A quick interactive map of biking for #tidytuesday

biking.R

library(tidyverse)
library(ggmap)
library(sf)
library(tmap)

#whereami?
here::here()

#get my apis flowin'
register_google(readLines("~/goog.api"))

# #download the data and add geocoding
# #note: this takes a while, so, do this once, 
# #then work on the data it writes out
# commute_mode <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-11-05/commute.csv")
# 
# commute_mode <- commute_mode %>%
#   cbind(geocode(paste(commute_mode$city, commute_mode$state, sep = ",")))
# 
# commute_mode_sf <- commute_mode %>%
#   st_as_sf(coords = c("lon", "lat"), remove=FALSE)
# 
# saveRDS(commute_mode_sf, "../data/acs_bike_commute_tidy_sf.RDS")

commute_mode_sf <- readRDS("../data/acs_bike_commute_tidy_sf.RDS")


ggplot(commute_mode_sf, aes(size = n)) + geom_sf(alpha = 0.1) + facet_wrap(~mode)

tmap_mode("view")
tm_basemap("Stamen.Watercolor") +
  tm_shape(commute_mode_sf %>% filter(mode == "Bike"),
           name = "No. people and % of City Biking") + 
  tm_bubbles(size = "n", col = "percent", 
             title.col = "Percent Biking") +
  tm_tiles("Stamen.TonerLabels")