Developed DataFrame Artifact Summary Functions

• Day: 2026-01-09
• Time: 14:25 to 14:35
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Dataframe, Data Processing, Artifact Integrity, CSV

Description

Session Goal

The session aimed to enhance data processing capabilities by developing functions to summarize and filter DataFrame artifacts, ensuring data integrity and structure consistency.

Key Activities

• Implemented a function to summarize the structure of artifacts in DataFrames, focusing on different file types such as CSV and JSON.
• Filtered DataFrames to identify null structures, displaying relevant columns for further analysis.
• Extracted and displayed file paths for CSV reports, including metadata about the columns.
• Printed columns from CSV files using Python functions to facilitate data inspection.
• Filtered specific columns from CSV files based on substrings, refining data extraction processes.
• Addressed tech lead directives on artifact integrity and data structure, including checks for missing run IDs and standardizing naming conventions.

Achievements

• Successfully developed and executed functions for summarizing and filtering DataFrame artifacts.
• Improved data governance by implementing checks for artifact integrity and consistency.

Pending Tasks

• Further refinement of data processing pipeline to address artifact integrity issues and standardize file registrations.

Evidence

• source_file=2026-01-09.sessions.jsonl, line_number=11, event_count=0, session_id=22404b3d4a99a9f861d4d5352d23175e49e6c80528551289cb4830265db9abfa
• event_ids: []