Code from R-Ladies RTP 2020_04_21

RladiesRTP_Beer.r

# https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-03-31/readme.md
library(tidyverse)

# Get the Data

brewing_materials <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/brewing_materials.csv')
beer_taxed <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/beer_taxed.csv')
brewer_size <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/brewer_size.csv')
beer_states <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/beer_states.csv')

summary(beer_states)
glimpse(beer_states)

beer_state_totals <- beer_states %>%
  filter(state!="total") %>%
  group_by(state, year) %>%
  summarise(TotalBarrels=sum(barrels)) %>%
  # filter(year==2019) %>%
  arrange(desc(TotalBarrels))


library(tidycensus)
# Note you need a Census API key to use this
# More info here: https://walkerke.github.io/tidycensus/articles/basic-usage.html 
v18 <- tidycensus::load_variables(year=2018, dataset="acs1", cache=TRUE)
statepops <- tidycensus::get_acs(geography="state", 
                     variables="B01001_001",
                     year=2018,
                     geometry=TRUE,
                     keep_geo_vars = TRUE,
                     shift_geo=TRUE,
                     survey="acs1")

fips_state_codes <- tidycensus::fips_codes %>%
  select(state, state_code) %>%
  distinct() %>%
  as_tibble()

statepops_wabb <- statepops %>%
  left_join(fips_state_codes, by=c("GEOID"="state_code"))

state_beer_pop <- beer_state_totals %>%
  left_join(statepops_wabb, by=c("state")) %>%
  mutate(BeerPerPop=TotalBarrels/estimate)

library(sf)

state_beer_pop %>%
  filter(year==2019) %>%
  ggplot() +
  geom_sf(aes(fill=BeerPerPop, geometry=geometry)) +
  scale_fill_continuous(low="lightblue", high="darkblue")

state_beer_pop %>%
  filter(year==2019) %>%
  ggplot() +
  geom_sf(aes(fill=TotalBarrels, geometry=geometry)) +
  scale_fill_continuous(low="lightblue", high="darkblue")