Django Stock Market Data Web Application

Project Directory Structure

Webapps/

• Data/

  • stock_market_data.csv
  • stock_market_data.json

• env/

  • Include/
  • Lib/
  • Scripts/
  • pyvenv.cfg

• Janata/

  • asgi.py
  • settings.py
  • urls.py
  • wsgi.py
  • static/
    • css/
      • styles.css
    • js/
      • main.js
  • Table_Apps/
    • management/
      • commands/
        • load_data.py
    • migrations/
    • init.py
    • admin.py
    • apps.py
    • models.py
    • tests.py
    • views.py
  • templates/
    • graphs.html
    • table_apps.html
    • table.html
  • db.sqlite3
  • manage.py

Project Overview

This Django learning project involves building a basic web application with data visualization and CRUD functionality. The project is divided into three main steps:

1. Initial Web App with JSON Data:

   • Creation of a basic web app using Python and Django.
   • Utilization of JSON data to generate a table visualization on the home page.

2. Integration with SQL Server and CRUD Functionality:

   • Loading the data into an SQL server for improved data management.
   • Implementation of CRUD operations for the table, allowing users to edit rows dynamically.
   • Creation of separate branches in the Git repository for each model version: jsonModel and sqlModel.

3. Enhanced Data Visualization:

   • Addition of a line chart above the table visualization.
   • Plotting the "close" column on the y-axis and "sorted date" on the x-axis in the line chart.
   • Incorporation of the "volume" column as a bar chart on a secondary y-axis.
   • Accommodate the line and bar chart together by making it a multi axis chart.
   • Implementation of a dropdown feature to switch between different "trade_code" columns, dynamically updating the all charts.

Getting Started

To run this project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/SalehAhmedShafin/Stock-Market-Data-Visualization-Django-Apps

Django Learning Project

Getting Started

1. Navigate to the project directory:

   cd Janata

2. Apply migrations to set up the database:

   python manage.py makemigrations
   python manage.py migrate

3. Run the development server:

   python manage.py runserver

4. Open your browser and go to http://localhost:8000/ to view the web app.

Challenges Faced

Transition from JSON to SQL

• Adapting the codebase to switch between JSON and SQL models posed challenges.
• Ensuring data consistency and integrity during the migration process.

Implementing CRUD Operations

• Integrating frontend and backend components to support editable rows in the table.
• Handling user input and updating the SQL database accordingly.

Multi-Axis Chart Integration

• Implementing a multi-axis chart with dynamic data based on user selections.
• Coordinating the line and bar charts for a cohesive visualization.

Chart.js integration issue

• After integrating Chart.js into the project, the chart is not displaying as expected on the webpage.

Key Learnings

Django and Backend Development

• Gained proficiency in using Django for web application development.
• Learned the intricacies of integrating backend functionality with frontend interfaces.

Data Visualization with Chart.js

• Acquired skills in implementing interactive charts using Chart.js.
• Explored the nuances of creating multi-axis charts for diverse data representation.

Database Management

• Applied principles of maintaining data integrity and consistency in a dynamic web environment.

Version Control and Collaboration

• Collaborated on a project involving frontend and backend development, enhancing coordination and communication skills.

This project provided valuable insights into full-stack web development, data visualization, and database management, enhancing skills in Python, Django, Chart.js, and version control.