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https://github.com/hatim001/vizwicket

https://github.com/hatim001/vizwicket

Science Score: 13.0%

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    CITATION.cff file
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    .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (9.4%) to scientific vocabulary
Last synced: 5 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: Hatim001
  • Language: TypeScript
  • Default Branch: main
  • Size: 10.2 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme

README.md

VizWicket: Interactive IPL Data Visualization

Introduction

Welcome to VizWicket, an intuitive web-based platform that brings the excitement and intricacies of the Indian Premier League (IPL) to your screen through advanced data visualization. VizWicket leverages the latest web technologies to transform IPL statistics into engaging visual stories, allowing users to delve into matches, player performance, and season trends with just a few clicks.

Built with ReactJS, VizWicket offers a responsive and user-friendly interface, while D3.js breathes life into the data with dynamic, interactive charts. The backend, powered by Python, ensures robust data handling and seamless integration. From Manhattan and Worm charts to Wicket Distribution and Boundary Scatter plots, VizWicket makes cricket analytics accessible and insightful for fans, analysts, and enthusiasts alike.

Dive into the data, uncover hidden narratives, and experience the IPL like never before with VizWicket.

Technologies Used

  • Backend: Django (Python 3.11), Poetry for dependency management
  • Frontend: React, D3.js for data visualization
  • Deployment: Render (Backend), Netlify (Frontend)

Deployment

Live Website URL: VizWicket

Steps for Installation

Backend Installation

Windows & macOS:

  1. Install Python 3.11: Download from python.org and follow the installation instructions.
  2. Install Poetry:
    • Windows: Run pip install poetry in Command Prompt.
    • macOS: Run pip3 install poetry in Terminal.
  3. Navigate to the backend/ directory.
  4. Install dependencies: Run poetry install --no-root.
  5. Start the server: Run poetry run python manage.py runserver.

Frontend Installation

Node.js Setup:

  • Windows & macOS: Download from nodejs.org and follow the setup instructions.

Yarn Setup:

If you don't have Yarn installed, after installing Node.js, run npm install --global yarn to install Yarn globally on your system.

Project Setup:

  1. Navigate to the frontend/ directory in your terminal.
  2. Install dependencies with Yarn: Run yarn install.
  3. Start the development server: Run yarn start.

Usage

After successful installation of both backend and frontend go to the following url http://localhost:3000

Owner

  • Login: Hatim001
  • Kind: user

GitHub Events

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Dependencies

frontend/package.json npm
  • @emotion/react ^11.11.4
  • @emotion/styled ^11.11.0
  • @mui/icons-material ^5.15.11
  • @mui/material ^5.15.11
  • @testing-library/jest-dom ^5.14.1
  • @testing-library/react ^13.0.0
  • @testing-library/user-event ^13.2.1
  • @types/d3 ^7.4.3
  • @types/jest ^27.0.1
  • @types/js-cookie ^3.0.6
  • @types/node ^16.7.13
  • @types/react ^18.0.0
  • @types/react-dom ^18.0.0
  • axios ^1.6.8
  • d3 ^7.8.5
  • js-cookie ^3.0.5
  • json-loader ^0.5.7
  • react ^18.2.0
  • react-dom ^18.2.0
  • react-router-dom ^6.22.2
  • react-scripts 5.0.1
  • typescript ^4.4.2
  • web-vitals ^2.1.0
frontend/yarn.lock npm
  • 1384 dependencies
backend/poetry.lock pypi
  • asgiref 3.8.1
  • django 4.2.11
  • django-cors-headers 4.3.1
  • djangorestframework 3.15.1
  • fuzzywuzzy 0.18.0
  • gunicorn 21.2.0
  • levenshtein 0.25.0
  • numpy 1.26.4
  • packaging 24.0
  • pandas 2.2.1
  • python-dateutil 2.9.0.post0
  • python-dotenv 1.0.1
  • python-levenshtein 0.25.0
  • pytz 2024.1
  • rapidfuzz 3.7.0
  • six 1.16.0
  • sqlparse 0.4.4
  • tzdata 2024.1
backend/pyproject.toml pypi
  • django 4.2.11
  • django-cors-headers ^4.3.1
  • djangorestframework ^3.15.1
  • fuzzywuzzy ^0.18.0
  • gunicorn ^21.2.0
  • pandas ^2.2.1
  • python ^3.11
  • python-dotenv ^1.0.1
  • python-levenshtein ^0.25.0