The purpose of this project is to extract financial data for popular stocks, including historical share prices and quarterly revenue reports, from various sources using Python libraries and web scraping techniques. The extracted data will then be used to create a dashboard that visualizes the information, allowing us to identify patterns and trends in the stock market.
To collect the financial data, we utilized Python libraries and implemented web scraping techniques to extract relevant information from multiple sources. This approach enables us to gather accurate and up-to-date data on the selected stocks. The stocks chosen for this project are Tesla, Amazon, AMD, and GameStop, which are well-known and widely traded companies in the stock market.
Once the data collection process is complete, the next step is to present the information in a dashboard format. A dashboard provides a comprehensive view of key performance indicators (KPIs) in a clear and visually appealing manner. By analyzing the dataset and extracting relevant KPIs, we gain insights into the performance of the selected stocks over time.
For the visualization aspect of the project, we utilized the Plotly library in Python. Plotly is a powerful tool for creating interactive and dynamic visualizations, making it ideal for presenting financial data in a dashboard format. With Plotly, we can create visually appealing charts and graphs that allow us to explore the historical share prices and quarterly revenue reports of the selected stocks.
The dashboard will display various analytics, including historical share price trends, quarterly revenue reports, and any other relevant financial metrics. These analytics will provide a holistic view of the performance of the stocks, allowing us to identify patterns, trends, and potential investment opportunities.
By leveraging the power of Python, web scraping techniques, and Plotly visualizations, this project aims to provide a comprehensive and user-friendly dashboard for analyzing the financial data of Tesla, Amazon, AMD, and GameStop. This dashboard will enable users to make informed decisions based on the insights gained from the visualizations and key performance indicators displayed.