there are a lot of packages should be installed, best install yfinance first if needed.

pip install yfinance

https://pypi.org/project/yfinance/

Run the app.py file for demo

Run the analysis.py file for data analysis & plot

1. Introduction

Project Goals: The aim of our project is to create an interactive stock market heat map that allows users to quickly understand market trends, sector performance, and individual stock movements. Motivation: With the increasing complexity of financial markets, there is a need for tools that can distill vast amounts of data into understandable visual formats. Our project addresses this need by offering a comprehensive visualization of stock performance data. Dataset: The dataset will consist of daily stock price movements, trading volumes, and market capitalization data from major stock exchanges, such as NYSE and NASDAQ.

2. Related Work

Our literature review will focus on existing financial data visualization tools, examining their design choices, functionalities, and limitations. We aim to identify gaps in current offerings and leverage insights to inform our design process.

3. Design Considerations

User Interface Design: The interface will feature a color-coded heat map, with stocks represented as tiles varying in size and color intensity based on performance metrics. Visualization Techniques: We will implement interactive elements such as hover-over details, click-through to detailed stock information, and filtering options to view specific sectors or performance metrics. Code Design: The project will be developed using D3.js for dynamic data visualization and Python for data processing and backend operations.

4. Expected Roles and Responsibilities

Data Analyst: Responsible for acquiring and cleaning the dataset. Frontend Developer: In charge of creating the interactive heat map visualization. Backend Developer: Focuses on server-side operations and data processing. Deliverables

A fully functional prototype of the stock market heat map. Documentation outlining the design process and justification for design choices. A user guide explaining how to interact with the visualization tool.

This project aims to create an interactive heat map of the stock market, utilizing data from the Alpaca API. It visualizes various market metrics like stock price changes and trading volumes, providing insights into market trends and movements.

1. Color-Coded Performance: Each tile's color indicates the stock's daily performance, with green for positive, red for negative, and white or grey for no change.

2. Company Logos: Each tile includes the company's logo, making it easier to identify the stock visually.

3. Percentage Change: The tiles show the percentage change of the stock price, providing quick insight into the stock's performance.

4. Size Coded Market Capitalization: The size of each tile appears to represent the market capitalization of the stock, with larger tiles indicating larger companies.

5. Interactive Tooltips: Hovering over a tile likely provides more detailed information, such as exact price change, market cap, or other relevant data.

6. Filtering Options: The top bar includes options to filter the view based on performance percentage, enabling users to quickly isolate stocks that are performing within a certain range.

7. Zooming and Panning: Users can zoom in or out to view more or fewer stocks in the heatmap.

8. Search Functionality: There is likely a search feature that allows users to find a specific stock within the heatmap.

9. Layout and Design: The overall design is grid-like, with a clear distinction between different sections of the market.

10. Dynamic Updating: The heatmap updates in real-time, or at a specified interval, to reflect current market conditions.

11. Responsive Design: The layout adjusts to different screen sizes and resolutions, ensuring usability across various devices.

12. Legend/Scale: There is a color scale or legend that helps users understand the color coding in relation to stock performance percentages.

To recreate this in Dash,

• Fetch real-time stock data, including daily changes and market capitalization.
• Create a layout with dynamically sized and colored tiles based on fetched data.
• Integrate company logos into the visualization.
• Implement interactivity with tooltips that display more data on hover.
• Add filtering functionality to view stocks based on performance criteria.
• Enable zooming and panning within the heatmap.
• Include a search feature to find specific stocks.
• Ensure that the layout is responsive and adjusts to different screen sizes.
• Update the data at regular intervals to reflect the current market state.

Each of these features would require careful consideration of the data structure, UI components, and interactivity provided by Dash and Plotly.