Elevators

library(tidyverse)

tuesdata <- tidytuesdayR::tt_load('2022-12-06')
elevators <- tuesdata$elevators
elevators%>%names

elevators%>%DataExplorer::profile_missing()%>%
  mutate(pct_missing=round(pct_missing,2))%>%
  arrange(pct_missing)

elevators1%>%head

elevators1 <- elevators%>%
  janitor::clean_names()%>%
  mutate(date=as.Date(as.character(dv_status_date), format='%Y%m%d',tz="UTC")) %>%
  select(zip_code,borough,device_type,latitude,longitude,
         date)%>% # dim 76088     8
  na.omit() %>% # dim 66789     8
  mutate(zip_code=as.numeric(sub("\\D*(\\d{5}).*", "\\1", zip_code)))%>%
  arrange(date)%>%
  filter(!zip_code==0 & !zip_code== 99999,
         longitude> -75)

elevators1 %>%
  ggplot(aes(longitude,latitude)) +
  geom_point(aes(color=factor(device_type)))+
  coord_equal()

library(ggnewscale)
ggnewscale::new_scale_color()

usdata::county_complete%>%names
library(zipcodeR)
zipcodeR::zip_code_db%>%head
elevators1%>%count(zip_code)%>%dim # 185
zipcodeR::zip_code_db%>%
  filter(zipcode%in%elevators1$zip_code)
zipcodeR::geocode_zip(elevators1$zip_code) # 183

us_county_map <- map_data("county")

ggplot()+
  geom_polygon(data=us_county_map,aes(x=long,y=lat,group = group),
               fill=NA,color = "lightblue")

us_county_map%>%head

us_county_map_centroids <- us_county_map%>%
  group_by(subregion) %>%
  mutate(long=mean(range(long)),lat=mean(range(lat)))%>%
  ungroup()%>%
  select(-order,-region)%>%
  distinct()
us_county_map_centroids

elevators1_centroids <- elevators1%>%
  group_by(borough) %>%
  mutate(long=mean(range(longitude)),lat=mean(range(latitude)))%>%
  ungroup()%>%
  select(borough,zip_code,long,lat)%>%
  distinct()

elevators1 %>%
  ggplot(aes(longitude,latitude)) +
   geom_polygon(data = us_county_map,
                aes(x=long,y=lat,group = group,fill=subregion),
                color = "lightblue",alpha=0.1)+
  geom_point(aes(color=factor(borough)),
             shape=21,stroke=0.1,size=0.5)+
  scale_color_discrete()+
  guides(color=guide_legend(title="Borough"),fill="none")+
  ggnewscale::new_scale_color()+
  geom_point(aes(color=zip_code),shape=".",alpha=0.2) +
  scale_color_continuous(type = "viridis")+
  geom_text(data = elevators1_centroids,
             aes(x=long,y=lat,label=borough)) +
  coord_map(xlim = range(elevators1$longitude),ylim = range(elevators1$latitude))+
  labs(title = "",
       subtitle = "",
       color=c("zip code","Borough"))+
  ggthemes::theme_map()+
  theme(legend.position = c(-0.2,0),
        legend.background = element_blank())+
  facet_wrap(vars(device_type))

elevators1 %>% # count(device_type)
  filter(device_type=="Passenger Elevator (P)") %>%
  ggplot(aes(longitude,latitude)) +
   geom_polygon(data = us_county_map,
                aes(x=long,y=lat,group = group,fill=subregion),
                color = "lightblue",alpha=0.1)+
  geom_point(aes(color=factor(borough)),
             shape=21,stroke=0.1,size=0.5)+
  scale_color_discrete()+
  guides(color=guide_legend(title="Borough"),fill="none")+
  ggnewscale::new_scale_color()+
  geom_point(aes(color=zip_code),shape=".",alpha=0.2) +
  scale_color_continuous(type = "viridis")+
  geom_point(data = elevators1 %>% filter(device_type=="Handicap Lift (H)"),
             aes(longitude,latitude),color="red",size=0.3)+
  geom_text(data = elevators1_centroids,
             aes(x=long,y=lat,label=borough),
            color="white",family="Roboto Condensed") +
  coord_map(xlim = range(elevators1$longitude),ylim = range(elevators1$latitude))+
  labs(title = "New York City Handicap Lifts availability",
       subtitle = "Registered Passenger Elevator devices from the Department of Buildings 2015",
       caption="DataSource: #TidyTuesday 2022 week49 Elevators by @emilhvitfeldt | Graphics: Federica Gazzelloni",
       color=c("zip code","Borough"))+
  ggthemes::theme_map()+
  theme(text = element_text(color="white",family="Roboto Condensed"),
        plot.title = element_text(size=14),
        plot.caption = element_text(size=10.5),
        legend.position = "none", # c(-0.2,0),
        legend.background = element_blank()) +
  annotate("text", 
           x = -74, y = 40.52, 
           label = "How to read it:\nPassenger Elevators are colored by borough and zip code,\nwhile red dots indicate the presence of Handicap Lifts",color="white",size=3,family="Roboto Condensed")

ggsave("w49_elevators.png",bg="black")