UK Museums

library(tidyverse)
tuesdata <- tidytuesdayR::tt_load(2022, week = 47)
museums <- tuesdata$museums
museums %>% head

museums %>%
  DataExplorer::profile_missing()

# https://stackoverflow.com/questions/54560369/png-of-static-map-using-r-and-mapdeck
library(tidyverse)
df = read.csv("https://git.io/geocompr-mapdeck")

df

library(mapdeck)

set_token("MAPBOX_TOKEN")
ms = mapdeck_style("dark")

df <- df[!is.na(df$lat), ]

mapdeck(style = ms, pitch = 45) %>%
  add_grid(data = df, lat = "lat", lon = "lng", 
           cell_size = 1000,
           elevation_scale = 50, 
           layer_id = "grid_layer",
           colour_range = colourvalues::colour_values(1:6, palette = "plasma")) 

mapdeck(style = mapdeck_style('dark'),zoom = 1) %>% 
    add_grid(data = df, 
             lat = "lat", 
             lon = "lng", 
             cell_size = 1000,
             elevation_scale = 50, 
             layer_id = "grid_layer",
             colour_range = colourvalues::colour_values(1:6, palette = "plasma")) %>%
  add_scatterplot(data = museums,
                  lat = "Latitude",
                  lon = "Longitude",
                  radius = 0.5,
                  legend = TRUE,
                  fill_colour = "Accreditation",
                  layer_id = "scatter_layer",
                  palette = "viridis") 

table <- museums %>%
select(museum_id,`Village,_Town_or_City`,Accreditation,Size,Subject_Matter) %>%
  janitor::clean_names() %>%
  group_by(accreditation) %>%
  count(size) %>%
  mutate(pct=round(n/sum(n)*100,2)) %>%
   ungroup() %>%
  pivot_wider(names_from = size,values_from = pct) %>%
  select(-n) %>%
  pivot_longer(cols = 2:6,names_to = "Type",values_to = "pct")%>%
  na.omit() %>%
  pivot_wider(names_from = accreditation,values_from = pct) %>%
  gt::gt()

table

library(cowplot)

ggdraw() +
  draw_image("base_map.png") +
  draw_image("table.png",
             scale=0.25,
             x=-0.3,y=0)

ggplot2::ggsave("test.png",
       dpi=320)