📅 2025-02-06 — Session: Enhanced financial data processing and visualization
🕒 18:50–21:20
🏷️ Labels: Python, Financial Reporting, Data Visualization, CSS, Pandas
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal
The session aimed to improve financial data processing, visualization, and reporting techniques using Python and CSS.
Key Activities
- Best Practices: Reviewed best practices for managing cumulative vs. net variables in financial data to ensure accurate insights.
- Financial Analysis: Conducted a comprehensive analysis of current financial variables, identifying key metrics for monitoring.
- Accumulator Function: Designed an accumulator function in Python for transforming Pandas data into cumulative forms.
- Plotting Functions: Created specialized Python functions for visualizing financial time series data.
- Financial Monitoring: Outlined strategies for monitoring key financial indicators in a rental business.
- Data Filtering: Implemented a method to filter DataFrame columns by absolute sum using Python.
- Ledger Enhancements: Analyzed and suggested improvements for monthly ledger reports.
- Code Refactor: Refactored Python code to generate HTML-formatted financial reports.
- CSS Styling: Enhanced the visual appeal of ledger reports with CSS.
Achievements
- Developed Python functions for financial data transformation and visualization.
- Improved monthly financial reporting with HTML and CSS styling.
- Enhanced clarity and effectiveness of financial monitoring strategies.
Pending Tasks
- Further enhancements to plotting functions for better visualization.
- Additional CSS improvements for table styling in reports.