Data Processing and Analysis with Python and Pandas

• Day: 2026-01-09
• Time: 18:55 to 19:05
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Pandas, Data Processing, JSON, Data Analysis

Description

Session Goal

The session aimed to explore and execute various data processing and analysis tasks using Python and Pandas, focusing on JSON Lines data.

Key Activities

• Loaded JSON Lines files into Python and converted them into Pandas DataFrames for analysis.
• Extracted unique stages and roles from JSON records to understand data structure.
• Created and previewed DataFrames to examine data columns and structure.
• Developed functions for retrieving and manipulating data columns from materialized views.
• Filtered and sorted DataFrames based on specific criteria to prepare data for further analysis.
• Iterated through view names to print corresponding column data, enhancing data exploration.
• Utilized regular expressions to locate function definitions within Python code, aiding in code analysis.
• Extracted text snippets and substrings from larger text bodies for targeted data extraction.
• Conducted a simulated team review on views mart artifacts, discussing data stability and compliance.

Achievements

• Successfully loaded and manipulated JSON Lines data using Pandas.
• Extracted and analyzed unique data elements, improving data understanding.
• Enhanced data exploration through effective DataFrame operations.
• Improved code analysis and text extraction capabilities with Python scripts.

Pending Tasks

• Further review and refine the data transformation processes discussed in the simulated team review.
• Implement proposed contracts for views mart to ensure data compliance and stability.

Evidence

• source_file=2026-01-09.sessions.jsonl, line_number=1, event_count=0, session_id=922f7a2304801f0c0201c830ae9f06669e3c33771bc04781ffec6a9ebd985c92
• event_ids: []