Developed Python functions for data extraction and file handling

• Day: 2023-01-04
• Time: 20:15 to 23:55
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Extraction, File Handling, Optimization

Description

Session Goal: The session aimed to develop and optimize Python functions for data extraction and file handling, particularly focusing on handling GeoJSON files and extracting arguments from pandas DataFrames.

Key Activities:

• Discussed Python code and potential issues related to file search and data extraction.
• Implemented a Python function to search for strings within files and handle errors gracefully.
• Developed a function to search for strings in text files and store results in a Pandas DataFrame.
• Created a method to extract arguments from pd.read_csv and gpd.read_file using regular expressions.
• Implemented a boolean series in a DataFrame to detect commented lines.
• Provided instructions for selecting cells in a Pandas DataFrame using Visual Studio Code.
• Listed GeoJSON files in a directory using the os module.
• Developed a script to calculate zonal statistics for raster data using GeoJSON files.
• Suggested code optimization techniques for data processing, including using pathlib, list comprehensions, and groupby.

Achievements:

• Successfully implemented Python functions for file searching and data extraction.
• Enhanced data processing scripts with optimization techniques.

Pending Tasks:

• Further optimize the zonal statistics calculation script for larger datasets.
• Explore additional file handling techniques using the glob module for recursive searches.

Evidence

• source_file=2023-01-04.sessions.jsonl, line_number=1, event_count=0, session_id=5c81896719b10c3dc20e7f0a4cfb111156a352ae8a9358a2846b26763a03988f
• event_ids: []