Collecting and Analyzing Stock Data with Python

Overview

Created for the Seminar in Advanced Software Development course, this project automates the collection and analysis of daily closing prices for selected stock tickers using Python and cloud-based scheduling. The system fetches data from the AlphaVantage API and generates visualizations to track stock performance over time.

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Features

1. Automated Data Collection:

   • Utilizes the AlphaVantage API to retrieve daily closing prices for specified stock tickers.
   • Deployed on PythonAnywhere to execute automatically at 6 PM EST on trading days.

2. Data Analysis and Visualization:

   • Processes the collected data to generate graphs illustrating stock performance.
   • Supports multiple stock tickers, including AAPL, AMZN, GOOGL, and MSFT.

3. Historical Data Management:

   • Stores historical data in text files for reference and further analysis.
   • Generates visual comparisons of stock performance over different time periods.

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Key Functions

Data Collection (main.py):

• Fetches daily closing prices for specified stock tickers using the AlphaVantage API.
• Appends new data to existing historical records.

Data Visualization (2024_graphs.py):

• Generates line graphs for each stock ticker to visualize performance over time.
• Saves the graphs as PNG images for review and reporting.

Historical Data Management (file_gen.py):

• Creates and updates text files containing historical stock data.
• Ensures data integrity and readiness for analysis.

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Performance Highlights

• Automation: Eliminates manual data collection by automating daily retrieval and storage.
• Visualization: Provides clear graphical representations of stock trends over time.
• Scalability: Easily extendable to include additional stock tickers or different data points.

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Video Presentation

Project Presentation

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All materials used in presentation are available in this repository.