📅 2023-10-02 — Session: Enhanced hierarchical JSON export function for quarterly data
🕒 17:50–18:35
🏷️ Labels: Python, JSON, Data Export, Error Handling, Code Optimization
📂 Project: Dev
⭐ Priority: MEDIUM
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
datakey 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.