DataFrame manipulation and file structure analysis
- Day: 2026-01-09
- Time: 14:20 to 14:30
- Project: Dev
- Workspace: WP 2: Operational
- Status: Completed
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Pandas, Dataframe, File_Management, Python, Data_Analysis
Description
Session Goal
The session aimed to analyze and manipulate data using pandas, focusing on creating DataFrames, comparing file manifests, and retrieving file structures.
Key Activities
- DataFrame Creation: Demonstrated how to create a DataFrame and count unique values in the ‘stage’ column.
- File Manifest Comparison: Compared expected files against actual files in a manifest, identifying discrepancies.
- Function Development: Developed a function to retrieve the structure of files from a DataFrame based on their paths.
- File Structure Analysis: Iterated through financial report files, printing their structures using the developed function.
- Data Extraction: Extracted dictionaries from DataFrame rows using conditional filters and extracted JSON metadata paths from the ‘meta/’ directory.
- CSV Column Extraction: Created a function to extract column names from CSV files listed in a DataFrame.
Achievements
- Successfully created and manipulated DataFrames for data analysis.
- Developed functions to retrieve file structures and extract specific data from DataFrames.
- Identified and documented missing and extra files in a file manifest.
Pending Tasks
- Further validation of file structure retrieval functions to ensure accuracy in diverse datasets.
- Expansion of CSV column extraction to handle additional file formats if necessary.
Evidence
- source_file=2026-01-09.sessions.jsonl, line_number=15, event_count=0, session_id=171543162a5721c007ece612f6e054ff480d3b0d48e4d91ea1b139febb1ab0e5
- event_ids: []