GATEWAYS 2025 Fest Analysis

This project is a Streamlit Web Application designed to analyze and visualize data from the GATEWAYS-2025 National Level Fest. It provides an interactive dashboard to explore participation metrics, event popularity, revenue, and participant feedback.

Features

The application is divided into three main pages:

1. 🏠 Dashboard

   • High-level overview metrics (Total Participants, Top Event, Average Rating, Total Revenue).
   • Visualizations of participants per event and state-wise participant share.
   • Rating distribution and Revenue by event type.
   • A complete preview of the underlying dataset.

2. 👥 Participation Analysis

   • Detailed breakdowns of participant counts by Event, College, and State.
   • Bar charts and data tables for deep dives into participation stats.
   • Interactive India Map (using GeoPandas) to visually display the geographic distribution of participants.

3. 💬 Feedback Analysis

   • Participant rating analysis with bar charts.
   • Text processing of feedback comments to extract the most common words and themes.
   • Average rating comparison across different events.
   • A basic rule-based Sentiment Analysis (Positive, Neutral, Negative) applied to the text feedback.

Project Structure

├── app.py                  # Main Streamlit application file
├── requirements.txt        # Python dependencies
├── assets/
│   ├── favicon.ico         # App favicon
│   └── logo.png            # App logo
└── data/
    ├── fest_dataset.csv    # The primary dataset of fest participants and feedback
    └── india_states.geojson # GeoJSON file for plotting the state-wise map

Setup and Installation

1. Clone the repository:

   git clone https://github.com/Mani2815/fest_analytics.git
   cd fest_analytics

2. Install the required dependencies: Make sure you have Python installed. It is recommended to use a virtual environment.

   pip install -r requirements.txt

Running the Application

To start the Streamlit application, run the following command in your terminal:

streamlit run app.py

The application will launch in your default web browser (typically at http://localhost:8501).

Technologies Used

• Streamlit: For building the interactive web application.
• Pandas: For data manipulation and analysis.
• Matplotlib: For rendering charts and graphs.
• GeoPandas: For geographical plotting (India map).
• Scikit-Learn: Included in dependencies for potential machine learning/advanced analysis tasks.