diff --git a/.gitignore b/.gitignore
index ced15ba9f77a230a5fa158fd0cd129909af26c5f..ebd418282458bf4e7f8e237c11f8ef79e3bf8a59 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,3 +7,5 @@ inst/doc
doc
Meta
www
+/doc/
+/Meta/
diff --git a/DESCRIPTION b/DESCRIPTION
index abcbb44797bf1582033df00eb6a2f8fc80d22fbd..89eb5868411f8ad4a6b84f008538d5b62855b59b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -14,8 +14,8 @@ Authors@R:
family = "Theuliere",
role = c("aut", "cre"),
email = "mael.theuliere@gmail.com"))
-Description: The goal of propre.artificialisation is to produce
- a publication on land use in Pays de la Loire.
+Description: The goal of propre.artificialisation is to produce a
+ publication on land use in Pays de la Loire.
License: GPL (>= 3)
Depends:
R (>= 2.10)
@@ -26,13 +26,15 @@ Imports:
forcats,
ggiraph,
ggplot2,
- ggradar,
ggtext,
glue,
gouvdown (>= 0.0.0.9000),
+ htmlwidgets,
+ htmltools,
lubridate,
magrittr,
mapfactory (>= 0.0.0.9000),
+ reactable,
scales,
sf,
stats,
@@ -50,7 +52,6 @@ Remotes:
gitlab::dreal-datalab/mapfactory,
maeltheuliere/COGiter,
pachevalier/tricky,
- github::ricardo-bion/ggradar,
spyrales/gouvdown
Config/testthat/edition: 3
Encoding: UTF-8
diff --git a/NAMESPACE b/NAMESPACE
index 78e433fb1a7274132490ae93e3ebdc3847966817..beeda600f56dbf574be90ad27d90a6c7dab121c8 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -9,12 +9,17 @@ export(creer_carte_3_2)
export(creer_graphe_1_1)
export(creer_graphe_1_4)
export(creer_graphe_1_5)
+export(creer_graphe_1_6)
export(creer_graphe_2_3)
export(creer_graphe_2_4)
export(creer_graphe_2_5)
export(creer_graphe_3_1)
export(creer_graphe_3_4)
+export(creer_tableau_1_6)
export(format_fr_pct)
+import(COGiter)
+importFrom(COGiter,ajouter_typologie)
+importFrom(COGiter,charger_zonage)
importFrom(COGiter,filtrer_cog)
importFrom(attempt,stop_if_not)
importFrom(dplyr,arrange)
@@ -29,6 +34,7 @@ importFrom(dplyr,left_join)
importFrom(dplyr,mutate)
importFrom(dplyr,pull)
importFrom(dplyr,rename)
+importFrom(dplyr,row_number)
importFrom(dplyr,select)
importFrom(dplyr,summarise)
importFrom(dplyr,ungroup)
@@ -71,6 +77,12 @@ importFrom(ggtext,element_textbox_simple)
importFrom(glue,glue)
importFrom(gouvdown,scale_fill_gouv_continuous)
importFrom(gouvdown,scale_fill_gouv_discrete)
+importFrom(htmltools,div)
+importFrom(htmltools,h2)
+importFrom(htmltools,p)
+importFrom(htmlwidgets,appendContent)
+importFrom(htmlwidgets,prependContent)
+importFrom(lubridate,as_date)
importFrom(lubridate,make_date)
importFrom(lubridate,year)
importFrom(magrittr,"%>%")
@@ -80,6 +92,10 @@ importFrom(mapfactory,creer_carte_communes_prop)
importFrom(mapfactory,fond_carto)
importFrom(mapfactory,format_fr)
importFrom(mapfactory,format_fr_pct)
+importFrom(mapfactory,format_fr_pct_2)
+importFrom(reactable,colDef)
+importFrom(reactable,reactable)
+importFrom(reactable,reactableTheme)
importFrom(scales,label_number)
importFrom(scales,number_format)
importFrom(sf,read_sf)
@@ -91,8 +107,11 @@ importFrom(sf,st_crs)
importFrom(sf,st_geometry)
importFrom(sf,st_point_on_surface)
importFrom(stats,quantile)
+importFrom(stringr,str_split_fixed)
+importFrom(stringr,str_trim)
importFrom(stringr,str_wrap)
importFrom(tidyr,gather)
importFrom(tidyr,pivot_longer)
+importFrom(tidyr,pivot_wider)
importFrom(tidyr,spread)
importFrom(tricky,set_standard_names)
diff --git a/NEWS.md b/NEWS.md
index 74af4769e8cc2ac7b68196637dba667eb018ea7b..caac5a9e902332ad3294598a3314a326dcb76acb 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,6 +1,7 @@
# propre.artificialisation 0.0.0.9000
* Création site pkgdown
-* Ajout fonctions d'illustration `creer_carte_1_3()`,`creer_carte_1_7()`,`creer_carte_2_2()`,`creer_carte_2_7()`,`creer_carte_3_2()`, `creer_graphe_1_1()`, `creer_graphe_1_4()`, `creer_graphe_1_5()`, `creer_graphe_2_3()`, `creer_graphe_2_4()`, `creer_graphe_2_5()`, `creer_graphe_3_1()`, `creer_graphe_3_4()` et leurs tests
+* Ajout fonctions d'illustration `creer_carte_1_3()`,`creer_carte_1_7()`,`creer_carte_2_2()`,`creer_carte_2_7()`,`creer_carte_3_2()`, `creer_graphe_1_1()`, `creer_graphe_1_4()`, `creer_graphe_1_5()`,`creer_graphe_1_6()`, `creer_graphe_2_3()`, `creer_graphe_2_4()`, `creer_graphe_2_5()`, `creer_graphe_3_1()`, `creer_graphe_3_4()`,`creer_tableau_1_6()` et leurs tests
* Ajout template de publication
* Ajout fichier `NEWS.md` pour tracer les changements dans le package.
+
diff --git a/R/creer_carte_1_3.R b/R/creer_carte_1_3.R
index 843ca4ffc59c52ecb8a3d4b56dbebde5377edaab..f15efa663af2209dcec9bc1732bfef06ab8e94d6 100644
--- a/R/creer_carte_1_3.R
+++ b/R/creer_carte_1_3.R
@@ -5,21 +5,24 @@
#'
#' @return Une carte
#'
-#' @importFrom dplyr filter mutate
+#' @importFrom dplyr filter mutate select
#' @importFrom glue glue
#' @importFrom mapfactory creer_carte_communes_prop fond_carto
#'
#' @export
#'
#' @examples
-#' creer_carte_1_3(millesime_ocsge=2017)
+#' creer_carte_1_3(millesime_ocsge=2016)
creer_carte_1_3 <- function(millesime_ocsge){
- data <- result %>%
- dplyr::filter(.data$variable == "espace_artificialise") %>%
- dplyr::mutate(valeur=round(.data$valeur / 10000,0))
+ data <- ocsge %>%
+ dplyr::filter(grepl(millesime_ocsge, .data$date)) %>%
+ dplyr::select(.data$TypeZone,.data$Zone,.data$CodeZone,.data$date,.data$espace_artificialise) %>%
+ dplyr::mutate(valeur=round(.data$espace_artificialise / 10000,0)) %>%
+ dplyr::select(-.data$espace_artificialise)
+
fond_carto <- mapfactory::fond_carto(nom_reg = "Pays de la Loire")
diff --git a/R/creer_carte_1_7.R b/R/creer_carte_1_7.R
index 4c4335693758acce645161c06f1756c7d7ce521c..85b1d43579a6b3c4ecd0d0ce4c5c68c1dbe7fd2e 100644
--- a/R/creer_carte_1_7.R
+++ b/R/creer_carte_1_7.R
@@ -10,20 +10,22 @@
#' @importFrom lubridate make_date
#' @importFrom stats quantile
#' @importFrom mapfactory fond_carto creer_carte_communes
+#' @importFrom tidyr gather
#'
#' @export
#'
#' @examples
-#' creer_carte_1_7(millesime_ocsge=2017)
+#' creer_carte_1_7(millesime_ocsge=2016)
+
+
+
creer_carte_1_7 <- function(millesime_ocsge){
- data <- result %>%
- dplyr::mutate(valeur=as.numeric(.data$valeur)) %>%
- dplyr::filter(.data$TypeZone == "Communes",
- .data$date == lubridate::make_date(millesime_ocsge,"01","01"),
- .data$variable %in% c("a_definir","autre_surface_naturelle","espace_agricole",
- "espace_artificialise","surface_en_eau","surface_naturelle_boisee")) %>%
+ data <- ocsge %>%
+ dplyr::filter(grepl(millesime_ocsge, .data$date),
+ .data$TypeZone == "Communes") %>%
+ tidyr::gather(variable,valeur,.data$a_definir:.data$surface_naturelle_boisee) %>%
dplyr::arrange(.data$CodeZone) %>%
dplyr::group_by(.data$TypeZone,.data$Zone,.data$CodeZone,.data$date) %>%
dplyr::summarise(variable=.data$variable,valeur=.data$valeur / sum(.data$valeur,na.rm=T)) %>%
@@ -32,6 +34,22 @@ creer_carte_1_7 <- function(millesime_ocsge){
dplyr::select(.data$TypeZone,.data$CodeZone,.data$Zone,.data$date,.data$valeur) %>%
dplyr::mutate(valeur=.data$valeur * 100)
+
+
+ # data <- result %>%
+ # dplyr::mutate(valeur=as.numeric(.data$valeur)) %>%
+ # dplyr::filter(.data$TypeZone == "Communes",
+ # .data$date == lubridate::make_date(millesime_ocsge,"01","01"),
+ # .data$variable %in% c("a_definir","autre_surface_naturelle","espace_agricole",
+ # "espace_artificialise","surface_en_eau","surface_naturelle_boisee")) %>%
+ # dplyr::arrange(.data$CodeZone) %>%
+ # dplyr::group_by(.data$TypeZone,.data$Zone,.data$CodeZone,.data$date) %>%
+ # dplyr::summarise(variable=.data$variable,valeur=.data$valeur / sum(.data$valeur,na.rm=T)) %>%
+ # dplyr::filter(.data$variable == "espace_artificialise") %>%
+ # dplyr::ungroup() %>%
+ # dplyr::select(.data$TypeZone,.data$CodeZone,.data$Zone,.data$date,.data$valeur) %>%
+ # dplyr::mutate(valeur=.data$valeur * 100)
+
fond_carto <- mapfactory::fond_carto(nom_reg = "Pays de la Loire")
bins <- stats::quantile(data$valeur,probs = c(0,0.1, 0.25, 0.5,0.75,0.9,1),na.rm=TRUE)
diff --git a/R/creer_graphe_1_6.R b/R/creer_graphe_1_6.R
new file mode 100644
index 0000000000000000000000000000000000000000..a5c89a1256be1c77f8662774fb77048af508e83f
--- /dev/null
+++ b/R/creer_graphe_1_6.R
@@ -0,0 +1,107 @@
+#' Creation du graphique de l artificialisation OCSGE par type de territoire.
+#' @description Graphique de l artificialisation OCSGE par type de territoire.
+#'
+#' @param millesime_ocsge une annee parmi les millesimes selectionnables par l'utilisateur, au format numerique.
+#' @return Un graphique en barres
+#' @import COGiter
+#'
+#' @importFrom COGiter charger_zonage ajouter_typologie
+#' @importFrom dplyr mutate filter select group_by summarise ungroup arrange
+#' @importFrom ggplot2 ggplot aes geom_point position_dodge geom_linerange geom_label coord_flip scale_y_continuous labs theme element_blank element_text scale_color_manual
+#' @importFrom ggtext element_textbox_simple
+#' @importFrom glue glue
+#' @importFrom lubridate year as_date
+#' @importFrom mapfactory format_fr_pct_2
+#' @importFrom scales label_number
+#' @importFrom tidyr pivot_longer
+#' @importFrom forcats fct_drop fct_inorder fct_rev
+#'
+#' @export
+#'
+#' @examples
+#' creer_graphe_1_6(millesime_ocsge = 2016)
+creer_graphe_1_6 <- function(millesime_ocsge = NULL) {
+
+ # preparation des donnees
+ ocsge2 <- ocsge %>%
+ dplyr::mutate(
+ date = lubridate::year(lubridate::as_date(.data$date)),
+ espace_naturel = .data$autre_surface_naturelle + .data$surface_en_eau + .data$surface_naturelle_boisee
+ ) %>%
+ dplyr::filter(.data$date == millesime_ocsge, .data$TypeZone %in% c("Communes", "R\u00e9gions")) %>%
+ dplyr::select(
+ .data$TypeZone, .data$Zone, .data$CodeZone,
+ .data$espace_naturel,
+ .data$espace_agricole, .data$espace_artificialise
+ )
+
+ zonage_aav <- COGiter::charger_zonage("CATEAAV2020")
+
+ ocsge3 <- COGiter::ajouter_typologie(ocsge2,
+ zonage_df = zonage_aav,
+ departements = FALSE,
+ regions = TRUE,
+ metro = FALSE,
+ metrodrom = FALSE,
+ drom = FALSE, franceprovince = FALSE
+ ) %>%
+ dplyr::filter(
+ !(.data$TypeZone %in% c("Communes")),
+ stringr::str_detect(.data$CodeZone, "NA", negate = TRUE)
+ ) %>%
+ dplyr::arrange(.data$CodeZone)
+
+ # preparation graphiques
+ data <- ocsge3 %>%
+ tidyr::pivot_longer(.data$espace_naturel:.data$espace_artificialise,
+ names_to = "variable",
+ values_to = "valeur"
+ ) %>%
+ dplyr::group_by(.data$TypeZone, .data$Zone, .data$CodeZone) %>%
+ dplyr::mutate(
+ variable = .data$variable,
+ valeur = .data$valeur / 10000,
+ taux = .data$valeur / sum(.data$valeur, na.rm = T) * 100
+ ) %>%
+ dplyr::ungroup() %>%
+ mutate(Zone = forcats::fct_drop(.data$Zone) %>%
+ forcats::fct_inorder() %>%
+ forcats::fct_rev(),
+ variable = forcats::fct_relevel(variable,"espace_naturel","espace_agricole","espace_artificialise"))
+
+
+
+ # graphique pourcentages
+ graph_1_6 <- data %>%
+ ggplot2::ggplot() +
+ ggplot2::aes(x = .data$Zone, y = .data$taux, ymin = 0, ymax = .data$taux, group = .data$variable, color = .data$variable) +
+ ggplot2::geom_linerange(size = 1.1, position = ggplot2::position_dodge(width = 0.5)) +
+ ggplot2::geom_point(size = 1.5, position = ggplot2::position_dodge(width = 0.5)) +
+ ggplot2::aes(label = mapfactory::format_fr_pct_2(.data$taux)) +
+ ggplot2::geom_label(
+ position = ggplot2::position_dodge(width = 0.5),
+ vjust = 0.5, hjust = -0.5, alpha = .7
+ ) +
+ ggplot2::coord_flip() +
+ ggplot2::scale_y_continuous(
+ limits = c(0, max(data$taux) * 1.2),
+ labels = scales::label_number(big.mark = " ", decimal.mark = ",", suffix = " %"),
+ expand = c(0, 0)
+ ) +
+ ggplot2::labs(
+ title = "R\u00e9partition des surfaces entre <span style = 'color:#FF8D7E'>espaces artificialis\u00e9s </span>, <br> <span style = 'color:#E3CE00'>espaces agricoles</span> et <span style = 'color:#169B62'>espaces naturels </span>",
+ subtitle = glue::glue("en {millesime_ocsge}, en %"),
+ caption = glue::glue("Source : OCSGE {millesime_ocsge}"),
+ x = NULL, y = NULL
+ ) +
+ ggplot2::theme(
+ panel.grid.major.y = ggplot2::element_blank(),
+ legend.position = "none",
+ plot.title = ggtext::element_textbox_simple(size = 14, lineheight = 1, hjust = 0),
+ plot.subtitle = ggplot2::element_text(size = 12),
+ plot.caption = ggplot2::element_text(size = 10),
+ ) +
+ ggplot2::scale_color_manual(values = c("#169B62","#E3CE00","#FF8D7E" ))
+
+ return(graph_1_6)
+}
diff --git a/R/creer_tableau_1_6.R b/R/creer_tableau_1_6.R
new file mode 100644
index 0000000000000000000000000000000000000000..6e69bee8276384f1f2d575f3da710179f88196f0
--- /dev/null
+++ b/R/creer_tableau_1_6.R
@@ -0,0 +1,152 @@
+#' Creation du tableau de l artificialisation OCSGE par type de territoire par departement.
+#' @description Graphique de l artificialisation OCSGE par type de territoire par departement.
+#'
+#' @param millesime_ocsge une annee parmi les millesimes selectionnables par l'utilisateur, au format numerique.
+#'
+#' @return Un tableau
+#' @import COGiter
+#'
+#' @importFrom COGiter charger_zonage ajouter_typologie
+#' @importFrom dplyr mutate filter select group_by summarise ungroup row_number
+#' @importFrom lubridate year as_date
+#' @importFrom reactable reactable reactableTheme colDef
+#' @importFrom stringr str_split_fixed str_trim
+#' @importFrom tidyr pivot_longer pivot_wider
+#' @importFrom htmltools div p h2
+#' @importFrom htmlwidgets prependContent appendContent
+#'
+#' @export
+#'
+#' @examples
+#' creer_tableau_1_6(millesime_ocsge = 2016)
+
+creer_tableau_1_6 <- function(millesime_ocsge = NULL){
+
+# preparation des donnees
+ocsge2 <- ocsge %>%
+ dplyr::mutate(date=lubridate::year(lubridate::as_date(.data$date)),
+ espace_naturel= .data$autre_surface_naturelle + .data$surface_en_eau + .data$surface_naturelle_boisee) %>%
+ dplyr::filter(.data$date == millesime_ocsge) %>%
+ dplyr::select (.data$TypeZone,.data$Zone,.data$CodeZone,
+ .data$espace_naturel,
+ .data$espace_agricole,.data$espace_artificialise) %>%
+ dplyr::filter(.data$TypeZone == "Communes")
+
+zonage_aav <- COGiter::charger_zonage("CATEAAV2020")
+
+ocsge3 <- COGiter::ajouter_typologie(ocsge2,
+ zonage_df = zonage_aav,
+ departements = TRUE,
+ regions = FALSE,
+ metro = FALSE,
+ metrodrom = FALSE,
+ drom = FALSE, franceprovince = FALSE
+) %>%
+ dplyr::filter(
+ !(.data$TypeZone %in% c("Communes")),
+ stringr::str_detect(.data$CodeZone, "NA", negate = TRUE)
+ )
+
+# preparation graphiques
+data <- ocsge3 %>%
+ tidyr::gather(variable,valeur,.data$espace_naturel:.data$espace_artificialise)%>%
+ dplyr::group_by(.data$TypeZone,.data$Zone,.data$CodeZone) %>%
+ dplyr::mutate(variable=.data$variable,valeur=.data$valeur/10000, taux=.data$valeur / sum(.data$valeur,na.rm=T)*100) %>%
+ dplyr::ungroup()
+
+# donnees du tableau
+data2 <- data %>%
+ dplyr::filter(.data$TypeZone == "CATEAAV2020 - D\u00e9partements") %>%
+ dplyr::select (.data$CodeZone,.data$Zone,.data$variable,.data$taux)%>%
+ tidyr::pivot_wider(names_from = "variable",values_from="taux",values_fill=0)%>%
+ dplyr::mutate(TypeZone=stringr::str_split_fixed(.data$Zone," - ",n=2)[,1],
+ Departement=stringr::str_split_fixed(.data$Zone," - ",n=2)[,2]) %>%
+ dplyr::select (.data$TypeZone,.data$Departement,.data$espace_agricole,.data$espace_artificialise,.data$espace_naturel)
+
+ data <- data2 %>%
+ dplyr::group_by(.data$TypeZone) %>%
+ dplyr::mutate(n = dplyr::row_number(),
+ nmax=(.data$n==max(.data$n))) %>%
+ dplyr::ungroup() %>%
+ dplyr::mutate(TypeZone = ifelse(.data$n == 1, .data$TypeZone, "")) %>%
+ dplyr::select(.data$TypeZone, .data$Departement, .data$espace_artificialise, .data$espace_agricole, .data$espace_naturel,.data$nmax)
+ # Render a bar chart with a label on the left
+ bar_chart <- function(label, width = "100%", height = "14px", fill = "#00bfc4", background = NULL) {
+ bar <- htmltools::div(style = list(background = fill, width = width, height = height))
+ chart <- htmltools::div(style = list(flexGrow = 1, marginLeft = "6px", background = background), bar)
+ htmltools::div(style = list(display = "flex", alignItems = "center"), label, chart)
+ }
+ tableau_1_6 <- reactable::reactable(
+ data %>% dplyr::select(-.data$nmax),
+ defaultPageSize = 100,
+ sortable = FALSE,
+ rowStyle = function(index) {
+ if (data[index, "nmax"] == TRUE) {
+ list(borderBottom = "1pt solid #DEDEDE")
+ }
+ },
+ defaultColDef = reactable::colDef(headerStyle = "border-bottom: 2px solid #555;"),
+ theme = reactable::reactableTheme(
+ style = list(fontFamily = "Marianne"),
+ ),
+ columns = list(
+ TypeZone = reactable::colDef(
+ name = "Type de territoire"
+ ),
+ Departement = reactable::colDef(
+ name = "D\u00e9partement"
+ ),
+ espace_agricole = reactable::colDef(
+ name = "Espaces agricoles",
+ cell = function(value) {
+ # Format as percentages with 1 decimal place
+ width <- paste0(format(value, nsmall = 1), "%")
+ label <- paste0(format(value, nsmall = 1, decimal.mark = ",",digits = 1), "%")
+ label <- ifelse(value<10, paste0("0", stringr::str_trim(label)), label)#pour gerer les valeurs à l'unite
+ bar_chart(label, width = width, fill = "#E3CE00", background = "#e1e1e1")
+ },
+ # And left-align the columns
+ align = "left"
+ ),
+ espace_artificialise = reactable::colDef(
+ name = "Espaces artificialis\u00e9s",
+ cell = function(value) {
+ # Format as percentages with 1 decimal place
+ width <- paste0(format(value, nsmall = 1), "%")
+ label <- paste0(format(value, nsmall = 1, decimal.mark = ",",digits = 1), "%")
+ label <- ifelse(value<10, paste0("0", stringr::str_trim(label)), label)#pour gerer les valeurs à l'unite
+ bar_chart(label, width = width, fill = "#FF8D7E", background = "#e1e1e1")
+ },
+ # And left-align the columns
+ align = "left"
+ ),
+ espace_naturel = reactable::colDef(
+ name = "Espaces naturels",
+ cell = function(value) {
+ # Format as percentages with 1 decimal place
+ width <- paste0(format(value, nsmall = 1), "%")
+ label <- paste0(format(value, nsmall = 1, decimal.mark = ",",digits = 1), "%")
+ label <- ifelse(value<10, paste0("0", stringr::str_trim(label)), label)#pour gerer les valeurs à l'unite
+ bar_chart(label, width = width, fill = "#169B62", background = "#e1e1e1")
+ },
+ # And left-align the columns
+ align = "left"
+ )
+ )
+ )
+ css_header <- "font-family: Marianne;"
+ css_caption <- "font-family: Marianne;text-align: right;"
+ tableau_1_6_with_title <- htmlwidgets::prependContent(tableau_1_6,
+ htmltools::h2(style = css_header, "R\u00e9partition de l'occupation du sol"),
+ htmltools::p(style = css_header,"Par d\u00e9partement et aire d'attraction des villes")
+ )
+ tableau_1_6_with_caption <- htmlwidgets::appendContent(tableau_1_6_with_title,
+ htmltools::p(style = css_caption,glue::glue("Source : OCSGE {millesime_ocsge}")
+ )
+ )
+return(tableau_1_6_with_caption)
+
+
+}
+
+
diff --git a/R/data.R b/R/data.R
index 226b1233f8eb280776e0e26b01ca9d3c3920031f..82e4c74655d7258c50592c603608d1ad5a87ef58 100644
--- a/R/data.R
+++ b/R/data.R
@@ -102,3 +102,22 @@
#' }
#' @source \url{https://agreste.agriculture.gouv.fr/agreste-web/disaron/W0020/detail/}
"population_legale"
+
+#' Table contenant les différents indicateurs de la source OCSGE pour la publication.
+#'
+#' @encoding UTF-8
+#' @format Table de 2630 lignes et 10 colonnes:
+#' \describe{
+#' \item{TypeZone}{Type de territoire}
+#' \item{Zone}{Libellé du territoire}
+#' \item{CodeZone}{Code du territoire}
+#' \item{date}{Millésime de la source}
+#' \item{a_definir}{a definir}
+#' \item{autre_surface_naturelle}{autre surface naturelle}
+#' \item{espace_agricole}{espace agricole}
+#' \item{espace_artificialise}{espace artificialise}
+#' \item{surface_en_eau}{surface en eau}
+#' \item{surface_naturelle_boisee}{surface naturelle boisee}
+#' }
+#' @source \url{https://agreste.agriculture.gouv.fr/agreste-web/disaron/W0020/detail/}
+"ocsge"
diff --git a/R/globals.R b/R/globals.R
index cb9335c66f5873059aaab4648a3df09347de1283..e1833d1b308e8380bbe1d430074ec9c4b7bdd330 100644
--- a/R/globals.R
+++ b/R/globals.R
@@ -1,4 +1,4 @@
utils::globalVariables(
c("teruti","result","observatoire_artificialisation",".data","variable",".",
- "valeur","etalement_urbain","observatoire_artificialisation_gk3","population_legale")
+ "valeur","etalement_urbain","observatoire_artificialisation_gk3","population_legale","ocsge")
)
diff --git a/data-raw/dataprep.R b/data-raw/dataprep.R
index 92aedf1e3501ee8de6442af16a3c2423ec2c72f9..b253992f86bdff8038e7d055f69eebd41707dd9d 100644
--- a/data-raw/dataprep.R
+++ b/data-raw/dataprep.R
@@ -73,14 +73,14 @@ population_legale<-dbReadTable(con_datamart,
c("portrait_territoires","cogifiee_population_legale"))
-# chargement donnees population legale depuis SGBD
-population_legale<-dbReadTable(con_datamart,
- c("portrait_territoires","cogifiee_population_legale"))
+# chargement donnees ocsge depuis SGBD
+ocsge<-dbReadTable(con_datamart,
+ c("portrait_territoires","cogifiee_ocsge"))
# chargement des tables cogifiées d'indicateurs territoriaux
load("extdata/cogifiee_chargement_ocsge.RData")
-ocsge <- data_cogifiee %>%
+ocsge_it <- data_cogifiee %>%
mutate(variable = str_replace(variable, "a_définir", "a_definir"))
load("extdata/cogifiee_chargement_pci.RData")
pci <- data_cogifiee
@@ -94,7 +94,7 @@ load("extdata/indicateur_pci_lgt_rgp_insee.RData")
load("extdata/indicateur_pci_population_legale.RData")
result <- bind_rows(
- ocsge, pci,
+ ocsge_it, pci,
pop_rgp_insee,
indicateur_observatoire_artificialisation_geokit3,
indicateur_observatoire_artificialisation_population_legale_cogiter,
@@ -102,7 +102,7 @@ result <- bind_rows(
indicateur_pci_population_legale
)
rm(
- data_cogifiee, ocsge, pci,
+ data_cogifiee, ocsge_it, pci,
pop_rgp_insee,
indicateur_observatoire_artificialisation_population_legale_cogiter,
indicateur_observatoire_artificialisation_geokit3,
@@ -149,7 +149,11 @@ population_legale<- population_legale %>%
TypeZone = iconv(TypeZone,to = "UTF-8")) %>%
mutate(across(where(is.character),as.factor))
-
+ocsge<- ocsge %>%
+ filter(CodeZone %in% liste_52 | TypeZone == "Régions"| TypeZone == "D\u00e9partements") %>%
+ mutate(Zone = iconv(Zone,to = "UTF-8"),
+ TypeZone = iconv(TypeZone,to = "UTF-8")) %>%
+ mutate(across(where(is.character),as.factor))
@@ -162,5 +166,6 @@ usethis::use_data(observatoire_artificialisation, overwrite = TRUE, internal = F
usethis::use_data(observatoire_artificialisation_gk3, overwrite = TRUE, internal = FALSE)
usethis::use_data(etalement_urbain, overwrite = TRUE, internal = FALSE)
usethis::use_data(population_legale, overwrite = TRUE, internal = FALSE)
+usethis::use_data(ocsge, overwrite = TRUE, internal = FALSE)
usethis::use_data(metadata_donnee, overwrite = TRUE, internal = FALSE)
diff --git a/data/etalement_urbain.rda b/data/etalement_urbain.rda
index efd499a48116078048d4bd171d783df66d828347..17fb77d8efa7f4c52c470281cacb43520d203599 100644
Binary files a/data/etalement_urbain.rda and b/data/etalement_urbain.rda differ
diff --git a/data/metadata_donnee.rda b/data/metadata_donnee.rda
index 78c958493d6dc9974ffff784b3998af027275dc7..fa4805d4ce3244a950fa7e3247d965fcaa37afbd 100644
Binary files a/data/metadata_donnee.rda and b/data/metadata_donnee.rda differ
diff --git a/data/observatoire_artificialisation.rda b/data/observatoire_artificialisation.rda
index 31b362548fbe41af3fe63dfb653c00b6af7e5eb7..3a0bc2951a246c238c304306267499f7914d46f7 100644
Binary files a/data/observatoire_artificialisation.rda and b/data/observatoire_artificialisation.rda differ
diff --git a/data/observatoire_artificialisation_gk3.rda b/data/observatoire_artificialisation_gk3.rda
index e9965a47d9915ece81d48a94df6bb12939fce2da..6f307da9250591685aea613ac0ddd9fc4b9860df 100644
Binary files a/data/observatoire_artificialisation_gk3.rda and b/data/observatoire_artificialisation_gk3.rda differ
diff --git a/data/ocsge.rda b/data/ocsge.rda
new file mode 100644
index 0000000000000000000000000000000000000000..acc277b35a7c72e636b9f01204fb21fedb7a4eb3
Binary files /dev/null and b/data/ocsge.rda differ
diff --git a/data/population_legale.rda b/data/population_legale.rda
index 2fff93e5b317b65f1d700b9cb4d8fe260696d227..a73e8e1bbe4db4e6c8f0e1ffab37e5ed7399e664 100644
Binary files a/data/population_legale.rda and b/data/population_legale.rda differ
diff --git a/data/result.rda b/data/result.rda
index ee6507087219ae9adb475f7249a4038cbce5c0dc..ca420a5c8da8a759290a30486953f1a2bcc5cc31 100644
Binary files a/data/result.rda and b/data/result.rda differ
diff --git a/data/teruti.rda b/data/teruti.rda
index 60723695fc1c71f788fff0b18bafd7158358963f..80f00ed6907d7c2e6a6eaa355fd047026c183011 100644
Binary files a/data/teruti.rda and b/data/teruti.rda differ
diff --git a/devstuff_history.R b/devstuff_history.R
index d9afcb362843dc1cdf4ed624488ffa012da2fb8d..62f89746e7623e2ccba40f85c52680b442e7f0a9 100644
--- a/devstuff_history.R
+++ b/devstuff_history.R
@@ -19,6 +19,9 @@ usethis::use_package("lubridate")
usethis::use_package("mapfactory")
usethis::use_package("sf")
usethis::use_package("ggradar")
+usethis::use_package("htmlwidgets")
+
+
usethis::use_dev_package("COGiter",remote = "maeltheuliere/COGiter")
usethis::use_dev_package("gouvdown",remote = "spyrales/gouvdown")
usethis::use_dev_package("mapfactory",remote = "gitlab::dreal-datalab/mapfactory")
@@ -51,6 +54,15 @@ usethis::use_vignette("ae-ch1-5","ae- Chapitre 1 Graphe 5")
usethis::use_r("creer_graphe_1_5")
usethis::use_test("creer_graphe_1_5")
+##creer_graphe_1_6
+usethis::use_vignette("af-ch1-6","af- Chapitre 1 Graphe 6")
+usethis::use_r("creer_graphe_1_6")
+usethis::use_test("creer_graphe_1_6")
+
+##creer_tableau_1_6
+usethis::use_r("creer_tableau_1_6")
+usethis::use_test("creer_tableau_1_6")
+
##creer_carte_1_7
usethis::use_vignette("af-ch1-7","af- Chapitre 1 Carte 7")
usethis::use_r("creer_carte_1_7")
diff --git a/inst/extdata/mes_barres.css b/inst/extdata/mes_barres.css
new file mode 100644
index 0000000000000000000000000000000000000000..ab581b1264f094aaaa5d1dd5f587148b95915b6a
--- /dev/null
+++ b/inst/extdata/mes_barres.css
@@ -0,0 +1,13 @@
+.bar-cell {
+ display: flex;
+ align-items: center;
+}.number {
+ font-size: 13.5px;
+ white-space: pre;
+}.bar-chart {
+ flex-grow: 1;
+ margin-left: 6px;
+ height: 22px;
+}.bar {
+ height: 100%;
+}
\ No newline at end of file
diff --git a/inst/rmarkdown/templates/publication/skeleton/skeleton.Rmd b/inst/rmarkdown/templates/publication/skeleton/skeleton.Rmd
index cba366ef6d8faeeeb237c84c577c161be04718d7..652fc7c49f15657db38671b8414d4102eda934c3 100644
--- a/inst/rmarkdown/templates/publication/skeleton/skeleton.Rmd
+++ b/inst/rmarkdown/templates/publication/skeleton/skeleton.Rmd
@@ -7,7 +7,7 @@ output:
logo: "prefecture_r52"
params:
millesime_teruti: 2018
- millesime_ocsge: 2017
+ millesime_ocsge: 2016
millesime_obs_artif: 2019
millesime_etalement_urbain: 2018
millesime_obs_artif_gk3: 2019
@@ -22,6 +22,7 @@ library(gouvdown)
library(propre.artificialisation)
ggplot2::theme_set(gouvdown::theme_gouv(plot_title_size = 14, subtitle_size = 12, base_size = 10, caption_size = 10) +
ggplot2::theme(plot.caption.position = "plot"))
+ggplot2::update_geom_defaults("label",list(family = "Marianne"))
```
texte d'introduction...
@@ -61,6 +62,17 @@ texte...
```{r graph surfaces artificialisees en volume}
creer_graphe_1_4( params$millesime_teruti)
```
+texte...
+
+
+```{r graph artificialisation OCSGE}
+creer_graphe_1_6( params$millesime_ocsge)
+```
+texte...
+
+```{r tableau artificialisation OCSGE}
+creer_tableau_1_6( params$millesime_ocsge)
+```
```{r carte part du territoire communal artificialise, fig.width=9,fig.height=7}
creer_carte_1_7( params$millesime_ocsge)
diff --git a/man/creer_carte_1_3.Rd b/man/creer_carte_1_3.Rd
index a678fcbe7b4ff3449df89f551df580ced5b0ed43..bbefdb563791a8c96d5153efe5615d6d95d00386 100644
--- a/man/creer_carte_1_3.Rd
+++ b/man/creer_carte_1_3.Rd
@@ -16,5 +16,5 @@ Une carte
Carte communale Pays de la Loire de l'artificialisation en volume selon OCSGE
}
\examples{
-creer_carte_1_3(millesime_ocsge=2017)
+creer_carte_1_3(millesime_ocsge=2016)
}
diff --git a/man/creer_carte_1_7.Rd b/man/creer_carte_1_7.Rd
index da4ca4bfafc5563a9c1ba42efd89ff60f5f520e4..cafb4b3c1fe409c43b6f1878221f070a2041afaa 100644
--- a/man/creer_carte_1_7.Rd
+++ b/man/creer_carte_1_7.Rd
@@ -16,5 +16,5 @@ Une carte
Carte de la part du territoire communal artificialise selon OCSGE
}
\examples{
-creer_carte_1_7(millesime_ocsge=2017)
+creer_carte_1_7(millesime_ocsge=2016)
}
diff --git a/man/creer_graphe_1_6.Rd b/man/creer_graphe_1_6.Rd
new file mode 100644
index 0000000000000000000000000000000000000000..cd66a30ca8f455891b256288d7cdd7ede372835b
--- /dev/null
+++ b/man/creer_graphe_1_6.Rd
@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/creer_graphe_1_6.R
+\name{creer_graphe_1_6}
+\alias{creer_graphe_1_6}
+\title{Creation du graphique de l artificialisation OCSGE par type de territoire.}
+\usage{
+creer_graphe_1_6(millesime_ocsge = NULL)
+}
+\arguments{
+\item{millesime_ocsge}{une annee parmi les millesimes selectionnables par l'utilisateur, au format numerique.}
+}
+\value{
+Un graphique en barres
+}
+\description{
+Graphique de l artificialisation OCSGE par type de territoire.
+}
+\examples{
+creer_graphe_1_6(millesime_ocsge = 2016)
+}
diff --git a/man/creer_tableau_1_6.Rd b/man/creer_tableau_1_6.Rd
new file mode 100644
index 0000000000000000000000000000000000000000..9fe3fa3970d7b46620875dca187d5c8b5da31ec2
--- /dev/null
+++ b/man/creer_tableau_1_6.Rd
@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/creer_tableau_1_6.R
+\name{creer_tableau_1_6}
+\alias{creer_tableau_1_6}
+\title{Creation du tableau de l artificialisation OCSGE par type de territoire par departement.}
+\usage{
+creer_tableau_1_6(millesime_ocsge = NULL)
+}
+\arguments{
+\item{millesime_ocsge}{une annee parmi les millesimes selectionnables par l'utilisateur, au format numerique.}
+}
+\value{
+Un tableau
+}
+\description{
+Graphique de l artificialisation OCSGE par type de territoire par departement.
+}
+\examples{
+creer_tableau_1_6(millesime_ocsge = 2016)
+}
diff --git a/man/ocsge.Rd b/man/ocsge.Rd
new file mode 100644
index 0000000000000000000000000000000000000000..abba9ae1b9a622bd01f47b6820c04cda783671ab
--- /dev/null
+++ b/man/ocsge.Rd
@@ -0,0 +1,32 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\encoding{UTF-8}
+\name{ocsge}
+\alias{ocsge}
+\title{Table contenant les différents indicateurs de la source OCSGE pour la publication.}
+\format{
+Table de 2630 lignes et 10 colonnes:
+\describe{
+\item{TypeZone}{Type de territoire}
+\item{Zone}{Libellé du territoire}
+\item{CodeZone}{Code du territoire}
+\item{date}{Millésime de la source}
+\item{a_definir}{a definir}
+\item{autre_surface_naturelle}{autre surface naturelle}
+\item{espace_agricole}{espace agricole}
+\item{espace_artificialise}{espace artificialise}
+\item{surface_en_eau}{surface en eau}
+\item{surface_naturelle_boisee}{surface naturelle boisee}
+}
+}
+\source{
+\url{https://agreste.agriculture.gouv.fr/agreste-web/disaron/W0020/detail/}
+}
+\usage{
+ocsge
+}
+\description{
+Table contenant les différents indicateurs de la source OCSGE pour la publication.
+}
+\keyword{datasets}
diff --git a/propre.artificialisation.Rproj b/propre.artificialisation.Rproj
index 69fafd4b6dddad27500cfc67efb9fb16e86a96bd..4adc5c8d1d1009ce845fc96061fbb03ab53f5c0c 100644
--- a/propre.artificialisation.Rproj
+++ b/propre.artificialisation.Rproj
@@ -19,4 +19,7 @@ LineEndingConversion: Posix
BuildType: Package
PackageUseDevtools: Yes
PackageInstallArgs: --no-multiarch --with-keep.source
+PackageBuildArgs: --no-build-vignettes
+PackageBuildBinaryArgs: --no-build-vignettes
+PackageCheckArgs: --no-build-vignettes
PackageRoxygenize: rd,collate,namespace
diff --git a/tests/testthat/test-creer_carte_1_3.R b/tests/testthat/test-creer_carte_1_3.R
index 5b2f55eff3b5458d50a6fefd80d8f8ae570771e4..27db4051bd3dd0cf39b459e96356fb7f6d54524f 100644
--- a/tests/testthat/test-creer_carte_1_3.R
+++ b/tests/testthat/test-creer_carte_1_3.R
@@ -1,7 +1,7 @@
test_that("creer_CARTE_1_3 fonctionne", {
# Test que la carte est un ggplot
- objet <- creer_carte_1_3(millesime_ocsge = 2017)
+ objet <- creer_carte_1_3(millesime_ocsge = 2016)
testthat::expect_equal(attr(objet, "class"), c("gg","ggplot"))
})
diff --git a/tests/testthat/test-creer_carte_1_7.R b/tests/testthat/test-creer_carte_1_7.R
index ff88beaebdeeca05614e797617d797acba20b456..9897c9b7f0d62c0a1c8e24d5062be7cd4029fba9 100644
--- a/tests/testthat/test-creer_carte_1_7.R
+++ b/tests/testthat/test-creer_carte_1_7.R
@@ -1,7 +1,7 @@
test_that("creer_carte_1_7 fonctionne", {
# Test que la carte est un ggplot
- objet <- creer_carte_1_7(millesime_ocsge = 2017)
+ objet <- creer_carte_1_7(millesime_ocsge = 2016)
testthat::expect_equal(attr(objet, "class"), c("gg","ggplot"))
})
diff --git a/tests/testthat/test-creer_graphe_1_6.R b/tests/testthat/test-creer_graphe_1_6.R
new file mode 100644
index 0000000000000000000000000000000000000000..841d2cf4b38f5de9a0a4d7b1c0145362c222b06f
--- /dev/null
+++ b/tests/testthat/test-creer_graphe_1_6.R
@@ -0,0 +1,7 @@
+test_that("creer_graphe_1_6 fonctionne", {
+
+ # Test que le graphe est un ggplot
+ objet <- creer_graphe_1_6(millesime_ocsge = 2016)
+ testthat::expect_equal(attr(objet, "class"), c("gg","ggplot"))
+
+})
diff --git a/tests/testthat/test-creer_tableau_1_6.R b/tests/testthat/test-creer_tableau_1_6.R
new file mode 100644
index 0000000000000000000000000000000000000000..ef55a7fab815cfd60771c2532c682e727bc52fcd
--- /dev/null
+++ b/tests/testthat/test-creer_tableau_1_6.R
@@ -0,0 +1,7 @@
+test_that("creer_tableau_1_6 fonctionne", {
+
+ # Test que le tableau est un reactable
+ objet <- creer_tableau_1_6(millesime_ocsge = 2016)
+ testthat::expect_equal(attr(objet, "class"), c("reactable","htmlwidget"))
+
+})
diff --git a/vignettes/ac-ch1-3.Rmd b/vignettes/ac-ch1-3.Rmd
index 89cca9f53c8f9d03328a23ae8edc048298e3bee8..1aa7341588f01d4df9cddf2ff99c82d37c1a3866 100644
--- a/vignettes/ac-ch1-3.Rmd
+++ b/vignettes/ac-ch1-3.Rmd
@@ -26,5 +26,5 @@ La fonction `creer_carte_1_3()` produit la carte communale des Pays de la Loire
```{r viz}
library(propre.artificialisation)
-creer_carte_1_3(millesime_ocsge=2017)
+creer_carte_1_3(millesime_ocsge=2016)
```
diff --git a/vignettes/af-ch1-6.Rmd b/vignettes/af-ch1-6.Rmd
new file mode 100644
index 0000000000000000000000000000000000000000..d2d43817aead5bdef56ab20a8acfa89bd5905740
--- /dev/null
+++ b/vignettes/af-ch1-6.Rmd
@@ -0,0 +1,41 @@
+---
+title: "af- Chapitre 1 Graphe 6"
+output: rmarkdown::html_vignette
+vignette: >
+ %\VignetteIndexEntry{af- Chapitre 1 Graphe 6}
+ %\VignetteEngine{knitr::rmarkdown}
+ %\VignetteEncoding{UTF-8}
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+ collapse = TRUE,
+ echo = FALSE,
+ message = FALSE,
+ warning = FALSE,
+ error = FALSE,
+ comment = "#>"
+)
+
+```
+
+# Descriptif
+La fonction `creer_graphe_1_6()` produit le graphique de l artificialisation OCSGE par type de territoire.
+La fonction `creer_tableau_1_6()` produit le tableau de l artificialisation OCSGE par type de territoire par departement.
+
+
+```{r viz, fig.height=5,fig.width=8}
+library(propre.artificialisation)
+library(COGiter)
+library(gouvdown)
+ggplot2::theme_set(gouvdown::theme_gouv(plot_title_size = 14, subtitle_size = 12, base_size = 10, caption_size = 10,strip_text_size = 10))
+
+creer_graphe_1_6(millesime_ocsge = 2016)
+```
+
+```{r tab, fig.height=5,fig.width=8}
+library(propre.artificialisation)
+library(COGiter)
+
+creer_tableau_1_6(millesime_ocsge = 2016)
+```
diff --git a/vignettes/af-ch1-7.Rmd b/vignettes/af-ch1-7.Rmd
index a412e8459a7b1744c3d2a99a3af33d54ebd2e3de..368d99da1e455d653be45d2ab665ed82a551be6e 100644
--- a/vignettes/af-ch1-7.Rmd
+++ b/vignettes/af-ch1-7.Rmd
@@ -26,5 +26,5 @@ La fonction `creer_carte_1_7()` produit la carte de la part du territoire commun
```{r setup}
library(propre.artificialisation)
-creer_carte_1_7(millesime_ocsge=2017)
+creer_carte_1_7(millesime_ocsge=2016)
```
diff --git a/vignettes/test.R b/vignettes/test.R
index 6d4e0101ea8b9072d9ee0f5950f4e3dadf3e45d8..8180bc9586ebced838a5465d59cf56c04f20d7aa 100644
--- a/vignettes/test.R
+++ b/vignettes/test.R
@@ -1,93 +1,87 @@
-#' Creation du graphique araignee de l etalement urbain par departement sur 10 ans.
-#' @description Graphique araignee de l etalement urbain par departement sur 10 ans.
+#' Creation du graphique de l artificialisation OCSGE par type de territoire.
+#' @description Graphique de l artificialisation OCSGE par type de territoire.
#'
-#' @param millesime_obs_artif_gk3 une année parmi les millesimes sélectionnables par l'utilisateur, au format numerique.
-#' @param millesime_population une année parmi les millesimes sélectionnables par l'utilisateur, au format numerique.
+#' @param millesime_ocsge une annee parmi les millesimes selectionnables par l'utilisateur, au format numerique.
#'
-#' @return Un graphique araignee
+#' @return Un graphique en barres
#'
-#' @importFrom dplyr mutate filter select group_by ungroup
-#' @importFrom ggplot2 labs theme
-#' @importFrom ggtext element_markdown
+#' @importFrom dplyr mutate filter select group_by summarise ungroup
+#' @importFrom ggplot2 ggplot aes geom_point position_dodge geom_linerange geom_label coord_flip scale_y_continuous labs theme element_blank element_text scale_color_manual
+#' @importFrom ggtext element_textbox_simple
#' @importFrom glue glue
-#' @importFrom tidyr spread
+#' @importFrom lubridate year as_date
+#' @importFrom mapfactory format_fr_pct
+#' @importFrom scales label_number
+#' @importFrom tidyr gather
+#' @importFrom dplyr mutate filter select group_by summarise ungroup
+#' @importFrom ggplot2 ggplot aes geom_point position_dodge geom_linerange geom_label coord_flip scale_y_continuous labs theme element_blank element_text scale_color_manual
+#' @importFrom ggtext element_textbox_simple
+#' @importFrom glue glue
+#' @importFrom lubridate year as_date
+#' @importFrom mapfactory format_fr_pct
+#' @importFrom scales label_number
+#' @importFrom tidyr gather
#'
#' @export
#'
#' @examples
-#' creer_graphe_3_1(millesime_obs_artif_gk3 = 2019,millesime_population = 2018)
-
-
-creer_graphe_3_1 <- function(millesime_obs_artif_gk3,millesime_population){
-
-
-
- millesime_debut <- millesime_obs_artif_gk3 - 9
-
-
- # Creation de la table utile a la production du graphique
- evol_artif <- observatoire_artificialisation_gk3 %>%
- dplyr::mutate(date=year(.data$date)) %>%
- dplyr::filter((.data$TypeZone == "D\u00e9partements" & .data$CodeZone %in% c("44","49","53","72","85")) |
- (.data$TypeZone == "R\u00e9gions" & .data$CodeZone =="52"),
- .data$date == millesime_obs_artif_gk3 | .data$date == millesime_obs_artif_gk3 - 9) %>%
- dplyr::select (-.data$surface_naf) %>%
- dplyr::group_by(.data$TypeZone,.data$Zone,.data$CodeZone) %>%
- summarise(evolution_artificialisation=round(((sum(.data$surface_artificialisee[which(date==millesime_obs_artif_gk3)],na.rm=T) / sum(.data$surface_artificialisee[which(date==millesime_obs_artif_gk3-9)],na.rm=T))-1)*100,2)) %>%
- dplyr::ungroup() %>%
- dplyr::mutate(CodeZone= as.character(CodeZone),
- CodeZone = replace(CodeZone, CodeZone=="52","Région")) %>%
- dplyr::select (CodeZone,evolution_artificialisation)
+#' creer_graphe_1_6(millesime_ocsge = 2016)
- evol_artif <- evol_artif %>%
- tidyr::spread(key=CodeZone,value=evolution_artificialisation,fill=0)
- cat <- data.frame(x = "surfaces artificialisees (hors routes)")
- evol_artif <- cbind(cat,evol_artif)
- evol_popul <- population_legale %>%
- dplyr::mutate(date=year(.data$date)) %>%
- dplyr::filter((.data$TypeZone == "D\u00e9partements" & .data$CodeZone %in% c("44","49","53","72","85")) |
- (.data$TypeZone == "R\u00e9gions" & .data$CodeZone =="52"),
- .data$date == millesime_population | .data$date == millesime_population - 9) %>%
- dplyr::group_by(.data$TypeZone,.data$Zone,.data$CodeZone) %>%
- summarise(evolution_population=round(((sum(.data$population_municipale[which(date==millesime_population)],na.rm=T) / sum(.data$population_municipale[which(date==millesime_population-9)],na.rm=T))-1)*100,2)) %>%
- dplyr::ungroup() %>%
- dplyr::mutate(CodeZone= as.character(CodeZone),
- CodeZone = replace(CodeZone, CodeZone=="52","Région")) %>%
- dplyr::select (CodeZone,evolution_population)
+creer_graphe_1_6 <- function(millesime_ocsge = NULL){
- evol_popul <- evol_popul %>%
- tidyr::spread(key=CodeZone,value=evolution_population,fill=0)
- cat <- data.frame(x = "population municipale")
- evol_popul <- cbind(cat,evol_popul)
+ # preparation des donnees
+ ocsge2 <- ocsge %>%
+ dplyr::mutate(date=lubridate::year(lubridate::as_date(.data$date)),
+ espace_naturel= autre_surface_naturelle + surface_en_eau + surface_naturelle_boisee) %>%
+ dplyr::filter(.data$date == millesime_ocsge) %>%
+ dplyr::select (.data$TypeZone,.data$Zone,.data$CodeZone,
+ .data$date,.data$espace_naturel,
+ .data$espace_agricole,.data$espace_artificialise)
- data <- bind_rows(evol_artif,evol_popul)
+ # preparation graphiques
+ data1 <- ocsge2 %>%
+ dplyr::filter(.data$TypeZone == "Départements") %>%
+ tidyr::gather(variable,valeur,.data$espace_naturel:.data$espace_artificialise)%>%
+ dplyr::group_by(.data$TypeZone,.data$Zone,.data$CodeZone,.data$date) %>%
+ dplyr::summarise(variable=.data$variable,valeur=.data$valeur, taux=.data$valeur / sum(.data$valeur,na.rm=T)*100) %>%
+ dplyr::ungroup()
- graph_3_1<-ggradar::ggradar(
- data,
- base.size = 1,
- values.radar = c("0%", "10%", "20%"),
- grid.min = 0, grid.mid = 10, grid.max = 20,
- group.line.width = 1,
- group.point.size = 5,
- background.circle.colour = "blue",
- background.circle.transparency = 0.1,
- group.colours = c("#00AFBB", "#E7B800"),
- axis.line.colour = "gray60",
- gridline.min.colour = "gray60",
- gridline.mid.colour = "gray60",
- gridline.max.colour = "gray60",
- legend.position = "top"
-)+
- ggplot2::labs(
- title = glue::glue("Taux de croissance compar\u00e9s\n{millesime_debut}/{millesime_obs_artif_gk3} (%)"),
- subtitle = "<span style = 'color:#00AFBB'>surfaces artificialis\u00e9es (hors routes)</span> et <span style = 'color:#E7B800'>population municipale</span>",
- caption = glue::glue("Source : Observatoire artificialisation {millesime_obs_artif_gk3} / Insee"))+
- ggplot2::theme(
- legend.position = "none",
- plot.subtitle = ggtext::element_markdown(size = 16, lineheight = 1.8),
- plot.caption = ggtext::element_markdown(size = 12, lineheight = 1.8))
+ # graphique pourcentages
+ graph_1_6a <- data1 %>%
+ ggplot2::ggplot() +
+ ggplot2::aes(x = .data$Zone, y = .data$taux, group = .data$variable, color = .data$variable) +
+ ggplot2::geom_point(size = 2, position = ggplot2::position_dodge(width = 0.5)) +
+ ggplot2::aes(x = .data$Zone, ymin = 0, ymax = .data$taux, group = .data$variable, color = .data$variable) +
+ ggplot2::geom_linerange(size = 1.2, position = ggplot2::position_dodge(width = 0.5)) +
+ ggplot2::aes(label = mapfactory::format_fr_pct(.data$taux, dec = 1)) +
+ ggplot2::geom_label(
+ position = ggplot2::position_dodge(width = 0.5),
+ vjust = 0.5, hjust = -0.5
+ ) +
+ ggplot2::coord_flip() +
+ ggplot2::scale_y_continuous(
+ # breaks = seq(0, max(data1$taux) * 1.2, by = 10),
+ # minor_breaks = NULL,
+ limits = c(0, max(data1$taux) * 1.2),
+ labels = scales::label_number(big.mark = " ", decimal.mark = ",", suffix = " %"),
+ expand = c(0,0)
+ ) +
+ ggplot2::labs(
+ title = "R\u00e9partition des surfaces entre <span style = 'color:#2E8B57'>espaces naturels </span> <br><span style = 'color:#FF9940'>espaces artificialis\u00e9s </span> et <span style = 'color:#5770BE'>espaces agricoles</span>",
+ subtitle = glue::glue("en {millesime_ocsge}, en %"),
+ caption = glue::glue("Source : OCSGE {millesime_ocsge}"),
+ x = NULL, y = NULL
+ ) +
+ ggplot2::theme(
+ panel.grid.major.y = ggplot2::element_blank(),
+ legend.position = "none",
+ plot.title = ggtext::element_textbox_simple(size = 14, lineheight = 1, hjust = 0),
+ plot.subtitle = ggplot2::element_text(size = 12),
+ plot.caption = ggplot2::element_text(size = 10),
+ ) +
+ ggplot2::scale_color_manual(values = c("#5770BE", "#FF9940","#2E8B57"))
+ return(graph_1_6a)
- return(graph_3_1)
}