Using the geofacet package to spatially arrange plots
R
datavisualization
french
spatial
Author
Michaël
Published
2020-06-15
Modified
2023-10-03
The {geofacet} package allows to “arrange a sequence of plots of data for different geographical entities into a grid that strives to preserve some of the original geographical orientation of the entities”.
Like the previous post, it’s interesting if you view each entity as a unit and don’t care for its real size or weight, and don’t want to spend too much time manually finding the best grid.
We will again use the sameCOVID-19 dataset. We manually add the overseas départements once we have found the right grid (by trying different seeds) and adjust Corsica position.
# packages ----------------------------------------------------------------library(tidyverse)library(httr)library(fs)library(sf)library(readxl)library(janitor)library(glue)library(geofacet)# sources -----------------------------------------------------------------# https://www.data.gouv.fr/fr/datasets/donnees-hospitalieres-relatives-a-lepidemie-de-covid-19/fichier_covid <-"donnees/covid.csv"url_donnees_covid <-"https://www.data.gouv.fr/fr/datasets/r/63352e38-d353-4b54-bfd1-f1b3ee1cabd7"# https://www.insee.fr/fr/statistiques/2012713#tableau-TCRD_004_tab1_departementsfichier_pop <-"donnees/pop.xlsx"url_donnees_pop <-"https://www.insee.fr/fr/statistiques/fichier/2012713/TCRD_004.xlsx"# Adminexpress : à télécharger manuellement# https://geoservices.ign.fr/documentation/diffusion/telechargement-donnees-libres.html#admin-expressaex <-path_expand("~/data/adminexpress/adminexpress_cog_simpl_000_2022.gpkg")# config ------------------------------------------------------------------options(scipen =999)force_download <-FALSE# retélécharger même si le fichier existe et a été téléchargé aujourd'hui ?# téléchargement -------------------------------------------------if (!dir_exists("donnees")) dir_create("donnees")if (!file_exists(fichier_covid) |file_info(fichier_covid)$modification_time <Sys.Date() | force_download) {GET(url_donnees_covid,progress(),write_disk(fichier_covid, overwrite =TRUE)) |>stop_for_status()}
Figure 1: COVID-19 deceased in hospital, by département, for 100 000 inhab.
Source Code
---title: "Using the geofacet package to spatially arrange plots"description: ""author: "Michaël"date: "2020-06-15"date-modified: last-modifiedcategories: - R - datavisualization - french - spatial draft: falsefreeze: trueeditor_options: chunk_output_type: consolechunk_output_type: console---The [{geofacet}](https://CRAN.R-project.org/package=geofacet) package allows to "*arrange a sequence of plots of data for different geographical entities into a grid that strives to preserve some of the original geographical orientation of the entities*".Like the [previous post](/posts/2020/polygons_to_hexagons/), it's interesting if you view each entity as a unit and don't care for its real size or weight, and don't want to spend too much time manually finding the best grid.We will again use the [same](/posts/2020/covid_19_decease_animation_map/)[COVID-19](/posts/2020/coronavirus_spatially_smoothed_decease_in_france/) dataset. We manually add the overseas départements once we have found the right grid (by trying different seeds) and adjust Corsica position.```{r}#| label: config-preprocess# packages ----------------------------------------------------------------library(tidyverse)library(httr)library(fs)library(sf)library(readxl)library(janitor)library(glue)library(geofacet)# sources -----------------------------------------------------------------# https://www.data.gouv.fr/fr/datasets/donnees-hospitalieres-relatives-a-lepidemie-de-covid-19/fichier_covid <-"donnees/covid.csv"url_donnees_covid <-"https://www.data.gouv.fr/fr/datasets/r/63352e38-d353-4b54-bfd1-f1b3ee1cabd7"# https://www.insee.fr/fr/statistiques/2012713#tableau-TCRD_004_tab1_departementsfichier_pop <-"donnees/pop.xlsx"url_donnees_pop <-"https://www.insee.fr/fr/statistiques/fichier/2012713/TCRD_004.xlsx"# Adminexpress : à télécharger manuellement# https://geoservices.ign.fr/documentation/diffusion/telechargement-donnees-libres.html#admin-expressaex <-path_expand("~/data/adminexpress/adminexpress_cog_simpl_000_2022.gpkg")# config ------------------------------------------------------------------options(scipen =999)force_download <-FALSE# retélécharger même si le fichier existe et a été téléchargé aujourd'hui ?# téléchargement -------------------------------------------------if (!dir_exists("donnees")) dir_create("donnees")if (!file_exists(fichier_covid) |file_info(fichier_covid)$modification_time <Sys.Date() | force_download) {GET(url_donnees_covid,progress(),write_disk(fichier_covid, overwrite =TRUE)) |>stop_for_status()}if (!file_exists(fichier_pop)) {GET(url_donnees_pop,progress(),write_disk(fichier_pop)) |>stop_for_status()}covid <-read_csv2(fichier_covid) |>filter(dep !="978")pop <-read_xlsx(fichier_pop, skip =2) |>clean_names() |>select(insee_dep = x1, x2020)# adminexpress prétéléchargédep <-read_sf(aex, layer ="departement") |>filter(insee_dep <"971") |>st_transform(2154)# construction de la grille ----------------------------------------grid_fr <- dep |>select(insee_dep, nom) |>grid_auto(names ="nom", codes ="insee_dep", seed =4) |>add_row(row =8,col =1,name_nom ="Guadeloupe",code_insee_dep ="971") |>add_row(row =9,col =1,name_nom ="Martinique",code_insee_dep ="972") |>add_row(row =10,col =1,name_nom ="Guyane",code_insee_dep ="973") |>add_row(row =7,col =13,name_nom ="Mayotte",code_insee_dep ="976") |>add_row(row =8,col =13,name_nom ="La Réunion",code_insee_dep ="974")grid_fr[grid_fr$code_insee_dep %in%c("2A", "2B"), "col"] <-13grid_fr[grid_fr$code_insee_dep %in%c("2A", "2B"), "row"] <- grid_fr[grid_fr$code_insee_dep %in%c("2A", "2B"), "row"] -1``````{r}#| label: fig-geofacet#| fig-cap: COVID-19 deceased in hospital, by département, for 100 000 inhab.#| fig-height: 8#| dev: ragg_png#| dev.args:#| scaling: .5covid |>filter(sexe ==0) |>select(insee_dep = dep, jour,deces = dc,reanim = rea,hospit = hosp) |>left_join(pop,join_by(insee_dep)) |>mutate(incidence = deces / x2020 *1e5) |>left_join(grid_fr |>select(nom = name_nom,insee_dep = code_insee_dep),by =join_by(insee_dep)) |>drop_na(insee_dep) |>ggplot() +geom_area(aes(jour, incidence)) +facet_geo(~ nom, grid = grid_fr) +labs(title ="Mortalité",subtitle ="COVID-19 - France",x ="date",y ="décès pour\n100 000 hab.",caption =glue("http://r.iresmi.net/\ndonnées SPF {Sys.Date()}")) +theme_minimal() +theme(strip.text =element_text(hjust =0, size =7))```
