The Project

This project is a simple guide to coffee roasters who aim to roast their beans and create a unique roast profile by selecting and purchasing specialty green coffee beans based on their variety, cup quality, processing method, and origin. However, doing an ocular inspection and cupping(tasting) coffee is still the definitive way to evaluate and compare coffee beans.

The Objective

• To provide supplementary data on selecting and buying green coffee beans by presenting the origin, processing method, and cup quality.

• Include a simplified visual on the coffee bean's sensory evaluation.

The Data

The dataset is from the Coffee Quality Institute, it includes a wide range of information on several factors that affect the quality of coffee such as farm name, farm's altitude, harvest yield, arabica varieties, processing method, sensory evaluation, etc.

Did you know?

In the year 1511, a corrupt governor of Mecca, tried to ban coffee. He feared that drinking coffee would spark a rebellion against him. The sultan at the time proclaimed coffee sacred and had the governor executed. The more you know!

Techniques

My approach focused on presenting the coffee cup quality and sensory evaluation. I cleaned and transformed the data by trimming the long data table, concatenating strings, converting data types, standardizing capitalization, and adding calculated columns.

Analytics

This is an informative report for coffee roasters to read, they can treat this as an additional resource for their green coffee beans purchasing research process.

I used the 'clustered column chart' to show the sensory evaluation of each type of coffee bean, the origins, farm name, and overall cup quality.

What else I might add:

• Look for a dataset with available auction prices because including it in the visuals will help roasters narrow down their options before making their final purchases.