Resolved Data Merging and Processing Issues

• Day: 2025-06-22
• Time: 19:25 to 20:05
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Data_Processing, Python, CSV, Merging, Debugging

Description

Session Goal:

The session aimed to diagnose and resolve issues related to data merging and processing, ensuring data integrity and improving the data pipeline for article management.

Key Activities:

• Diagnosed merging issues in data processing, identifying root causes and recommending fixes for incorrect merging of editorial ideas with articles from different topics.
• Implemented Python code for merging JSONL and CSV files into a clean DataFrame, ensuring topic-level consistency.
• Corrected code to reconstruct the ‘digest_file’ column and normalize data using Python and Pandas.
• Proposed a strategy to reorganize the article pipeline to enhance traceability and uniqueness of identifiers, including creating new tables and implementation code.
• Resolved a common import error with the glob module in Python, providing solutions based on different import styles.
• Debugged CSV file processing issues, addressing the absence of the master_index.[[csv]] file and improving file handling in Python scripts.

Achievements:

• Successfully resolved data merging issues and improved the data processing pipeline.
• Enhanced the robustness of CSV file processing in Python scripts.

Pending Tasks:

• Further testing and validation of the new data pipeline structure to ensure long-term stability and efficiency.

Evidence

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• event_ids: []