adigabay2003/coffee-sales-eda

🎥 Video Presentation: https://drive.google.com/file/d/1a8autv5yuVIufOrDvcZNBlskkQ3Pq8-/view?usp=drivelink ☕ Coffee Sales Analysis Overview

This notebook explores a coffee shop sales dataset and examines how sales change by coffee type, weekday, and time of day. The goal was to identify patterns that could help improve business decisions such as inventory management and promotions.

Data Cleaning

Before starting the analysis, the data was checked for errors:

No missing or duplicate rows were found.

Date and time columns were converted to the correct format.

Numeric and categorical values were verified.

Research Questions

Which coffee types are the most popular and profitable?

Which weekdays generate the highest total revenue?

Does the time of day influence total sales?

Visual Insights

Sales by Coffee Type Latte and Americano with Milk are the most sold items.

Revenue by Weekday Revenue is highest on Monday and Tuesday, and lowest on Sunday.

Revenue by Time of Day The afternoon slightly leads in revenue, followed closely by morning hours.

Findings

Lattes and Americanos with Milk are both top sellers and main revenue drivers.

Early-week days are busier than weekends, suggesting higher weekday demand.

Sales are steady throughout the day, with a slight peak after lunch.

Tools

Python libraries: pandas, matplotlib, seaborn

Environment: Google Colab

Dataset: Coffee Sales (Kaggle)

Conclusion

The analysis shows clear behavioral patterns in coffee consumption. People tend to buy more coffee at the beginning of the week and during midday hours. These insights can help coffee shop staff, plan inventory, and design promotions more effectively.

HuggingFace Dataset

URL: https://huggingface.co/datasets/adigabay2003/coffee-sales-eda

Included files:

coffee_sales.csv

• https://colab.research.google.com/drive/1JJRG3nc6GMmKfAYMnaH26D-Bq5GKLE?usp=drive_link

README.md