Hydro Wastewater plants

library(tidyverse)

HydroWASTE_v10 <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-09-20/HydroWASTE_v10.csv')

HydroWASTE_v10%>%names

HydroWASTE_v10%>%DataExplorer::profile_missing()

# HydroWASTE_v10%>%View()

df <- HydroWASTE_v10%>%
  janitor::clean_names()%>%
  count(country,lat_wwtp,lon_wwtp,source,
        qual_loc,qual_pop,qual_waste,qual_level,qual_cap)

# source: https://stackoverflow.com/questions/68278789/how-to-rotate-world-map-using-mollweide-projection-with-sf-rnaturalearth-ggplot
library(rnaturalearth)
library(rnaturalearthdata)
library(sf)

target_crs <- st_crs("+proj=moll +x_0=0 +y_0=0 +lat_0=0 +lon_0=133")

worldrn <- ne_countries(scale = "medium", returnclass = "sf") %>%
  st_make_valid()


# define a long & slim polygon that overlaps the meridian line & set its CRS 
# Centered in lon 133
offset <- 180 - 133

# build a polygon
polygon <- st_polygon(x = list(rbind(
  c(-0.0001 - offset, 90),
  c(0 - offset, 90),
  c(0 - offset, -90),
  c(-0.0001 - offset, -90),
  c(-0.0001 - offset, 90)))) %>%
  st_sfc() %>%
  st_set_crs(4326)


# set the polygons
world2 <- worldrn %>% 
  st_difference(polygon) %>% 
  st_transform(crs = target_crs)

Set the values for hydro waste to the new target crs.

coords <- df %>% 
  rename(lat=lat_wwtp,lon=lon_wwtp) %>%
  sf::st_as_sf(coords = c("lon", "lat"), crs = 4326) %>% 
  sf::st_transform(crs = target_crs) 

Set the colors.

library(RColorBrewer)
my_palette <- RColorBrewer::brewer.pal(12,"Set3")

my_values <- c("1"="#8DD3C7", 
               "2"="#FFFFB3",
               "3"="#BEBADA", 
               "4"="#FB8072",
               "5"="#80B1D3", 
               "6"="#FDB462",
               "7"="#B3DE69",   
               "8"="#FCCDE5",
               "9"="#D9D9D9",
               "10"="#BC80BD",
               "11"="#CCEBC5", 
               "12"="#FFED6F")

my_labels<-c("Europe", "United States",
             "Brazil", "Mexico",
             "China", "Canada",
             "Australia",   "South Africa",
             "India", "New Zealand",
             "Peru", "Remaining Countries")

Make the mollweide, more info on how to set the projections here: https://epsg.io/54009

ggplot() + 
  geom_sf(data = world3, aes(group = admin), 
          fill = "#f5f5f5") + 
  geom_sf(data = coords,
          mapping = aes(color=factor(source)),
          key_glyph = draw_key_rect,
          size=0.1) + 
  scale_color_manual(labels=my_labels,values=my_values)+
  labs(title="Wastewater Plants",
       subtitle="Concentrated point sources of residual contaminant loads into surface waters",
       caption="DataSource: #TidyTuesday 2022 week38 Hydro Wastewater | DataViz: Federica Gazzelloni @fgazzelloni",
       color="Source of\nwaterwaste")+
  coord_sf()+
  ggthemes::theme_map() +
  theme(plot.title = element_text(size=14,face="bold"),
        plot.subtitle = element_text(size=12,face="bold"),
        text=element_text(family="Roboto Condensed",color="#89a5b9"),
        panel.grid = element_line(color="#bfd0dd"),
        plot.background = element_rect(fill="#275477",color="#275477"),
        panel.background = element_rect(fill="#275477",color="#275477"),
        legend.background = element_blank(),
        legend.position = c(-0.05,0.05),
        legend.key = element_rect(size=4))

Save it.

ggsave("w38_hydro_waterwaste.png",
       dpi=320,
       width = 10,
       height = 5)