{"repo":"AmirhosseinHonardoust/Retail-Calendar-Pattern-Finder","free":true,"listed":false,"github":"https://github.com/AmirhosseinHonardoust/Retail-Calendar-Pattern-Finder","clone":"git clone https://github.com/AmirhosseinHonardoust/Retail-Calendar-Pattern-Finder.git","description":"A retail analytics capstone that converts transactions into a calendar intelligence system. It quantifies day-of-week and monthly seasonality, builds a baseline expected revenue model, detects event-like spike days using robust residual z-scores, and explains spikes via transactions, units, AOV, and category mix, with a Streamlit dashboard+exports.","language":"Python","stars":11,"topics":["anomaly-detection","baseline-model","dashboard","data-analysis","data-science","exploratory-data-analysis","feature-engineering","kaggle-dataset","matplotlib","numpy"],"license":"MIT","category":"dashboards-admin","readme_excerpt":"Retail Calendar Pattern Finder Seasonality + Event-like Spike Detection (Data Analyst × Data Science Capstone) This project turns raw retail transactions into a calendar intelligence system : - Seasonality : Which days and months consistently perform better? - Calendar interactions : Which month × day-of-week combinations are unusually strong/weak? - Spike detection : Which days look like events (promotions, anomalies, shifts) after removing normal seasonality? - Spike explanation : For each spike day, what drove it, transactions , units , AOV , or category mix ? It includes: - A reproducible Python pipeline that generates metrics + figures + report artifacts - A Streamlit dashboard to explore seasonality and drill into spike days - Exportable outputs ( CSV , JSON ) designed for analyst workflows and portfolio review --- Table of Contents - What you get - Business questions answered - Dataset - Data dictionary - Coverage note (critical) - Methodology - Daily rollups - Seasonality analysis - Baseline expected revenue - Spike detection - Spike explanation - Results & Figures - 1) Day-of-week seasonality - 2) Monthly revenue - 3) Month × day-of-week heatmap - 4) Residual spike scatter - Outputs - How to run - Install - Run pipeline - Run dashboard - Dashboard guide - Project structure - Quality checks - Limitations & assumptions - Improvements / roadmap --- What you get Pipeline artifacts - outputs/daily metrics.csv daily revenue / txns / units / AOV - outputs/weekly metrics.csv","default_branch":null,"files":null,"tree":[],"storefront":"/r/AmirhosseinHonardoust","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AmirhosseinHonardoust/Retail-Calendar-Pattern-Finder/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}