This project comprises a set of Python scripts designed to analyze and visualize stock market data. It uses matplotlib for generating insightful plots that represent various aspects of stock performance over time.
- Generate bar charts to showcase the adjusted closing prices of stocks.
- Create horizontal bar charts that compare the opening and closing prices.
- Utilize pie charts to represent the distribution of high, low, and volume data points.
- Plot time series data to analyze trends in stock adjustments.
- Fill area charts for visualizing stock volume changes.
- Ensure you have
matplotlibandcsvlibraries installed in your Python environment. - Place your stock data in CSV format within the same directory as the scripts.
- Run
data.pyto load and format your data appropriately. - Execute
Plots.pyto create and view the visualizations.
The data.py script expects a CSV file with the following columns:
- Date
- Open
- High
- Low
- Close
- Adj_Close
- Volume
Ensure your CSV follows this format for the scripts to function correctly.
The plots generated by Plots.py will be saved to a dynamically named directory based on the current date and time, ensuring that each visualization session is neatly organized and timestamped for future reference.