Resolved notebook issues and improved data pipeline

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Resolved notebook issues and improved data pipeline

  • Day: 2026-01-06
  • Time: 00:10 to 00:40
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Notebooks, Data Pipeline, Troubleshooting, Data Normalization, Pandas

Description

Session Goal

The session aimed to resolve technical issues with Jupyter notebooks using nbconvert, normalize data variables in pandas DataFrames, and review the data pipeline’s output structure for integrity.

Key Activities

  • Troubleshooting Notebooks: Addressed common errors like ‘FileNotFoundError’ and empty CSVs by adjusting directory paths and environment variables.
  • Data Normalization: Implemented a helper function to normalize party variables in pandas, ensuring error-free operations.
  • Pipeline Review: Evaluated the current output structure, identifying problematic areas and making decisions to enhance clarity before generating plots.

Achievements

  • Successfully resolved notebook execution issues, improving reliability and reducing errors.
  • Enhanced data processing by normalizing variables, which improved data handling in pandas.
  • Improved the pipeline’s output structure, setting the stage for more robust data processing and visualization.

Pending Tasks

  • Further improvements in the views layer for data processing to ensure currency integrity and observability in financial outputs.

Evidence

  • source_file=2026-01-06.sessions.jsonl, line_number=0, event_count=0, session_id=fa94b2f3aca3c1fe0215ed345245beae1a0becc9d18cf9d5a829d9110c86bf02
  • event_ids: []

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