Enhanced hierarchical JSON export function for quarterly data

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Enhanced hierarchical JSON export function for quarterly data

  • Day: 2023-10-02
  • Time: 17:50 to 18:35
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, JSON, Data Export, Error Handling, Code Optimization

Description

Session Goal

The primary objective of this session was to enhance a Python function for exporting data into a hierarchical JSON format, focusing on organizing data by ‘observable’, ‘sintetico’, and quarters.

Key Activities

  • Data Update Function Modification: Adjusted the function to append new data points while avoiding unnecessary columns, ensuring only relevant data is included.
  • Nesting Data: Implemented nesting of data under ‘observable’ and ‘sintetico’ categories using Python and Pandas, handling existing records and updating metadata.
  • Code Review and Optimization: Conducted a review of the JSON export function to eliminate variable duplication and redundancy, resulting in a streamlined version.
  • Error Handling: Addressed a KeyError by ensuring proper access to necessary columns before dropping them, thus fixing the JSON export function.
  • Quarterly Data Export: Modified the function to ensure each record under the data key represents a dictionary of quarters and their values.

Achievements

  • Successfully modified the JSON export function to handle hierarchical data, including quarters, and ensured proper nesting and updating of records.
  • Resolved a KeyError issue, improving the function’s reliability and accuracy.

Pending Tasks

  • Further testing of the modified function with diverse datasets to ensure robustness and accuracy in various scenarios.

Evidence

  • source_file=2023-10-02.sessions.jsonl, line_number=4, event_count=0, session_id=45632ffaf469f929e76ad93dba0c1e522dcec3fc3d9c4024c7869264dd78104f
  • event_ids: []

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