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.
We aim to understand:
- Key determinants of coffee quality (aroma, flavor, etc.).
- Correlations between processing methods, origin regions, and quality scores.
- Trends in defect occurrences and their impact on quality.
- Interactions influencing Total Cup Points.
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
- 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.
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Power BI: For data analysis, visualization and reporting.
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Excel: For analysis and manipulation.
- This project is for educational purposes only and does not have a formal license.