📊 EduFlow Student Dashboard (Dash + Plotly)
A web-based interactive analytics dashboard built using Python, Dash, Plotly, and Pandas to analyze academic performance of BCA students. This dashboard allows faculty or administrators to upload student marks data and instantly visualize performance insights such as pass/fail status, gender-wise distribution, mark ranges, and KPIs.
🚀 Features
• 📂 Upload CSV or Excel files (Drag & Drop supported)
• 🎯 Subject-wise performance analysis
• 📈 Automatic calculation of Total Marks
• 🧮 Key Performance Indicators (KPIs):
○ Total Students
○ Boys Percentage (%)
○ Girls Percentage (%)
○ Average Marks
• 📊 Interactive visualizations:
○ Gender distribution (Pie chart)
○ Marks distribution by range (Histogram)
○ Pass vs Fail comparison (Bar chart)
○ Gender-wise Pass & Fail analysis (Donut charts)
• 🎨 Clean pastel UI suitable for academic dashboards
🛠️ Tech Stack
• Python 3.9+
• Dash – Web framework
• Plotly Express – Interactive charts
• Pandas – Data processing
• Base64 / IO – File upload handling
📁 Project Structure
student-dashboard/ │ ├── app.py # Main Dash application ├── README.md # Project documentation ├── requirements.txt # Python dependencies └── sample_data.xlsx # (Optional) Sample dataset
📊 Required Dataset Format
The uploaded file must contain the following columns:
Column Name Description
Course Course name (e.g., BCA)
Gender Boy / Girl
Subject Subject name
Internal_1 Internal exam 1 marks
Internal_2 Internal exam 2 marks
External External exam marks
⚙️ Installation & Setup
1️⃣ Clone the Repository
git clone https://github.com/your-username/bca-student-dashboard.git cd bca-student-dashboard
2️⃣ Create Virtual Environment (Optional but Recommended)
python -m venv venv source venv/bin/activate # For Windows: venv\Scripts\activate
3️⃣ Install Dependencies
pip install dash plotly pandas
4️⃣ Run the Application
python app.py
Open your browser and go to:
🧠 How It Works
-
Upload student marks file (CSV / Excel)
-
Dashboard filters data for BCA course only
-
Select a subject from the dropdown
-
Dashboard updates all KPIs and charts dynamically
-
Pass/Fail is calculated using:
PASS_MARK = 50
🎯 Use Cases
• College internal assessment analysis
• Department level academic reviews
• Faculty performance tracking
• Student result visualization
📌 Customization Ideas
• Add semester-wise filters
• Export reports as PDF
• Role-based login (Admin / Faculty)
• Predict performance using ML
• Connect with database (MySQL / PostgreSQL)
📸 Screenshots
🧑💻 Author
Sreelekshmi A A (https://github.com/sreelekshmiaa)
Theertha Sunil (https://github.com/theerthasunil066-boop)
Shivganga R T (https://github.com/shivgangart)
Course: BCA (Data Science & AI)
Institution: Asian School of Business
📜 License
This project is for educational purposes. You are free to modify and use it for academic projects.