{"repo":"AmirhosseinHonardoust/Digital-Balance-Index-Dashboard","free":true,"listed":false,"github":"https://github.com/AmirhosseinHonardoust/Digital-Balance-Index-Dashboard","clone":"git clone https://github.com/AmirhosseinHonardoust/Digital-Balance-Index-Dashboard.git","description":"Composition-first analytics for daily screen time. Computes the Digital Balance Index (DBI) using normalized entropy, plus dominance, tiers, and a “high-load & skewed” flag. Exports scored rows, segment summaries, daily trends, and figures, and ships a Streamlit dashboard to explore patterns by age group, primary device, and internet type.","language":"Python","stars":10,"topics":["behavioral-analytics","composition-analysis","dashboard","data-analytics","data-science","digital-behavior","entropy","exploratory-data-analysis","feature-engineering","matplotlib"],"license":"MIT","category":"dashboards-admin","readme_excerpt":"Digital Balance Index (DBI) Dashboard --- A portfolio-grade analytics project that turns raw “hours spent” into composition-first behavioral insights . Most screen-time analyses stop at totals (“people spend 8 hours/day”). This project focuses on how that time is distributed across: - Social - Work/Study - Entertainment It ships: - a reproducible scoring pipeline ( python -m src.pipeline ) - clean exported datasets + figures - a Streamlit dashboard for interactive exploration across age group , primary device , and internet type --- Dataset (source + thanks) This project uses the Kaggle dataset: - Daily Internet Usage Statistics by Age Group by jayjoshi37 - Dataset URL: https://www.kaggle.com/datasets/jayjoshi37/daily-internet-usage-statistics-by-age-group Thanks to the dataset author and Kaggle for making the data available. --- Why this project exists The problem with “total hours” Two users can both have 10 hours/day of screen time, but with completely different patterns: - One: mostly Work/Study (structured use) - Another: mostly Social/Entertainment (dominant categories) Totals alone can’t describe behavior. Composition metrics can. The core idea For each record, we compute: 1) Shares of total screen time for each category 2) DBI (Digital Balance Index): how evenly those shares are distributed 3) Dominance : how strongly one category “owns” the day 4) Practical tiers and a flag: High-load & Skewed --- What’s inside (pipeline + dashboard) Pipeline outputs After running th","default_branch":null,"files":null,"tree":[],"storefront":"/r/AmirhosseinHonardoust","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AmirhosseinHonardoust/Digital-Balance-Index-Dashboard/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."}