📅 2023-10-02 — Session: Enhanced JSON export function for hierarchical data
🕒 17:50–18:35
🏷️ Labels: Python, JSON, Data Processing, Optimization, Error Handling
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance and optimize a JSON export function in Python to handle hierarchical data structures more effectively.
Key Activities
- Modified a data update function to append new data points while avoiding unwanted columns.
- Implemented nesting of data by ‘observable’ and ‘sintetico’ categories using Python and Pandas.
- Conducted a code review and optimization of the JSON export function to eliminate variable duplication and redundancy.
- Designed a hierarchical JSON export function to organize data by ‘observable’ and ‘sintetico’, ensuring proper nesting and updates to existing records.
- Addressed a KeyError in the JSON export function by ensuring proper access to necessary columns before dropping them.
- Modified the JSON export function to handle quarterly data, ensuring each record represents a dictionary of quarters and their associated values.
Achievements
- Successfully refactored the JSON export function to handle hierarchical data structures, improving data organization and processing efficiency.
- Resolved errors related to data access and column management, ensuring robust data handling.
Pending Tasks
- Further testing of the JSON export function with diverse datasets to ensure robustness and accuracy.
- Consideration of additional data structures or formats that may benefit from similar optimization techniques.