Enhanced Data Processing for Erste Transactions

2 min read

Enhanced Data Processing for Erste Transactions

  • Day: 2025-07-05
  • Time: 23:30 to 23:50
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Csv Processing, Data Cleaning, Python, Error Handling, Finance

Description

Session Goal

The session aimed to address various challenges related to processing and saving CSV transaction data from Erste bank accounts.

Key Activities

  • Error Handling in DataFrame Access: Resolved a column access error in a DataFrame by modifying the code and suggesting pre-slicing column verification.
  • Transaction Structure Review: Evaluated a canonical transaction structure, identifying strengths and areas for improvement.
  • CSV Parsing and Saving: Developed a script to parse multiple CSV files from Erste accounts, assign metadata, and save cleaned data.
  • Encoding Detection: Implemented automatic encoding detection for CSV files to prevent UnicodeDecodeErrors.
  • File Processing Automation: Ensured directories exist before saving processed CSVs, handling errors related to missing folders.
  • Pipeline Development: Created a notebook pipeline for processing Erste account statements, including reading CSVs, handling encodings, cleaning data, applying a canonical transaction schema, and exporting results.
  • CSV Comma Handling: Addressed issues with unprotected commas in CSV fields, using tokenization to preserve data integrity.

Achievements

  • Successfully saved Erste transactions in a standardized format, ready for system integration.
  • Improved robustness in CSV parsing and data cleaning processes.

Pending Tasks

  • Further refinement of the transaction structure based on the review insights.
  • Continuous enhancement of error handling strategies for CSV processing.

Evidence

  • source_file=2025-07-05.sessions.jsonl, line_number=6, event_count=0, session_id=27a5330e7e347a2d1090b49da2d39bdced028474df0dce58a1bae957aae65458
  • event_ids: []

Graph View

Backlinks