How yashpawar-ds/cafe-sales-analysis works
This repository is a notebook-based analysis of a messy cafe-sales dataset. Its documented workflow takes the raw CSV through cleaning and type correction, then explores sales over time, item performance, and customer preferences before reporting findings. The analysis includes quantity and revenue, item popularity, dining mode, and payment method. The README describes these capabilities, but no notebook source was sampled, so the graph shows only documented data flow and does not infer specific function calls or chart outputs.
Main entry points: Cafe_sales.ipynb Clean and convert · dirty_cafe_sales.csv Dirty sales CSV
Components 6
Data preparation
- Clean and convert
Cafe_sales.ipynb
Sales analysis
- Monthly sales
Cafe_sales.ipynb - Item performance
Cafe_sales.ipynb - Customer preferences
Cafe_sales.ipynb
Reported results
- Key findings
Cafe_sales.ipynb
Other components
- Dirty sales CSV
dirty_cafe_sales.csv
Connections 7
- Dirty sales CSV → Clean and convert: loads
- Clean and convert → Monthly sales: prepares data
- Clean and convert → Item performance: prepares data
- Clean and convert → Customer preferences: prepares data
- Monthly sales → Key findings: summarizes
- Item performance → Key findings: summarizes
- Customer preferences → Key findings: summarizes