📅 2025-07-06 — Session: Financial Data Analysis and Visualization

🕒 00:55–01:15
🏷️ Labels: Data_Analysis, Financial_Data, Python, Pandas, Visualization
📂 Project: Accounting
⭐ Priority: MEDIUM

Session Goal

The primary aim of this session was to perform a comprehensive analysis of financial data files, focusing on data cleaning, aggregation, and visualization.

Key Activities

  • Conducted a diagnostic overview of financial data files to assess their status and determine next steps for analysis.
  • Developed a Python script to analyze monthly inflow and outflow per currency from ledger files.
  • Addressed issues with non-datetime columns in Pandas, ensuring proper data types for further processing.
  • Managed timezone-aware datetimes in CSV files, converting them to naive datetimes for compatibility.
  • Implemented robust date handling in Pandas DataFrames to prevent errors during date parsing.
  • Solved mixed timezone offsets in Pandas posted_date columns by converting timestamps to UTC.
  • Visualized financial flows using bar charts in Python, leveraging Matplotlib for data pivoting and plotting.

Achievements

  • Successfully cleaned and processed financial data for accurate analysis.
  • Developed visualizations to represent financial inflows and outflows effectively.

Pending Tasks

  • Further refinement of visualization techniques to enhance clarity and insights.
  • Exploration of additional data sources for more comprehensive analysis.