📅 2025-07-06 — Session: Processed Financial Data with Pandas for Monthly Analysis
🕒 00:55–01:10
🏷️ Labels: Data_Processing, Financial_Analysis, Pandas, CSV, Datetime
📂 Project: Accounting
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to process and analyze multiple financial data files to generate a unified DataFrame for aggregation and analysis.
Key Activities
- Conducted a diagnostic overview of financial data files, assessing their status and contents.
- Implemented scripts using Pandas to process CSV files, compute monthly inflows and outflows, and group results by month, currency, and flow direction.
- Addressed data cleaning and transformation steps, including handling non-datetime columns and timezone-aware datetimes in DataFrames.
- Developed a robust solution for mixed-type date columns to ensure accurate data parsing and prevent errors.
Achievements
- Successfully processed financial data files into a unified DataFrame, ready for further analysis.
- Enhanced data integrity by resolving datetime handling issues and ensuring accurate reporting.
Pending Tasks
- Further analysis and visualization of the processed financial data to derive insights.
- Integration of the processed data into a larger financial reporting system.