📊 Student Performance Analyser — README

A simple and modular data‑analysis dashboard built using Python and Streamlit. This project is designed for exploring datasets, computing statistics, visualising patterns, and generating insights with minimal setup.

This is a Streamlit-based dashboard. I built to analyse student performance in a clean, visual, and interactive way. The idea is simple: upload a CSV or Excel file, and the app breaks down everything — overall performance, CSL100 specific analysis, and even detailed individual student insights.

It’s mainly designed around the My own Structure of data, but as long as your dataset has the required columns, it will work fine. Currently it works on the 14 Columns of dataset that I have used. All the datasets are being provided for the testing of the Project.

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📦 Features

• Load and preview datasets
• Clean and preprocess data
• Generate descriptive statistics
• Interactive charts and visualisations
• Individual and overall student analysis features
• Fast and responsive Streamlit UI

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Tech Stack

NUMPY -- For math support
PANDAS -- For making DataFrames and dealing with DataFrames
MATPLOTLIB -- For constructing all the visual graphs, pie chats and donut charts
SCIKIT-LEARN -- For Data Preprocessing\

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🚀 Run Locally

Follow these steps to set up and run the project on your machine.

1. Clone the repository

git clone https://github.com/SumiRann1/Data-Analysis-and-Visualisation-Project.git

2. Go to the project directory

cd Data-Analysis-and-Visualisation-Project

3. Open Virtual Environment

python -m venv venv

4. Activate the Virtual Environment

for Linux/MacOS

source venv/bin/activate

or for Windows

venv\Scripts\activate

5. Install dependencies

Make sure Python 3.10+ is installed. Then install all required packages:

pip install matplotlib scikit-learn pandas numpy streamlit openpyxl

or

pip install -r requirements.txt

6. Start the server

Run the Streamlit development server:

streamlit run Home.py

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📁 Project Structure

project/
│
├── Home.py                    # Entry point for Streamlit app
├── pages/                     # Additional Streamlit pages
├── requirements.txt           # List of Python dependencies
└── README.md                  # Documentation

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🛠 Technologies Used

• Python
• Streamlit
• Pandas
• NumPy
• Matplotlib

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Screenshots

Screenshot 1 - Home Page - Upload the data provided for testing

Screenshot 2 - A short glimpses of GENERAL Feature Analysis

Screenshot 3 - Second Page to Compare Overall all Courses Performanse

Screenshot 4 - CSL Performance Analysis

📄 License

This project is open-source. Use it freely for learning, analysis, and development. Made for My First Semester Course Project.

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