Burger Project

Motivation

This is a fun little project where I analyzed my burger consumption at Burgerista. As a JKU student, I took full advantage of their 1+1 deal, which explains why I visited so often. Since I almost always paid by card, I was able to export my debit transaction history and dig into the data. That’s what this project is all about.

Method

1. Data Cleaning: Structured raw transaction data using pandas in clean_data.py.
2. Exploration: Created visualizations in data_exploration.ipynb to analyze trends, frequency, timing, and dietary impact.
3. Reporting: Compiled graphs and summary stats into "Burger Report.pdf", with a short intro (in German).

Tools

• Python, pandas, matplotlib, seaborn, numpy