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# Code for quick exploration of
# https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-05-26
# Video at https://youtu.be/kHFmtKCI_F4
library(tidyverse)
cocktails <- readr::read_csv("boston_cocktails.csv")
# Are name and row_id equivalent? -----------------------------------------
cocktails %>% count(name)
cocktails %>% count(row_id)
cocktails %>%
group_by(name) %>%
summarise(ids = n_distinct(row_id)) %>%
filter(ids > 1)
# Yes, they are
# How many ingredients are in each cocktail? ------------------------------
cocktails %>%
count(name) %>%
count(n)
# These 1-ingredient cocktails suggest that non-alcoholic ingredients
# are not included
cocktails %>%
group_by(name) %>%
filter(n() == 1)
cocktails %>%
group_by(name) %>%
filter(n() == 2)
# How big is each cocktail? -----------------------------------------------
cocktails %>% count(measure, sort = TRUE)
non_spirit <- c("Chilled Champagne", "Water", "Orange Juice", "Cranberry Juice", "Light Cream (if desired)", "Fresh orange juice", "Orange juice")
# Have removed all cocktails with ounces of bitters - that is most
# likely a data entry error (it certainly doesn't give me much confidence
# in the quality of this data)
sizes <- cocktails %>%
filter(str_detect(measure, "oz")) %>%
filter(!str_detect(ingredient, fixed("bitters", ignore_case = TRUE))) %>%
filter(!ingredient %in% non_spirit) %>%
mutate(oz = str_replace(measure, " oz", "")) %>%
mutate(oz = str_replace(oz, " ?1/2", ".5")) %>%
mutate(oz = str_replace(oz, " ?1/4", ".25")) %>%
mutate(oz = str_replace(oz, " ? ?3/4", ".75")) %>%
mutate(oz = str_replace(oz, " ?1/3", ".33")) %>%
mutate(oz = str_replace(oz, " ?2/3", ".33")) %>%
mutate(oz = as.numeric(oz))
filter(sizes, oz > 3)
filter(sizes, oz > 10)
total_size <- sizes %>% group_by(name) %>% summarise(n = n(), oz = sum(oz))
total_size %>% filter(oz > 20)
total_size %>%
filter(oz < 20) %>%
ggplot(aes(oz)) +
geom_histogram(binwidth = 0.5)
total_size %>%
filter(oz > 6) %>%
semi_join(cocktails, ., by = "name") %>%
View()
cocktails %>%
filter(str_detect(ingredient, "bitters"))
sizes %>%
group_by(ingredient) %>%
summarise(n = n(), oz = mean(oz)) %>%
filter(n > 5) %>%
arrange(desc(oz), sort = TRUE)
# What are the primary ingredients ----------------------------------------
cocktails <- cocktails %>% mutate(ingredient = tolower(ingredient))
cocktails %>%
count(ingredient = tolower(ingredient), sort = TRUE) %>%
head(20)
standard_ingredients <- tribble(
~ ingredient, ~ standard_name,
"fresh lemon juice", "lemon juice",
"juice of a lemon", "lemon juice",
"fresh lime juice", "lime juice",
"juice of a lime", "lime juice",
"bitters", "angostura bitters"
)
ingredient_changes <- cocktails %>%
select(name, ingredient_number, ingredient) %>%
right_join(standard_ingredients) %>%
select(name, ingredient_number, ingredient = standard_name)
cocktails %>%
rows_update(ingredient_changes, by = c("name", "ingredient_number")) %>%
count(ingredient, sort = TRUE) %>%
head(20)
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