code-forlife / library-management-dashboard

Library Management Dashboard

This project is a web-based dashboard built using Dash and Plotly, designed to visualize and manage library data. It empowers you to gain valuable insights into library usage, user trends, and book popularity.

Key Features

• Individual Analysis: Gain a comprehensive view of specific users, including:
  • Transaction Breakdown: Visualize the distribution of transaction types (borrowing, returning, fines) for a user using a pie chart.
  • Fine Distribution: Analyze fine trends over time with a histogram, helping identify frequent defaulters.
  • Book Issuance History: Explore a histogram that reveals which books a user has borrowed and the frequency.
• Overall Analysis: Understand library usage patterns on a broader scale:
  • Top 10 Issued Books: Identify the most popular books based on their total issuance count (histogram).
  • Monthly Issuance Trends: Uncover seasonal trends or changes in borrowing patterns over time with a line chart.
  • Issuance by Year of Study: Gain insights into which student groups borrow the most books and generate the highest fines (bar chart).
  • Monthly Fine Variations: Analyze the fluctuation of fines due, fines paid, and fines waived off across months (line chart).
• Book Analysis: Assess book popularity and usage:
  • Monthly Book Issuance: Uncover trends in book demand throughout the year (bar chart).
  • Book Issuance vs. Monthly Fines: Explore the relationship between book issuance and fines paid per month (line chart), potentially revealing semesters with higher borrowing and overdue occurrences.
• Author Analysis: Drill down into specific authors and their works:
  • Author Book Popularity: View a histogram for each author, showing the individual issuance count of their books.
• Email Alerts: Manage user communication:
  • Fine Delinquency Management: Filter students by specific date ranges, identify unpaid fines, and send email alerts for timely collections.
• Variety Analysis: Explore book category trends:
  • 3D Borrow Count Distribution: Visualize the distribution of borrowed books by category and year in a 3D plot. This helps identify shifts in borrowing patterns between years (e.g., more diverse categories in 2024 compared to 2023).

Technologies

• Dash: A Python framework for building analytical web apps https://dash.plotly.com/
• Plotly: A library for creating interactive visualizations in Python https://plotly.com/python/

Installation

1. Clone this repository:

   git clone https://github.com/Code-forlife>/Library-Management-Dashboard.git

2. Install required dependencies:

   pip install dash dash-renderer dash-core-components dash-html-components plotly wordcloud

Usage

1. Run the application:

   python app.py

2. Open http://127.0.0.1:8050/ in your web browser to access the dashboard.

Note: This is a basic example. Data connection may require additional configuration based on your chosen database. Explore and customize the app.py script to tailor the visualizations and functionalities of the dashboard to your specific needs.

Contributing

Sahil Shah, Pranay Singhvi(DesiCoder), Sarthak Gharat, Shivam Kamble, Palaash Jain

License

This project is licensed under the MIT License. See the LICENSE file for details.