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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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