r.iresmi.net

Day 15 of 30DayMapChallenge : « food » (previously).

Results of State food controls in restaurants in La Réunion.

library(dplyr)
library(sf)
library(janitor)
library(mapsf)
library(glue)
library(lubridate)

# https://geoservices.ign.fr/adminexpress 
# COG
dep <- read_sf("~/ADE-COG_2-1_SHP_WGS84G_FRA/DEPARTEMENT.shp") %>% 
  filter(INSEE_DEP == "974")

# https://dgal.opendatasoft.com/explore/dataset/export_alimconfiance/download/?format=shp
alim <- read_sf("~/../Downloads/export_alimconfiance.shp") %>% 
  clean_names() %>% 
  filter(str_sub(code_postal, 1, 3) == "974") %>% 
  mutate(date_inspec = ymd_hms(date_inspec),
         synthese_ev = factor(synthese_ev, levels = c("A corriger de manière urgente",               
                                                      "A améliorer",
                                                      "Satisfaisant",
                                                      "Très satisfaisant")))
alim %>% 
  ggplot() +
  geom_sf(data = dep,  fill = "grey90", color = "lightblue3") +
  geom_sf(aes(color = synthese_ev)) +
  scale_color_manual(values = c(
    "A corriger de manière urgente" = "red",               
    "A améliorer" = "orange",
    "Satisfaisant" = "blue",
    "Très satisfaisant" = "green")) +
  labs(title = "Food quality control",
       subtitle = "La Réunion",
       color = "Control result",
       caption = glue("data: alim-confiance.gouv.fr
                      {min(alim$date_inspec)} - {max(alim$date_inspec)}
                  r.iresmi.net - {Sys.Date()}")) +
  theme_minimal() +
  theme(panel.background = element_rect(fill = "lightblue1"),
        plot.caption = element_text(size = 7))


ggsave("food.png", width = 20, height = 20, units = "cm", scale = 1.1)

Day 12 of 30DayMapChallenge : « scales » (previously).

French « départements » at the same size but tidily ordered by area.

library(tidyverse)
library(sf)
library(units)
library(tmap)

# data from https://geoservices.ign.fr/adminexpress
fr <- read_sf("~/adminexpress.gpkg", 
              layer = "departement")

png("scales.png", width = 20, height = 12.36, units = "cm", res = 300)
fr %>%  
  mutate(surf_km2 =  set_units(st_area(geom), km^2), 
         rank = dense_rank(surf_km2), 
         nom_dep = fct_rev(fct_reorder(as_factor(nom_dep), rank))) %>% 
  tm_shape() +
  tm_polygons(fill = "lightgrey") +
  tm_facets(by = "nom_dep", free.scales = TRUE)
dev.off()  

Day 9 of 30DayMapChallenge : « space » (previously).

Scrape and geolocate data from Wikipedia. We will map the active space launch sites.

library(tidyverse)
library(lubridate)
library(janitor)
library(sf)
library(glue)
library(rvest)
library(rnaturalearth)

# read all tables from the page
# keep only those containing a country column
# clean and merge
launch <- read_html("https://en.wikipedia.org/wiki/List_of_rocket_launch_sites") %>% 
  html_table() %>% 
  keep(~ names(.x)[[1]] == "Country") %>% 
  map(~ mutate(.x, across(everything(), as.character))) %>% 
  reduce(bind_rows) %>% 
  clean_names() 

# keep only active sites : roughly "YYYY-"
# and extract coordinates
active <- launch %>% 
  filter(str_detect(operational_date, "\\d{4}s?–(\\[.*\\])?$")) %>% 
  mutate(x = str_extract(coordinates, "(?<=;\\s)\\-?\\d*\\.\\d*"),
         y = str_extract(coordinates, "\\-?\\d*\\.\\d*(?=;)")) %>% 
  select(country,location, coordinates, x, y) %>% 
  drop_na(x, y) %>% 
  st_as_sf(coords = c("x", "y"), crs = "EPSG:4326")

# map
ne_countries(scale = "small", type = "countries", returnclass = "sf") %>% 
  ggplot() +
  geom_sf(color = "darkblue", fill = "darkblue") + 
  geom_sf(data = active, color = "yellow", size = 1) +
  coord_sf(crs = "+proj=robin") +
  labs(title = "Active space launch sites",
       subtitle = year(Sys.Date()),
       caption = glue("data : https://en.wikipedia.org/wiki/List_of_rocket_launch_sites
                      r.iresmi.net - {Sys.Date()}")) +
  theme(plot.background = element_rect(fill = "grey10", color = NA),
        panel.background = element_blank(),
        panel.grid = element_line(color = "grey20"),
        plot.title = element_text(color = "grey90", family = "Waree"),
        plot.subtitle = element_text(color = "grey90"),
        plot.caption = element_text(color = "grey90", size = 6))

ggsave("space.png", width = 20, height = 12.36, units = "cm", scale = 1.1)

Day 6 of 30DayMapChallenge : « network » (previously).

Using GIS data directly from data.gouv.fr : railways network of France.

library(dplyr)
library(ggplot2)
library(sf)
library(glue)
library(httr)

# https://www.data.gouv.fr/fr/datasets/fichier-de-formes-des-voies-du-reseau-ferre-national/
GET("https://www.data.gouv.fr/fr/datasets/r/71e38477-1166-4074-a532-c51f3f399b09",
    write_disk("~/data.zip"))
unzip("~/data.zip")

network <- read_sf("~/fichier-de-formes-des-voies-du-reseau-ferre-national.shp") %>% 
  st_transform("EPSG:2154")

network %>% 
  ggplot() +
  geom_sf() +
  theme_minimal() +
  theme(plot.background = element_rect(fill = "white", color = NA)) +
  labs(title = "Réseau ferré français",
       caption = glue("données SNCF 2020 - data.gouv.fr
                      r.iresmi.net - {Sys.Date()}"))

ggsave("sncf.png", width = 20, height = 12.36, units = "cm", scale = 1.1)