Developed Python pipeline for Wise transaction transformation
- Day: 2025-07-06
- Time: 00:30 to 00:55
- Project: Dev
- Workspace: WP 2: Operational
- Status: Completed
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Python, Data Transformation, Finance, Pandas, Data Pipeline
Description
Session Goal
The goal of this session was to develop a Python pipeline capable of transforming Wise-style transaction data into a standardized ledger format for financial analysis.
Key Activities
- Data Manipulation: Added missing transaction rows to a pandas DataFrame using a list of dictionaries.
- DataFrame Generation: Created a DataFrame from extra Wise transactions, adding unique IDs for each entry.
- Ledger Entry Formatting: Provided missing ledger entries formatted to match existing transactions.
- Pipeline Development: Developed a Python pipeline to read, parse, and transform Wise-style transaction datasets into a canonical ledger format.
- Data Aggregation: Outlined steps for monthly aggregation of financial transactions, including calculations for net monthly flow and visual summaries.
- Data Accuracy Considerations: Addressed potential issues such as date format inconsistencies and currency misalignment before data aggregation.
- Troubleshooting: Identified and resolved file reading issues in directories, ensuring proper file management.
Achievements
- Successfully developed a comprehensive Python pipeline for transforming and aggregating Wise transaction data.
- Enhanced data accuracy and processing efficiency through detailed troubleshooting and data manipulation techniques.
Pending Tasks
- Review and refine the data aggregation function to ensure accuracy in monthly financial summaries.
- Implement additional error handling mechanisms in the pipeline to address potential data inconsistencies.
Evidence
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- event_ids: []