Developed Python utilities for data file management

• Day: 2023-05-22
• Time: 02:30 to 03:00
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Processing, File Handling, Pandas, Numpy

Description

Session Goal: The session aimed to develop Python utilities for managing data files, focusing on generating base names from data structures and saving them in various formats.

Key Activities:

• Implemented a Python script to save modified style data to a JSON file.
• Developed a method to generate base names from series data using two-level indices.
• Utilized NumPy’s ravel function to flatten nested arrays before base name generation.
• Demonstrated the use of iterrows() to iterate over a Pandas series with multi-level indices for base name generation.
• Converted a DataFrame into a multi-index series to generate base names by combining index values.
• Created base names from a DataFrame using specific tags and unique values.
• Saved generated base names to a text file, ensuring each name was on a new line.
• Provided a solution to save data to CSV files, separating list lengths and styles into different files.

Achievements:

• Successfully created a suite of Python scripts for data manipulation and file operations, enhancing the ability to manage and store data efficiently.

Pending Tasks:

• Review and optimize the code for performance improvements and potential edge cases.

Evidence

• source_file=2023-05-22.sessions.jsonl, line_number=5, event_count=0, session_id=afaaa86239af3ce54e8a2c832dff75fa1c7ff4d75e2678a44f9dcb701a854743
• event_ids: []