Data Resampling and Visualization Enhancements

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📅 2025-03-12 — Session: Data Resampling and Visualization Enhancements

🕒 00:00–04:10
🏷️ Labels: Pandas, Data Visualization, Financial Data, Resampling, Matplotlib
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance data handling and visualization techniques in Python, focusing on Pandas and Matplotlib.

Key Activities

  • Preserving Time Index in Pandas CSV Operations: Implemented strategies to ensure time index preservation when saving/loading DataFrames, recommending Parquet for performance.
  • Aesthetic Guidelines for Financial Visualization: Developed guidelines for effective financial data visualization using line plots and clear labeling.
  • Fixing PeriodIndex Issues in Matplotlib: Addressed PeriodIndex plotting issues by converting to DatetimeIndex.
  • Understanding Retained Earnings and Cumulative Net Profit: Explored financial concepts and their application in data analysis.
  • Fixing Resampling for Cumulative Data: Improved resampling techniques to preserve cumulative data integrity.
  • Fixing Weekly Resampling Mismatch: Ensured consistent weekly resampling in financial datasets.
  • Avoiding NaNs with .reindex(): Provided solutions to prevent null values during data alignment.
  • Aligning PeriodIndex to DatetimeIndex: Converted PeriodIndex to DatetimeIndex for consistent data alignment.

Achievements

  • Enhanced data resampling methods to ensure accurate financial reporting.
  • Improved visualization techniques for financial time series data.

Pending Tasks

  • Further exploration of advanced visualization techniques for complex financial datasets.

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