Namaste
I'm
Shri Krishna Pandey
Project work
TracKKaroo, tracker webapp, employs Flask, Jinja2 templates, and Bootstrap for seamless HTML generation.
Utilizing SQLite for the database, users can sign up/login, create personalized Numeric/ Boolean trackers, and log entries dynamically.
The app empowers users to track progress through trendline graphs, providing a comprehensive experience for managing, updating, and visualizing their unique trackers.
TracKKaroo Version1
TracKKaroo, Tracker webapp combines Flask backend, VueJS frontend, Bootstrap, SQLite, Redis, and Celery for a robust user experience.
Users can design and manage numeric/Boolean trackers, log entries, and visualize trends with dynamic graphs.
The app ensures user engagement through automated monthly reports, daily reminders, and export options for tracker details in CSV format to their email.
TracKKaroo Version2
This React-Todo application marks my first endeavor in creating a React application. I've put in efforts to design a user-friendly and efficient platform for managing your daily tasks.
How to Use
Add Todos: Provide a title and a brief description, then hit "Submit" to save it.
Remove Todos: Completed a task? Just click on the delete icon below the todo to remove it from your list.
Data Privacy
Rest assured, your data privacy is our top priority. The app stores your todos locally in your browser's localStorage, ensuring that your information stays secure and private.
Business Data Management
The capstone project on the MKP Store delves into analyzing its financial performance.
With insights gathered from 10 physical meetings and unstructured data collection, the report addresses challenges like excess inventory and mismatched product procurement.
A comprehensive analysis of sales by category, coupled with a neighborhood survey, forms the basis of actionable recommendations.
The addition of a small-scale app for streamlined data input underscores the practical solutions proposed to enhance the business's profitability and operational efficiency.
Analysis of Structured Shopping Data