tuesdata <- tidytuesdayR::tt_load('2020-07-07')
coffee_ratings <- tuesdata$coffee_ratingsUnderstanding Data Distributions Recitation ☕
Week 7
Introduction
Today you will be investigating some data from the Coffee Quality Database on coffee evaluation by the Coffee Quality Institute. You will look at the distribution of coffee evaluation scores across different characteristics, and include various metadata.
More information can be found on the Tidy Tuesday github repo on coffee ratings.
Read in data
Load libraries
library(???)Total cupping score in Arabica and Robusta
Make 3 different visualizations that shows the distribution of total cupping score (i.e. total_cup_points) across Arabica and Robusta beans. Make the plots so you think they look good.
Individual characteristic cupping scores in Arabica and Robusta
Make 3 different visualizations that show the distribution of all the individual contributors (i.e., aroma, flavor, aftertaste, acidity, body, balance, uniformity, clean_cup, sweetness, cupper_points) to total cupping score across Arabica and Robusta in one plot.