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Coffee Quality Analysis

Overview

This project leverages data from the Coffee Quality Institute (CQI), a non-profit organization aimed at improving coffee quality worldwide. We explore factors contributing to coffee quality using sensory evaluation data.

Objective

We aim to understand:

  1. Key determinants of coffee quality (aroma, flavor, etc.).
  2. Correlations between processing methods, origin regions, and quality scores.
  3. Trends in defect occurrences and their impact on quality.
  4. Interactions influencing Total Cup Points.

Data

The dataset includes:

  • Production Weight
  • Number of Bags
  • Region
  • Country of Origin
  • Sensory Attributes: Aroma, flavor, aftertaste, acidity, body, balance, uniformity, clean cup, and sweetness.
  • Defects:
    • Category One: Visual defects (e.g., black beans).
    • Category Two: Taste defects (e.g., staleness).
  • Total Cup Points: Sum of sensory evaluation features.
  • Harvest Year
  • Grading Date
  • Expiration Date

Insights Generated

  • Identified key sensory attributes that significantly impact overall coffee quality.
  • Discovered correlations between processing methods and higher quality scores.
  • Highlighted common defects and their relationship to lower quality ratings.
  • Uncovered trends in coffee quality over different origin regions.

Tools Used

  • Power BI: For data analysis, visualization and reporting.

  • Excel: For analysis and manipulation.

    License

    • This project is for educational purposes only and does not have a formal license.