Developed financial data manipulation and integration scripts

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Developed financial data manipulation and integration scripts

  • Day: 2024-01-07
  • Time: 00:30 to 23:40
  • Project: Accounting
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, Google Sheets, Currency Conversion, Financial Analysis, Data Integration

Description

Session Goal

The session aimed to enhance financial data manipulation capabilities by developing Python scripts for currency conversion, financial analysis, and integration with Google Sheets.

Key Activities

  • Modified the add_balance function to handle multiple currencies within a unified DataFrame, ensuring accurate running balance calculations.
  • Developed a method to convert historical ARS values using the IPC dataset, implementing a Python function for currency conversion.
  • Implemented ARS currency conversion in a DataFrame and updated currency values based on a target date.
  • Explored financial data analysis techniques, including weekly balances, cash flow, and spending analysis.
  • Calculated weekly balances for accounts using Python and Pandas.
  • Formalized a family accounting scheme to manage transactions and plan debt cancellation.
  • Loaded data from Google Sheets into Python using the gspread library, including setting up Google Cloud credentials and resolving common errors.
  • Addressed issues with empty cells in Google Sheets data using [[pandas]] for data cleaning.
  • Calculated three-way accounting balances and developed a debt cancellation plan among family members.

Achievements

  • Successfully modified and implemented functions for handling multiple currencies and converting ARS values.
  • Established methods for integrating Google Sheets data into Python workflows, resolving access and error issues.
  • Developed comprehensive financial analysis and accounting scripts to manage and analyze family financial data.

Pending Tasks

  • Further refinement of financial analysis techniques and integration scripts may be needed to enhance accuracy and efficiency.

Evidence

  • source_file=2024-01-07.sessions.jsonl, line_number=0, event_count=0, session_id=269ea4f59e0e3d162210aacc4264bdd18f10046888136fa1516ac9f3bcab189b
  • event_ids: []

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