mutate_if(is.character, as.factor)
+
+# On ne garde que les régions métro
+indic_ecln <- indic_ecln %>%
+  filter(!(REG %in% c("01", "02", "03", "04", "05", "06")))
+
+
+rm(ECLN)
+
+taux_redressement <- indic_ecln %>%
+  filter(
+    Indicateur %in% unique(valeur_redressees$Indicateur),
+    as.character(REG) %in% unique(valeur_redressees$REG),
+    Periode == max(as.character(Periode))
+  ) %>%
+  select(REG, Periode, Indicateur, Valeur) %>%
+  group_by(REG, Periode, Indicateur) %>%
+  summarise_all(funs(sum)) %>%
+  ungroup() %>%
+  left_join(valeur_redressees, by = c("REG", "Periode", "Indicateur")) %>%
+  mutate(taux_redressement = ifelse(Valeur.x > 0, Valeur.y / Valeur.x, 1)) %>%
+  select(REG, Periode, Indicateur, taux_redressement)
+
+indic_ecln <- indic_ecln %>%
+  left_join(taux_redressement) %>%
+  mutate(Valeur = ifelse(Periode == max(Periode) & Indicateur %in% unique(valeur_redressees$Indicateur),
+                         Valeur * taux_redressement,
+                         Valeur
+  )) %>%
+  select(-taux_redressement, -REG) %>%
+  mutate_if(is.character, as.factor)
+
+
+# Calcul sur total logements ----------------------------------------------
+
+
+indic_ecln <- bind_rows(
+  indic_ecln,
+  indic_ecln %>%
+    mutate(Indicateur = str_split_fixed(Indicateur, " - ", 2)[, 1] %>% str_c(" - Logements") %>% as.factor()) %>%
+    group_by_if(is.factor) %>%
+    summarise_all(funs(sum(., na.rm = T))) %>%
+    ungroup()
+) %>%
+  mutate_if(is.character, as.factor)
+
+# Aggrégation de l'ensemble des calculs sur les zones -----------------------------------
+indic_ecln <- indic_ecln %>%
+  group_split(Periode) %>%
+  furrr::future_map_dfr(cogifier)
+
+# Rajout des zones abc
+# update 2019
+# zonage_abc_r52<-zonage_abc_r52 %>%
+#   passer_au_cog_a_jour(aggrege = F,garder_info_supra = F) %>%
+#   distinct() %>%
+#   arrange(DEPCOM,zonage_abc) %>%
+#   group_by(DEPCOM) %>%
+#   slice(1) %>%
+#   ungroup()
+
+
+indic_ecln_abc <- indic_ecln %>%
+  filter(TypeZone == "Communes", CodeZone %in% (liste_zone %>%
+                                                  filter(str_detect(REG, "52"), TypeZone == "Communes") %>%
+                                                  pull(CodeZone))) %>%
+  left_join(zonage_abc, by = c("CodeZone" = "DEPCOM")) %>%
+  select(zonage_abc, Periode, Indicateur, Valeur) %>%
+  rename(CodeZone = zonage_abc) %>%
+  mutate(
+    Zone = CodeZone,
+    TypeZone = "ABC"
+  ) %>%
+  group_by(TypeZone, Zone, CodeZone, Periode, Indicateur) %>%
+  summarise(Valeur = sum(Valeur)) %>%
+  ungroup()
+
+# indic_ecln_pinel <- indic_ecln %>%
+#   filter(TypeZone == "Communes", CodeZone %in% (liste_zone %>%
+#     filter(str_detect(REG, "52"), TypeZone == "Communes") %>%
+#     pull(CodeZone))) %>%
+#   left_join(zonage_pinel_r52, by = c("CodeZone" = "DEPCOM")) %>%
+#   select(zonage_pinel, Periode, Indicateur, Valeur) %>%
+#   rename(CodeZone = zonage_pinel) %>%
+#   mutate(
+#     Zone = CodeZone,
+#     TypeZone = "Pinel"
+#   ) %>%
+#   group_by(TypeZone, Zone, CodeZone, Periode, Indicateur) %>%
+#   summarise(Valeur = sum(Valeur)) %>%
+#   ungroup()
+
+# Aggrégation de l'ensemble des calculs sur les zones -----------------------------------
+
+
+indic_ecln <- bind_rows(indic_ecln, indic_ecln_abc)%>%
+  arrange(TypeZone, Zone, CodeZone, Indicateur, Periode) %>%
+  filter(TypeZone != "Communes")
+
+rm(list=setdiff(ls(),c("indic_ecln","FormatDate")))
+
+# Utilisation du package dtplyr pour la performance
+
+indicateurs_non_sommables <- str_subset(levels(indic_ecln$Indicateur),"Encours")
+
+indic_ecln <- indic_ecln %>%
+  lazy_dt() %>%
+  group_by(TypeZone, Zone, CodeZone, Indicateur) %>%
+  mutate(Valeur_cumul = Valeur + lag(Valeur) + lag(Valeur, 2) + lag(Valeur, 3)
+  ) %>%
+  ungroup() %>%
+  mutate(Valeur_cumul=ifelse(Indicateur %in% indicateurs_non_sommables,Valeur,Valeur_cumul)) %>%
+  as_tibble()
+
+
+# Calcul des valeurs trimestrielles et cumul annuel ---------------------------
+
+
+indic_ecln_trim <- indic_ecln %>%
+  select(-Valeur_cumul) %>%
+  mutate(Indicateur = str_replace_all(Indicateur, " - ", "_")) %>%
+  spread(Indicateur, Valeur, fill = 0) %>%
+  mutate(
+    PrixM2_Maisons = Prix_Maisons / Surface_Maisons,
+    PrixM2_Appartements = Prix_Appartements / Surface_Appartements,
+    PrixM2_Logements = Prix_Logements / Surface_Logements,
+    PrixPar_Maisons = Prix_Maisons / Ventes_Maisons,
+    PrixPar_Appartements = Prix_Appartements / Ventes_Appartements,
+    PrixPar_Logements = Prix_Logements / Ventes_Logements
+  ) %>%
+  gather(Indicateur, Valeur, Encours_Appartements:PrixPar_Logements) %>%
+  mutate(
+    Indicateur = str_replace_all(Indicateur, "_", " - "),
+    Periode = FormatDate(Periode, Periodicite = "Trim", sep = "T"),
+    Source = "ECLN",
+    TypeIndicateur = "Trimestriel"
+  ) %>%
+  filter(Periode > "2010-01-01")
+
+indic_ecln_cumul <- indic_ecln %>%
+  select(-Valeur) %>%
+  mutate(Indicateur = str_replace_all(Indicateur, " - ", "_")) %>%
+  spread(Indicateur, Valeur_cumul, fill = 0) %>%
+  mutate(
+    PrixM2_Maisons = Prix_Maisons / Surface_Maisons,
+    PrixM2_Appartements = Prix_Appartements / Surface_Appartements,
+    PrixM2_Logements = Prix_Logements / Surface_Logements,
+    PrixPar_Maisons = Prix_Maisons / Ventes_Maisons,
+    PrixPar_Appartements = Prix_Appartements / Ventes_Appartements,
+    PrixPar_Logements = Prix_Logements / Ventes_Logements
+  ) %>%
+  gather(Indicateur, Valeur, Encours_Appartements:PrixPar_Logements) %>%
+  mutate(
+    Indicateur = str_replace_all(Indicateur, "_", " - "),
+    Periode = FormatDate(Periode, Periodicite = "Trim", sep = "T"),
+    Source = "ECLN",
+    TypeIndicateur = "Cumul annuel"
+  ) %>%
+  filter(Periode > "2011-01-01")
+
+# Aggrétation finale -----
+
+TauxEvolution12Mois <- function(.data) {
+  .data %>%
+    arrange(Source, TypeZone, Zone, CodeZone, TypeIndicateur, Indicateur) %>%
+    select(Source, TypeZone, Zone, CodeZone, TypeIndicateur, Indicateur, Periode, Valeur) %>%
+    group_by(Source, TypeZone, Zone, CodeZone, TypeIndicateur, Indicateur) %>%
+    mutate(TauxEvolution12Mois = round(100 * Valeur / lag(Valeur, 4) - 100, 1)) %>%
+    ungroup()
+}
+indic_ecln_cumul <- TauxEvolution12Mois(indic_ecln_cumul)
+indic_ecln_trim <- TauxEvolution12Mois(indic_ecln_trim)
+
+indic_ecln <- bind_rows(indic_ecln_cumul, indic_ecln_trim) %>%
+  mutate_if(is.character, as.factor) %>%
+  mutate(TypeZone = fct_relevel(TypeZone, "France", "Régions", "Départements", "Epci", "ABC"))
+
+
+usethis::use_data(indic_ecln, overwrite = TRUE)

devstuff.R

+usethis::create_package(".")
+usethis::use_gpl3_license()
+usethis::use_build_ignore("devstuff.R")
+usethis::use_data_raw("data-raw-ecln-sas.R")
+usethis::use_build_ignore("extdata/")
+usethis::use_r("FormatDate.R")
+usethis::use_package('dplyr')
+usethis::use_package('lubridate')
+usethis::use_package('stringr')
+usethis::use_r("creer_graphique_evolution_annuelle")
+usethis::use_r('data_prep')
+usethis::use_r('globals')
+usethis::use_r("graphique_series_temporelles")
+usethis::use_r("graphique_evolution_trim")
+usethis::use_r("label_rang")
+usethis::use_pipe()
+usethis::use_r("indic_ecln")
+usethis::use_r("graphique_investissement_locatif.R")
+devtools::check()
+usethis::use_r("graphique_series_temporelles_prix")
+usethis::use_r("tableau_synthese_annuelle")
+usethis::use_package('kableExtra')
+usethis::use_package('knitr')
+usethis::use_package('tidyr')
+usethis::use_r("tableau_synthese_trimestrielle")