Developed JSON data processing pipeline in Python

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Developed JSON data processing pipeline in Python

  • Day: 2023-06-29
  • Time: 08:00 to 08:25
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, JSON, Data Processing, Pandas, Error Handling

Description

Session Goal

The goal of this session was to develop a robust data processing pipeline in Python to handle JSON files from 2022 and 2023, extract specific elements, and convert them into a structured format using pandas DataFrames.

Key Activities

  • Loaded JSON files using Python’s [[json]] module and os for directory traversal.
  • Clarified the relationship between a list named data and the JSON loading process.
  • Extracted placeVisit elements from JSON data using list comprehension.
  • Converted extracted data into pandas DataFrames, addressing an AttributeError by replacing the deprecated append method with concat.
  • Provided error handling for potential KeyError during JSON data extraction using try-except blocks.

Achievements

  • Successfully loaded and processed JSON files, extracting relevant placeVisit data.
  • Created pandas DataFrames from the extracted data, ensuring compatibility and stability by using the concat method.
  • Implemented error handling to manage missing keys gracefully.

Pending Tasks

  • Further testing and validation of the data processing pipeline with additional JSON datasets to ensure robustness and accuracy.

Evidence

  • source_file=2023-06-29.sessions.jsonl, line_number=0, event_count=0, session_id=ffe4428c49b6be92a8833ff02d19c77bbeb723050a4407621b6643d1b238ed3f
  • event_ids: []

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