📊 Superstore Dataset · 3,500 Transactions · Dynamic Web Dashboards & Business Analytics 📈

🌐 Live Streamlit App | 🎨 Live Static Portal

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⚡ System Command Overview

Welcome to the E-Commerce Sales Command Center. This unified intelligence hub consolidates client-side custom dashboards and enterprise reporting panels. Driven by a high-octane Python data compiler, the platform extracts complex commercial records (3,500 transactions) into stunning analytical canvases. Sift through variables, view growth patterns, and inspect margins dynamically across two custom-styled views.

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🎨 Dual-Visual Command Decks

🌌 DARK NEON PORTAL Glassmorphism UI A modern dark command deck tailored for real-time overview and analytical data discovery. 🔒 Fully reactive JavaScript slicer grids 📊 3-month moving average forecasting lines 🚀 Lightweight Chart.js rendering engines Launch Deck

💼 BI WORKSPACE Corporate Report A bright, clean interface structured according to official Power BI visual report layouts. 🏢 Power BI style cards & growth metrics 📍 Advanced regional grid matrices 📌 Slicer chip region drill-throughs Launch Workspace

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🛠️ Cybernetic Tech Stack

Core Language	Framework	Custom Styling	Analytics

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🔄 Automated Data Pipeline

graph TD
    Excel[Excel Data Source] -->|Pandas Compilation| Proc[process_data.py]
    Proc -->|JSON Export| JSON[transactions.json]
    JSON -->|Dynamic Injections| Comp[build_dynamic_dashboards.py]
    Comp -->|Static Compiles| HTML1[ecommerce_dashboard.html]
    Comp -->|Static Compiles| HTML2[ecommerce_powerbi_dashboard.html]
    HTML1 & HTML2 -->|Direct Embed| Streamlit[Streamlit app.py]

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🧠 Recursive cross-filtering

Fully responsive JavaScript controllers filter transaction lists recursively. Selecting key segments instantly recalculates visual graphs, metrics, and categories dynamically.

🔮 Predictive Moving Averages

Appends a 3-month moving average calculation alongside historical figures to visualize upcoming business trends.

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⚙️ Local Configuration Guide

To deploy the dashboard portal on your local system:

1️⃣ Clone the Repository

git clone https://github.com/Shivam09xc/E-Commerce-Dashboard.git
cd E-Commerce-Dashboard

2️⃣ Install Required Modules

pip install -r requirements.txt

3️⃣ Launch Streamlit Dashboard

python -m streamlit run app.py

Streamlit starts the web portal locally and opens your browser at http://localhost:8501.

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🔄 Preprocessing Database Pipeline

If you update or modify raw transaction records inside ecommerce_analytics (1).xlsx, run the automated pipeline to compile fresh assets:

# 1. Process Excel rows into transactions.json
python process_data.py

# 2. Inject updated JSON and compile HTML dashboards
python build_dynamic_dashboards.py

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☁️ Deployment Pipeline Guide

🌐 GitHub Pages Deployment (Free Web Hosting)

1. Go to Settings > Pages inside your repository.
2. Under "Build and deployment", set Source to Deploy from a branch.
3. Set Branch to main and Folder to / (root).
4. Click Save. The portal is live at: https://shivam09xc.github.io/E-Commerce-Dashboard/

☁️ Streamlit Cloud Deployment (Free App Hosting)

1. Sign in to share.streamlit.io via GitHub.
2. Select your repository Shivam09xc/E-Commerce-Dashboard.
3. Set the Main File path to app.py and click Deploy.
4. Access the live dashboard at: https://e-commerce-dashboardgit-qd3gjlse3fsulugafbvx5c.streamlit.app/

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🐍 Contribution Snake Automation

This repository utilizes an automated GitHub Action workflow (snake.yml) with write permissions configured. Every 12 hours, the workflow generates a glowing cybernetic contribution snake SVG:

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📈 Developer Core Analytics

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🔮 Roadmap & Future Enhancements

• Machine Learning Models: Replacing moving averages with neural forecasting models (ARIMA / LSTM).
• PostgreSQL Connector: Replacing local Excel pipelines with active database instances.
• Auto-Reporting Engine: Automatic daily PDF summary compilation and email alerts.
• Security Gateway: Multi-tenant dashboard configurations with secure OAuth.

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💙 Crafted with Passion by Shivam Soni

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