For the past century, much of the world has treated coffee as either a stimulant or a bitter ingredient in a dessert drink. Neither is necessarily inaccurate... However, recent movements in the specialty coffee sphere have sparked increased interest in the research and elevation of coffee flavor quality, from the agricultural side down to the retail & consumer realm. Using this (quite limited) dataset of coffee samples, I aim to explore the relationship between certain coffees' attributes (such as species, processing method, variety, and country of origin) and their quality scores. Could certain plants, methods, and countries produce objectively "better" coffees? From there, one could then dive deeper into the economical, climate, political, social, and biological reasons why these relationships exist (unfortunately I do not have that data yet...). Further explorations of this data could also be used to help small farmers make decisions that increase the value of their product. Also- the data I'm using seems to sample almost exclusively high-quality coffees, so results are highly biased and not representative of all coffees.
The following figures are made using data that comes from the
Coffee Quality Institute (CQI) database,
scraped and uploaded to
Github
by James LeDoux in May 2018, merged and uploaded to
Kaggle
by Diego Volpatto in 2019, and further cleaned and uploaded to
Github
by myself in December 2022.
It contains data on roughly 1,300 Arabica coffee samples,
including cupping quality scores, which are standardized by the
Specialty Coffee Association (SCA).
More information about cupping, coffee quality scoring, and the meanings
of each attribute and metric can be found
here.
More information about coffee species and varieties can be found
here.
More information about coffee processing methods and their effects on flavor can be found
here.
The following data visualizations are interactive.
Some figures allow you to use the dropdown menus to change what data is visualized on an axis.
On desktop, hover over data points and countries to see tooltips with additional data.
It's worth noting that this page is NOT optimized for mobile viewing.